chat/completions 和 completions 是 OpenAI API 中的两个不同的端点，它们提供了不同的功能和交互模式。以下是它们的主要区别：
completions 端点
用途:
主要用于生成文本补全。你提供一个提示（prompt），模型会基于这个提示生成后续的文本。交互模式:
单次请求-响应模式。你发送一个提示，模型返回一个补全结果。适用场景:
适用于需要连续生成文本的场景，如编写文章、代码补全、生成故事等。示例请求:
{ "model": "text-davinci-003", "prompt": "Once upon a time, in a land far, far away,", "max_tokens": 100}示例响应:
{ "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 端点
用途:
主要用于对话生成。你提供一系列对话消息，模型会基于这些消息生成下一条回复。交互模式:
多轮对话模式。你可以提供一个包含多轮对话的消息列表，模型会基于整个对话上下文生成回复。适用场景:
适用于需要多轮对话的场景，如聊天机器人、客户服务、对话系统等。示例请求:
{ "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?"} ]}示例响应:
{ "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 }}总结
completions 端点适用于单次文本补全任务，通常用于连续文本生成。chat/completions 端点适用于多轮对话生成任务，提供更自然的对话体验。 选择哪个端点取决于你的具体需求。
如果你需要生成连续的文本，completions 端点可能更合适。如果你需要处理多轮对话，chat/completions 端点会更适合。