import openai

# 初始化客户端
client = openai.OpenAI(
    base_url="http://localhost:8080/v1",
    api_key="your-auth-token"  # 替换为你的 AUTH_TOKEN
)

# 普通对话
response = client.chat.completions.create(
    model="GLM-4.5",
    messages=[{"role": "user", "content": "你好，介绍一下 Python"}],
    stream=False
)

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

# 定义工具
tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "获取天气信息",
        "parameters": {
            "type": "object",
            "properties": {
                "city": {"type": "string", "description": "城市名称"}
            },
            "required": ["city"]
        }
    }
}]

# 使用工具
response = client.chat.completions.create(
    model="GLM-4.5",
    messages=[{"role": "user", "content": "北京天气怎么样？"}],
    tools=tools,
    tool_choice="auto"
)

response = client.chat.completions.create(
    model="GLM-4.5-Thinking",
    messages=[{"role": "user", "content": "解释量子计算"}],
    stream=True
)

for chunk in response:
    content = chunk.choices[0].delta.content
    reasoning = chunk.choices[0].delta.reasoning_content

    if content:
        print(content, end="")
    if reasoning:
        print(f"\n🤔 思考: {reasoning}\n")

# 集成到现有应用
from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:8080/v1",
    api_key="your-token"
)

# 智能客服
def chat_with_ai(message):
    response = client.chat.completions.create(
        model="GLM-4.5",
        messages=[{"role": "user", "content": message}]
    )
    return response.choices[0].message.content

# 结合外部 API
def call_external_api(tool_name, arguments):
    # 执行实际工具调用
    return result

# 处理工具调用
if response.choices[0].message.tool_calls:
    for tool_call in response.choices[0].message.tool_calls:
        result = call_external_api(
            tool_call.function.name,
            json.loads(tool_call.function.arguments)
        )
        # 将结果返回给模型继续对话