didilili/ai-agents-from-zero
🚀 2026 最系统的 AI Agent 速成指南｜智能体实战教程 · 完整学习路径 + 实战项目 + 面试题库 · 对标大模型应用开发工程师岗位 · 覆盖LangChain / LangGraph / Coze / Dify / MCP / skills / LLM / RAG / 提示词 · 企业级部署与微调 · 从0到企业级落地 + 从学习到上线项目 + 面试准备一体化
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
The project lists 2 contributors on GitHub.
Peaked at #51 in the weekly ranking the week of Jun 28, its best in the past year.
Use Cases & Benefits
- Provides a comprehensive, systematized AI agent development tutorial from zero to enterprise-level deployment using Python and popular frameworks like LangChain and LangGraph.
- Offers a continuously updated, integrated learning path combining theory, runnable source code, real-world projects, and interview question banks aligned with AI application engineer job requirements.
- Use for beginners seeking a structured, end-to-end AI agent learning roadmap including environment setup, core concepts, and practical coding exercises.
- Use for developers aiming to build enterprise-grade RAG and multi-agent AI applications with hands-on projects like NL2SQL and DeepAgents.
- Use for job seekers preparing for AI agent and large model application development interviews with curated, real-world question banks and system design explanations.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
Watch-outs
- Owned by an individual account with only 2 contributors on GitHub; plan for bus-factor risk.
- No GitHub releases; pin a commit or tag instead of a release.
General guidance from repository metadata, not legal advice. How we score
From the README
ai-agents-from-zero 2026 持续更新中 · 目标打造「地表最强」AI Agent 教程 —— 系统教程 + 可跑源码 + 面试题库 + 企业级实战项目 + 长期技术栈更新，全面对齐「AI 智能体 / 大模型应用开发工程师」培训课表与招聘 JD的一条龙学习路线
📢 更新说明：AI 不停，更新不止。本仓库将伴随 AI 大模型技术栈持续进化，坚持 开源、系统化、长期更新。模型、框架、Agent、实战项目，都会随着生态变化持续完善和升级。它不只是帮你入门，而是陪你一路成长，从零基础到能真正落地。
目前 概念篇 已全部更新完毕，两个完整实战项目也已更新完毕：
NL2SQL + LangGraph实战项目 电商问数（源码仓库）已于 5 月 3 日完成。DeepAgents多智能体实战项目 深度研搜（源码仓库）已于 5 月 17 日完成。你可以点击更新日志，了解最新仓库动态。市面上 AI 大模型应用内容很多，但绝大多数是碎片化帖子、收费训 练营等；本仓库就是让你不用先花大几千甚至上万，也能系统进入大模型应用开发。若对你有帮助，欢迎 Star ⭐~
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
802+304
Open issues
11-28
Compared with peers in AI Agents
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| vercel-labs/agent-desktop | 17.0K | +13.3K | 33 | today |
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| stablyai/orca | 116.8K | +6.6K | 40 | today |
| milind-soni/OpenMausBot | 13.5K | +6.0K | 45 | today |
| HKUDS/DeepTutor | 55.5K | +5.5K | 65 | 5 days ago |
| didilili/ai-agents-from-zero | 5.8K | — | 15 | — |
| Category median | 55.5K | +6.6K | 40 | — |
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