75 lines
2.1 KiB
Python
75 lines
2.1 KiB
Python
from typing import TypedDict, Annotated
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import operator
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import time
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from langgraph.graph import StateGraph, END
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class GraphState(TypedDict):
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messages: Annotated[list, operator.add]
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step_count: int
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result: str
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def step_1(state: GraphState) -> GraphState:
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print("🔄 执行步骤1: 数据准备阶段")
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time.sleep(0.5)
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return {
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"messages": ["步骤1: 开始数据准备"],
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"step_count": state.get("step_count", 0) + 1,
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"result": "数据准备完成",
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}
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def step_2(state: GraphState) -> GraphState:
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print("🔄 执行步骤2: 数据处理阶段")
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time.sleep(0.7)
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return {
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"messages": ["步骤2: 正在处理数据"],
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"step_count": state.get("step_count", 0) + 1,
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"result": "数据处理完成，准备分析",
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}
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def step_3(state: GraphState) -> GraphState:
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print("🔄 执行步骤3: 数据分析阶段")
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time.sleep(0.9)
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total_messages = len(state.get("messages", []))
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return {
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"messages": ["步骤3: 分析完成，生成最终结果"],
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"step_count": state.get("step_count", 0) + 1,
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"result": f"分析完成！总共处理了 {total_messages + 1} 条消息，执行了 {state.get('step_count', 0) + 1} 个步骤",
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}
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def create_workflow():
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wf = StateGraph(GraphState)
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wf.add_node("step_1", step_1)
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wf.add_node("step_2", step_2)
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wf.add_node("step_3", step_3)
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wf.set_entry_point("step_1")
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wf.add_edge("step_1", "step_2")
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wf.add_edge("step_2", "step_3")
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wf.add_edge("step_3", END)
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return wf.compile()
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def main():
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print("=" * 60)
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print("🚀 LangGraph stream_mode='values' 示例（返回完整状态）")
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print("=" * 60)
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app = create_workflow()
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initial = {"messages": [], "step_count": 0, "result": ""}
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for i, state in enumerate(app.stream(initial, stream_mode="values")):
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print(f"\n🔍 步骤 {i} 完成后的状态:")
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print(f" 📝 messages: {state.get('messages', [])}")
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print(f" 🔢 step_count: {state.get('step_count', 0)}")
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print(f" ✨ result: {state.get('result', '')}")
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print("\n✅ 完成！")
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if __name__ == "__main__":
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main()
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