API Evangelist conversational phrasing for Elk Stack Ml API

# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Elk Stack Ml API
  version: 1.0.0
extends: openapi/elk-stack-ml-api-openapi.yml
actions:
- target: $.info
  update:
    x-apievangelist-phrasing:
      method: generated
      generated: '2026-09-26'
      generator: build-phrasing.py
      label: Generated by API Evangelist
      operations: 7
- target: $.paths['/_ml/memory/_stats'].get
  update:
    x-apievangelist-phrasing:
      intent: Get ML memory usage across all nodes
      effect: read
      questions:
      - How much memory are my machine learning jobs and models using across the cluster?
      - Can I see ML memory use both inside and outside the JVM heap for every node?
      instructions:
      - text: Show machine learning memory usage for all nodes.
      - text: Get cluster-wide ML memory stats with a timeout of {timeout}.
        slots:
          timeout: query.timeout
      method: generated
      generated: '2026-09-26'
- target: $.paths['/_ml/memory/{node_id}/_stats'].get
  update:
    x-apievangelist-phrasing:
      intent: Get ML memory usage for one node
      effect: read
      questions:
      - How much memory is machine learning using on a specific node?
      - Can I check ML native memory for just one node?
      instructions:
      - text: Show machine learning memory usage on node {node_id}.
        slots:
          node_id: path.node_id
      - text: Get ML memory stats for node {node_id} only.
        slots:
          node_id: path.node_id
      method: generated
      generated: '2026-09-26'
- target: $.paths['/_ml/info'].get
  update:
    x-apievangelist-phrasing:
      intent: Get machine learning defaults and limits
      effect: read
      questions:
      - What are the default settings and limits for machine learning jobs?
      - What is the maximum ML job size my cluster can run?
      instructions:
      - text: Get the machine learning defaults and limits.
      - text: Show the ML configuration defaults for this cluster.
      method: generated
      generated: '2026-09-26'
- target: $.paths['/_ml/set_upgrade_mode'].post
  update:
    x-apievangelist-phrasing:
      intent: Toggle ML upgrade mode
      effect: write
      questions:
      - How do I pause all machine learning jobs before upgrading my cluster?
      - Does enabling ML upgrade mode stop new jobs from opening?
      instructions:
      - text: Set machine learning upgrade mode to {enabled}.
        slots:
          enabled: query.enabled
      - text: Turn off ML upgrade mode, waiting up to {timeout}.
        slots:
          timeout: query.timeout
      method: generated
      generated: '2026-09-26'
- target: $.paths['/api/ml/saved_objects/sync'].get
  update:
    x-apievangelist-phrasing:
      intent: Sync ML saved objects in the default space
      effect: write
      questions:
      - How do I fix machine learning jobs that are missing from Kibana's saved objects?
      - Can I preview what an ML saved object sync would change?
      instructions:
      - text: Sync machine learning saved objects in the default space.
      - text: Run the ML saved object sync with simulate set to {simulate}.
        slots:
          simulate: query.simulate
      method: generated
      generated: '2026-09-26'
- target: $.paths['/api/ml/saved_objects/update_jobs_spaces'].post
  update:
    x-apievangelist-phrasing:
      intent: Change which spaces ML jobs belong to
      effect: write
      questions:
      - How do I share a machine learning job with another Kibana space?
      - Can I remove anomaly detection jobs from a space?
      instructions:
      - text: Add these machine learning jobs to the listed spaces.
      - text: Remove these ML jobs from the given spaces.
      method: generated
      generated: '2026-09-26'
- target: $.paths['/api/ml/saved_objects/update_trained_models_spaces'].post
  update:
    x-apievangelist-phrasing:
      intent: Change which spaces trained models belong to
      effect: write
      questions:
      - How do I make a trained model available in another Kibana space?
      - Can I remove a trained model from a space?
      instructions:
      - text: Add these trained models to the listed spaces.
      - text: Remove these trained models from the given spaces.
      method: generated
      generated: '2026-09-26'