Eric Wang
6d0a2169c8
- graph.py: LangGraph-native DI - StateGraph(context_schema=GraphDeps), nodes take (state, runtime: Runtime[GraphDeps]); build_graph() decoupled from LLM; deleted scaffold _event_reply/_fake_llm_propose/stub nodes - photo.py: model proposes stage+body via per-mode prompts (direct/addon); validator enforces clientMode exits; deterministic event forcing removed - confirm.py: single runtime for single/dual confirm, extraction call isolated per person_index - llm.py: workflow_fake_llm() (offline workflow-faithful responder, history-aware) for smoke/tests - backend: LangGraphBackend(graph, llm) passes context per call - tests: invoke helpers inject GraphDeps; illegal-proposal test asserts error + state untouched via second well-behaved fake Verified: 143 passed; smoke turns 1/2/1 with original welcome text
42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
"""LangGraph 脚手架冒烟脚本。
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同一 thread 输入两次、另一个 thread 输入一次，打印轮数和文本。
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预期轮数依次为 1、2、1；首轮为 welcome（1001 固定问候，不调模型），
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第二轮起由注入的 workflow fake LLM 按提示词语义回复。
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本脚本不导入 FastGPT、不读取其密钥；离线即可运行：
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python -m examples.langgraph_smoke
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"""
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import asyncio
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from src.agent.graph import GraphDeps, build_graph, workflow_fake_llm
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async def main() -> None:
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graph = build_graph()
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deps = GraphDeps(llm=workflow_fake_llm())
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async def ask(thread_id: str, text: str) -> None:
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# 只传本轮变化的字段；会话字段（turn_count/stage_code 等）
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# 由 checkpoint 保管。注意：对已有 checkpoint 的 thread 传
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# 完整初始状态会覆盖已累计的值。
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result = await graph.ainvoke(
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{"session_id": thread_id, "input_text": text},
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config={"configurable": {"thread_id": thread_id}},
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context=deps,
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)
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print(
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f"thread={thread_id} turn_count={result['turn_count']} "
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f"stage_code={result['stage_code']} text={result['response_text']}"
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)
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await ask("thread-a", "你好")
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await ask("thread-a", "发生了交通事故")
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await ask("thread-b", "你好")
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if __name__ == "__main__":
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asyncio.run(main())
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