\n| output_schema<\/td>\n | \u56fe\u8fd4\u56de\u4ec0\u4e48\u8f93\u51fa<\/td>\n | \u53ef\u9009，\u9ed8\u8ba4\u7b49\u4e8e state_schema<\/td>\n | \u9650\u5236\u51fa\u53e3\u53ea\u8fd4\u56de\u8fd9\u4e9b\u5b57\u6bb5，\u662f state_schema \u7684\u5b50\u96c6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \u4e3a\u4ec0\u4e48\u8981\u8fd9\u4e48\u8bbe\u8ba1？\u6253\u4e2a\u6bd4\u65b9：\u53a8\u623f\u5185\u90e8\u53ef\u80fd\u6709\u4e09\u5341\u79cd\u8c03\u6599（state_schema），\u4f46\u987e\u5ba2\u70b9\u5355\u65f6\u53ea\u9700\u8981\u8bf4"\u8981\u4e00\u4efd\u756a\u8304\u7092\u86cb"（input_schema），\u7aef\u4e0a\u684c\u65f6\u4e5f\u53ea\u9700\u8981\u90a3\u76d8\u83dc（output_schema）\u3002\u4e2d\u95f4\u8fc7\u7a0b\u5bf9\u8c03\u7528\u65b9\u4e0d\u53ef\u89c1，\u63a5\u53e3\u5c31\u5e72\u51c0\u4e86\u3002<\/p>\n from typing import TypedDict
\nfrom langgraph.constants import START, END
\nfrom langgraph.graph import StateGraph<\/p>\n class MyStateFull(TypedDict):
\n rag_result: str
\n web_search_result: str
\n final_answer: str
\n query: str
\n a_new_key: str<\/p>\n class InputSchema(TypedDict):
\n query: str # \u53ea\u5141\u8bb8\u5916\u90e8\u4f20 query<\/p>\n class OutputSchema(TypedDict):
\n final_answer: str # \u53ea\u628a final_answer \u4ea4\u51fa\u53bb<\/p>\n graph = StateGraph(
\n state_schema=MyStateFull,
\n input_schema=InputSchema,
\n output_schema=OutputSchema,
\n)<\/p>\n def rag_search_node(state: MyStateFull):
\n print(state)
\n query = state["query"]
\n rag_result = f"\u5173\u4e8e{query}\u7684rag_result"
\n return {"rag_result": rag_result, "a_new_key": "a_new_key_value"}<\/p>\n def web_search_node(state: MyStateFull):
\n print(state)
\n query = state["query"]
\n web_search_result = f"\u5173\u4e8e{query}\u7684web_search_result"
\n return {"web_search_result": web_search_result}<\/p>\n def final_answer_node(state: MyStateFull):
\n print("\u5728final_answer_node\u5f53\u4e2d\u7684state", state)
\n rag_result = state["rag_result"]
\n web_search_result = state["web_search_result"]
\n final_answer = f"LLM\u57fa\u4e8e{rag_result}\u548c{web_search_result}\u7684\u6700\u7ec8\u56de\u590d"
\n return {"final_answer": final_answer}<\/p>\n graph.add_node(rag_search_node)
\ngraph.add_node(web_search_node)
\ngraph.add_node(final_answer_node)<\/p>\n graph.add_edge(START, "rag_search_node")
\ngraph.add_edge(START, "web_search_node")
\ngraph.add_edge("rag_search_node", "final_answer_node")
\ngraph.add_edge("web_search_node", "final_answer_node")
\ngraph.add_edge("final_answer_node", END)<\/p>\n compiled_graph = graph.compile()
\nres = compiled_graph.invoke({"query": "\u5982\u4f55\u4f7f\u7528LangGraph", "a_new_key": "a_new_key_value"})
\nprint("\u6700\u7ec8\u7ed3\u679c\u4e3a", res)<\/p>\n \u5b9e\u6218\u5c0f\u63d0\u793a：\u5982\u679c\u4f60\u5728 input_schema \u91cc\u6ca1\u6709\u58f0\u660e a_new_key，\u90a3\u4e48\u8c03\u7528\u65f6\u4f20\u5b83\u8fdb\u53bb\u662f\u4e0d\u751f\u6548\u7684（\u4f1a\u88ab\u8fc7\u6ee4）\u3002\u8fd9\u6b63\u597d\u53ef\u4ee5\u7528\u6765\u9632\u6b62\u8c03\u7528\u65b9\u4e71\u585e\u6570\u636e\u3002<\/p>\n 6.3 \u8282\u70b9\u95f4\u6570\u636e\u9694\u79bb：\u6bcf\u4e2a\u8282\u70b9\u4e5f\u80fd\u6709\u81ea\u5df1\u7684"\u79c1\u6709\u72b6\u6001"<\/h4>\n\u9664\u4e86\u56fe\u7ea7\u522b\u7684\u72b6\u6001，LangGraph \u8fd8\u5141\u8bb8\u67d0\u4e2a\u8282\u70b9\u53ea\u770b\u5230\u81ea\u5df1\u5173\u5fc3\u7684\u4e00\u90e8\u5206\u5b57\u6bb5\u3002\u505a\u6cd5\u662f\u7ed9\u8fd9\u4e2a\u8282\u70b9\u51fd\u6570\u6362\u4e2a state \u7c7b\u578b\u6ce8\u89e3：<\/p>\n from typing import TypedDict
\nfrom langgraph.constants import START, END
