Chat Completions

兼容 OpenAI 的大模型对话端点。支持流式输出和工具调用。可无缝替换：只需修改 base URL 和 API 密钥。

#请求体

参数	类型	必填	说明
`model`	string	是	你的密钥模型列表中的模型 ID
`messages`	array	是	由 {role, content} 对象组成的数组。角色：system \| user \| assistant
`temperature`	number	否	采样温度，取值 0 到 2。默认值：1
`max_tokens`	integer	否	生成的最大 token 数。省略时采用模型上限
`stream`	boolean	否	若为 true，则通过 SSE 流式返回 token。默认值：false
`top_p`	number	否	核采样，可作为 temperature 的替代
`stop`	string \| array	否	最多 4 个停止序列
`tools`	array	否	用于函数调用的 OpenAI tool-use schema

#请求示例

terminalbash

curl https://relayrouter.io/v1/chat/completions \
  -H "Authorization: Bearer $RELAYROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4-flash",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user",   "content": "Explain quantum computing in 2 sentences."}
    ],
    "temperature": 0.7,
    "max_tokens": 256
  }'

#响应（非流式）

response.jsonjson

{
  "id":      "chatcmpl-abc123",
  "object":  "chat.completion",
  "created": 1749300000,
  "model":   "deepseek-v4-flash",
  "choices": [
    {
      "index":         0,
      "message":       { "role": "assistant", "content": "Quantum computing uses quantum bits..." },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens":     32,
    "completion_tokens": 48,
    "total_tokens":      80
  }
}

#流式输出

设置 stream: true 即可以 Server-Sent Events 的形式接收 token：

stream_response.txttext

data: {"id":"chatcmpl-abc123","choices":[{"delta":{"content":"Quantum"},"index":0}]}
data: {"id":"chatcmpl-abc123","choices":[{"delta":{"content":" computing"},"index":0}]}
...
data: [DONE]

#工具调用

tools.jsonjson

{
  "model": "deepseek-v4-flash",
  "messages": [{"role": "user", "content": "What's the weather in Tokyo?"}],
  "tools": [
    {
      "type": "function",
      "function": {
        "name":        "get_weather",
        "description": "Get the current weather for a location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {"type": "string", "description": "City name"}
          },
          "required": ["location"]
        }
      }
    }
  ]
}

不同模型对工具调用和参数的支持有所不同。上游会忽略不支持的参数。

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