结构化输出

ZenMux 提供结构化输出功能，确保模型响应严格遵循您定义的JSON Schema格式。 当您有固定的结构化数据需求时，您可以用到此功能！

参数

response_format

• 设置{ "type": "json_object" }, 输出是有效的 JSON 格式，但不保证特定的结构或字段。
• 设置{ "type": "json_schema", "json_schema": {...} }, 更严格的控制 JSON 输出结构, 提供更强的类型和结构保证

1. 设置 json_object 模式

输入结构：

{
  "response_format": {
    "type": "json_object"
  }
}

输出结构: content 会返回有效的 JSON 格式内容

{
    "model": "openai/gpt-5-nano",
    "choices": [
        {
            "message": {
                // 实际content为json字符串，这个为了可读性，展示为json
                "content": {
                    "description": "I am ChatGPT, an AI assistant built by OpenAI. I help answer questions, brainstorm ideas, draft text, explain concepts, debug code, and learn topics. I use patterns from training data to generate helpful, clear responses while recognizing limits and inviting follow-up questions. I adapt tone and detail to your needs."
                }
            }
            ....
        }
    ]
    ....
}

2. 设置 json_schema 模式

输入按照标准的 JSON Schema 格式定义好

{
  "response_format": {
    "type": "json_schema",
    // 标准的json_schema数据
    "json_schema": {
      "name": "role",
      "description": "Introduce yourself",
      "schema": {
        "type": "object",
        "description": "Your messages",
        "properties": {
          "name": {
            "type": "string",
            "description": "your name"
          },
          "city": {
            "type": "string",
            "description": "where your city"
          },
          "desc": {
            "type": "string",
            "description": "description"
          }
        },
        "required": ["name", "city", "desc"],
        "additionalProperties": false
      }
    }
  }
}

输出的 content 会按照指定的 schema 格式返回 JSON 数据

{
    "model": "openai/gpt-5-nano",
    "choices": [
        {
            "message": {
                // 实际content为json字符串，这个为了可读性，展示为json
                "content": {
                    "name": "ChatGPT",
                    "city": "Internet",
                    "desc": "I am ChatGPT, an AI language model created by OpenAI. I help with questions, ideas, writing, and problem-solving. I learn from patterns in text and aim to be helpful, accurate, and respectful. I don't have personal experiences, but I strive to understand your needs and respond clearly and kindly today."
                }
                ...
            }
        }
    ],
    ...
}

支持的模型

在模型卡片页面找到对应供应商，查看支持参数中是否有 response_format, 如下图所示：

API 调用示例

Python

from openai import OpenAI

# 1. 初始化 OpenAI 客户端
client = OpenAI(
    # 2. 将基础 URL 指向 ZenMux 端点
    base_url="https://zenmux.ai/api/v1", 
    # 3. 替换为你从 ZenMux 用户控制台获取的 API Key
    api_key="<你的 ZENMUX_API_KEY>", 
)

# 4. 发起请求
completion = client.chat.completions.create(
    # 5. 指定你想使用的模型，格式为 "供应商/模型名称"
    model="openai/gpt-5", 
    messages=[
        {
            "role": "user",
            "content": "Hi, who are you? Describe yourself using about 50 words. Use JSON response format?"
        }
    ],
    # 方式一: 输出是有效的JSON格式，但不保证特定的结构或字段。
    # response_format = {
    #      "type": "json_object"
    #  }
    # 方式二: 更严格地控制 JSON 输出结构，提供更强的类型和结构保证
    response_format = { 
        "type": "json_schema", 
        "json_schema": {
            "name": "role",
            "description": "Introduce yourself",
            "schema": {
                "type": "object",
                "description": "Your messages",
                "properties": {
                    "name": {
                        "type": "string",
                        "description": "your name"
                    },
                    "city": {
                        "type": "string",
                        "description": "where your city"
                    },
                    "desc": {
                        "type": "string",
                        "description": "description"
                    }
                },
                "required": ["name", "city", "desc"],
                "additionalProperties": False
            }
        }
    }
)

print(completion.choices[0].message.content)

TypeScript

import OpenAI from "openai";

// 1. 初始化 OpenAI 客户端
const openai = new OpenAI({
  // 2. 将基础 URL 指向 ZenMux 端点
  baseURL: "https://zenmux.ai/api/v1", 
  // 3. 替换为你从 ZenMux 用户控制台获取的 API Key
  apiKey = "<你的 ZENMUX_API_KEY>", 
});

async function main() {
  // 4. 发起请求
  const completion = await openai.chat.completions.create({
    // 5. 指定你想使用的模型，格式为 "供应商/模型名称"
    model: "openai/gpt-5",
    messages: [
      {
        role: "user",
        content:
          "Hi, who are you? Describe yourself using about 50 words. Use JSON response format?",
      },
    ],
    // 方式一: 输出是有效的JSON格式，但不保证特定的结构或字段。
    // response_format: {
    //     "type": "json_object"
    // }
    // 方式二: 更严格地控制 JSON 输出结构，提供更强的类型和结构保证
    response_format: {
      type: "json_schema", 
      json_schema: {
        name: "role",
        description: "Introduce yourself",
        schema: {
          type: "object",
          description: "Your messages",
          properties: {
            name: {
              type: "string",
              description: "your name",
            },
            city: {
              type: "string",
              description: "where your city",
            },
            desc: {
              type: "string",
              description: "description",
            },
          },
          required: ["name", "city", "desc"],
          additionalProperties: false,
        },
      },
    },
  });

  console.log(completion.choices[0].message.content);
}

main();