大模型chat/completions和completions區(qū)別解析

更新時間：2025年03月04日 09:50:58 作者：sdbhewfoqi

OpenAI的completions和chat/completions是兩個不同的端點,completions用于單次文本補全,而chat/completions用于多輪對話生成,選擇哪個端點取決于你的具體需求,本文介紹大模型chat/completions和completions區(qū)別,感興趣的朋友一起看看吧

completions 端點

用途:

主要用于生成文本補全。你提供一個提示（prompt），模型會基于這個提示生成后續(xù)的文本。

交互模式:

單次請求-響應模式。你發(fā)送一個提示，模型返回一個補全結果。

適用場景:

適用于需要連續(xù)生成文本的場景，如編寫文章、代碼補全、生成故事等。

示例請求:

{
    "model": "text-davinci-003",
    "prompt": "Once upon a time, in a land far, far away,",
    "max_tokens": 100
}

示例響應:

{
    "id": "cmpl-5eU3oZz1w9Q8Jt3B3o5Q5Z5Z1",
    "object": "text_completion",
    "created": 1609459200,
    "model": "text-davinci-003",
    "choices": [
        {
            "text": " there lived a wise old owl who knew all the secrets of the forest...",
            "index": 0,
            "logprobs": null,
            "finish_reason": "length"
        }
    ],
    "usage": {
        "prompt_tokens": 10,
        "completion_tokens": 100,
        "total_tokens": 110
    }
}

chat/completions 端點

用途:

主要用于對話生成。你提供一系列對話消息，模型會基于這些消息生成下一條回復。

交互模式:

多輪對話模式。你可以提供一個包含多輪對話的消息列表，模型會基于整個對話上下文生成回復。

適用場景:

適用于需要多輪對話的場景，如聊天機器人、客戶服務、對話系統(tǒng)等。

示例請求:

{
    "model": "gpt-4",
    "messages": [
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Who won the world series in 2020?"},
        {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
        {"role": "user", "content": "Where was it played?"}
    ]
}

示例響應:

{
    "id": "chatcmpl-5eU3oZz1w9Q8Jt3B3o5Q5Z5Z1",
    "object": "chat.completion",
    "created": 1609459200,
    "model": "gpt-4",
    "choices": [
        {
            "message": {
                "role": "assistant",
                "content": "The 2020 World Series was played at Globe Life Field in Arlington, Texas."
            },
            "index": 0,
            "finish_reason": "stop"
        }
    ],
    "usage": {
        "prompt_tokens": 50,
        "completion_tokens": 20,
        "total_tokens": 70
    }
}