<?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>框架测评 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/categories/%E6%A1%86%E6%9E%B6%E6%B5%8B%E8%AF%84/</link><description>Recent content in 框架测评 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 11:39:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/categories/%E6%A1%86%E6%9E%B6%E6%B5%8B%E8%AF%84/index.xml" rel="self" type="application/rss+xml"/><item><title>大模型推理引擎横评：vLLM、SGLang、TensorRT-LLM</title><link>https://guijiagi.com/posts/b1-f50aea03/</link><pubDate>Thu, 16 Jul 2026 11:39:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-f50aea03/</guid><description>对比分析三大主流推理引擎的架构设计、性能特征与适用场景，给出选型建议</description></item><item><title>AI 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10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/crewai-deep-review/</guid><description>CrewAI 如何用角色扮演编排多 Agent 协作？顺序与层级流程孰优孰劣？与 AutoGen、LangGraph 相比有何差距？本文从架构到生产可用性全面拆解。</description></item><item><title>Haystack 2.0 评测：deepset 的 RAG 框架重生</title><link>https://guijiagi.com/posts/haystack-20-review/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/haystack-20-review/</guid><description>Haystack 2.0 相比 1.x 有哪些根本性变化？Pipeline 组件架构如何设计？与 LangChain 相比在企业 RAG 部署上有何优势？本文全面拆解。</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>LlamaIndex Agent 评测：从 RAG 到 Agent 的进化</title><link>https://guijiagi.com/posts/llama-index-agent-review/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llama-index-agent-review/</guid><description>LlamaIndex 不只是 RAG 框架。Data Agent、Agent Worker、Agent Runner 如何将检索增强生成进化为智能体？RAG+Agent 融合有哪些实战模式？</description></item><item><title>OpenClaw 评测：个人 AI Agent 的开源实践</title><link>https://guijiagi.com/posts/openclaw-agent-review/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/openclaw-agent-review/</guid><description>OpenClaw 如何用 Skill 系统构建个人 AI Agent？多渠道集成、Memory/Heartbeat 记忆机制、Cron 定时调度——开源 Agent 框架的实战评测。</description></item><item><title>Semantic Kernel 评测：微软的 AI 编排内核</title><link>https://guijiagi.com/posts/semantic-kernel-review/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/semantic-kernel-review/</guid><description>Semantic Kernel 如何用 Plugin 系统编排 AI 能力？Planner 自动编排、Memory 语义记忆、Connector 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评估框架，分析评估维度、数据集规模与适用场景</description></item><item><title>AutoGen 多智能体框架评测：微软的 Agent 雄心</title><link>https://guijiagi.com/posts/autogen-multi-agent-review/</link><pubDate>Wed, 24 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/autogen-multi-agent-review/</guid><description>AutoGen v0.4 新架构解析、多 Agent 对话模式、GroupChat、代码执行、与 LangGraph/CrewAI 横向对比</description></item><item><title>Haystack 框架评测：deepset 的 RAG 之选</title><link>https://guijiagi.com/posts/haystack-review/</link><pubDate>Wed, 24 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/haystack-review/</guid><description>深度评测 deepset Haystack 框架，涵盖 Pipeline 架构、Node 体系、RAG 最佳实践及生产部署经验</description></item><item><title>LlamaIndex 框架评测：RAG 领域的瑞士军刀</title><link>https://guijiagi.com/posts/llama-index-review/</link><pubDate>Wed, 24 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llama-index-review/</guid><description>深度评测 LlamaIndex 框架，涵盖核心架构、索引类型、查询引擎、Agent 模式及与 LangChain 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