capabilities:
  - id: invoke-foundation-models
    name: Invoke Foundation Models
    description: >-
      Invoke foundation models for text generation, image generation, and
      embeddings. Supports synchronous, streaming, and asynchronous invocation
      patterns via InvokeModel, ConverseAPI, and batch inference.
    operations:
      - InvokeModel
      - InvokeModelWithResponseStream
      - Converse
      - ConverseStream
      - ApplyGuardrail
    tags:
      - Inference
      - Foundation Models
      - Streaming
      - Text Generation

  - id: manage-foundation-models
    name: Manage Foundation Models
    description: >-
      List and retrieve metadata for available foundation models in Amazon
      Bedrock, including provider, modalities, and inference parameters.
    operations:
      - ListFoundationModels
      - GetFoundationModel
      - ListFoundationModelAgreementOffers
      - GetFoundationModelAvailability
    tags:
      - Foundation Models
      - Model Discovery

  - id: manage-custom-models
    name: Manage Custom Models
    description: >-
      Fine-tune and customize foundation models with proprietary data using
      model customization jobs, then deploy custom models for inference.
    operations:
      - CreateModelCustomizationJob
      - GetModelCustomizationJob
      - ListModelCustomizationJobs
      - StopModelCustomizationJob
      - GetCustomModel
      - ListCustomModels
      - DeleteCustomModel
    tags:
      - Fine-Tuning
      - Custom Models
      - Model Training

  - id: manage-provisioned-throughput
    name: Manage Provisioned Throughput
    description: >-
      Purchase and manage provisioned throughput for consistent model
      inference performance at scale.
    operations:
      - CreateProvisionedModelThroughput
      - GetProvisionedModelThroughput
      - UpdateProvisionedModelThroughput
      - DeleteProvisionedModelThroughput
      - ListProvisionedModelThroughputs
    tags:
      - Provisioned Throughput
      - Performance
      - Scaling

  - id: manage-guardrails
    name: Manage Guardrails
    description: >-
      Create and manage guardrails to enforce responsible AI policies,
      filter harmful content, deny topics, redact PII, and detect
      prompt injection attacks.
    operations:
      - CreateGuardrail
      - GetGuardrail
      - UpdateGuardrail
      - DeleteGuardrail
      - ListGuardrails
      - CreateGuardrailVersion
      - ListGuardrailVersions
    tags:
      - Guardrails
      - Safety
      - Responsible AI
      - Content Filtering

  - id: manage-knowledge-bases
    name: Manage Knowledge Bases
    description: >-
      Create and manage knowledge bases for retrieval-augmented generation (RAG).
      Ingest documents, sync data sources, and retrieve relevant context.
    operations:
      - CreateKnowledgeBase
      - GetKnowledgeBase
      - UpdateKnowledgeBase
      - DeleteKnowledgeBase
      - ListKnowledgeBases
      - CreateDataSource
      - GetDataSource
      - UpdateDataSource
      - DeleteDataSource
      - ListDataSources
      - StartIngestionJob
      - GetIngestionJob
      - ListIngestionJobs
    tags:
      - Knowledge Bases
      - RAG
      - Data Ingestion
      - Vector Store

  - id: manage-agents
    name: Manage Agents
    description: >-
      Create and manage autonomous AI agents that orchestrate multi-step
      tasks, call APIs, query knowledge bases, and execute workflows.
    operations:
      - CreateAgent
      - GetAgent
      - UpdateAgent
      - DeleteAgent
      - ListAgents
      - PrepareAgent
      - CreateAgentActionGroup
      - GetAgentActionGroup
      - UpdateAgentActionGroup
      - DeleteAgentActionGroup
      - CreateAgentAlias
      - GetAgentAlias
      - UpdateAgentAlias
      - DeleteAgentAlias
      - ListAgentAliases
    tags:
      - Agents
      - Orchestration
      - Autonomous AI
      - Action Groups

  - id: run-agent-inference
    name: Run Agent Inference
    description: >-
      Invoke Bedrock agents to handle user requests through multi-step
      orchestration and retrieve results from knowledge bases.
    operations:
      - InvokeAgent
      - InvokeInlineAgent
      - Retrieve
      - RetrieveAndGenerate
      - RetrieveAndGenerateStream
    tags:
      - Agent Inference
      - RAG
      - Retrieval

  - id: manage-model-evaluation
    name: Manage Model Evaluation
    description: >-
      Create and manage model evaluation jobs to assess foundation model
      quality, accuracy, and performance on specific tasks.
    operations:
      - CreateEvaluationJob
      - GetEvaluationJob
      - ListEvaluationJobs
      - StopEvaluationJob
    tags:
      - Evaluation
      - Model Quality
      - Benchmarking

  - id: manage-tags
    name: Manage Tags
    description: >-
      Apply and remove metadata tags on Amazon Bedrock resources for
      cost allocation and governance.
    operations:
      - TagResource
      - UntagResource
      - ListTagsForResource
    tags:
      - Tags
      - Governance

compositions:
  - id: rag-application
    name: RAG Application
    description: >-
      End-to-end workflow for building a retrieval-augmented generation
      application: create a knowledge base, ingest documents, and invoke
      a model with retrieved context.
    steps:
      - capability: manage-knowledge-bases
        operation: CreateKnowledgeBase
      - capability: manage-knowledge-bases
        operation: CreateDataSource
      - capability: manage-knowledge-bases
        operation: StartIngestionJob
      - capability: run-agent-inference
        operation: RetrieveAndGenerate
    tags:
      - RAG
      - Workflow
      - Knowledge Bases

  - id: responsible-ai-deployment
    name: Responsible AI Deployment
    description: >-
      Deploy a foundation model with guardrails for content filtering,
      topic blocking, and PII protection.
    steps:
      - capability: manage-guardrails
        operation: CreateGuardrail
      - capability: invoke-foundation-models
        operation: Converse
    tags:
      - Responsible AI
      - Safety
      - Workflow

  - id: custom-model-deployment
    name: Custom Model Deployment
    description: >-
      Fine-tune a foundation model and deploy it with provisioned throughput
      for consistent production performance.
    steps:
      - capability: manage-custom-models
        operation: CreateModelCustomizationJob
      - capability: manage-provisioned-throughput
        operation: CreateProvisionedModelThroughput
      - capability: invoke-foundation-models
        operation: InvokeModel
    tags:
      - Fine-Tuning
      - Provisioned Throughput
      - Workflow