from openai import OpenAI
import os
from dotenv import load_dotenv

load_dotenv()

client = OpenAI(
    api_key=os.environ.get("DEEPSEEK_API_KEY"),
    base_url="https://api.deepseek.com",
)

# 1. 定义一个获取天气的工具
tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "获取指定城市的天气",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {"type": "string", "description": "城市名，如杭州"},
                },
                "required": ["location"],
            },
        },
    }
]

# 2. 用户提问
messages = [{"role": "user", "content": "你好,杭州的天气怎么样"}]

# 第一次调用模型：模型会返回 tool_calls
response = client.chat.completions.create(
    model="deepseek-v4-pro",  # 换成你实际可用的模型名，如 deepseek-v4-pro
    messages=messages,
    tools=tools,  # 传入工具列表
)

# 获取模型的回复（通常包含 tool_calls）
assistant_msg = response.choices[0].message
print(assistant_msg)
print(assistant_msg.model_dump_json(indent=2))
print(assistant_msg.content)
print("模型第一次回复：", assistant_msg.content)


if assistant_msg.tool_calls:
    name=assistant_msg.tool_calls[0].function.name
    print(name)
    import json
    r=json.loads(assistant_msg.tool_calls[0].function.arguments)
    print(r)
    arg=r.get('location')
    print(arg)
    tool_id=assistant_msg.tool_calls[0].id
    print(tool_id)


    name2=assistant_msg.tool_calls[1].function.name
    print(name)
    import json
    r2=json.loads(assistant_msg.tool_calls[1].function.arguments)
    print(r)
    arg2=r.get('location')
    print(arg)
    tool_id2=assistant_msg.tool_calls[1].id
    print(tool_id)

def get_weather(location: str) -> str:
    return f"{location}的天气为 880℃"

tools_map={'get_weather':get_weather}
tools_result=tools_map.get(name)(**r)
tools_result=tools_map.get(name2)(**r2)
print(tools_result)
messages.append(assistant_msg)
messages.append({'role':"tool","tool_call_id": tool_id,'content':tools_result})

response = client.chat.completions.create(
    model="deepseek-v4-pro",  # 换成你实际可用的模型名，如 deepseek-v4-pro
    messages=messages,
    tools=tools,  # 传入工具列表
)
print("模型第二次回复：", response.choices[0].message.content)