Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch
| Date | Stars |
|---|---|
| 2026-07-31 | 348 |
| 2026-08-01 | 350 |
| 2026-08-02 | 352 |
| 2026-08-03 | 354 |
| 2026-08-04 | 355 |
| 2026-08-05 | 364 |
| 2026-08-06 | 367 |
Today
+3 stars today
This week
— stars this week
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Momentum
12.0
growth rate 0.00%/day
<div align="center"> <img src="readme_img.png" width="900" alt="Agent Learning Roadmap"> <br> # 🤖 Agent Learning: Learn Agent Development from Scratch **A practical AI Agent book for Python developers — go from a first working Agent in 30 minutes to evaluated, production-ready Agent systems.** > Go beyond calling a chatbot: understand and connect tool use, RAG, memory, planning, LangGraph, MCP, evaluation, safety, and deployment by building a complete mental model. **23 chapters · 120+ original diagrams · 5 interactive animations · bilingual online book · daily Agent research tracking** <br> [](https://opensource.org/licenses/MIT) [](https://github.com/Haozhe-Xing/agent_learning) [](https://github.com/Haozhe-Xing/agent_learning/pulls) [](https://rust-lang.github.io/mdBook/) [](https://arxiv.org) <br> [<img src="https://img.shields.io/badge/📖_Build_your_first_Agent-4CAF50?style=for-the-badge" alt="Start with your first Agent">](https://Haozhe-Xing.github.io/agent_learning/en/chapter_intro/) [<img src="https://img.shields.io/badge/🗺️_Choose_a_learning_path-2196F3?style=for-the-badge" alt="Choose a learning path">](#-choose-your-outcome) [<img src="https://img.shields.io/badge/📖_Read_online_(English)-673AB7?style=for-the-badge" alt="Read online in English">](https://Haozhe-Xing.github.io/agent_learning/en/) </div> ## 🎯 Choose your outcome | Your goal | What you will be able to do | Start here | | --- | --- | --- | | **Build your first Agent in 30 minutes** | Form a concrete intuition for the perceive-think-act loop and tool use | [Chapter 1: Agent Basics](https://Haozhe-Xing.github.io/agent_learning/en/chapter_intro/) → [Appendix: Hello Agent](https://Haozhe-Xing.github.io/agent_learning/en/chapter_setup/04_hello_agent.html) | | **Build a useful Agent application** | Combine tool calling, RAG, memory, planning, and context engineering | [Chapter 3: Tool Use](https://Haozhe-Xing.github.io/agent_learning/en/chapter_tools/) → [Chapter 6: RAG](https://Haozhe-Xing.github.io/agent_learning/en/chapter_rag/) | | **Ship an Agent to production** | Develop an engineering perspective on evaluation, safety, observability, deployment, and cost | [Chapter 17: Evaluation](https://Haozhe-Xing.github.io/agent_learning/en/chapter_evaluation/) → [Chapter 19: Deployment](https://Haozhe-Xing.github.io/agent_learning/en/chapter_deployment/) | > ⭐ If this path saves you research time and avoids common pitfalls, please Star the repository. It helps more developers discover this actively maintained open-source guide. <div align="center"> [🐛 Report an issue](https://github.com/Haozhe-Xing/agent_learning/issues) · [💡 Suggest an improvement](https://github.com/Haozhe-Xing/agent_learning/issues/new) · [🇨🇳 中文版 README](README_ZH.md) </div> --- ## 🚀 Auto-Tracking Frontier: Daily arXiv Paper Updates <div align="center"> 🤖 **This repository automatically searches arXiv for the latest AI Agent-related papers every day and updates the content accordingly — ensuring you always stay at the cutting edge of research!** </div> - 📡 **Daily Automated Search**: A scheduled pipeline scans arXiv daily for new papers on Agent architectures, tool use, memory systems, multi-agent collaboration, reinforcement learning for agents, and more. - 📝 **Auto-Updated Content**: Relevant findings are automatically integrated into the corresponding chapters, keeping the book's frontier sections fresh and up-to-date. - 🔔 **Never Miss a Breakthrough**: No need to manually track dozens of research feeds — this repo does it for you, so you can focus on learning a
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:adfa61e45277b257, topic:ai-agent, topic:agentic-workflow, desc:ai agent
matched fp:adfa61e45277b257, topic:large-language-models, topic:llm