from typing import TypedDict, Annotated
import operator
import time

from langgraph.graph import StateGraph, END


class GraphState(TypedDict):
    messages: Annotated[list, operator.add]
    step_count: int
    result: str


def step_1(state: GraphState) -> GraphState:
    time.sleep(0.3)
    return {
        "messages": ["步骤1: 开始数据准备"],
        "step_count": state.get("step_count", 0) + 1,
        "result": "数据准备完成",
    }


def step_2(state: GraphState) -> GraphState:
    time.sleep(0.4)
    return {
        "messages": ["步骤2: 正在处理数据"],
        "step_count": state.get("step_count", 0) + 1,
        "result": "数据处理完成，准备分析",
    }


def step_3(state: GraphState) -> GraphState:
    time.sleep(0.5)
    total_messages = len(state.get("messages", []))
    return {
        "messages": ["步骤3: 分析完成，生成最终结果"],
        "step_count": state.get("step_count", 0) + 1,
        "result": f"分析完成！共 {total_messages + 1} 条消息，步骤 {state.get('step_count', 0) + 1}",
    }


def create_workflow():
    wf = StateGraph(GraphState)
    wf.add_node("step_1", step_1)
    wf.add_node("step_2", step_2)
    wf.add_node("step_3", step_3)
    wf.set_entry_point("step_1")
    wf.add_edge("step_1", "step_2")
    wf.add_edge("step_2", "step_3")
    wf.add_edge("step_3", END)
    return wf.compile()


def main():
    print("=" * 60)
    print("🔄 LangGraph stream_mode='updates' 示例（仅返回增量）")
    print("=" * 60)

    app = create_workflow()
    initial = {"messages": [], "step_count": 0, "result": ""}

    # 自行维护完整状态
    current_state = dict(initial)
    for chunk in app.stream(initial, stream_mode="updates"):
        for node_name, updates in chunk.items():
            print(f"📦 {node_name} 更新: {updates}")
            current_state.update(updates)

    print("\n✅ 最终合并状态:")
    print(current_state)


if __name__ == "__main__":
    main()