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67 lines
1.8 KiB
Python
67 lines
1.8 KiB
Python
# import asyncio
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# from langchain_openai import ChatOpenAI
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# from langgraph.prebuilt import create_react_agent
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# from langchain_core.tools import tool
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# from langgraph.graph import END, START, StateGraph
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# from langgraph.graph import MessagesState
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# @tool
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# def get_weather(city: str) -> str:
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# """
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# Get the weather of a city
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# """
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# return f"The weather of {city} is sunny."
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# agent = create_react_agent(
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# model=ChatOpenAI(
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# model="gpt-4.1-mini",
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# temperature=0,
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# ),
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# prompt="""
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# You are a helpful travel assistant that can help user to get travel information.
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# When providing travel information, please also include:
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# 1. Top tourist attractions and landmarks
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# 2. Any travel recommendations based on the city weather
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# """,
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# tools=[get_weather],
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# )
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# async def node(state: MessagesState) -> MessagesState:
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# print("BEGIN")
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# msg_content = ""
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# async for ns, msg in agent.astream(
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# {
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# "messages": [
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# ("user", state["messages"][-1].content),
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# ]
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# },
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# stream_mode="messages",
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# # subgraphs=True,
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# ):
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# msg_content += msg[0].content
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# print("END")
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# return {"messages": [("assistant", msg_content)]}
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# graph = StateGraph(state_schema=MessagesState)
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# graph.add_node("node", node)
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# graph.add_edge(START, "node")
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# graph.add_edge("node", END)
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# workflow = graph.compile()
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# async def main():
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# result = await workflow.ainvoke({"messages": [("user", "What is the weather in Tokyo?")]})
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# print(result)
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# if __name__ == "__main__":
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# asyncio.run(main())
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from langchain.chat_models import init_chat_model
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model = init_chat_model("openai:gpt-4o-mini", message_version="v1") |