# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Cloudflare Workers AI OpenAI Compatible API
  version: 1.0.0
extends: openapi/cloudflare-openai-compatible-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['/accounts/{account_id}/ai/v1/chat/completions'].post
  update:
    x-apievangelist-phrasing:
      intent: Generate a chat completion
      effect: write
      questions:
      - How do I send a list of chat messages to a Workers AI model and get a reply?
      - Can I stream a chat response back as server-sent events?
      - Which temperature range does the chat completions endpoint accept?
      instructions:
      - text: Send chat messages {messages} to model {model} and return the reply.
        slots:
          messages: requestBody.messages
          model: requestBody.model
      - text: In account {account}, run a streaming chat completion on {model} for {messages}, capped at {max_tokens} tokens.
        slots:
          account: path.account_id
          model: requestBody.model
          messages: requestBody.messages
          max_tokens: requestBody.max_tokens
      method: generated
      generated: '2026-09-26'
- target: $.paths['/accounts/{account_id}/ai/v1/completions'].post
  update:
    x-apievangelist-phrasing:
      intent: Complete a text prompt
      effect: write
      questions:
      - How do I have a model continue a plain text prompt rather than a chat?
      - Can I limit how many tokens a prompt continuation generates?
      instructions:
      - text: Continue the prompt {prompt} using model {model}.
        slots:
          prompt: requestBody.prompt
          model: requestBody.model
      - text: Generate a text completion of {prompt} in account {account} with temperature {temperature}.
        slots:
          account: path.account_id
          prompt: requestBody.prompt
          temperature: requestBody.temperature
      method: generated
      generated: '2026-09-26'
- target: $.paths['/accounts/{account_id}/ai/v1/embeddings'].post
  update:
    x-apievangelist-phrasing:
      intent: Create text embeddings
      effect: write
      questions:
      - How do I turn text into vectors for semantic search?
      - Can I embed a whole array of texts in a single request?
      instructions:
      - text: Create embeddings for {input} with model {model}.
        slots:
          input: requestBody.input
          model: requestBody.model
      - text: Convert {input} into embedding vectors in account {account} for a similarity search.
        slots:
          account: path.account_id
          input: requestBody.input
      method: generated
      generated: '2026-09-26'
- target: $.paths['/accounts/{account_id}/ai/v1/responses'].post
  update:
    x-apievangelist-phrasing:
      intent: Generate a model response
      effect: write
      questions:
      - Is there a responses endpoint that supports tool use and structured output?
      - Can I get a model response with structured output from a single input text?
      instructions:
      - text: Generate a response from model {model} for input {input} using the responses endpoint.
        slots:
          model: requestBody.model
          input: requestBody.input
      - text: Call the responses API in account {account} with input {input}.
        slots:
          account: path.account_id
          input: requestBody.input
      method: generated
      generated: '2026-09-26'