add langgraph use
This commit is contained in:
lingyuzeng
53
examples/stream_modes/debug_demo.py
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53
examples/stream_modes/debug_demo.py
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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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time.sleep(0.2)
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return {"messages": ["S1"], "step_count": state.get("step_count", 0) + 1, "result": "r1"}
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def step_2(state: GraphState) -> GraphState:
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time.sleep(0.2)
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return {"messages": ["S2"], "step_count": state.get("step_count", 0) + 1, "result": "r2"}
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def step_3(state: GraphState) -> GraphState:
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time.sleep(0.2)
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return {"messages": ["S3"], "step_count": state.get("step_count", 0) + 1, "result": "done"}
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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='debug' 示例（开发定位用）")
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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 info in app.stream(initial, stream_mode="debug"):
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print(info)
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if __name__ == "__main__":
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main()
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67
examples/stream_modes/graph_visualize.py
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67
examples/stream_modes/graph_visualize.py
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"""
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Demonstrate compiling a LangGraph and visualizing its structure.
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Requires no external viz packages for ASCII. To export PNG, install:
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uv pip install -e '.[viz]'
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and ensure Graphviz is present on your system.
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"""
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from typing import TypedDict, Annotated
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import operator
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from langgraph.graph import StateGraph, START, END
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class S(TypedDict):
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a: int
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b: int
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c: int
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def n1(s: S) -> S:
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return {"a": s.get("a", 0) + 1, "b": s.get("b", 0), "c": s.get("c", 0)}
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def n2(s: S) -> S:
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return {"a": s.get("a", 0), "b": s.get("b", 0) + 2, "c": s.get("c", 0)}
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def n3(s: S) -> S:
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return {"a": s.get("a", 0), "b": s.get("b", 0), "c": s.get("c", 0) + 3}
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def build_app():
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g = StateGraph(S)
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g.add_node("n1", n1)
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g.add_node("n2", n2)
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g.add_node("n3", n3)
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g.add_edge(START, "n1")
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g.add_edge("n1", "n2")
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g.add_edge("n2", "n3")
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g.add_edge("n3", END)
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return g.compile()
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def main():
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app = build_app()
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graph = app.get_graph()
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# Try ASCII render if available
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draw_ascii = getattr(graph, "draw_ascii", None)
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if callable(draw_ascii):
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print("=== Graph ASCII ===")
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print(draw_ascii())
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# Try PNG export if available and pydot/graphviz installed
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draw_png = getattr(graph, "draw_png", None)
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if callable(draw_png):
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try:
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out = "graph_demo.png"
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draw_png(out)
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print(f"Saved PNG: {out}")
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except Exception as e:
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print(f"PNG export unavailable: {e}")
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if __name__ == "__main__":
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main()
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43
examples/stream_modes/messages_demo.py
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43
examples/stream_modes/messages_demo.py
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from typing import TypedDict
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from langgraph.graph import StateGraph, START
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from langchain_core.messages import HumanMessage
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from langgraph_qwen import ChatQwenOpenAICompat
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class SimpleState(TypedDict):
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topic: str
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joke: str
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model = ChatQwenOpenAICompat(temperature=0)
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def call_model(state: SimpleState):
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llm_response = model.invoke([HumanMessage(content=f"Generate a joke about {state['topic']}")])
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return {"joke": llm_response.content}
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graph = (
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StateGraph(SimpleState)
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.add_node("call_model", call_model)
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.add_edge(START, "call_model")
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.compile()
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)
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def main():
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print("=" * 60)
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print("💬 LangGraph stream_mode='messages' 示例（捕获 LLM tokens）")
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print("=" * 60)
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for msg, meta in graph.stream({"topic": "cats"}, stream_mode="messages"):
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if hasattr(msg, "content") and msg.content:
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node = meta.get("langgraph_node", "unknown")
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print(f"[{node}] {msg.content}", end="", flush=True)
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print("\n\n✅ 完成！")
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if __name__ == "__main__":
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main()
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75
examples/stream_modes/updates_demo.py
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75
examples/stream_modes/updates_demo.py
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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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time.sleep(0.3)
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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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time.sleep(0.4)
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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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time.sleep(0.5)
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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！共 {total_messages + 1} 条消息，步骤 {state.get('step_count', 0) + 1}",
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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='updates' 示例（仅返回增量）")
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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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# 自行维护完整状态
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current_state = dict(initial)
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for chunk in app.stream(initial, stream_mode="updates"):
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for node_name, updates in chunk.items():
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print(f"📦 {node_name} 更新: {updates}")
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current_state.update(updates)
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print("\n✅ 最终合并状态:")
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print(current_state)
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if __name__ == "__main__":
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main()
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74
examples/stream_modes/values_demo.py
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74
examples/stream_modes/values_demo.py
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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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