如何让AI智能体（Agent）像人类一样拥有持久的记忆，从而在复杂的连续任务中保持上下文感知和深度理解？这已成为构建高级智能体的核心挑战。本文将深入探讨Agent Memory的核心概念，并聚焦于LangGraph框架下的长短期记忆实现，详解短期会话与长期知识的存储 ...

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 ...

What if you could build your own AI agent, one that operates entirely on your local machine, free from cloud dependencies and API costs? Imagine having complete control over your data, making sure ...