RAGxplorer is a tool to build Retrieval Augmented Generation (RAG) visualisations.

Installation

pip install ragxplorer

Usage

from ragxplorer import RAGxplorer
client = RAGxplorer(embedding_model="thenlper/gte-large")
client.load_pdf("presentation.pdf", verbose=True)
client.visualize_query("What are the top revenue drivers for Microsoft?")

A quickstart Jupyter notebook tutorial on how to use ragxplorer can be found at https://github.com/gabrielchua/RAGxplorer/blob/main/tutorials/quickstart.ipynb

Or as a Colab notebook:

The demo can be found here: https://ragxplorer.streamlit.app/

View the project here

Contributions to RAGxplorer are welcome. Please read our contributing guidelines (WIP) for details.

This project is licensed under the MIT license - see the LICENSE for details.

• DeepLearning.AI and Chroma for the inspiration and code labs in their Advanced Retrival course.
• The Streamlit community for the support and resources.