\nfrom langgraph.graph import StateGraph<\/p>\n class MyState(TypedDict):
\n query: str
\n final_answer: str<\/p>\n class SearchState(TypedDict):
\n rag_result: str
\n web_search_result: str<\/p>\n graph = StateGraph(state_schema=MyState)<\/p>\n def rag_search_node(state: MyState):
\n query = state["query"]
\n return {"rag_result": f"\u5173\u4e8e{query}\u7684rag_result"}<\/p>\n def web_search_node(state: MyState):
\n query = state["query"]
\n return {"web_search_result": f"\u5173\u4e8e{query}\u7684web_search_result"}<\/p>\n def final_answer_node(state: SearchState): # \u6ce8\u610f：\u8fd9\u4e2a\u8282\u70b9\u53ea\u5173\u5fc3\u68c0\u7d22\u7ed3\u679c
\n print("\u5728final_answer_node\u5f53\u4e2d\u7684state", state)
\n rag_result = state["rag_result"]
\n web_search_result = state["web_search_result"]
\n final_answer = f"LLM\u57fa\u4e8e{rag_result}，\u548c{web_search_result}\u7684\u6700\u7ec8\u56de\u590d"
\n return {"final_answer": final_answer}<\/p>\n graph.add_node(rag_search_node)
\ngraph.add_node(web_search_node)
\ngraph.add_node(final_answer_node)<\/p>\n graph.add_edge(START, "rag_search_node")
\ngraph.add_edge(START, "web_search_node")
\ngraph.add_edge("rag_search_node", "final_answer_node")
\ngraph.add_edge("web_search_node", "final_answer_node")
\ngraph.add_edge("final_answer_node", END)<\/p>\n compiled_graph = graph.compile()
\nres = compiled_graph.invoke({"query": "\u5982\u4f55\u4f7f\u7528LangGraph"})
\nprint("\u6700\u7ec8\u7ed3\u679c\u4e3a", res)<\/p>\n \u4e3a\u4ec0\u4e48\u6709\u7528？ \u4e24\u4e2a\u597d\u5904：\u4e00\u662f\u8fd9\u4e2a\u8282\u70b9\u770b\u4e0d\u5230\u4e5f\u4e0d\u9700\u8981\u770b\u4e0d\u5230\u65e0\u5173\u6570\u636e，\u903b\u8f91\u66f4\u7eaf\u7cb9；\u4e8c\u662f\u5f53\u72b6\u6001\u5b57\u6bb5\u5f88\u591a（\u51e0\u5341\u4e2a）\u65f6，\u8282\u70b9\u53ea\u4f1a\u6536\u5230\u5b83\u58f0\u660e\u7684\u90a3\u51e0\u4e2a，\u80fd\u51cf\u5c11\u610f\u5916\u6539\u9519\u5b57\u6bb5\u7684\u98ce\u9669\u3002\u8fd9\u6709\u70b9\u50cf\u51fd\u6570\u53ea\u63a5\u6536\u81ea\u5df1\u9700\u8981\u7684\u53c2\u6570，\u800c\u4e0d\u662f\u628a\u6574\u4e2a\u5168\u5c40\u53d8\u91cf\u90fd\u585e\u8fdb\u53bb\u3002<\/p>\n 6.4 Reducer：\u72b6\u6001\u5230\u5e95\u600e\u4e48"\u5408\u5e76"<\/h4>\n\u8fd9\u662f LangGraph \u91cc\u6700\u5bb9\u6613\u8e29\u5751\u3001\u4e5f\u6700\u7cbe\u9ad3\u7684\u673a\u5236，\u8bf7\u52a1\u5fc5\u770b\u61c2\u3002<\/p>\n \u524d\u9762\u53cd\u590d\u8bf4"\u8282\u70b9\u8fd4\u56de\u7684\u53ea\u662f\u589e\u91cf"\u3002\u90a3\u4e48\u95ee\u9898\u6765\u4e86：\u589e\u91cf\u62ff\u5230\u4e4b\u540e，\u600e\u4e48\u548c\u5168\u5c40\u72b6\u6001\u5408\u5e76？ \u7b54\u6848\u5c31\u662f\u6bcf\u4e2a\u5b57\u6bb5\u90fd\u6709\u81ea\u5df1\u7684 Reducer（\u5f52\u7ea6\u51fd\u6570）\u3002<\/p>\n Reducer \u5c31\u662f\u4e00\u4e2a\u51fd\u6570：\u63a5\u6536"\u5de6\u8fb9\u7684\u65e7\u503c"\u548c"\u53f3\u8fb9\u7684\u589e\u91cf"，\u8fd4\u56de\u5408\u5e76\u540e\u7684\u65b0\u503c\u3002<\/p>\n \u60c5\u51b5\u4e00：\u4e0d\u5199 Reducer = \u9ed8\u8ba4\u8986\u76d6<\/p>\n \u8fd9\u662f\u9ed8\u8ba4\u884c\u4e3a\u3002\u65b0\u503c\u76f4\u63a5\u628a\u65e7\u503c\u76d6\u6389，\u5c31\u50cf\u7ed9\u53d8\u91cf\u91cd\u65b0\u8d4b\u503c\u3002<\/p>\n from typing import List
\nfrom typing_extensions import TypedDict
\nfrom langgraph.graph import StateGraph, START, END<\/p>\n class DefaultReducerState(TypedDict):
\n foo: int
\n bar: List[str]<\/p>\n def node_default_1(state: DefaultReducerState) -> dict:
\n return {"foo": 2} # foo: 1 -> 2<\/p>\n def node_default_2(state: DefaultReducerState) -> dict:
