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115 lines
3.7 KiB
Markdown
115 lines
3.7 KiB
Markdown
# API
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- [OpenAI ChatCompletion](#openai-chatcompletion)
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- [Ollama ChatCompletion](#ollama-chatcompletion)
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- [OpenAI Assistant](#openai-assistant)
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## OpenAI ChatCompletion
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```bash
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POST /v1/chat/completions
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```
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根据选定的模型生成回复。
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### 参数
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- `messages`：一个 `message` 的数组所有的历史消息。`message`：表示用户（user）或者模型（assistant）的消息。`message`包含：
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- `role`: 取值`user`或`assistant`，代表这个 message 的创建者。
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- `content`: 用户或者模型的消息。
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- `model`：选定的模型名
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- `stream`：取值 true 或者 false。表示是否使用流式返回。如果为 true，则以 http 的 event stream 的方式返回模型推理结果。
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### 响应
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- 流式返回：一个 event stream，每个 event 含有一个`chat.completion.chunk`。`chunk.choices[0].delta.content`是每次模型返回的增量输出。
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- 非流式返回：还未支持。
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### 例子
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```bash
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curl -X 'POST' \
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'http://localhost:9112/v1/chat/completions' \
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-H 'accept: application/json' \
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-H 'Content-Type: application/json' \
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-d '{
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"messages": [
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{
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"content": "tell a joke",
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"role": "user"
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}
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],
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"model": "Meta-Llama-3-8B-Instruct",
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"stream": true
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}'
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```
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```bash
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data:{"id":"c30445e8-1061-4149-a101-39b8222e79e1","object":"chat.completion.chunk","created":1720511671,"model":"not implmented","system_fingerprint":"not implmented","usage":null,"choices":[{"index":0,"delta":{"content":"Why ","role":"assistant","name":null},"logprobs":null,"finish_reason":null}]}
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data:{"id":"c30445e8-1061-4149-a101-39b8222e79e1","object":"chat.completion.chunk","created":1720511671,"model":"not implmented","system_fingerprint":"not implmented","usage":null,"choices":[{"index":0,"delta":{"content":"","role":"assistant","name":null},"logprobs":null,"finish_reason":null}]}
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data:{"id":"c30445e8-1061-4149-a101-39b8222e79e1","object":"chat.completion.chunk","created":1720511671,"model":"not implmented","system_fingerprint":"not implmented","usage":null,"choices":[{"index":0,"delta":{"content":"couldn't ","role":"assistant","name":null},"logprobs":null,"finish_reason":null}]}
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...
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data:{"id":"c30445e8-1061-4149-a101-39b8222e79e1","object":"chat.completion.chunk","created":1720511671,"model":"not implmented","system_fingerprint":"not implmented","usage":null,"choices":[{"index":0,"delta":{"content":"two-tired!","role":"assistant","name":null},"logprobs":null,"finish_reason":null}]}
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event: done
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data: [DONE]
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```
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## Ollama ChatCompletion
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```bash
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POST /api/generate
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```
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根据选定的模型生成回复。
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### 参数
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- `prompt`：一个字符串，代表输入的 prompt。
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- `model`：选定的模型名
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- `stream`：取值 true 或者 false。表示是否使用流式返回。如果为 true，则以 http 的 event stream 的方式返回模型推理结果。
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### 响应
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- 流式返回：一个流式的 json 返回，每行是一个 json。
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- `response`：模型补全的增量结果。
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- `done`：是否推理结束。
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- 非流式返回：还未支持。
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### 例子
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```bash
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curl -X 'POST' \
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'http://localhost:9112/api/generate' \
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-H 'accept: application/json' \
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-H 'Content-Type: application/json' \
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-d '{
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"model": "Meta-Llama-3-8B-Instruct",
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"prompt": "tell me a joke",
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"stream": true
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}'
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```
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```bash
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{"model":"Meta-Llama-3-8B-Instruct","created_at":"2024-07-09 08:13:11.686513","response":"I'll ","done":false}
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{"model":"Meta-Llama-3-8B-Instruct","created_at":"2024-07-09 08:13:11.729214","response":"give ","done":false}
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...
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{"model":"Meta-Llama-3-8B-Instruct","created_at":"2024-07-09 08:13:33.955475","response":"for","done":false}
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{"model":"Meta-Llama-3-8B-Instruct","created_at":"2024-07-09 08:13:33.956795","response":"","done":true}
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```
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