openapi: 3.0.0 info: title: Portkey Analytics > Graphs Images API description: The Portkey REST API. Please see https://portkey.ai/docs/api-reference for more details. version: 2.0.0 termsOfService: https://portkey.ai/terms contact: name: Portkey Developer Forum url: https://portkey.wiki/community license: name: MIT url: https://github.com/Portkey-AI/portkey-openapi/blob/master/LICENSE servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint security: - Portkey-Key: [] tags: - name: Images description: Given a prompt and/or an input image, the model will generate a new image. paths: /images/generations: servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_GATEWAY_URL description: Self-Hosted Gateway URL post: operationId: createImage tags: - Images summary: Create Image requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/CreateImageRequest' responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/ImagesResponse' security: - Portkey-Key: [] Virtual-Key: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] - Portkey-Key: [] Config: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] Custom-Host: [] x-code-samples: - lang: curl label: Default source: "curl https://api.portkey.ai/v1/images/generations \\\n -H \"Content-Type: application/json\" \\\n -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n -d '{\n \"model\": \"dall-e-3\",\n \"prompt\": \"A cute baby sea otter\",\n \"n\": 1,\n \"size\": \"1024x1024\"\n }'\n" - lang: python label: Default source: "from portkey_ai import Portkey\n\nclient = Portkey(\n api_key = \"PORTKEY_API_KEY\",\n virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nclient.images.generate(\n model=\"dall-e-3\",\n prompt=\"A cute baby sea otter\",\n n=1,\n size=\"1024x1024\"\n)\n" - lang: javascript label: Default source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n apiKey: 'PORTKEY_API_KEY',\n virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n const image = await client.images.generate({ model: \"dall-e-3\", prompt: \"A cute baby sea otter\" });\n\n console.log(image.data);\n}\nmain();\n" - lang: curl label: Self-Hosted source: "curl -X POST \"SELF_HOSTED_GATEWAY_URL/images/generations\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n -d '{\n \"model\": \"dall-e-3\",\n \"prompt\": \"A cute baby sea otter\",\n \"n\": 1,\n \"size\": \"1024x1024\"\n }'\n" - lang: python label: Self-Hosted source: "from portkey_ai import Portkey\n\nclient = Portkey(\n api_key=\"PORTKEY_API_KEY\",\n virtual_key=\"PROVIDER_VIRTUAL_KEY\",\n base_url=\"SELF_HOSTED_GATEWAY_URL\"\n)\n\nimage = client.images.generate(\n model=\"dall-e-3\",\n prompt=\"A cute baby sea otter\",\n n=1,\n size=\"1024x1024\"\n)\n\nprint(image.data)\n" - lang: javascript label: Self-Hosted source: "import Portkey from 'portkey-ai';\n\nconst portkey = new Portkey({\n apiKey: 'PORTKEY_API_KEY',\n virtualKey: 'PROVIDER_VIRTUAL_KEY',\n baseURL: 'SELF_HOSTED_GATEWAY_URL'\n});\n\nconst image = await portkey.images.generate({\n model: \"dall-e-3\",\n prompt: \"A cute baby sea otter\",\n n: 1,\n size: \"1024x1024\"\n});\n\nconsole.log(image.data);\n" /images/edits: servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_GATEWAY_URL description: Self-Hosted Gateway URL post: operationId: createImageEdit tags: - Images summary: Create Image Edit requestBody: required: true content: multipart/form-data: schema: $ref: '#/components/schemas/CreateImageEditRequest' responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/ImagesResponse' security: - Portkey-Key: [] Virtual-Key: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] - Portkey-Key: [] Config: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] Custom-Host: [] x-code-samples: - lang: curl label: Default source: "curl https://api.portkey.ai/v1/images/edits \\\n -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n -F image=\"@otter.png\" \\\n -F mask=\"@mask.png\" \\\n -F prompt=\"A cute baby sea otter wearing a beret\" \\\n -F n=2 \\\n -F size=\"1024x1024\"\n" - lang: python label: Default source: "from portkey_ai import Portkey\n\nclient = Portkey(\n api_key = \"PORTKEY_API_KEY\",\n virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nclient.images.edit(\n image=open(\"otter.png\", \"rb\"),\n mask=open(\"mask.png\", \"rb\"),\n prompt=\"A cute baby sea otter wearing a beret\",\n n=2,\n