\n return {"bar": ["bye"]} # bar: ["hi"] -> ["bye"]，\u6ce8\u610f "hi" \u6ca1\u4e86！<\/p>\n builder = StateGraph(DefaultReducerState)
\nbuilder.add_node("node1", node_default_1)
\nbuilder.add_node("node2", node_default_2)
\nbuilder.add_edge(START, "node1")
\nbuilder.add_edge("node1", "node2")
\nbuilder.add_edge("node2", END)<\/p>\n graph = builder.compile()
\nresult = graph.invoke({"foo": 1, "bar": ["hi"]})
\nprint(f"\u521d\u59cb\u72b6\u6001: {{'foo': 1, 'bar': ['hi']}}")
\nprint(f"\u6267\u884c\u7ed3\u679c: {result}")<\/p>\n \u8dd1\u4e00\u4e0b\u4f60\u4f1a\u53d1\u73b0，bar \u6700\u7ec8\u662f ["bye"]，\u539f\u6765\u7684 "hi" \u88ab\u8986\u76d6\u6389\u4e86\u3002\u5982\u679c\u4f60\u60f3\u8981\u7684\u662f"\u8ffd\u52a0"，\u5c31\u5fc5\u987b\u81ea\u5df1\u6307\u5b9a Reducer\u3002<\/p>\n \u60c5\u51b5\u4e8c：\u81ea\u5b9a\u4e49 Reducer（\u6700\u5e38\u7528：\u6d88\u606f\u8ffd\u52a0）<\/p>\n \u7528 Annotated[\u7c7b\u578b, \u51fd\u6570] \u7684\u8bed\u6cd5\u628a Reducer \u6302\u5230\u5b57\u6bb5\u4e0a\u3002\u4e0b\u9762\u8fd9\u4e2a add_message \u5c31\u662f\u628a\u65e7\u6d88\u606f\u5217\u8868\u548c\u65b0\u6d88\u606f\u5217\u8868\u62fc\u8d77\u6765：<\/p>\n from typing import Annotated, TypedDict, List
\nfrom langgraph.graph import StateGraph
\nfrom langgraph.constants import START
\nfrom langchain_core.messages import ToolMessage, HumanMessage, AIMessage, BaseMessage<\/p>\n # \u81ea\u5b9a\u4e49 Reducer：\u5de6\u8fb9 + \u53f3\u8fb9
\ndef add_message(message_list_left: list, message_list_right: list):
\n print("=" * 20)
\n print("\u6b63\u5728\u6267\u884cadd_message")
\n print("\u5de6\u8fb9\u7684", message_list_left)
\n print("\u53f3\u8fb9\u7684", message_list_right)
\n print("=" * 20)
\n return message_list_left + message_list_right<\/p>\n class MyAgent(TypedDict):
\n # \u5173\u952e：\u7528 Annotated \u6302\u4e0a\u81ea\u5b9a\u4e49 reducer
\n messages: Annotated[List[BaseMessage], add_message]<\/p>\n def tool_node(state: MyAgent):
\n return {"messages": [ToolMessage(content="\u6765\u81eatool_node\u7684\u5185\u5bb9", tool_call_id="xxx")]}<\/p>\n def llm_node(state: MyAgent):
\n return {"messages": [AIMessage(content="\u6765\u81eallm_node\u7684\u5185\u5bb9")]}<\/p>\n builder = StateGraph(state_schema=MyAgent)
\nbuilder.add_node(tool_node)
\nbuilder.add_node(llm_node)
\nbuilder.add_edge(START, "tool_node")
\nbuilder.add_edge("tool_node", "llm_node")<\/p>\n graph = builder.compile()
\ngraph.invoke({"messages": [HumanMessage(content="\u4f60\u597d")]})<\/p>\n \u8dd1\u5b8c\u4f60\u4f1a\u770b\u5230 messages \u91cc\u4f9d\u6b21\u662f：\u7528\u6237\u8bf4\u7684"\u4f60\u597d" \u2192 \u5de5\u5177\u7684\u8fd4\u56de \u2192 \u6a21\u578b\u7684\u56de\u590d\u3002\u4e09\u6761\u90fd\u5728，\u4e00\u6761\u6ca1\u4e22\u3002\u8fd9\u4e5f\u662f\u4e3a\u4ec0\u4e48\u5bf9\u8bdd\u7c7b\u5e94\u7528\u51e0\u4e4e\u90fd\u7528\u8ffd\u52a0\u578b Reducer\u2014\u2014\u804a\u5929\u8bb0\u5f55\u5fc5\u987b\u662f\u7d2f\u52a0\u7684，\u4e0d\u80fd\u4e92\u76f8\u8986\u76d6\u3002<\/p>\n \u60c5\u51b5\u4e09：\u4f7f\u7528\u5185\u7f6e Reducer<\/p>\n LangGraph \u5df2\u7ecf\u5185\u7f6e\u4e86\u4e00\u4e9b\u5e38\u7528 Reducer，\u6bd4\u5982 langgraph.graph.messages \u91cc\u7684 add_messages，\u4ee5\u53ca\u505a\u5217\u8868\u76f8\u52a0\u7684 operator.add\u3002\u540e\u8005\u5728\u5e76\u884c\u573a\u666f\u7279\u522b\u597d\u7528：<\/p>\n import operator
\nfrom typing import Annotated
\nfrom typing_extensions import TypedDict<\/p>\n class State(TypedDict):
