Vercel Generate App Then Explain Code

arazzo: 1.0.1
info:
  title: Vercel Generate App Then Explain Code
  summary: Generate an app with v0, fetch its files, then explain the code via the AI Gateway.
  description: >-
    A cross-API flow that links the v0 Platform generation pipeline with the AI
    Gateway chat endpoint. The workflow creates a v0 chat from a prompt, reads the
    chat back to capture the generated files, and then asks a model through the
    Vercel AI Gateway to explain the generated code. It chains three real
    operations across two Vercel APIs, each carrying its own Bearer token. Every
    step inlines its request and documents the success status.
  version: 1.0.0
sourceDescriptions:
- name: v0PlatformApi
  url: ../openapi/vercel-v0-platform-openapi.yml
  type: openapi
- name: aiGatewayApi
  url: ../openapi/vercel-ai-gateway-openapi.yml
  type: openapi
workflows:
- workflowId: generateAppThenExplainCode
  summary: Generate a v0 app, capture its files, then explain the code with the AI Gateway.
  description: >-
    Creates a v0 chat from a prompt, reads back the generated files, and asks an AI
    Gateway chat model to explain the generated code, returning the explanation.
  inputs:
    type: object
    required:
    - v0ApiKey
    - gatewayApiKey
    - message
    - chatModel
    properties:
      v0ApiKey:
        type: string
        description: v0 API key (V0_API_KEY) used as a Bearer token for the v0 Platform API.
      gatewayApiKey:
        type: string
        description: AI Gateway API key (AI_GATEWAY_API_KEY) used as a Bearer token for the gateway.
      message:
        type: string
        description: Natural language prompt describing the app to generate.
      chatModel:
        type: string
        description: "AI Gateway chat model id in 'provider/model-name' form."
  steps:
  - stepId: createChat
    description: Start a new v0 chat session to generate the application.
    operationId: createChat
    parameters:
    - name: Authorization
      in: header
      value: Bearer $inputs.v0ApiKey
    requestBody:
      contentType: application/json
      payload:
        message: $inputs.message
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      chatId: $response.body#/id
  - stepId: getFiles
    description: Read the chat back to capture the generated code files.
    operationId: getChat
    parameters:
    - name: chatId
      in: path
      value: $steps.createChat.outputs.chatId
    - name: Authorization
      in: header
      value: Bearer $inputs.v0ApiKey
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      firstFilePath: $response.body#/files/0/path
      firstFileContent: $response.body#/files/0/content
  - stepId: explainCode
    description: >-
      Ask an AI Gateway chat model to explain the first generated code file.
    operationId: createChatCompletion
    parameters:
    - name: Authorization
      in: header
      value: Bearer $inputs.gatewayApiKey
    requestBody:
      contentType: application/json
      payload:
        model: $inputs.chatModel
        messages:
        - role: system
          content: You are a senior engineer who explains source code clearly and concisely.
        - role: user
          content: $steps.getFiles.outputs.firstFileContent
        stream: false
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      explanation: $response.body#/choices/0/message/content
      totalTokens: $response.body#/usage/total_tokens
  outputs:
    chatId: $steps.createChat.outputs.chatId
    filePath: $steps.getFiles.outputs.firstFilePath
    explanation: $steps.explainCode.outputs.explanation