hello-agents
Hello-Agents is a tutorial for learning the principles and practice of AI agents. It guides readers from core concepts to building agent systems and applications.
Share on XCustom license (see repository)
Overview
Hello-Agents is a structured, open learning tutorial for understanding and building AI-native agents, addressing the lack of a practical guide that connects agent principles with implementation. Readers can study it online or locally, moving from agent and language-model fundamentals to classic patterns, low-code platforms, and frameworks. Later chapters cover building an agent framework, memory and retrieval, context engineering, communication protocols, training, and evaluation. Case studies include a travel assistant, a deep-research agent, and a simulated cyber town.
Key features
- Introduces agent concepts, history, language models, and classic patterns such as ReAct, Plan-and-Solve, and Reflection.
- Covers low-code platforms and agent frameworks, and guides readers through building an agent framework.
- Explains memory and retrieval, context engineering, communication protocols, training, and agent evaluation.
- Includes practical projects for a travel assistant, a deep-research agent, and a simulated cyber town.
Best for
Learners who want a theory-to-practice introduction to AI-native agents, including developers building agent systems and applications.
- Upstream
- datawhalechina/hello-agents
- Fork on GitHub
- Guo-astro/hello-agents
- Upstream stars
- 82k
- Category
- AI agents and LLM tools
- Language
- Python
- License
- Custom license (see repository)
- Forked
- 2026-10-10
- Sync status
- In syncLast synced 2026-10-11
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