API Evangelist conversational phrasing for Dify Service Knowledge Pipeline API

# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Dify Service Knowledge Pipeline API
  version: 1.0.0
extends: openapi/dify-knowledge-pipeline-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: 4
- target: $.paths['/datasets/pipeline/file-upload'].post
  update:
    x-apievangelist-phrasing:
      intent: Upload a file for a knowledge pipeline run
      effect: write
      questions:
      - How do I upload a local file to feed into a knowledge pipeline?
      - What size limit applies to documents uploaded for a pipeline?
      instructions:
      - text: Upload {file} for use in a knowledge pipeline run.
        slots:
          file: requestBody.file
      - text: Upload pipeline input file {file} and return its reference ID.
        slots:
          file: requestBody.file
      method: generated
      generated: '2026-09-26'
- target: $.paths['/datasets/{dataset_id}/pipeline/datasource-plugins'].get
  update:
    x-apievangelist-phrasing:
      intent: List a pipeline's datasource nodes and plugins
      effect: read
      questions:
      - Which datasource nodes and plugins are configured in my knowledge pipeline?
      - Can I see the datasource nodes from the published pipeline instead of the draft?
      instructions:
      - text: List the datasource plugins in the pipeline of knowledge base {dataset_id}.
        slots:
          dataset_id: path.dataset_id
      - text: Show datasource nodes for {dataset_id} from the published version {is_published}.
        slots:
          dataset_id: path.dataset_id
          is_published: query.is_published
      method: generated
      generated: '2026-09-26'
- target: $.paths['/datasets/{dataset_id}/pipeline/datasource/nodes/{node_id}/run'].post
  update:
    x-apievangelist-phrasing:
      intent: Run a single datasource node in a pipeline
      effect: write
      questions:
      - Can I test just one datasource node of my knowledge pipeline on its own?
      - Which credential does a datasource node use when I run it individually?
      instructions:
      - text: Run datasource node {node_id} in knowledge base {dataset_id} with inputs {inputs}, type {datasource_type}, published {is_published}.
        slots:
          node_id: path.node_id
          dataset_id: path.dataset_id
          inputs: requestBody.inputs
          datasource_type: requestBody.datasource_type
          is_published: requestBody.is_published
      - text: Execute only node {node_id} of {dataset_id}'s pipeline using credential {credential_id}.
        slots:
          node_id: path.node_id
          dataset_id: path.dataset_id
          credential_id: requestBody.credential_id
      method: generated
      generated: '2026-09-26'
- target: $.paths['/datasets/{dataset_id}/pipeline/run'].post
  update:
    x-apievangelist-phrasing:
      intent: Run the full knowledge pipeline
      effect: write
      questions:
      - How do I run my whole knowledge pipeline over a set of datasources?
      - Can I run the draft pipeline to test unpublished changes?
      instructions:
      - text: Run the knowledge pipeline for {dataset_id} from node {start_node_id} over {datasource_info_list} of type {datasource_type}.
        slots:
          dataset_id: path.dataset_id
          start_node_id: requestBody.start_node_id
          datasource_info_list: requestBody.datasource_info_list
          datasource_type: requestBody.datasource_type
      - text: Execute the pipeline of {dataset_id} in {response_mode} mode, published {is_published}, with inputs {inputs}.
        slots:
          dataset_id: path.dataset_id
          response_mode: requestBody.response_mode
          is_published: requestBody.is_published
          inputs: requestBody.inputs
      method: generated
      generated: '2026-09-26'