\n aggregate: Annotated[list, operator.add] # \u591a\u4e2a\u8282\u70b9\u540c\u65f6\u5199，\u7ed3\u679c\u4f1a\u62fc\u63a5\u8d77\u6765<\/p>\n \u6ce8\u610f：\u5f53\u4e00\u4e2a\u5b57\u6bb5\u6709\u591a\u4e2a\u5e76\u884c\u8282\u70b9\u540c\u65f6\u5199，\u53c8\u6ca1\u6709\u914d\u7f6e Reducer \u65f6，LangGraph \u4f1a\u56e0\u4e3a"\u4e0d\u77e5\u9053\u8be5\u4ee5\u8c01\u4e3a\u51c6"\u800c\u62a5\u9519\u3002\u8fd9\u662f\u65b0\u624b\u6700\u5e38\u89c1\u7684\u62a5\u9519\u6765\u6e90\u4e4b\u4e00，\u770b\u5230 InvalidUpdateError \u4e4b\u7c7b\u7684\u63d0\u793a，\u5148\u68c0\u67e5\u662f\u4e0d\u662f\u5e76\u884c\u7684\u8282\u70b9\u5199\u4e86\u540c\u4e00\u4e2a\u952e\u5374\u6ca1\u914d Reducer\u3002<\/p>\n \u4e03\u3001\u72b6\u6001\u5b58\u50a8：Checkpointer \u4e0e thread_id<\/h3>\n7.1 \u5148\u8bf4\u4e24\u4e2a\u771f\u5b9e\u573a\u666f，\u4f60\u5c31\u77e5\u9053\u4e3a\u4ec0\u4e48\u9700\u8981\u5b83<\/h4>\n\u5728\u524d\u9762\u6240\u6709\u4f8b\u5b50\u91cc，\u6bcf\u6b21 invoke，LangGraph \u90fd\u4f1a\u521d\u59cb\u5316\u4e00\u4e2a\u7a7a\u72b6\u6001，\u7136\u540e\u628a\u4f60\u7684\u521d\u59cb\u72b6\u6001\u5408\u8fdb\u53bb，\u8dd1\u5b8c\u5c31\u4e22\u3002\u7b80\u5355\u4efb\u52a1\u6ca1\u95ee\u9898，\u4f46\u9047\u5230\u4e0b\u9762\u4e24\u79cd\u60c5\u51b5\u5c31\u5e9f\u4e86\u3002<\/p>\n \u573a\u666f\u4e00：\u540c\u4e00\u4e2a\u4f1a\u8bdd\u91cc\u8981\u8bb0\u4f4f\u4e0a\u4e00\u8f6e<\/p>\n \u7528\u6237\u7b2c\u4e00\u53e5\u8bf4"\u5e2e\u6211\u67e5\u4e00\u4e0b\u5317\u4eac\u660e\u5929\u5929\u6c14"，\u7b2c\u4e8c\u53e5\u95ee"\u9002\u5408\u51fa\u53bb\u73a9\u5417"\u3002\u7b2c\u4e8c\u6b21\u8c03\u7528\u65f6，\u72b6\u6001\u88ab\u91cd\u7f6e，messages \u662f\u7a7a\u7684，\u6a21\u578b\u6839\u672c\u4e0d\u77e5\u9053"\u5b83"\u6307\u4ec0\u4e48\u2014\u2014\u4e0a\u4e0b\u6587\u65ad\u4e86\u3002<\/p>\n \u573a\u666f\u4e8c：\u8dd1\u5230\u4e00\u534a\u62a5\u9519\u4e86，\u4e0d\u60f3\u4ece\u5934\u518d\u6765<\/p>\n \u5047\u8bbe Node2 \u56e0\u4e3a\u67d0\u4e2a bug \u629b\u5f02\u5e38\u3002\u4f60\u4fee\u597d\u4ee3\u7801\u540e\u60f3"\u4ece Node2 \u7ee7\u7eed"，\u4f46\u5185\u5b58\u91cc\u7684\u72b6\u6001\u5df2\u7ecf\u968f\u8fdb\u7a0b\u9000\u51fa\u6d88\u5931\u4e86，Node1 \u7684\u7ed3\u679c\u5f97\u91cd\u65b0\u7b97\u4e00\u904d\u3002\u5982\u679c Node1 \u521a\u521a\u82b1\u4e86\u4e24\u6bdb\u94b1\u8c03\u7528\u5927\u6a21\u578b，\u4f60\u4f1a\u5f88\u5fc3\u75bc\u3002<\/p>\n 7.2 \u89e3\u51b3\u65b9\u6848：Checkpointer + thread_id<\/h4>\n\u601d\u8def\u5f88\u6734\u7d20：\u628a\u6bcf\u4e00\u6b65\u6267\u884c\u5b8c\u7684\u72b6\u6001\u5b58\u8d77\u6765，\u4e0b\u6b21\u7528\u7684\u65f6\u5019\u6309 id \u53d6\u56de\u6765，\u800c\u4e0d\u662f\u8ba9 LangGraph \u6bcf\u6b21\u90fd\u4ece\u7a7a\u767d\u5f00\u59cb\u3002<\/p>\n LangGraph \u63d0\u4f9b\u7684\u5b58\u50a8\u673a\u5236\u53eb Checkpointer（\u68c0\u67e5\u70b9），\u76f8\u5173\u7684\u7c7b\u90fd\u5728 langgraph.checkpointer \u5305\u4e0b，\u53ef\u4ee5\u5b58\u5230\u5185\u5b58\u3001SQLite\u3001Postgres \u7b49\u5730\u65b9\u3002<\/p>\n \u540c\u65f6，\u56e0\u4e3a\u4e00\u4e2a\u5e94\u7528\u53ef\u80fd\u540c\u65f6\u670d\u52a1\u5f88\u591a\u7528\u6237\u3001\u6bcf\u4e2a\u7528\u6237\u53c8\u6709\u5f88\u591a\u4f1a\u8bdd，\u6240\u4ee5\u9700\u8981\u7ed9\u72b6\u6001\u6253\u4e2a"\u7f16\u53f7"\u6765\u9694\u79bb\u3002\u8fd9\u4e2a\u7f16\u53f7\u5c31\u662f thread_id\u3002<\/p>\n \u5212\u91cd\u70b9：thread_id \u548c\u7f16\u7a0b\u91cc\u7684"\u7ebf\u7a0b"\u6ca1\u6709\u534a\u70b9\u5173\u7cfb！ \u5b83\u53ea\u662f\u4e00\u4e2a\u7528\u6765\u9694\u79bb\u72b6\u6001\u7a7a\u95f4\u7684\u5b57\u7b26\u4e32，\u4f60\u53ef\u4ee5\u628a\u5b83\u7406\u89e3\u6210"\u4f1a\u8bdd\u7f16\u53f7"\u3002\u53eb\u5f20\u4e09\u7684\u7f16\u53f7 user_1_session_1，\u53eb\u674e\u56db\u7684\u7f16\u53f7 user_2_session_1，\u4e24\u4eba\u7684\u8bb0\u5fc6\u4e92\u4e0d\u5e72\u6270\u3002<\/p>\n \u7f16\u7801\u4e0a\u5c31\u4e09\u6b65：<\/p>\n \u521b\u5efa checkpointer \u5b9e\u4f8b；<\/li>\n\u7f16\u8bd1\u56fe\u65f6\u628a checkpointer \u4f20\u8fdb\u53bb；<\/li>\n\u8c03\u7528\u65f6\u5728 config \u91cc\u4f20 thread_id\u3002\u60f3\u8981\u5ef6\u7eed\u4e0a\u4e0b\u6587\u5c31\u4f20\u540c\u4e00\u4e2a id，\u60f3\u5f00\u65b0\u4f1a\u8bdd\u5c31\u6362\u4e00\u4e2a\u65b0 id\u3002<\/li>\n7.3 \u5b9e\u6218\u4e00：\u7528 InMemorySaver \u505a"\u77ed\u671f\u8bb0\u5fc6"<\/h4>\n\u4e0b\u9762\u8fd9\u6bb5\u4ee3\u7801\u7528 create_agent \u6f14\u793a（\u5b83\u5e95\u5c42\u4e5f\u662f LangGraph \u56fe），\u91cd\u70b9\u662f\u770b\u6ce8\u91ca\u91cc\u6807\u4e86\u5e8f\u53f7\u7684\u56db\u6b65：<\/p>\n def scenario_1_demo():
\n from langchain.agents import create_agent
\n from langchain.tools import tool
\n from langchain_openai import ChatOpenAI<\/p>\n # 1\u3001\u5f15\u5165 checkpointer
\n from langgraph.checkpoint.memory import InMemorySaver<\/p>\n llm = ChatOpenAI(model="gpt-4o-mini")<\/p>\n # 2\u3001\u5b9a\u4e49 checkpointer \u5b9e\u4f8b
\n checkpointer = InMemorySaver()<\/p>\n @tool
\n def weather_tool(city: str, date: str) -> str:
\n """\u67e5\u5929\u6c14\u7684\u5de5\u5177"""
\n return f"{city}\u5728{date}\u7684\u5929\u6c14\u662f\u6674\u6717\u7684"<\/p>\n # 3\u3001\u6784\u5efa Agent \u65f6\u5f15\u5165 checkpointer
\n agent = create_agent(
\n model=llm,
\n tools=[weather_tool],
\n checkpointer=checkpointer,
\n )<\/p>\n # 4\u3001\u7528\u6237\u7b2c\u4e00\u6b21\u8c03\u7528
\n user1_res = agent.invoke(
\n {"messages": "\u5317\u4eac2026-01-14\u5929\u6c14\u600e\u4e48\u6837"},
\n config={"configurable": {"thread_id": "user_1_session_1"}},
\n )
\n print("\u7b2c\u4e00\u6b21\u8c03\u7528", user1_res["messages"][-1])<\/p>\n # 5\u3001\u540c\u4e00\u4e2a\u4f1a\u8bdd\u91cc，\u7b2c\u4e8c\u6b21\u8c03\u7528（thread_id \u76f8\u540c！）
\n user1_res_2 = agent.invoke(
\n {"messages": "\u9002\u5408\u51fa\u53bb\u73a9\u5417"},
\n config={"configurable": {"thread_id": "user_1_session_1"}},
\n )
\n print("\u7b2c\u4e8c\u6b21\u8c03\u7528", user1_res_2["messages"][-1])<\/p>\n \u7b2c\u4e8c\u6b21\u63d0\u95ee"\u9002\u5408\u51fa\u53bb\u73a9\u5417"，\u6a21\u578b\u80fd\u7b54\u4e0a\u6765，\u56e0\u4e3a\u5b83\u4ece checkpointer \u91cc\u8bfb\u5230\u4e86\u4e0a\u4e00\u8f6e\u7684"\u5317\u4eac\u3001\u6674\u5929"\u3002\u8fd9\u5c31\u662f\u6240\u8c13\u7684 Agent \u77ed\u671f\u8bb0\u5fc6\u3002<\/p>\n 7.4 \u5b9e\u6218\u4e8c：\u7528 SqliteSaver \u505a"\u65ad\u70b9\u7eed\u8dd1"<\/h4>\nInMemorySaver \u53ea\u5b58\u5728\u5185\u5b58\u91cc，\u8fdb\u7a0b\u4e00\u6302\u5c31\u5168\u6ca1\u4e86，\u6240\u4ee5\u5b83\u89e3\u51b3\u4e0d\u4e86\u573a\u666f\u4e8c\u3002\u751f\u4ea7\u73af\u5883\u8981\u843d\u5230\u6570\u636e\u5e93，\u672c\u5730\u5f00\u53d1\u6700\u65b9\u4fbf\u7684\u662f SQLite\u3002<\/p>\n \u7b2c\u4e00\u6b21\u8fd0\u884c：Node2 \u6545\u610f\u62a5\u9519<\/p>\n def scenario_2_demo():
\n """\u573a\u666f\u4e8c：\u5982\u4f55\u4ece checkpointer \u4e2d\u6062\u590d\u72b6\u6001"""
\n from langgraph.graph import StateGraph, START
\n from typing import TypedDict<\/p>\n # 1\u3001\u5f15\u5165 sqlite3 \u548c SqliteSaver
\n import sqlite3
\n from langgraph.checkpoint.sqlite import SqliteSaver<\/p>\n # 2\u3001\u6784\u5efa Connection \u5bf9\u8c61
\n conn = sqlite3.connect(database=".\/sqlite_data\/langgraph_sqlite", check_same_thread=False)
\n # 3\u3001\u901a\u8fc7 connection \u5bf9\u8c61\u6784\u5efa checkpointer \u5b9e\u4f8b
\n memory = SqliteSaver(conn)<\/p>\n class MyState(TypedDict):
\n key_1: str
\n key_2: str
