A open-source tool to to visualise your RAG documents 🔮.
Project description
RAGxplorer 🦙🦺
RAGxplorer is tool to build Retrieval Augmented Generation (RAG) visualisations.
Quick Start ⚡
Installation
pip install ragxplorer
Usage
from embedding_adapter import EmbeddingAdapter
client = RAGxplorer(embedding_model="thenlper/gte-large") # Choose any HuggingFace or OpenAI embedding model
client.load_pdf("presentation.pdf", verbose=True)
client.visualize_query("What are the top revenue drivers for Microsoft?")
Streamlit Demo (WIP) 🔎
Contributing 👋
Contributions to RAGxplorer are welcome. Please read our contributing guidelines (WIP) for details.
License 👀
This project is licensed under the MIT license - see the LICENSE file for details.
Acknowledgments 💙
- DeepLearning.AI and Chroma for the inspiration and code labs in their Advanced Retrival course.
- The Streamlit community for the support and resources.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ragxplorer-0.1.1.tar.gz
(9.6 kB
view hashes)
Built Distribution
ragxplorer-0.1.1-py3-none-any.whl
(10.5 kB
view hashes)
Close
Hashes for ragxplorer-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 03bc434cfe924b804805bf8a2787e24ef2ea57398eb3bc4fcb27a4b9475af077 |
|
MD5 | 131aa918701ac392b6ac7cc95241a4c8 |
|
BLAKE2b-256 | 45fc29dcb190ece19ae6124696348593dfb4543d6bf26395946704cfde949053 |