---
title: Easy RAG
emoji: 🐢
colorFrom: purple
colorTo: indigo
sdk: gradio
sdk_version: 5.8.0
app_file: app.py
pinned: false
license: mit
short_description: Chat with your docs very Easy
---
# Easy RAG 🤖

Easy RAG is a powerful and user-friendly Retrieval Augmented Generation (RAG) system that allows users to upload their own documents and query them using state-of-the-art language models.

## Features

- 📄 Support for multiple document formats (PDF, TXT, DOCX)
- 📚 Upload up to 5 documents (max 10MB each)
- 🔍 Advanced document processing and chunking
- 💡 Intelligent question answering using Llama-2
- 🌐 Multilingual support
- 🚀 GPU-accelerated inference
- 📊 Source tracking and citation

## Technical Stack

- **Language Model**: Meta-llama/Llama-2-7b-chat-hf
- **Embeddings**: intfloat/multilingual-e5-large
- **Vector Store**: FAISS
- **UI Framework**: Gradio
- **Document Processing**: LangChain

## Installation

1. Clone the repository
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Set up your HuggingFace token as an environment variable:
```bash
export HUGGINGFACE_TOKEN=your_token_here
```
4. Run the application:
```bash
python app.py
```

## Usage

1. Upload your documents using the file upload interface
2. Wait for the system to process and index your documents
3. Start asking questions about your documents
4. View answers with source citations

## Requirements

See `requirements.txt` for a complete list of dependencies.

## Credits

Based on original work by [Camilo Vega](https://www.linkedin.com/in/camilo-vega-169084b1/), AI Professor and Solutions Consultant.

## License

MIT License