\n key_3: str<\/p>\n def node_1(state: MyState) -> MyState:
\n print("node_1\u521d\u59cb\u72b6\u6001\u4e3a", state)
\n return {"key_1": "value_1"}<\/p>\n def node_2(state: MyState) -> MyState:
\n # 5\u3001\u6a21\u62df\u751f\u4ea7\u73af\u5883\u4e0b\u7684 bug \u6216\u4e0d\u53ef\u9884\u89c1\u60c5\u51b5
\n raise Exception("node_2\u8282\u70b9\u6267\u884c\u62a5\u9519")
\n return {"key_2": "value_2"}<\/p>\n def node_3(state: MyState) -> MyState:
\n return {"key_3": "value_3"}<\/p>\n builder = StateGraph(MyState)
\n builder.add_node(node_1)
\n builder.add_node(node_2)
\n builder.add_node(node_3)
\n builder.add_edge(START, "node_1")
\n builder.add_edge("node_1", "node_2")
\n builder.add_edge("node_1", "node_3")<\/p>\n config = {"configurable": {"thread_id": "123"}}<\/p>\n # 6\u3001compile \u65f6\u4f20\u5165 checkpointer
\n graph = builder.compile(checkpointer=memory)<\/p>\n # 7\u3001\u8c03\u7528\u65f6\u4f20\u5165 config
\n graph.invoke({}, config=config)<\/p>\n \u8fd9\u4e00\u8dd1，\u7a0b\u5e8f\u4f1a\u5728 Node2 \u629b\u5f02\u5e38\u4e2d\u65ad\u3002\u4f46\u56e0\u4e3a\u6302\u4e86 checkpointer，node_1 \u7684\u7ed3\u679c\u5df2\u7ecf\u843d\u76d8\u4e86\u3002<\/p>\n \u7b2c\u4e8c\u6b21\u8fd0\u884c：\u4fee\u597d bug，\u4ece\u65ad\u70b9\u7ee7\u7eed<\/p>\n \u628a Node2 \u91cc\u90a3\u884c raise \u6ce8\u91ca\u6389，\u7136\u540e\u53ea\u6539\u4e24\u4e2a\u5730\u65b9：<\/p>\n invoke \u7684\u7b2c\u4e00\u4e2a\u53c2\u6570\u4f20 None（\u8868\u793a"\u4e0d\u8981\u65b0\u7684\u521d\u59cb\u72b6\u6001，\u7528\u5b58\u597d\u7684"）；<\/li>\nthread_id \u4fdd\u6301\u548c\u4e0a\u6b21\u4e00\u6837（"123"）\u3002<\/li>\n def node_2(state: MyState) -> MyState:
\n # 1\u3001\u4fee\u590d\u9519\u8bef，\u6ce8\u91ca\u6389\u62a5\u9519\u4ee3\u7801
\n # raise Exception("node_2\u8282\u70b9\u6267\u884c\u62a5\u9519")
\n return {"key_2": "value_2"}<\/p>\n # …（\u5176\u4ed6\u90e8\u5206\u4e0e\u4e0a\u9762\u5b8c\u5168\u76f8\u540c）<\/p>\n # 2\u3001\u6ce8\u610f！\u4ece\u6545\u969c\u4e2d\u6062\u590d，\u7b2c\u4e00\u4e2a\u53c2\u6570\u4f20 None
\n graph.invoke(None, config=config)<\/p>\n \u6b64\u65f6\u4f60\u4f1a\u53d1\u73b0，node_1 \u91cc\u7684\u6253\u5370\u8bed\u53e5\u6ca1\u6709\u518d\u6267\u884c\u4e00\u6b21\u2014\u2014\u5b83\u662f\u4ece Node2 \u63a5\u7740\u8dd1\u7684\u3002\u8fd9\u5c31\u662f"\u65ad\u70b9\u7eed\u8dd1"\u3002<\/p>\n \u4e00\u4e2a\u5fc5\u987b\u8bb0\u4f4f\u7684\u5751：\u6062\u590d\u6267\u884c\u65f6，\u88ab\u4e2d\u65ad\u7684\u90a3\u4e2a\u8282\u70b9\u51fd\u6570\u4f1a\u4ece\u51fd\u6570\u5f00\u5934\u91cd\u65b0\u8dd1\u4e00\u904d，\u800c\u4e0d\u662f\u4ece interrupt \u90a3\u4e00\u884c\u63a5\u7740\u8dd1\u3002\u6240\u4ee5\u5982\u679c\u8282\u70b9\u91cc\u6709"\u53d1\u90ae\u4ef6""\u6263\u6b3e""\u5199\u6570\u636e\u5e93"\u8fd9\u7c7b\u64cd\u4f5c，\u4e00\u5b9a\u4fdd\u8bc1\u5e42\u7b49，\u6216\u8005\u628a\u5b83\u62c6\u6210\u5355\u72ec\u8282\u70b9\u3002\u8fd9\u4e2a\u5751\u5728\u7b2c\u5341\u4e8c\u8282\u8bb2 interrupt \u65f6\u8fd8\u4f1a\u518d\u5f3a\u8c03\u4e00\u6b21\u3002<\/p>\n \u516b\u3001\u63ed\u5f00\u5e95\u724c：Pregel \u662f\u600e\u4e48\u628a\u56fe\u8dd1\u8d77\u6765\u7684<\/h3>\n\u524d\u9762\u8bf4"\u56fe\u4f1a\u5e76\u884c""\u4f1a\u5faa\u73af"，\u90a3\u5b83\u5185\u90e8\u5230\u5e95\u600e\u4e48\u8c03\u5ea6\u7684？\u7406\u89e3\u8fd9\u4e00\u5c42，\u4f60\u8c03\u8bd5\u590d\u6742\u56fe\u65f6\u4f1a\u8f7b\u677e\u5f88\u591a\u3002<\/p>\n 8.1 \u4e24\u4e2a\u4e3b\u89d2：Actor \u548c Channel<\/h4>\nLangGraph \u5e95\u5c42\u6709\u4e2a\u53eb Pregel \u7684\u7c7b，\u8d1f\u8d23\u7ba1\u7406\u6574\u4e2a\u56fe\u4ece\u5f00\u59cb\u5230\u7ed3\u675f\u7684\u8fed\u4ee3\u6267\u884c\u3002\u5b83\u91cc\u9762\u53ea\u6709\u4e24\u5927\u7ec4\u4ef6：<\/p>\n \n- Actors（\u8282\u70b9）：\u5bf9\u5e94\u4f60\u5199\u7684 Node，\u5728\u5e95\u5c42\u53eb PregelNode\u3002\u5b83\u8ba2\u9605\u67d0\u4e9b\u901a\u9053（\u4ece\u901a\u9053\u8bfb\u6570\u636e），\u4e5f\u4f1a\u5199\u5165\u67d0\u4e9b\u901a\u9053\u3002<\/li>\n
