# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Hugging Face Inference Computer Vision API
  version: 1.0.0
extends: openapi/hugging-face-computer-vision-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: 2
- target: $.paths['/models/{model_id}/image-classification'].post
  update:
    x-apievangelist-phrasing:
      intent: Classify an image into categories
      effect: write
      questions:
      - Can I find out what an image shows by sending its URL to an image classification model?
      - What labels and confidence scores does image classification return for a picture?
      instructions:
      - text: Classify the image at {inputs} with model {model_id}.
        slots:
          inputs: requestBody.inputs
          model_id: path.model_id
      - text: Tell me what category this picture falls into using {model_id}.
        slots:
          model_id: path.model_id
      method: generated
      generated: '2026-10-01'
- target: $.paths['/models/{model_id}/object-detection'].post
  update:
    x-apievangelist-phrasing:
      intent: Detect objects and bounding boxes in an image
      effect: write
      questions:
      - Can a Hugging Face model find every object in a photo and tell me where each one is?
      - Which inference task returns bounding boxes with labels rather than a single category?
      instructions:
      - text: Detect the objects in this photo using model {model_id} and give me their bounding boxes.
        slots:
          model_id: path.model_id
      - text: Run object detection with {model_id} and list each label it finds with its box.
        slots:
          model_id: path.model_id
      method: generated
      generated: '2026-10-01'