29 lines
810 B
Python
29 lines
810 B
Python
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from typing import TypedDict
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from langgraph.graph import StateGraph, START
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from langgraph.checkpoint.memory import MemorySaver
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from langchain_openai import ChatOpenAI
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from os import getenv
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from dotenv import load_dotenv
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load_dotenv()
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class State(TypedDict):
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messages: list
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llm = ChatOpenAI(
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openai_api_key=getenv("OPENROUTER_API_KEY"),
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openai_api_base=getenv("OPENROUTER_BASE_URL"),
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model_name="qwen/qwen3-235b-a22b-07-25",
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)
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def call_model(state: State):
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# simple memory trim example: keep last 20 messages
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trimmed = state["messages"][-20:]
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response = llm.invoke(trimmed)
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return {"messages": [response]}
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workflow = StateGraph(State)
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workflow.add_node("model", call_model)
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workflow.add_edge(START, "model")
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memory = MemorySaver()
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app_graph = workflow.compile(checkpointer=memory)
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