agent-craft and AgentGuide
These are **complements** — Annyfee/agent-craft provides systematized runnable code examples for building agents with LangChain/RAG/LangGraph/MCP, while adongwanai/AgentGuide offers comprehensive development guidance, advanced RAG patterns, and interview preparation to understand the conceptual and practical foundations needed to effectively use those tools.
About agent-craft
Annyfee/agent-craft
AI Agent 教学仓库 | 系统化 LangChain、RAG、LangGraph、MCP 全栈实战代码 | 万字博客详解 | 开源可运行示例 | 从零构建智能体
This project is a systematic guide for developers looking to build sophisticated AI agents from scratch using Python. It takes you from basic large language model (LLM) calls to integrating advanced features like external tools and knowledge bases. You'll learn to create intelligent systems that can understand, reason, and act, ultimately deploying them as functional applications.
About AgentGuide
adongwanai/AgentGuide
https://adongwanai.github.io/AgentGuide | AI Agent开发指南 | LangGraph实战 | 高级RAG | 转行大模型 | 大模型面试 | 算法工程师 | 面试题库 | 强化学习｜数据合成
This guide provides a comprehensive pathway for individuals looking to build and deploy AI Agent applications or transition into roles like AI Agent Algorithm Engineer or LLM Application Engineer. It takes you from understanding core concepts and practical application development using frameworks like LangGraph, through advanced RAG systems, to preparing for technical interviews and crafting standout resumes. The guide helps aspiring AI professionals transform fragmented knowledge into a structured, career-focused learning journey.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work