Python 基础对话 - Crazyrouter

更新日期：2026-06-06

安装依赖

pip install openai requests

基础对话

from openai import OpenAI

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

response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[
        {"role": "system", "content": "你是一个有帮助的助手。"},
        {"role": "user", "content": "用一句话解释什么是人工智能"}
    ]
)

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

import requests

response = requests.post(
    "https://api.crazyrouter.com/v1/chat/completions",
    headers={
        "Authorization": "Bearer sk-xxx",
        "Content-Type": "application/json"
    },
    json={
        "model": "gpt-5.5",
        "messages": [
            {"role": "user", "content": "用一句话解释什么是人工智能"}
        ]
    }
)

data = response.json()
print(data["choices"][0]["message"]["content"])

连续对话

通过维护 messages 列表实现多轮对话：

from openai import OpenAI

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

messages = [
    {"role": "system", "content": "你是一个 Python 编程助手。"}
]

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

    response = client.chat.completions.create(
        model="gpt-5.5",
        messages=messages
    )

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

# 多轮对话
print(chat("如何读取 CSV 文件？"))
print(chat("如果文件很大怎么办？"))
print(chat("能用 pandas 实现吗？"))

流式输出

from openai import OpenAI

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

stream = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "写一首关于编程的诗"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)
print()

使用 requests 实现流式

import requests
import json

response = requests.post(
    "https://api.crazyrouter.com/v1/chat/completions",
    headers={
        "Authorization": "Bearer sk-xxx",
        "Content-Type": "application/json"
    },
    json={
        "model": "gpt-5.5",
        "messages": [{"role": "user", "content": "你好"}],
        "stream": True
    },
    stream=True
)

for line in response.iter_lines():
    if line:
        line = line.decode("utf-8")
        if line.startswith("data: ") and line != "data: [DONE]":
            data = json.loads(line[6:])
            content = data["choices"][0]["delta"].get("content", "")
            print(content, end="", flush=True)
print()

所有示例默认使用 2026 年 3 月 23 日已在生产环境实测成功的 gpt-5.5。如果你要切换模型，优先改成同样已验证的 claude-opus-4-8 或 gemini-3.1-pro。