AgentLoop:LangChain ve LangGraph uygulamalarını entegre edin

import os
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
from langchain_core.tools import tool
@tool
def get_weather(city: str) -> str:
    """Get weather information for a specified city"""
    weather_data = {"Beijing": "Sunny 25°C", "Shanghai": "Cloudy 22°C", "Hangzhou": "Light rain 20°C"}
    return weather_data.get(city, f"{city}: No weather data available")
@tool
def search_product(keyword: str) -> str:
    """Search product information by keyword"""
    products = {
        "ECS": "Elastic Compute Service, providing secure and reliable cloud servers",
        "RDS": "Relational Database Service, supports MySQL/PostgreSQL/SQL Server",
        "OSS": "Object Storage Service, massive, secure, and highly reliable cloud storage",
    }
    return products.get(keyword, f"No product found for '{keyword}'")
llm = ChatOpenAI(
    model="qwen-plus",
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
    api_key=os.environ.get("DASHSCOPE_API_KEY"),
    streaming=True,
    stream_usage=True,  # When enabled, streamed responses include token usage
)
agent = create_react_agent(llm, tools=[get_weather, search_product])
result = agent.invoke({"messages": [{"role": "user", "content": "What's the weather like in Beijing today? Also look up what ECS is as a product"}]})
for msg in result["messages"]:
    if msg.content:
        print(msg.content)
                    

llm = ChatOpenAI(
    model="qwen-plus",
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
    api_key=os.environ.get("DASHSCOPE_API_KEY"),
    streaming=True,
    stream_usage=True,  # When enabled, streamed responses include token usage.
)

result = agent.invoke(
    {"messages": [{"role": "user", "content": "Hello"}]},
    config={
        "metadata": {
            "session_id": "sess_abc123",
            "user_id": "user_456",
        },
    },
)