size=\"1024x1024\"\n)\n" - lang: javascript label: Default source: "import fs from \"fs\";\nimport Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n apiKey: 'PORTKEY_API_KEY',\n virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n const image = await client.images.edit({\n image: fs.createReadStream(\"otter.png\"),\n mask: fs.createReadStream(\"mask.png\"),\n prompt: \"A cute baby sea otter wearing a beret\",\n });\n\n console.log(image.data);\n}\nmain();\n" - lang: curl label: Self-Hosted source: "curl -X POST \"SELF_HOSTED_GATEWAY_URL/images/edits\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n -d '{\n \"image\": \"@otter.png\",\n \"mask\": \"@mask.png\",\n \"prompt\": \"A cute baby sea otter wearing a beret\",\n \"n\": 2,\n \"size\": \"1024x1024\"\n }'\n" - lang: python label: Self-Hosted source: "from portkey_ai import Portkey\n\nclient = Portkey(\n api_key=\"PORTKEY_API_KEY\",\n virtual_key=\"PROVIDER_VIRTUAL_KEY\",\n base_url=\"SELF_HOSTED_GATEWAY_URL\"\n)\n\nimage = client.images.edit(\n image=open(\"otter.png\", \"rb\"),\n mask=open(\"mask.png\", \"rb\"),\n prompt=\"A cute baby sea otter wearing a beret\",\n n=2,\n size=\"1024x1024\"\n)\n\nprint(image.data)\n" - lang: javascript label: Self-Hosted source: "import fs from \"fs\";\nimport Portkey from 'portkey-ai';\n\nconst portkey = new Portkey({\n apiKey: 'PORTKEY_API_KEY',\n virtualKey: 'PROVIDER_VIRTUAL_KEY',\n baseURL: 'SELF_HOSTED_GATEWAY_URL'\n});\n\nasync function main() {\n const image = await portkey.images.edit({\n image: fs.createReadStream(\"otter.png\"),\n mask: fs.createReadStream(\"mask.png\"),\n prompt: \"A cute baby sea otter wearing a beret\",\n });\n\n console.log(image.data);\n}\nmain();\n" /images/variations: servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_GATEWAY_URL description: Self-Hosted Gateway URL post: operationId: createImageVariation tags: - Images summary: Creates Image Variation requestBody: required: true content: multipart/form-data: schema: $ref: '#/components/schemas/CreateImageVariationRequest' responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/ImagesResponse' security: - Portkey-Key: [] Virtual-Key: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] - Portkey-Key: [] Config: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] Custom-Host: [] x-code-samples: - lang: curl label: Default source: "curl https://api.portkey.ai/v1/images/variations \\\n -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n -F image=\"@otter.png\" \\\n -F n=2 \\\n -F size=\"1024x1024\"\n" - lang: python label: Default source: "from portkey_ai import Portkey\n\nclient = Portkey(\n api_key = \"PORTKEY_API_KEY\",\n virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nresponse = client.images.create_variation(\n image=open(\"image_edit_original.png\", \"rb\"),\n n=2,\n size=\"1024x1024\"\n)\n" - lang: javascript label: Default source: "import fs from \"fs\";\nimport Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n apiKey: 'PORTKEY_API_KEY',\n virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n const image = await client.images.createVariation({\n image: fs.createReadStream(\"otter.png\"),\n });\n\n console.log(image.data);\n}\nmain();\n" - lang: curl label: Self-Hosted source: "curl -X POST \"SELF_HOSTED_GATEWAY_URL/images/variations\" \\\n -H \"Content-Type: application/json\" \\\n -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n -d '{\n \"image\": \"@otter.png\",\n \"n\": 2,\n \"size\": \"1024x1024\"\n }'\n" - lang: python label: Self-Hosted source: "from portkey_ai import Portkey\n\nclient = Portkey(\n api_key=\"PORTKEY_API_KEY\",\n virtual_key=\"PROVIDER_VIRTUAL_KEY\",\n base_url=\"SELF_HOSTED_GATEWAY_URL\"\n)\n\nimage = client.images.create_variation(\n image=open(\"otter.png\", \"rb\"),\n n=2,\n size=\"1024x1024\"\n)\n\nprint(image.data)\n" - lang: javascript label: Self-Hosted source: "import fs from \"fs\";\nimport Portkey from 'portkey-ai';\n\nconst portkey = new Portkey({\n apiKey: 'PORTKEY_API_KEY',\n virtualKey: 'PROVIDER_VIRTUAL_KEY',\n baseURL: 'SELF_HOSTED_GATEWAY_URL'\n});\n\nasync function main() {\n const image = await portkey.images.createVariation({\n image: fs.createReadStream(\"otter.png\"),\n });\n\n console.log(image.data);\n}\nmain();\n" components: schemas: CreateImageRequest: type: object properties: prompt: