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导语 在过去的一两年里，大语言模型（LLM）的发展让 AI Agent 迎来了寒武纪大爆发。然而，当我们将 Agent 从简单的“单点对话”推向诸如“端到端旅游规划”这样长链路、多异构数据源的复杂生产场景时，传统基于单体 LLM 的 ReAct (Reason+Act) 模式迅速暴露出其工程瓶颈：响应极慢、状态易崩、逻辑与执行深度耦合。