<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>LangGraph on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/langgraph/</link><description>Recent content in LangGraph on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 16 Jul 2026 11:06:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/langgraph/index.xml" rel="self" type="application/rss+xml"/><item><title>智能体框架横评：LangGraph vs AutoGen vs CrewAI</title><link>https://guijiagi.com/posts/b1-4d8adb63/</link><pubDate>Thu, 16 Jul 2026 11:06:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-4d8adb63/</guid><description>横向对比三大主流智能体框架的架构设计、编程模型、适用场景与优劣分析</description></item><item><title>开源智能体框架LangGraph深度实践：构建生产级Agent系统</title><link>https://guijiagi.com/posts/b2-39413525/</link><pubDate>Thu, 16 Jul 2026 10:42:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-39413525/</guid><description>深入LangGraph框架的工程实践，涵盖状态管理、检查点、人机协作与生产部署的完整方案</description></item><item><title>AI Agent框架横评：LangGraph、AutoGen与Crewy的架构设计与实战对比</title><link>https://guijiagi.com/posts/b2-587a38c5/</link><pubDate>Thu, 16 Jul 2026 10:11:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-587a38c5/</guid><description>深入对比2026年三大主流AI Agent框架的架构设计、编程模型与适用场景，提供框架选型决策指南</description></item><item><title>Agent编排引擎对比：LangGraph vs CrewAI vs AutoGen</title><link>https://guijiagi.com/posts/article-13/</link><pubDate>Sun, 12 Jul 2026 19:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-13/</guid><description>深入对比三大主流Agent编排框架的架构理念和适用场景，帮助开发者做出正确的框架选型</description></item><item><title>Agent编排引擎对比：LangGraph vs CrewAI vs AutoGen</title><link>https://guijiagi.com/posts/b2-85369398/</link><pubDate>Sun, 12 Jul 2026 19:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-85369398/</guid><description>深入对比三大主流Agent编排框架的架构理念和适用场景，帮助开发者做出正确的框架选型</description></item><item><title>Agent框架基准测试2026：谁是最佳智能体框架</title><link>https://guijiagi.com/posts/agent-framework-benchmark-2026/</link><pubDate>Thu, 02 Jul 2026 11:35:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-framework-benchmark-2026/</guid><description>2026年主流Agent框架基准测试与对比，从性能到功能的全面评测</description></item><item><title>LangChain 2026演进：从框架到平台</title><link>https://guijiagi.com/posts/langchain-2026-evolution/</link><pubDate>Thu, 02 Jul 2026 11:27:00 +0800</pubDate><guid>https://guijiagi.com/posts/langchain-2026-evolution/</guid><description>2026年LangChain生态系统演进全景，从LLM框架到AI应用平台</description></item><item><title>多智能体协作 2026：从 LangGraph 到 CrewAI 的架构演进</title><link>https://guijiagi.com/posts/multi-agent-collaboration-2026/</link><pubDate>Tue, 30 Jun 2026 16:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/multi-agent-collaboration-2026/</guid><description>多智能体协作框架全景对比：LangGraph、CrewAI、AutoGen、MetaGPT的核心架构差异与选型指南</description></item><item><title>LangGraph 2026：图式Agent工作流的最佳实践</title><link>https://guijiagi.com/posts/langgraph-2026-graph-agent-workflow-best-practices/</link><pubDate>Tue, 30 Jun 2026 09:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/langgraph-2026-graph-agent-workflow-best-practices/</guid><description>深入解析LangGraph 2026版本的图式Agent工作流引擎，从状态管理到条件路由的完整实践指南</description></item><item><title>LangGraph 2026：图式Agent工作流的最佳实践</title><link>https://guijiagi.com/posts/langgraph-2026-graph-agent-workflow/</link><pubDate>Tue, 30 Jun 2026 09:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/langgraph-2026-graph-agent-workflow/</guid><description>深入解析LangGraph 2026版本的图式Agent工作流架构，涵盖状态管理、条件路由、并行执行等核心特性与生产级最佳实践</description></item><item><title>CrewAI vs AutoGen vs LangGraph：多 Agent 框架终决</title><link>https://guijiagi.com/posts/crewai-vs-autogen-vs-langgraph/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/crewai-vs-autogen-vs-langgraph/</guid><description>深度对比 2026 年三大主流多 Agent 框架 CrewAI、AutoGen、LangGraph 的架构设计、性能表现、开发体验与适用场景</description></item><item><title>LangChain 2026 生态全景：从 LangGraph 到 LangSmith</title><link>https://guijiagi.com/posts/langchain-2026-ecosystem/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/langchain-2026-ecosystem/</guid><description>全面解析 LangChain 2026 年生态系统，涵盖 LangGraph 状态机编排、LangSmith 可观测性平台、LangServe 部署工具及最新生态组件</description></item><item><title>LangGraph Agent工作流评测</title><link>https://guijiagi.com/posts/langgraph-agent-workflow/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/langgraph-agent-workflow/</guid><description>LangGraph Agent工作流评测</description></item><item><title>智能体工作流编排：从 DAG 到动态执行</title><link>https://guijiagi.com/posts/agent-workflow-orchestration/</link><pubDate>Fri, 26 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-workflow-orchestration/</guid><description>深入探讨智能体工作流编排的演进路径，从静态 DAG 到动态执行图，涵盖 LangGraph 等主流框架的架构设计与实践</description></item><item><title>LangGraph vs LangChain：该用哪个构建 Agent</title><link>https://guijiagi.com/posts/langgraph-vs-langchain/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/langgraph-vs-langchain/</guid><description>LangChain 的痛点在哪？LangGraph 如何用图结构解决 Agent 编排问题？本文从状态管理、条件边、检查点到 Human-in-the-loop，全面对比两个框架并给出迁移建议。</description></item><item><title>LangChain vs LangGraph：Agent 框架的演进与选择</title><link>https://guijiagi.com/posts/langchain-langgraph-review/</link><pubDate>Wed, 24 Jun 2026 12:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/langchain-langgraph-review/</guid><description>LangChain 生态深度解析：从链式调用到图式编排的范式转变</description></item><item><title>LangGraph 深度解析：基于图的工作流引擎如何重塑 Agent 开发</title><link>https://guijiagi.com/posts/langgraph-deep-dive/</link><pubDate>Tue, 23 Jun 2026 14:10:00 +0800</pubDate><guid>https://guijiagi.com/posts/langgraph-deep-dive/</guid><description>从架构设计到实战代码，全面解读 LangGraph 的图工作流模型</description></item></channel></rss>