55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
"""
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Finalize 节点 - 轻量后处理
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"""
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from typing import Dict, Any, Optional
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from langchain_core.runnables.config import RunnableConfig
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from langchain_core.messages import AIMessage
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from backend.app.main_graph.state import AgentState
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from backend.app.logger import info
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async def finalize_node(state: AgentState, config: Optional[RunnableConfig] = None) -> Dict[str, Any]:
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"""
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Finalize 节点：轻量后处理
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职责：
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1. 从 messages 中提取最后一条 AIMessage.content 作为最终回复
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2. 汇总元数据：步数、使用的工具、停止原因
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3. 如果 final_reply 为空且有 stop_reason，生成说明文本
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"""
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info("[Finalize] 执行后处理")
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# 获取最终回复
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final_reply = ""
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for msg in reversed(state.messages):
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if isinstance(msg, AIMessage) and msg.content:
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final_reply = msg.content
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break
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# 获取停止原因
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stop_reason = getattr(state, "stop_reason", "")
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if not final_reply and stop_reason:
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# 如果没有回复但有停止原因，生成说明
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reason_messages = {
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"loop_detected": "[系统] 检测到工具调用循环，已终止。",
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"max_steps": "[系统] 已达到最大步数限制。",
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}
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final_reply = reason_messages.get(stop_reason, f"[系统] 已终止，原因: {stop_reason}")
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# 汇总元数据
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metadata = {
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"steps_taken": getattr(state, "current_step", 0),
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"tools_used": getattr(state, "tools_used", []),
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"stop_reason": stop_reason,
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"llm_calls": getattr(state, "llm_calls", 0),
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}
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info(f"[Finalize] 完成 - steps: {metadata['steps_taken']}, tools: {len(metadata['tools_used'])}")
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return {
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"final_reply": final_reply,
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"metadata": metadata,
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}
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