# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Microsoft Azure Computer Vision Client Image Retrieval API
  version: 1.0.0
extends: openapi/microsoft-azure-imageretrieval-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: 2
- target: $.paths['/retrieval:vectorizeText'].post
  update:
    x-apievangelist-phrasing:
      intent: Get a vector embedding for text
      effect: read
      questions:
      - How do I turn a search phrase into a vector for multimodal image retrieval?
      - Can I embed text so it can be compared with image vectors?
      instructions:
      - text: Vectorize the text {text}.
        slots:
          text: requestBody.text
      - text: Create a text embedding for {text} using model version {model_version}.
        slots:
          text: requestBody.text
          model_version: query.model-version
      method: generated
      generated: '2026-09-26'
- target: $.paths['/retrieval:vectorizeImage'].post
  update:
    x-apievangelist-phrasing:
      intent: Get a vector embedding for an image
      effect: read
      questions:
      - How do I get an embedding vector for an image at a URL?
      - Can I vectorize a picture so I can search it with text queries?
      instructions:
      - text: Vectorize the image at {url}.
        slots:
          url: requestBody.url
      - text: Generate an image embedding for {url} with model version {model_version}.
        slots:
          url: requestBody.url
          model_version: query.model-version
      method: generated
      generated: '2026-09-26'