https://github.com/huggingface/agents-course

This repository contains the Hugging Face Agents Course.

https://github.com/huggingface/agents-course

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    3 of 146 committers (2.1%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (7.7%) to scientific vocabulary

Keywords

agentic-ai agents course huggingface langchain llamaindex smolagents

Keywords from Contributors

transformer vlm audio deepseek gemma glm model-hub pretrained-models pytorch-transformers qwen
Last synced: 4 months ago · JSON representation

Repository

This repository contains the Hugging Face Agents Course.

Basic Info
  • Host: GitHub
  • Owner: huggingface
  • License: apache-2.0
  • Language: MDX
  • Default Branch: main
  • Homepage:
  • Size: 27.4 MB
Statistics
  • Stars: 22,972
  • Watchers: 184
  • Forks: 1,607
  • Open Issues: 79
  • Releases: 0
Topics
agentic-ai agents course huggingface langchain llamaindex smolagents
Created about 1 year ago · Last pushed 4 months ago
Metadata Files
Readme License

README.md

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 🤗.

Star the repo

Content

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

Sign up here (it's free) 👉 https://bit.ly/hf-learn-agents

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:

bibtex @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}, }

Owner

  • Name: Hugging Face
  • Login: huggingface
  • Kind: organization
  • Location: NYC + Paris

The AI community building the future.

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 1,035
  • Total Committers: 146
  • Avg Commits per committer: 7.089
  • Development Distribution Score (DDS): 0.816
Past Year
  • Commits: 1,035
  • Committers: 146
  • Avg Commits per committer: 7.089
  • Development Distribution Score (DDS): 0.816
Top Committers
Name Email Commits
Thomas Simonini s****o@g****m 190
sergiopaniego s****o@g****m 189
burtenshaw b****w@g****m 120
Joffrey THOMAS j****y@h****o 104
davidberenstein1957 d****n@g****m 74
Pedro Cuenca p****o@h****o 25
ShawnSiao x****x@q****m 21
Jannik Maierhöfer j****k@l****m 19
JiamingHuangHJM h****x@g****m 15
Xuan Son Nguyen s****n@h****o 13
Christophe DUC g****b@c****e 11
Artyom Boyko b****n@y****u 11
Aileen Villanueva a****l@g****m 10
Roger Gomez Olivares r****l 7
Gereey 1****y 6
omahs 7****s 6
Aryan Bagale a****2@g****m 6
Daniel Zhang D****8@o****m 5
Alejandro Garcia 1****b 5
Erin La 1****b 5
Nicorb 6****i 5
Y M 9****a 5
CharlesCNorton 1****n 4
little_huang 5****g 4
Japheth Ishola j****h@g****m 4
ww-6 w****g@l****m 4
Aymeric a****r@g****m 4
Sébastien DIDIER s****v@g****m 4
20021108 2****8@s****m 4
ddewaele d****e@g****m 3
and 116 more...

Issues and Pull Requests

Last synced: 5 months ago

All Time
  • Total issues: 145
  • Total pull requests: 675
  • Average time to close issues: 23 days
  • Average time to close pull requests: 3 days
  • Total issue authors: 116
  • Total pull request authors: 213
  • Average comments per issue: 0.84
  • Average comments per pull request: 1.21
  • Merged pull requests: 449
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 145
  • Pull requests: 675
  • Average time to close issues: 23 days
  • Average time to close pull requests: 3 days
  • Issue authors: 116
  • Pull request authors: 213
  • Average comments per issue: 0.84
  • Average comments per pull request: 1.21
  • Merged pull requests: 449
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • ShawnSiao (11)
  • yuka-with-data (4)
  • polisdi (3)
  • pcuenca (3)
  • carlosug (3)
  • smagara (2)
  • julurisaichandu (2)
  • newway-anshul (2)
  • artyomboyko (2)
  • sanguedemonstro (2)
  • burtenshaw (2)
  • crcdng (2)
  • joshhu (2)
  • DanielRamosHoogwout (2)
  • mehdinathani (2)
Pull Request Authors
  • sergiopaniego (40)
  • simoninithomas (33)
  • burtenshaw (30)
  • ShawnSiao (28)
  • christopheduc-me (26)
  • Jofthomas (19)
  • jannikmaierhoefer (13)
  • pcuenca (11)
  • bstraehle (11)
  • yuka-with-data (10)
  • karenwky (10)
  • artyomboyko (10)
  • danielzmeow (9)
  • decipherIO (8)
  • gabyorel (8)
Top Labels
Issue Labels
hands-on-bug (64) documentation (35) question (16) good first issue (1)
Pull Request Labels

Dependencies

.github/workflows/build_documentation.yml actions
.github/workflows/build_pr_documentation.yml actions
.github/workflows/upload_pr_documentation.yml actions
quiz/pyproject.toml pypi
  • datasets >=3.2.0
  • huggingface-hub >=0.27.1
  • ipykernel >=6.29.5
  • requests >=2.32.3
quiz/uv.lock pypi
  • agents-course 0.1.0
  • aiohappyeyeballs 2.4.4
  • aiohttp 3.11.11
  • aiosignal 1.3.2
  • appnope 0.1.4
  • asttokens 3.0.0
  • attrs 25.1.0
  • certifi 2024.12.14
  • cffi 1.17.1
  • charset-normalizer 3.4.1
  • colorama 0.4.6
  • comm 0.2.2
  • datasets 3.2.0
  • debugpy 1.8.12
  • decorator 5.1.1
  • dill 0.3.8
  • executing 2.2.0
  • filelock 3.17.0
  • frozenlist 1.5.0
  • fsspec 2024.9.0
  • huggingface-hub 0.27.1
  • idna 3.10
  • ipykernel 6.29.5
  • ipython 8.31.0
  • jedi 0.19.2
  • jupyter-client 8.6.3
  • jupyter-core 5.7.2
  • matplotlib-inline 0.1.7
  • multidict 6.1.0
  • multiprocess 0.70.16
  • nest-asyncio 1.6.0
  • numpy 2.2.2
  • packaging 24.2
  • pandas 2.2.3
  • parso 0.8.4
  • pexpect 4.9.0
  • platformdirs 4.3.6
  • prompt-toolkit 3.0.50
  • propcache 0.2.1
  • psutil 6.1.1
  • ptyprocess 0.7.0
  • pure-eval 0.2.3
  • pyarrow 19.0.0
  • pycparser 2.22
  • pygments 2.19.1
  • python-dateutil 2.9.0.post0
  • pytz 2024.2
  • pywin32 308
  • pyyaml 6.0.2
  • pyzmq 26.2.0
  • requests 2.32.3
  • six 1.17.0
  • stack-data 0.6.3
  • tornado 6.4.2
  • tqdm 4.67.1
  • traitlets 5.14.3
  • typing-extensions 4.12.2
  • tzdata 2025.1
  • urllib3 2.3.0
  • wcwidth 0.2.13
  • xxhash 3.5.0
  • yarl 1.18.3