# P2P Federated Learning

**P2PFL** is a decentralized federated learning library that enables federated learning on peer-to-peer networks using gossip protocols, making collaborative AI model training possible without reliance on central servers.

## 🤗 Community

Have questions, need help, or want to contribute? Join our Slack community!

[![Slack](https://img.shields.io/badge/Chat-Slack-4B0082)](https://join.slack.com/t/p2pfl/shared_invite/zt-2lbqvfeqt-FkutD1LCZ86yK5tP3Duztw)

## 🏁 Getting Started

- **📘 [Introduction](introduction.md):** Learn about the P2PFL ecosystem and its core concepts.
- **📥 [Installation](installation.md):** Set up P2PFL on your system.
- **🚀 [Quickstart](quickstart.md):** A hands-on guide to training your first P2P federated learning model.

## 🤿 Deep Dive

- **🏛️ [Components](components/comp-index.md):** Understand the architecture and main components behind P2PFL.
- **👨‍🏫 [Tutorials](tutorials/index.md):** Comprehensive tutorials to P2PFL's features, options, and configurations.
- **📚 [API Reference](api):** 🤓 Detailed documentation of all functions, classes, and modules.

## ➕ Additional Resources

- **🌐 [Web Services](p2pfl_ws.md):** Utilize P2PFL's web services for monitoring and managing your federated learning tasks.
- **👫 [Contributing](contributing.md):** Join the development effort and contribute to P2PFL.

```{eval-rst}
.. toctree::
   :maxdepth: 1
   :hidden:

   introduction
   installation
   quickstart
   components/comp-index
   p2pfl_ws
   tutorials/index
   contributing
   api
```