description: A text description of the desired image(s). The maximum length is 1000 characters for `dall-e-2` and 4000 characters for `dall-e-3`. type: string example: A cute baby sea otter model: anyOf: - type: string - type: string enum: - dall-e-2 - dall-e-3 x-oaiTypeLabel: string default: dall-e-2 example: dall-e-3 nullable: true description: The model to use for image generation. n: type: integer minimum: 1 maximum: 10 default: 1 example: 1 nullable: true description: The number of images to generate. Must be between 1 and 10. For `dall-e-3`, only `n=1` is supported. quality: type: string enum: - standard - hd default: standard example: standard description: The quality of the image that will be generated. `hd` creates images with finer details and greater consistency across the image. This param is only supported for `dall-e-3`. response_format: type: string enum: - url - b64_json default: url example: url nullable: true description: The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated. size: type: string enum: - 256x256 - 512x512 - 1024x1024 - 1792x1024 - 1024x1792 default: 1024x1024 example: 1024x1024 nullable: true description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024` for `dall-e-2`. Must be one of `1024x1024`, `1792x1024`, or `1024x1792` for `dall-e-3` models. style: type: string enum: - vivid - natural default: vivid example: vivid nullable: true description: The style of the generated images. Must be one of `vivid` or `natural`. Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images. This param is only supported for `dall-e-3`. user: type: string example: user-1234 description: 'A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids). ' required: - prompt CreateImageVariationRequest: type: object properties: image: description: The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and square. type: string format: binary model: anyOf: - type: string - type: string enum: - dall-e-2 x-oaiTypeLabel: string default: dall-e-2 example: dall-e-2 nullable: true description: The model to use for image generation. Only `dall-e-2` is supported at this time. n: type: integer minimum: 1 maximum: 10 default: 1 example: 1 nullable: true description: The number of images to generate. Must be between 1 and 10. For `dall-e-3`, only `n=1` is supported. response_format: type: string enum: - url - b64_json default: url example: url nullable: true description: The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated. size: type: string enum: - 256x256 - 512x512 - 1024x1024 default: 1024x1024 example: 1024x1024 nullable: true description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024`. user: type: string example: user-1234 description: 'A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids). ' required: - image Image: type: object description: Represents the url or the content of an image generated by the Portkey API. properties: b64_json: type: string description: The base64-encoded JSON of the generated image, if `response_format` is `b64_json`. url: type: string description: The URL of the generated image, if `response_format` is `url` (default). revised_prompt: type: string description: The prompt that was used to generate the image, if there was any revision to the prompt. x-code-samples: name: The image object example: "{\n \"url\": \"...\",\n \"revised_prompt\": \"...\"\n}\n" ImagesResponse: properties: created: type: integer data: type: array items: $ref: '#/components/schemas/Image' required: - created - data CreateImageEditRequest: type: object properties: image: description: The image to edit. Must be a valid PNG file, less than 4MB, and square. If mask is not provided, image must have transparency, which will be used as the mask. type: string format: binary prompt: description: A text description of the desired image(s). The maximum length is 1000 characters. type: string example: A cute baby sea otter wearing a beret mask: description: An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where `image` should be edited. Must be a valid PNG file, less than 4MB, and have the same dimensions as `image`. type: string format: binary model: anyOf: - type: string - type: string enum: - dall-e-2 x-oaiTypeLabel: string default: dall-e-2 example: dall-e-2 nullable: true description: The model to use for image generation. Only `dall-e-2` is supported at this time. n: type: integer minimum: 1 maximum: 10 default: 1 example: 1 nullable: true description: The number of images to generate. Must be between 1 and 10. size: type: string enum: - 256x256 - 512x512 - 1024x1024 default: 1024x1024 example: 1024x1024 nullable: true description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024`. response_format: type: string enum: - url - b64_json default: url example: url nullable: true description: The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated. user: type: string example: user-1234 description: 'A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids). ' required: - prompt - image securitySchemes: Portkey-Key: type: apiKey in: header name: x-portkey-api-key Virtual-Key: type: apiKey in: header name: x-portkey-virtual-key Provider-Auth: type: http scheme: bearer Provider-Name: type: apiKey in: header name: x-portkey-provider Config: type: apiKey in: header name: x-portkey-config Custom-Host: type: apiKey in: header name: x-portkey-custom-host x-server-groups: ControlPlaneServers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_CONTROL_PLANE_URL description: Self-Hosted Control Plane URL DataPlaneServers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_GATEWAY_URL description: Self-Hosted Gateway URL PublicServers: - url: https://api.portkey.ai description: Portkey Public API (no auth required) x-mint: mcp: enabled: true name: Portkey MCP description: Official MCP Server for Portkey Docs & APIs x-code-samples: navigationGroups: - id: endpoints title: Endpoints - id: assistants title: Assistants - id: legacy title: Legacy groups: - id: audio title: Audio description: 'Learn how to turn audio into text or text into audio. Related guide: [Speech to text](https://platform.openai.com/docs/guides/speech-to-text) ' navigationGroup: endpoints sections: - type: endpoint key: createSpeech path: createSpeech - type: endpoint key: createTranscription path: createTranscription - type: endpoint key: createTranslation path: createTranslation - type: object key: CreateTranscriptionResponseJson path: json-object - type: object key: CreateTranscriptionResponseVerboseJson path: verbose-json-object - id: chat title: Chat description: 'Given a list of messages comprising a conversation, the model will return a response. Related guide: [Chat Completions](https://platform.openai.com/docs/guides/text-generation) ' navigationGroup: endpoints sections: - type: endpoint key: createChatCompletion path: create - type: object key: CreateChatCompletionResponse path: object - type: object key: CreateChatCompletionStreamResponse path: streaming - id: realtime title: Realtime description: 'WebSocket proxy for provider Realtime APIs (`GET` upgrade). Use `wss://` with the same `/v1` data-plane base as other gateway routes. Related guide: [OpenAI Realtime API](https://platform.openai.com/docs/guides/realtime) ' navigationGroup: endpoints sections: - type: endpoint key: connectRealtime path: connect - id: embeddings title: Embeddings description: 'Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. Related guide: [Embeddings](https://platform.openai.com/docs/guides/embeddings) ' navigationGroup: endpoints sections: - type: endpoint key: createEmbedding path: create - type: object key: Embedding path: object - id: rerank title: Rerank description: 'Rerank a list of documents based on their relevance to a query. Reranking improves search results by scoring documents based on semantic relevance rather than keyword matching. Supported providers: Cohere, Voyage, Jina, Pinecone, Bedrock, Azure AI. ' navigationGroup: endpoints sections: - type: endpoint key: createRerank path: create - type: object key: CreateRerankResponse path: object - id: fine-tuning title: Fine-tuning description: 'Manage fine-tuning jobs to tailor a model to your specific training data. Related guide: [Fine-tune models](https://platform.openai.com/docs/guides/fine-tuning) ' navigationGroup: endpoints sections: - type: endpoint key: createFineTuningJob path: create - type: endpoint key: listPaginatedFineTuningJobs path: list - type: endpoint key: listFineTuningEvents path: list-events - type: endpoint key: listFineTuningJobCheckpoints path: list-checkpoints - type: endpoint key: retrieveFineTuningJob path: retrieve - type: endpoint key: