# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Cortex Embed API
  version: 1.0.0
extends: openapi/snowflake-cortex-embed-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: 1
- target: $.paths['/api/v2/cortex/inference:embed'].post
  update:
    x-apievangelist-phrasing:
      intent: Generate text embeddings
      effect: read
      questions:
      - How do I turn text into vector embeddings with Snowflake Cortex?
      - Which embedding models can I choose, like the 768 or 1024 dimension ones?
      - Can I use provisioned throughput when generating embeddings?
      instructions:
      - text: Embed the text {text} using model {model}.
        slots:
          text: requestBody.text
          model: requestBody.model
      - text: Generate {model} embeddings for {text} on provisioned throughput {provisioned_throughput_id}.
        slots:
          model: requestBody.model
          text: requestBody.text
          provisioned_throughput_id: requestBody.provisioned_throughput_id
      method: generated
      generated: '2026-10-01'