- Channels（\u901a\u9053）：Actor \u4e4b\u95f4\u901a\u4fe1\u7684\u7ba1\u9053\u3002\u6bcf\u4e2a\u901a\u9053\u90fd\u6709\u503c\u7c7b\u578b\u3001\u66f4\u65b0\u7c7b\u578b\u3001\u4ee5\u53ca\u4e00\u4e2a\u66f4\u65b0\u51fd\u6570（\u63a5\u6536\u4e00\u6279\u66f4\u65b0，\u4fee\u6539\u5b58\u50a8\u7684\u503c）\u3002<\/li>\n<\/ul>\n
\u56e0\u4e3a\u8fd9\u79cd\u8bbe\u8ba1，LangGraph \u7684\u56fe\u4e0d\u662f\u4f20\u7edf\u610f\u4e49\u4e0a\u7684\u6709\u5411\u65e0\u73af\u56fe（DAG）\u3002\u5728\u4f20\u7edf DAG \u91cc，\u4e00\u4e2a\u8282\u70b9\u5fc5\u987b\u7b49\u5b83\u6240\u6709\u4e0a\u6e38\u90fd\u8dd1\u5b8c\u624d\u80fd\u8dd1，\u9760"\u8fb9"\u6765\u51b3\u5b9a\u987a\u5e8f\u3002<\/p>\n \u800c\u5728 LangGraph \u91cc，\u8282\u70b9\u4ec0\u4e48\u65f6\u5019\u6267\u884c，\u662f\u7531\u4e00\u4e2a\u4e2a \u8d85\u6b65（SuperStep） \u51b3\u5b9a\u7684\u3002<\/p>\n 8.2 \u4e00\u4e2a\u8d85\u6b65\u5206\u4e09\u4e2a\u9636\u6bb5<\/h4>\n\n\u9636\u6bb5\u505a\u4ec0\u4e48<\/tr>\n \n\n| Plan<\/td>\n | \u786e\u5b9a\u8fd9\u4e00\u6b65\u8981\u6267\u884c\u54ea\u4e9b Actor\u3002\u7b2c\u4e00\u6b65\u9009"\u8ba2\u9605\u4e86\u7279\u6b8a\u8f93\u5165\u901a\u9053"\u7684 Actor，\u540e\u7eed\u6b65\u9aa4\u9009"\u8ba2\u9605\u4e86\u4e0a\u4e00\u6b65\u88ab\u66f4\u65b0\u7684\u901a\u9053"\u7684 Actor<\/td>\n<\/tr>\n | \n| Execute<\/td>\n | \u5e76\u884c\u6267\u884c\u6240\u6709\u88ab\u9009\u4e2d\u7684 Actor，\u76f4\u5230\u5168\u90e8\u5b8c\u6210\u3001\u6216\u5176\u4e2d\u4e00\u4e2a\u5931\u8d25\u3001\u6216\u8d85\u65f6<\/td>\n<\/tr>\n | \n| Update<\/td>\n | \u7528\u8fd9\u4e00\u6b65 Actor \u5199\u5165\u7684\u503c，\u53bb\u66f4\u65b0\u5bf9\u5e94\u7684 Channel<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \u8fd9\u4e09\u4e2a\u9636\u6bb5\u7ec4\u6210\u7684\u4e00\u4e2a"\u8d85\u6b65"\u4f1a\u4e0d\u65ad\u91cd\u590d，\u76f4\u5230\u6ca1\u6709 Actor \u88ab\u9009\u4e2d，\u6216\u8005\u8fbe\u5230\u6700\u5927\u6b65\u6570\u3002<\/p>\n \u6362\u53e5\u8bdd\u8bf4：\u4e0d\u662f"\u8fb9\u901a\u5411\u8c01"\u51b3\u5b9a\u6267\u884c\u987a\u5e8f，\u800c\u662f"\u8c01\u5199\u4e86\u8fd9\u4e2a\u901a\u9053\u3001\u8c01\u8ba2\u9605\u4e86\u8fd9\u4e2a\u901a\u9053"\u51b3\u5b9a\u4e0b\u4e00\u6279\u8dd1\u8c01\u3002 \u8fb9\u53ea\u662f\u5e2e\u4f60\u628a"\u8ba2\u9605\u5173\u7cfb"\u81ea\u52a8\u751f\u6210\u51fa\u6765\u7684\u8bed\u6cd5\u7cd6\u3002<\/p>\n 8.3 \u8ddf\u7740\u4e00\u4e2a\u4f8b\u5b50\u6570\u4e00\u904d Step<\/h4>\n\u5047\u8bbe\u56fe\u662f\u8fd9\u6837\u7684：START \u2192 a \u2192 (b, c)；b \u2192 b_2 \u2192 d；c \u2192 d；d \u2192 END\u3002<\/p>\n \u7f16\u8bd1\u65f6，builder.compile() \u4f1a\u628a\u8fd9\u5f20\u903b\u8f91\u56fe\u8f6c\u6362\u6210 Pregel \u5b9e\u4f8b：\u8282\u70b9\u53d8\u6210 Actors，\u8fb9\u53d8\u6210 Channels\u3002<\/p>\n \u6267\u884c\u8fc7\u7a0b（Step \u4ece 0 \u5f00\u59cb\u6570）：<\/p>\n \n- Step -1：__START__ \u8282\u70b9\u6267\u884c（\u56fe\u4e2d\u770b\u4e0d\u89c1），\u628a\u72b6\u6001\u5199\u8fdb branch:to:a；<\/li>\n
- Step 0：\u8282\u70b9 a \u6267\u884c，\u628a\u72b6\u6001\u5199\u8fdb branch:to:b \u548c branch:to:c；<\/li>\n
- Step 1：\u8282\u70b9 b \u548c c \u5e76\u884c\u6267\u884c，\u5206\u522b\u5199\u8fdb branch:to:b_2 \u548c branch:to:d；<\/li>\n
- Step 2：\u8282\u70b9 b_2 \u548c\u8282\u70b9 d \u6267\u884c\u3002\u6ce8\u610f d \u8fd9\u65f6\u5019\u5df2\u7ecf\u88ab\u89e6\u53d1\u8fc7\u4e00\u6b21（\u56e0\u4e3a c \u5199\u4e86\u5b83），b_2 \u53c8\u5f80 branch:to:d \u5199\u4e86\u4e00\u6b21；<\/li>\n
