Amazon SageMaker Register Latest Completed Training

arazzo: 1.0.1
info:
  title: Amazon SageMaker Register Latest Completed Training
  summary: Find the most recent completed training job, read its artifacts, and register a model from them.
  description: >-
    A handoff flow from training to hosting. The workflow lists training jobs
    filtered to the Completed status and sorted by creation time, takes the most
    recent one, describes it to read the S3 path of its model artifacts, and
    registers a SageMaker model from those artifacts and an inference container.
    Each step spells out its request inline so the flow can be read and executed
    without opening the underlying OpenAPI description.
  version: 1.0.0
  x-realizes-capability-ids:
  - BC-610.60
  x-capability-derivation:
    method: 'deterministic join: sourceDescriptions -> per-tag OpenAPI -> tag/capability edge. No classification at this step.'
    min_confidence: 0.7
    sources:
    - capability_id: BC-610.60
      capability_name: Artificial Intelligence Management
      spec: amazon-sagemaker-training-jobs-api-openapi.yml
      confidence: 0.85
    model: Turbo EA Capabilities by Vincent Verdet — Turbo EA, https://github.com/vincentmakes/turbo-ea-capabilities, CC BY 4.0
sourceDescriptions:
- name: modelsApi
  url: ../openapi/amazon-sagemaker-models-api-openapi.yml
  type: openapi
- name: trainingJobsApi
  url: ../openapi/amazon-sagemaker-training-jobs-api-openapi.yml
  type: openapi
workflows:
- workflowId: register-latest-completed-training
  summary: Register a model from the most recently completed training job.
  description: >-
    Lists completed training jobs newest-first, describes the top result to get
    its artifact location, and creates a model from those artifacts.
  inputs:
    type: object
    required:
    - modelName
    - inferenceImage
    - executionRoleArn
    properties:
      modelName:
        type: string
        description: A unique name for the model to register.
      inferenceImage:
        type: string
        description: The registry path of the Docker image that contains the inference code.
      executionRoleArn:
        type: string
        description: The ARN of the IAM role SageMaker can assume to access the model artifacts.
  steps:
  - stepId: listCompletedTrainingJobs
    description: >-
      List training jobs filtered to the Completed status and sorted by creation
      time in descending order so the newest completed job is first.
    operationId: ListTrainingJobs
    parameters:
    - name: X-Amz-Target
      in: header
      value: SageMaker.ListTrainingJobs
    requestBody:
      contentType: application/x-amz-json-1.1
      payload:
        StatusEquals: Completed
        SortBy: CreationTime
        SortOrder: Descending
        MaxResults: 1
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      latestTrainingJobName: $response.body#/TrainingJobSummaries/0/TrainingJobName
    onSuccess:
    - name: foundCompletedJob
      type: goto
      stepId: describeTrainingJob
      criteria:
      - context: $response.body
        condition: $.TrainingJobSummaries.length > 0
        type: jsonpath
    - name: noCompletedJob
      type: end
      criteria:
      - context: $response.body
        condition: $.TrainingJobSummaries.length == 0
        type: jsonpath
  - stepId: describeTrainingJob
    description: >-
      Describe the most recent completed training job to read the S3 location of
      its model artifacts.
    operationId: DescribeTrainingJob
    parameters:
    - name: X-Amz-Target
      in: header
      value: SageMaker.DescribeTrainingJob
    requestBody:
      contentType: application/x-amz-json-1.1
      payload:
        TrainingJobName: $steps.listCompletedTrainingJobs.outputs.latestTrainingJobName
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      trainingJobStatus: $response.body#/TrainingJobStatus
      modelArtifacts: $response.body#/ModelArtifacts/S3ModelArtifacts
  - stepId: createModel
    description: >-
      Register a model from the inference container and the artifacts produced by
      the completed training job.
    operationId: CreateModel
    parameters:
    - name: X-Amz-Target
      in: header
      value: SageMaker.CreateModel
    requestBody:
      contentType: application/x-amz-json-1.1
      payload:
        ModelName: $inputs.modelName
        PrimaryContainer:
          Image: $inputs.inferenceImage
          ModelDataUrl: $steps.describeTrainingJob.outputs.modelArtifacts
        ExecutionRoleArn: $inputs.executionRoleArn
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      modelArn: $response.body#/ModelArn
  outputs:
    latestTrainingJobName: $steps.listCompletedTrainingJobs.outputs.latestTrainingJobName
    modelArtifacts: $steps.describeTrainingJob.outputs.modelArtifacts
    modelArn: $steps.createModel.outputs.modelArn