What Is Hello-Agents: Datawhale's Systematic Agent Learning Tutorial
Hello-Agents is Datawhale community's "Building Agents from Scratch" tutorial, from foundational theory to practice, comprehensively mastering AI Native Agent system design and implementation. Trendshift-listed, free in Chinese.
Core Content
- AI Native Agent: focuses on truly AI-driven agents (not Dify / Coze flow-driven), piercing through framework surfaces, starting from core principles.
- Classic paradigm implementation: ReAct, Plan-and-Solve, Reflection-hand-coded implementation.
- Self-built framework HelloAgents: builds an agent framework from scratch on OpenAI native API.
- Advanced skills: context engineering, Memory, protocols, evaluation.
- Agentic RL: full-pipeline hands-on LLM training from SFT to GRPO.
- Real projects: smart travel assistant, cyber town, and other comprehensive cases.
- Job interviews: agent-related interview questions.
How to Use
- Online reading: datawhalechina.github.io/hello-agents (China加速 hello-agents.datawhale.cc).
- Local: git clone the repo, study by chapter.
Who It's For
- AI learners: want to evolve from LLM "users" to Agent "builders," systematically learning agent principles + practice.
- Job seekers: agent interview questions + real projects, a job-hunt boost.
- Teaching: Datawhale community tutorial, suited for courses / self-study.
vs. Other Agent Tutorials
Most tutorials stop at Dify / Coze low-code usage; Hello-Agents dives into AI Native Agent principles (ReAct / Plan-Solve / Reflection code implementation + self-built framework + Agentic RL), from "using tools" to "building tools."