2026 年国内如何调用 Claude API？Claude Opus / Sonnet 接入完全指南

pip install openai

npm install openai

from openai import OpenAI

client = OpenAI(
    api_key="sk-你的CrazyrouterKey",
    base_url="https://crazyrouter.com/v1"
)

response = client.chat.completions.create(
    model="claude-sonnet-4-6",  # 或 claude-opus-4-7
    messages=[
        {"role": "user", "content": "用 Python 实现一个 LRU Cache"}
    ]
)

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

from openai import OpenAI

client = OpenAI(
    api_key="sk-你的CrazyrouterKey",
    base_url="https://crazyrouter.com/v1"
)

response = client.chat.completions.create(
    model="claude-opus-4-7",
    messages=[
        {"role": "system", "content": "你是一个资深软件架构师，擅长系统设计。"},
        {"role": "user", "content": "设计一个支持百万用户的实时聊天系统，给出架构方案和技术选型。"}
    ],
    temperature=0.7,
    max_tokens=4000
)

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

from openai import OpenAI

client = OpenAI(
    api_key="sk-你的CrazyrouterKey",
    base_url="https://crazyrouter.com/v1"
)

stream = client.chat.completions.create(
    model="claude-sonnet-4-6",
    messages=[
        {"role": "user", "content": "逐步解释 Transformer 的注意力机制"}
    ],
    stream=True
)

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

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'sk-你的CrazyrouterKey',
  baseURL: 'https://crazyrouter.com/v1',
});

async function main() {
  const response = await client.chat.completions.create({
    model: 'claude-sonnet-4-6',
    messages: [
      { role: 'user', content: '用 TypeScript 实现一个事件总线（EventBus）' },
    ],
    max_tokens: 2000,
  });

  console.log(response.choices[0].message.content);
}

main();

curl https://crazyrouter.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-你的CrazyrouterKey" \
  -d '{
    "model": "claude-sonnet-4-6",
    "messages": [
      {"role": "user", "content": "解释 Rust 的所有权机制"}
    ],
    "max_tokens": 2000
  }'

# 读取一个长文档
with open("long_document.txt", "r", encoding="utf-8") as f:
    document = f.read()

response = client.chat.completions.create(
    model="claude-opus-4-7",
    messages=[
        {"role": "user", "content": f"请阅读以下文档并生成一份结构化摘要：\n\n{document}"}
    ],
    max_tokens=4000
)

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

code_to_review = """
def process_data(data):
    result = []
    for i in range(len(data)):
        if data[i] != None:
            result.append(data[i] * 2)
    return result
"""

response = client.chat.completions.create(
    model="claude-sonnet-4-6",
    messages=[
        {"role": "system", "content": "你是一个严格的代码审查员。请指出代码中的问题并给出改进建议。"},
        {"role": "user", "content": f"请审查以下 Python 代码：\n```python\n{code_to_review}\n```"}
    ]
)

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

messages = [
    {"role": "system", "content": "你是一个 Python 教学助手。"},
    {"role": "user", "content": "什么是装饰器？"},
]

# 第一轮
response = client.chat.completions.create(
    model="claude-sonnet-4-6",
    messages=messages
)

assistant_reply = response.choices[0].message.content
print("Claude:", assistant_reply)

# 第二轮 — 追问
messages.append({"role": "assistant", "content": assistant_reply})
messages.append({"role": "user", "content": "能给一个带参数的装饰器的例子吗？"})

response = client.chat.completions.create(
    model="claude-sonnet-4-6",
    messages=messages
)

print("Claude:", response.choices[0].message.content)