# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Amazon Neptune Neptune ML Model Training API
  version: 1.0.0
extends: openapi/amazon-neptune-model-training-api-openapi.yml
actions:
- target: $.info
  update:
    x-apievangelist-phrasing:
      method: generated
      generated: '2026-10-01'
      generator: build-phrasing.py
      label: Generated by API Evangelist
      operations: 4
- target: $.paths['/ml/modeltraining'].get
  update:
    x-apievangelist-phrasing:
      intent: List active model training jobs
      effect: read
      questions:
      - Which Neptune ML model training jobs are active right now?
      - Can I limit the number of training job IDs returned?
      instructions:
      - text: List my active model training jobs.
      - text: Show up to {max} active training job IDs.
        slots:
          max: query.maxItems
      method: generated
      generated: '2026-10-01'
- target: $.paths['/ml/modeltraining'].post
  update:
    x-apievangelist-phrasing:
      intent: Train a graph neural network model
      effect: write
      questions:
      - How do I train a graph neural network on data from a finished processing job?
      - Can I run hyperparameter tuning with several parallel training jobs?
      - Is managed spot training available for Neptune ML model training?
      instructions:
      - text: Create a training job from processing job {processing_job} with output at {s3}.
        slots:
          processing_job: requestBody.dataProcessingJobId
          s3: requestBody.trainModelS3Location
      - text: Train a model from {processing_job} to {s3}, running at most {max_hpo} tuning jobs.
        slots:
          processing_job: requestBody.dataProcessingJobId
          s3: requestBody.trainModelS3Location
          max_hpo: requestBody.maxHPONumberOfTrainingJobs
      method: generated
      generated: '2026-10-01'
- target: $.paths['/ml/modeltraining/{id}'].get
  update:
    x-apievangelist-phrasing:
      intent: Check a model training job's status
      effect: read
      questions:
      - Is my graph model still training?
      - What's the current state of a particular model training job?
      instructions:
      - text: Get the status of training job {id}.
        slots:
          id: path.id
      - text: Tell me whether model training job {id} has finished.
        slots:
          id: path.id
      method: generated
      generated: '2026-10-01'
- target: $.paths['/ml/modeltraining/{id}'].delete
  update:
    x-apievangelist-phrasing:
      intent: Stop a model training job
      effect: destructive
      questions:
      - Can I stop a model training job that is running too long?
      - Will stopping a training job delete its S3 artifacts?
      instructions:
      - text: Stop model training job {id}.
        slots:
          id: path.id
      - text: Stop training job {id} and set clean to {clean}.
        slots:
          id: path.id
          clean: query.clean
      method: generated
      generated: '2026-10-01'