对话补全

POST https://gateway.mytokengate.com/v1/chat/completions

curl --request POST \
  --url https://gateway.mytokengate.com/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-4o",
    "messages": [
      {
        "role": "user",
        "content": "中国大模型行业2025年将会迎来哪些机遇和挑战？"
      }
    ]
  }'

Authorization: Bearer YOUR_API_KEY

{ "role": "system", "content": "You are a helpful assistant." }

{ "role": "developer", "content": "You are a coding expert." }

{ "role": "user", "content": "你好！" }

{
  "role": "user",
  "content": [
    { "type": "text", "text": "这张图片里有什么？" },
    {
      "type": "image_url",
      "image_url": {
        "url": "https://example.com/photo.jpg",
        "detail": "auto"
      }
    }
  ]
}

{
  "role": "assistant",
  "content": null,
  "tool_calls": [
    {
      "id": "call_abc123",
      "type": "function",
      "function": {
        "name": "get_weather",
        "arguments": "{\"location\": \"Paris\"}"
      }
    }
  ]
}

{
  "role": "tool",
  "tool_call_id": "call_abc123",
  "content": "巴黎今天22°C，晴天"
}

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1677858242,
  "model": "gpt-4o",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "响应内容...",
        "tool_calls": [
          {
            "id": "call_abc123",
            "type": "function",
            "function": {
              "name": "function_name",
              "arguments": "{\"arg\": \"value\"}"
            }
          }
        ]
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 123,
    "completion_tokens": 456,
    "total_tokens": 579,
    "prompt_tokens_details": {
      "cached_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 0
    }
  }
}

from openai import OpenAI
 
client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://gateway.mytokengate.com/v1"
)
 
stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "你好！"}],
    stream=True,
    stream_options={"include_usage": True}
)
 
for chunk in stream:
    delta = chunk.choices[0].delta
    if delta.content:
        print(delta.content, end="")

{
  "id": "chatcmpl-abc",
  "object": "chat.completion.chunk",
  "created": 1234,
  "model": "gpt-4o",
  "choices": [
    {
      "index": 0,
      "delta": {
        "role": "assistant",
        "content": "token text"
      },
      "finish_reason": null
    }
  ]
}

data: [DONE]

for chunk in stream:
    delta = chunk.choices[0].delta
    if getattr(delta, "reasoning_content", None):
        # 推理/思考内容
        print(f"[思考] {delta.reasoning_content}")
    if delta.content:
        # 最终响应文本
        print(delta.content, end="")

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "获取指定城市的当前天气",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {
                        "type": "string",
                        "description": "城市名称"
                    }
                },
                "required": ["city"]
            }
        }
    }
]
 
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "巴黎天气怎么样？"}],
    tools=tools
)
 
# 提取工具调用
tool_call = response.choices[0].message.tool_calls[0]
function_name = tool_call.function.name
function_args = json.loads(tool_call.function.arguments)
 
# 执行函数并返回结果
messages.append(response.choices[0].message)
messages.append({
    "role": "tool",
    "tool_call_id": tool_call.id,
    "content": get_weather(**function_args)
})
 
# 继续对话
response = client.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    tools=tools
)