What it does This repo hosts the Hugging Face Agents Course, a free curriculum split into four units plus bonus material. It starts with agent and LLM fundamentals, moves through three major frameworks—smolagents, LlamaIndex, and LangGraph—and ends with a final project that gets automatically evaluated and ranked on a public leaderboard. The course lives on Hugging Face’s learning platform; the repo is the source and star-magnet.

The interesting bit The course doesn’t pick a framework winner. It teaches smolagents as the lightweight option, LlamaIndex for data-heavy agents, and LangGraph for production flow control, then makes you apply all three to an agentic RAG use case. The Pokémon bonus unit is a nice touch—agents playing games tends to separate toy demos from actually competent systems.

Key highlights

• Four core units plus three bonus tracks (function-calling fine-tuning, observability, Pokémon agents)
• Covers smolagents, LangGraph, and LlamaIndex with dedicated deep-dives
• Final project includes automated evaluation and a student leaderboard
• Free signup, basic Python and LLM knowledge required
• Active contribution guidelines and Discord community

Caveats

• The repo itself is course infrastructure (MDX content), not a runnable framework
• “Production-ready” claims for LangGraph are the course’s framing, not independently benchmarked here

Verdict Worth bookmarking if you’re past the “what is an agent” blog post stage and want structured practice with multiple toolkits. Skip if you need a reference implementation or advanced research material; this is pedagogy, not a framework.