随着人工智能技术的快速发展，构建能够自主推理和执行复杂任务的智能体系统已成为当前研究的热点。ReAct（Reasoning + Action）智能体作为一种突破性的架构模式，成功地将语言模型的推理能力与外部工具的行动能力有机结合，为解决复杂的现实世界问题提供了 ...

LangGraph 设计的一个核心是：多智能体工作流本质上是图结构，而非线性链。早期 LLM 应用普遍采用"提示 → LLM → 响应"的线性模式，但这种架构难以应对真实智能体系统的复杂性。比如生产环境中的多智能体协作需要分支（基于数据选择不同执行路径）、循环 ...

LangGraph has been used to create a multi-agent large language model (LLM) coding framework. This framework is designed to automate various software development tasks, including coding, testing, and ...

In the rapidly evolving field of artificial intelligence, LangGraph has emerged as a groundbreaking tool that is transforming the way advanced AI agents, particularly research agents, are developed.