Setting ChatGPT LLM Responses

开发中

正式环境

https://api.302.ai

POST

/dataforseo/v3/ai_optimization/chat_gpt/llm_responses/task_post

ChatGPT LLM 响应端点允许您根据输入参数从特定的 ChatGPT 模型中获取结构化响应。
这是标准的数据检索方法。如果您不需要实时接收数据，这种方法是您的最佳选择。设置一个任务，并在我们的系统收集结果时检索结果。执行时间取决于系统负载。
如果您的系统需要即时结果，Live 方法将是更好的解决方案。此方法不需要对相应的端点进行单独的 POST 和 GET 请求。

参考：https://docs.dataforseo.com/v3/ai_optimization/chat_gpt/llm_responses/task_post/

价格：cost * 1PTC/次

请求参数

Header 参数

Body 参数application/json必填

示例


  {
    "system_message": "communicate as if we are in a business meeting",
    "message_chain": [
      {
        "role": "user",
        "message": "Hello, what’s up?"
      },
      {
        "role": "ai",
        "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
      }
    ],
    "model_name": "gpt-4.1-mini",
    "user_prompt": "provide information on how relevant the amusement park business is in France now"
  }
]

请求示例代码

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

curl --location --request POST 'https://api.302.ai/dataforseo/v3/ai_optimization/chat_gpt/llm_responses/task_post' \
--header 'Authorization: Bearer ' \
--header 'Content-Type: application/json' \
--data-raw '{
    "system_message": "communicate as if we are in a business meeting",
    "message_chain": [
      {
        "role": "user",
        "message": "Hello, what’s up?"
      },
      {
        "role": "ai",
        "message": "Hello! I’m doing well, thank you. How can I assist you today? Are there any specific topics or projects you’d like to discuss in our meeting?"
      }
    ],
    "model_name": "gpt-4.1-mini",
    "user_prompt": "provide information on how relevant the amusement park business is in France now"
  }
]'

返回响应

🟢200成功

application/json

Body

示例

{}

修改于 2026-03-16 08:03:32

ChatGPT LLM Responses Models List

Get Chat GPT LLM Responses