Python SDK 使用指南

ClawdRouter 兼容 OpenAI Python SDK 和 Anthropic Python SDK，你可以根据需要选择使用。

OpenAI SDK

安装

pip install openai

初始化客户端

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.clawdrouter.com/v1",
)

环境变量

建议通过环境变量管理 API Key，避免在代码中硬编码：

export OPENAI_API_KEY="YOUR_API_KEY"
export OPENAI_BASE_URL="https://api.clawdrouter.com/v1"

# 会自动读取环境变量
client = OpenAI()

基础对话

completion = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "你是一个有用的助手"},
        {"role": "user", "content": "用简单的话解释什么是机器学习"},
    ],
)

print(completion.choices[0].message.content)

流式输出

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "写一篇关于人工智能的短文"},
    ],
    stream=True,
)

for chunk in stream:
    content = chunk.choices[0].delta.content
    if content is not None:
        print(content, end="", flush=True)
print()  # 换行

多轮对话

messages = [
    {"role": "system", "content": "你是一个有用的助手"},
]

def chat(user_input):
    messages.append({"role": "user", "content": user_input})

    completion = client.chat.completions.create(
        model="gpt-4o",
        messages=messages,
    )

    reply = completion.choices[0].message.content
    messages.append({"role": "assistant", "content": reply})
    return reply

# 多轮对话
print(chat("什么是量子计算？"))
print(chat("它和传统计算有什么区别？"))
print(chat("目前有哪些实际应用？"))

异步调用

import asyncio
from openai import AsyncOpenAI

client = AsyncOpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.clawdrouter.com/v1",
)

async def main():
    completion = await client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "user", "content": "你好"},
        ],
    )
    print(completion.choices[0].message.content)

asyncio.run(main())

工具调用 (Function Calling)

import json

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "获取指定城市的天气信息",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {
                        "type": "string",
                        "description": "城市名称，如 北京",
                    },
                },
                "required": ["city"],
            },
        },
    }
]

completion = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "user", "content": "北京今天天气怎么样？"},
    ],
    tools=tools,
    tool_choice="auto",
)

message = completion.choices[0].message

if message.tool_calls:
    tool_call = message.tool_calls[0]
    print(f"调用工具: {tool_call.function.name}")
    print(f"参数: {tool_call.function.arguments}")

错误处理

from openai import (
    APIError,
    AuthenticationError,
    RateLimitError,
)

try:
    completion = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": "你好"}],
    )
except AuthenticationError:
    print("API Key 无效，请检查配置")
except RateLimitError:
    print("请求频率超限，请稍后重试")
except APIError as e:
    print(f"API 错误: {e.message}")

---

Anthropic SDK

如果你需要使用 Anthropic 原生协议 (/v1/messages) 调用 Claude 模型，可以使用 Anthropic Python SDK。

安装

pip install anthropic

初始化客户端

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_API_KEY",
    base_url="https://api.clawdrouter.com",
)

环境变量

export ANTHROPIC_API_KEY="YOUR_API_KEY"
export ANTHROPIC_BASE_URL="https://api.clawdrouter.com"

client = anthropic.Anthropic()

基础对话

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "用简单的话解释什么是机器学习"},
    ],
)

print(message.content[0].text)

带系统提示词

message = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    system="你是一个专业的技术文档撰写专家。",
    messages=[
        {"role": "user", "content": "帮我写一段 API 错误处理的最佳实践"},
    ],
)

print(message.content[0].text)

流式输出

with client.messages.stream(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "写一篇关于人工智能的短文"},
    ],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)
print()

异步调用

import asyncio
from anthropic import AsyncAnthropic

client = AsyncAnthropic(
    api_key="YOUR_API_KEY",
    base_url="https://api.clawdrouter.com",
)

async def main():
    message = await client.messages.create(
        model="claude-sonnet-4-6",
        max_tokens=1024,
        messages=[
            {"role": "user", "content": "你好"},
        ],
    )
    print(message.content[0].text)

asyncio.run(main())

错误处理

from anthropic import (
    APIError,
    AuthenticationError,
    RateLimitError,
)

try:
    message = client.messages.create(
        model="claude-sonnet-4-6",
        max_tokens=1024,
        messages=[{"role": "user", "content": "你好"}],
    )
except AuthenticationError:
    print("API Key 无效，请检查配置")
except RateLimitError:
    print("请求频率超限，请稍后重试")
except APIError as e:
    print(f"API 错误: {e.message}")