cancelFineTuningJob path: cancel - type: object key: FinetuneChatRequestInput path: chat-input - type: object key: FinetuneCompletionRequestInput path: completions-input - type: object key: FineTuningJob path: object - type: object key: FineTuningJobEvent path: event-object - type: object key: FineTuningJobCheckpoint path: checkpoint-object - id: batch title: Batch description: 'Create large batches of API requests for asynchronous processing. The Batch API returns completions within 24 hours for a 50% discount. Related guide: [Batch](https://platform.openai.com/docs/guides/batch) ' navigationGroup: endpoints sections: - type: endpoint key: createBatch path: create - type: endpoint key: retrieveBatch path: retrieve - type: endpoint key: cancelBatch path: cancel - type: endpoint key: listBatches path: list - type: object key: Batch path: object - type: object key: BatchRequestInput path: request-input - type: object key: BatchRequestOutput path: request-output - id: files title: Files description: 'Files are used to upload documents that can be used with features like [Assistants](https://platform.openai.com/docs/api-reference/assistants), [Fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning), and [Batch API](https://platform.openai.com/docs/guides/batch). ' navigationGroup: endpoints sections: - type: endpoint key: createFile path: create - type: endpoint key: listFiles path: list - type: endpoint key: retrieveFile path: retrieve - type: endpoint key: deleteFile path: delete - type: endpoint key: downloadFile path: retrieve-contents - type: object key: OpenAIFile path: object - id: images title: Images description: 'Given a prompt and/or an input image, the model will generate a new image. Related guide: [Image generation](https://platform.openai.com/docs/guides/images) ' navigationGroup: endpoints sections: - type: endpoint key: createImage path: create - type: endpoint key: createImageEdit path: createEdit - type: endpoint key: createImageVariation path: createVariation - type: object key: Image path: object - id: models title: Models description: 'List and describe the various models available in the API. You can refer to the [Models](https://platform.openai.com/docs/models) documentation to understand what models are available and the differences between them. ' navigationGroup: endpoints sections: - type: endpoint key: listModels path: list - type: endpoint key: retrieveModel path: retrieve - type: endpoint key: deleteModel path: delete - type: object key: Model path: object - id: moderations title: Moderations description: 'Given some input text, outputs if the model classifies it as potentially harmful across several categories. Related guide: [Moderations](https://platform.openai.com/docs/guides/moderation) ' navigationGroup: endpoints sections: - type: endpoint key: createModeration path: create - type: object key: CreateModerationResponse path: object - id: assistants title: Assistants beta: true description: 'Build assistants that can call models and use tools to perform tasks. [Get started with the Assistants API](https://platform.openai.com/docs/assistants) ' navigationGroup: assistants sections: - type: endpoint key: createAssistant path: createAssistant - type: endpoint key: listAssistants path: listAssistants - type: endpoint key: getAssistant path: getAssistant - type: endpoint key: modifyAssistant path: modifyAssistant - type: endpoint key: deleteAssistant path: deleteAssistant - type: object key: AssistantObject path: object - id: threads title: Threads beta: true description: 'Create threads that assistants can interact with. Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview) ' navigationGroup: assistants sections: - type: endpoint key: createThread path: createThread - type: endpoint key: getThread path: getThread - type: endpoint key: modifyThread path: modifyThread - type: endpoint key: deleteThread path: deleteThread - type: object key: ThreadObject path: object - id: messages title: Messages beta: true description: 'Create messages within threads Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview) ' navigationGroup: assistants sections: - type: endpoint key: createMessage path: createMessage - type: endpoint key: listMessages path: listMessages - type: endpoint key: getMessage path: getMessage - type: endpoint key: modifyMessage path: modifyMessage - type: endpoint key: deleteMessage path: deleteMessage - type: object key: MessageObject path: object - id: runs title: Runs beta: true description: 'Represents an execution run on a thread. Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview) ' navigationGroup: assistants sections: - type: endpoint key: createRun path: createRun - type: endpoint key: createThreadAndRun path: createThreadAndRun - type: endpoint key: listRuns path: listRuns - type: endpoint key: getRun path: getRun - type: endpoint key: modifyRun path: modifyRun - type: endpoint key: submitToolOuputsToRun path: submitToolOutputs - type: endpoint key: cancelRun path: cancelRun - type: object key: RunObject path: object - id: run-steps title: Run Steps beta: true description: 'Represents the steps (model and tool calls) taken during the run. Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview) ' navigationGroup: assistants sections: - type: endpoint key: listRunSteps path: listRunSteps - type: endpoint key: getRunStep path: getRunStep - type: object key: RunStepObject path: step-object - id: vector-stores title: Vector Stores beta: true description: 'Vector stores are used to store files for use by the `file_search` tool. Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search) ' navigationGroup: assistants sections: - type: endpoint key: createVectorStore path: create - type: endpoint key: listVectorStores path: list - type: endpoint key: getVectorStore path: retrieve - type: endpoint key: modifyVectorStore path: modify - type: endpoint key: deleteVectorStore path: delete - type: object key: VectorStoreObject path: object - id: vector-stores-files title: Vector Store Files beta: true description: 'Vector store files represent files inside a vector store. Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search) ' navigationGroup: assistants sections: - type: endpoint key: createVectorStoreFile path: createFile - type: endpoint key: listVectorStoreFiles path: listFiles - type: endpoint key: getVectorStoreFile path: getFile - type: endpoint key: deleteVectorStoreFile path: deleteFile - type: object key: VectorStoreFileObject path: file-object - id: vector-stores-file-batches title: Vector Store File Batches beta: true description: 'Vector store file batches represent operations to add multiple files to a vector store. Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search) ' navigationGroup: assistants sections: - type: endpoint key: createVectorStoreFileBatch path: createBatch - type: endpoint key: getVectorStoreFileBatch path: getBatch - type: endpoint key: cancelVectorStoreFileBatch path: cancelBatch - type: endpoint key: listFilesInVectorStoreBatch path: listBatchFiles - type: object key: VectorStoreFileBatchObject path: batch-object - id: assistants-streaming title: Streaming beta: true description: 'Stream the result of executing a Run or resuming a Run after submitting tool outputs. You can stream events from the [Create Thread and Run](https://platform.openai.com/docs/api-reference/runs/createThreadAndRun), [Create Run](https://platform.openai.com/docs/api-reference/runs/createRun), and [Submit Tool Outputs](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) endpoints by passing `"stream": true`. The response will be a [Server-Sent events](https://html.spec.whatwg.org/multipage/server-sent-events.html#server-sent-events) stream. Our Node and Python SDKs provide helpful utilities to make streaming easy. Reference the [Assistants API quickstart](https://platform.openai.com/docs/assistants/overview) to learn more. ' navigationGroup: assistants sections: - type: object key: MessageDeltaObject path: message-delta-object - type: object key: RunStepDeltaObject path: run-step-delta-object - type: object key: AssistantStreamEvent path: events - id: completions title: Completions legacy: true navigationGroup: legacy description: 'Given a prompt, the model will return one or more predicted completions along with the probabilities of alternative tokens at each position. Most developer should use our [Chat Completions API](https://platform.openai.com/docs/guides/text-generation/text-generation-models) to leverage our best and newest models. ' sections: - type: endpoint key: createCompletion path: create - type: object key: CreateCompletionResponse path: object