README.md

---
title: BestRAG
emoji: 🌖
colorFrom: indigo
colorTo: green
sdk: streamlit
sdk_version: 1.41.1
app_file: app.py
pinned: false
license: mit
short_description: 'BestRAG: Hybrid Retrieval-Augmented Generation library'
---

# BestRAG - Hybrid Retrieval-Augmented Generation (RAG)

**BestRAG** is a Python library that leverages a hybrid Retrieval-Augmented Generation (RAG) approach to efficiently store and retrieve embeddings. By combining dense, sparse, and late interaction embeddings, BestRAG offers a robust solution for managing large datasets.

## Features

- 🚀 **Hybrid RAG**: Utilizes dense, sparse, and late interaction embeddings for enhanced performance.
- 🔌 **Easy Integration**: Simple API for storing and searching embeddings.
- 📄 **PDF Support**: Directly store embeddings from PDF documents.

## How to Use

1. **Initialize BestRAG**: Enter your Qdrant URL, API Key, and Collection Name, then click "Initialize BestRAG".
2. **Create Embeddings**: Upload a PDF file and click "Create Embeddings" to store embeddings.
3. **Search Embeddings**: Enter a search query and set the limit, then click "Search" to retrieve results.

## Installation

You can use BestRAG freely by installing it with:

```bash
pip install bestrag
```

For more details, visit the [GitHub repository](https://github.com/samadpls/BestRAG).

[![GitHub stars](https://img.shields.io/github/stars/samadpls/BestRAG?color=red&label=stars&logoColor=black&style=social)](https://github.com/samadpls/BestRAG)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/bestrag?style=social)](https://pypi.org/project/bestrag/)

> **Note**: Qdrant offers a free tier with 4GB of storage. To generate your API key and endpoint, visit [Qdrant](https://qdrant.tech/).

Made with ❤️ by [samadpls](https://github.com/samadpls)

---

Please like this project on [GitHub](https://github.com/samadpls/BestRAG) if you find it useful!