The Hugging Face Agents Course

If you like the course, don’t hesitate to ⭐ star this repository. This helps us to make the course more visible 🤗.

Content

The course is divided into 4 units. These will take you from the basics of agents to a final assignment with a benchmark.

You can access the course here 👉 https://hf.co/learn/agents-course

Unit	Topic	Description
0	Welcome to the Course	Welcome, guidelines, necessary tools, and course overview.
1	Introduction to Agents	Definition of agents, LLMs, model family tree, and special tokens.
1 Bonus	Fine-tuning an LLM for Function-calling	Learn how to fine-tune an LLM for Function-Calling
2	Frameworks for AI Agents	Overview of `smolagents`, `LangGraph` and `LlamaIndex`.
2.1	The Smolagents Framework	Learn how to build effective agents using the `smolagents` library, a lightweight framework for creating capable AI agents.
2.2	The LlamaIndex Framework	Learn how to build LLM-powered agents over your data using indexes and workflows using the `LlamaIndex` toolkit.
2.3	The LangGraph Framework	Learn how to build production-ready applications using the `LangGraph` framework giving you control tools over the flow of your agent.
2 Bonus	Observability and Evaluation	Learn how to trace and evaluate your agents.
3	Use Case for Agentic RAG	Learn how to use Agentic RAG to help agents respond to different use cases using various frameworks.
4	Final Project - Create, Test and Certify Your Agent	Automated evaluation of agents and leaderboard with student results.
3 Bonus	Agents in Games with Pokemon	Explore the exciting intersection of AI Agents and games.

Prerequisites

Basic knowledge of Python
Basic knowledge of LLMs

Contribution Guidelines

If you want to contribute to this course, you’re welcome to do so. Feel free to open an issue or join the discussion in the Discord. For specific contributions, here are some guidelines:

Small typo and grammar fixes

If you find a small typo or grammar mistake, please fix it yourself and submit a pull request. This is very helpful for students.

New unit

If you want to add a new unit, please create an issue in the repository, describe the unit, and why it should be added. We will discuss it and if it’s a good addition, we can collaborate on it.

Citing the project

To cite this repository in publications:

@misc{agents-course,
  author = {Burtenshaw, Ben and Thomas, Joffrey and Simonini, Thomas and Paniego, Sergio},
  title = {The Hugging Face Agents Course},
  year = {2025},
  howpublished = {\url{https://github.com/huggingface/agents-course}},
  note = {GitHub repository},
}