dev-k99/RAG-Assistant

Not another tutorial RAG. Hybrid retrieval (BM25 + dense), cross-encoder reranking, RAGAS evaluation, FastAPI backend, persistent ChromaDB — 25–31% better than cosine similarity baseline. Built with Python, Groq, and Streamlit.

14
/ 100
Experimental
No License No Package No Dependents
Maintenance 13 / 25
Adoption 0 / 25
Maturity 1 / 25
Community 0 / 25

How are scores calculated?

Stars

Forks

Language

Jupyter Notebook

License

Last pushed

Mar 20, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/dev-k99/RAG-Assistant"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.