- Step 3：\u8282\u70b9 d \u518d\u6267\u884c\u4e00\u6b21，\u8fd9\u6b21\u6ca1\u6709\u65b0\u7684\u72b6\u6001\u66f4\u65b0，\u56fe\u7684\u6267\u884c\u7ed3\u675f\u3002<\/li>\n<\/ul>\n
\u8fd9\u4e2a\u4f8b\u5b50\u8bf4\u660e\u4e86\u4e00\u4ef6\u91cd\u8981\u7684\u4e8b：\u540c\u4e00\u4e2a\u8282\u70b9\u53ef\u4ee5\u5728\u591a\u4e2a Step \u91cc\u88ab\u591a\u6b21\u6267\u884c（d \u8dd1\u4e86\u4e24\u6b21）\u3002\u8fd9\u5c31\u662f\u4e3a\u4ec0\u4e48"\u5faa\u73af"\u5bf9 LangGraph \u6765\u8bf4\u662f\u5929\u7136\u7684，\u800c\u4e0d\u662f\u9760\u7279\u6b8a\u8bed\u6cd5\u5b9e\u73b0\u3002<\/p>\n import operator
\nfrom typing import Annotated
\nfrom typing_extensions import TypedDict
\nfrom langgraph.graph import StateGraph, START, END<\/p>\n class State(TypedDict):
\n aggregate: Annotated[list, operator.add]<\/p>\n def a(state: State, config):
\n print(f'Adding "A" to {state["aggregate"]}')
\n return {"aggregate": ["A"]}<\/p>\n def b(state: State, config):
\n print(f'Adding "B" to {state["aggregate"]}')
\n return {"aggregate": ["B"]}<\/p>\n def b_2(state: State, config):
\n print(f'Adding "B_2" to {state["aggregate"]}')
\n return {"aggregate": ["B_2"]}<\/p>\n def c(state: State, config):
\n print(f'Adding "C" to {state["aggregate"]}')
\n return {"aggregate": ["C"]}<\/p>\n def d(state: State, config):
\n print(f'Adding "D" to {state["aggregate"]}')
\n return {"aggregate": ["D"]}<\/p>\n builder = StateGraph(State)
\nbuilder.add_node("a", a)
\nbuilder.add_node("b", b)
\nbuilder.add_node("b_2", b_2)
\nbuilder.add_node("c", c)
\nbuilder.add_node("d", d)<\/p>\n builder.add_edge(START, "a")
\nbuilder.add_edge("a", "b")
\nbuilder.add_edge("a", "c")
\nbuilder.add_edge("b", "b_2")
\nbuilder.add_edge("b_2", "d")
\nbuilder.add_edge("c", "d")
\nbuilder.add_edge("d", END)<\/p>\n graph = builder.compile()<\/p>\n # 1\u3001\u67e5\u770b\u5f53\u524d\u56fe\u7684 channels
\nprint("\u5f53\u524d\u56fe\u7684channels\u4e3a", graph.channels)
\n# 2\u3001\u67e5\u770b\u5f53\u524d\u56fe\u7684\u8282\u70b9
\nprint("\u5f53\u524d\u56fe\u7684\u8282\u70b9\u4e3a", graph.nodes)
\n# 3\u3001\u67e5\u770b a \u8282\u70b9\u7684\u89e6\u53d1\u6761\u4ef6（\u8ba2\u9605）\u548c\u5199\u5165\u76ee\u6807
\nprint("\u8282\u70b9a\u7684triggers\u4e3a", graph.nodes["a"].triggers)
\nprint("\u8282\u70b9a\u7684writers\u4e3a", graph.nodes["a"].writers)
\n# 4\u3001\u67e5\u770b d \u8282\u70b9\u7684\u89e6\u53d1\u6761\u4ef6\u548c\u5199\u5165\u76ee\u6807
\nprint("\u8282\u70b9d\u7684triggers\u4e3a", graph.nodes["d"].triggers)
\nprint("\u8282\u70b9d\u7684writers\u4e3a", graph.nodes["d"].writers)<\/p>\n # 5\u3001\u6267\u884c\u56fe，\u67e5\u770b\u7ed3\u679c
\noutput_state = graph.invoke({"aggregate": []})
\nprint("\u6267\u884c\u56fe\u540e\u7684\u72b6\u6001\u4e3a", output_state)<\/p>\n \u6253\u5370\u51fa\u6765\u7684 triggers \u5c31\u662f"\u8fd9\u4e2a\u8282\u70b9\u8ba2\u9605\u4e86\u54ea\u4e9b\u901a\u9053"，writers \u5c31\u662f"\u8fd9\u4e2a\u8282\u70b9\u4f1a\u5199\u54ea\u4e9b\u901a\u9053"\u3002\u770b\u61c2\u8fd9\u4e24\u884c\u8f93\u51fa，\u4f60\u5c31\u80fd\u9884\u6d4b\u4efb\u4f55\u4e00\u5f20\u56fe\u7684\u6267\u884c\u987a\u5e8f\u4e86\u3002<\/p>\n \u4e5d\u3001\u68c0\u67e5\u70b9\u5feb\u7167：\u600e\u4e48\u628a\u5386\u53f2\u72b6\u6001\u7ffb\u51fa\u6765\u770b<\/h3>\n\u6709\u4e86 checkpointer，LangGraph \u4f1a\u5728\u6bcf\u4e2a\u8d85\u6b65\u7ed3\u675f\u65f6\u5b58\u4e00\u4efd\u5feb\u7167\u3002\u90a3\u600e\u4e48\u8bfb\u51fa\u6765？\u4e24\u4e2a\u65b9\u6cd5：<\/p>\n | |