metadata

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

Initialize BestRAG: Enter your Qdrant URL, API Key, and Collection Name, then click "Initialize BestRAG".
Create Embeddings: Upload a PDF file and click "Create Embeddings" to store embeddings.
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:

pip install bestrag

For more details, visit the GitHub repository.

Note: Qdrant offers a free tier with 4GB of storage. To generate your API key and endpoint, visit Qdrant.

Made with ❤️ by samadpls

Please like this project on GitHub if you find it useful!