101 lines
3.0 KiB
Python
101 lines
3.0 KiB
Python
"""13 - Subgraphs：把一个已编译的图作为父图节点。
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父图：START -> prepare -> research(subgraph) -> write_answer -> END
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子图：START -> search_web -> filter_results -> END
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运行：python 13_subgraphs.py
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"""
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from typing import TypedDict
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from langgraph.graph import END, START, StateGraph
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class ResearchState(TypedDict):
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question: str
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query: str
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raw_results: list[str]
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filtered_results: list[str]
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answer: str
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def search_web(state: ResearchState) -> dict:
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print(" [子图/search_web] 搜索：", state["query"])
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return {
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"raw_results": [
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"LangGraph 支持持久化、流式输出和人工介入",
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"无关内容：今天适合散步",
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"LangGraph 可以使用子图拆分复杂工作流",
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]
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}
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def filter_results(state: ResearchState) -> dict:
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print(" [子图/filter_results] 过滤结果")
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return {
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"filtered_results": [
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item for item in state["raw_results"] if "LangGraph" in item
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]
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}
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research_builder = StateGraph(ResearchState)
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research_builder.add_node("search_web", search_web)
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research_builder.add_node("filter_results", filter_results)
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research_builder.add_edge(START, "search_web")
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research_builder.add_edge("search_web", "filter_results")
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research_builder.add_edge("filter_results", END)
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research_graph = research_builder.compile()
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def prepare(state: ResearchState) -> dict:
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print("[父图/prepare] 准备查询")
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return {"query": state["question"].strip()}
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def write_answer(state: ResearchState) -> dict:
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print("[父图/write_answer] 生成回答")
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evidence = "\n".join(f"- {item}" for item in state["filtered_results"])
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return {"answer": f"问题：{state['question']}\n参考资料：\n{evidence}"}
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parent_builder = StateGraph(ResearchState)
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parent_builder.add_node("prepare", prepare)
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# 编译后的子图可以直接作为一个父图节点；双方共享同一 State schema。
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parent_builder.add_node("research", research_graph)
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parent_builder.add_node("write_answer", write_answer)
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parent_builder.add_edge(START, "prepare")
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parent_builder.add_edge("prepare", "research")
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parent_builder.add_edge("research", "write_answer")
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parent_builder.add_edge("write_answer", END)
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graph = parent_builder.compile()
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def main() -> None:
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initial: ResearchState = {
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"question": "LangGraph 为什么适合复杂 Agent？",
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"query": "",
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"raw_results": [],
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"filtered_results": [],
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"answer": "",
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}
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print("=== 普通调用 ===")
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result = graph.invoke(initial)
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print("\n", result["answer"])
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print("\n=== Streaming：包含子图内部事件 ===")
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for part in graph.stream(
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initial,
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stream_mode="updates",
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subgraphs=True,
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version="v2",
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):
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if part["type"] == "updates":
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location = "父图" if not part["ns"] else f"子图 {part['ns']}"
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print(f"{location}: {list(part['data'])}")
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if __name__ == "__main__":
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main()
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