openapi: 3.0.3 info: title: AMD Developer Cloud Configuration Models API description: The AMD Developer Cloud API provides access to AMD Instinct GPU instances for AI inference, training, and HPC workloads. Supports managing compute instances, deploying AI models, monitoring GPU utilization, and integrating with ROCm-compatible frameworks including PyTorch, TensorFlow, and vLLM. version: '1' contact: name: AMD Developer Support url: https://developer.amd.com/support/ termsOfService: https://www.amd.com/en/legal/terms-and-conditions.html license: name: AMD Terms and Conditions url: https://www.amd.com/en/legal/terms-and-conditions.html servers: - url: https://api.developer.amd.com/v1 description: AMD Developer Cloud API Production security: - apiKey: [] tags: - name: Models description: AI model deployment and management paths: /models: get: operationId: listModels summary: AMD Developer Cloud List Deployed Models description: List AI models deployed on the AMD Developer Cloud for inference serving. tags: - Models responses: '200': description: List of deployed models. content: application/json: schema: $ref: '#/components/schemas/ModelList' examples: listModels200Example: summary: Default listModels 200 response x-microcks-default: true value: models: - id: model-001 name: llama-3.1-70b framework: vLLM status: serving endpoint: https://inf.developer.amd.com/model-001/v1 '401': description: Unauthorized. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' examples: listModels401Example: summary: Default listModels 401 response x-microcks-default: true value: code: UNAUTHORIZED message: Invalid API key x-microcks-operation: delay: 0 dispatcher: FALLBACK post: operationId: deployModel summary: AMD Developer Cloud Deploy AI Model description: Deploy an AI model for inference serving on AMD Instinct GPUs using vLLM or another serving framework. tags: - Models requestBody: required: true description: Model deployment configuration. content: application/json: schema: $ref: '#/components/schemas/ModelInput' examples: deployModelRequestExample: summary: Default deployModel request x-microcks-default: true value: name: llama-3.1-70b modelId: meta-llama/Llama-3.1-70B-Instruct framework: vLLM gpuType: mi300x gpuCount: 2 responses: '201': description: Model deployed. content: application/json: schema: $ref: '#/components/schemas/Model' examples: deployModel201Example: summary: Default deployModel 201 response x-microcks-default: true value: id: model-002 name: llama-3.1-70b framework: vLLM status: deploying endpoint: https://inf.developer.amd.com/model-002/v1 '401': description: Unauthorized. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' examples: deployModel401Example: summary: Default deployModel 401 response x-microcks-default: true value: code: UNAUTHORIZED message: Invalid API key x-microcks-operation: delay: 0 dispatcher: FALLBACK components: schemas: Model: type: object description: A deployed AI model for inference serving. properties: id: type: string description: Model deployment identifier. example: model-001 name: type: string description: Model display name. example: llama-3.1-70b framework: type: string description: Inference serving framework. enum: - vLLM - TGI - TorchServe - Triton example: vLLM status: type: string description: Deployment status. enum: - deploying - serving - stopped - failed example: serving endpoint: type: string description: Inference endpoint URL. example: https://inf.developer.amd.com/model-001/v1 ModelList: type: object description: List of deployed AI models. properties: models: type: array description: Array of model deployments. items: $ref: '#/components/schemas/Model' ModelInput: type: object description: Request to deploy an AI model. required: - modelId - framework - gpuType properties: name: type: string description: Display name for the deployment. example: llama-3.1-70b modelId: type: string description: Hugging Face model ID or path. example: meta-llama/Llama-3.1-70B-Instruct framework: type: string description: Inference framework to use. enum: - vLLM - TGI - TorchServe - Triton example: vLLM gpuType: type: string description: GPU hardware type. example: mi300x gpuCount: type: integer description: Number of GPUs to allocate. example: 2 ErrorResponse: type: object description: API error response. properties: code: type: string description: Error code. example: NOT_FOUND message: type: string description: Error message. example: The requested resource was not found. securitySchemes: apiKey: type: apiKey in: header name: X-API-Key