renardeinside/chatten

RAG application (backend & frontend) with sources retriveal and highlighting on the Databricks Platform

40
/ 100
Emerging

This project helps you build an intelligent chat assistant that can answer questions based on your internal documents, such as PDFs. You provide your documents, and the system allows users to ask questions in natural language, receiving precise answers with highlighted sources from your original files. Data scientists, MLOps engineers, or AI developers working on the Databricks platform would use this to deploy RAG applications.

No commits in the last 6 months.

Use this if you need to deploy a Retrieval Augmented Generation (RAG) chat application on Databricks that leverages your own documents for informed responses.

Not ideal if you are looking for a pre-built, production-ready RAG application without needing to customize or deploy it yourself on Databricks.

RAG application deployment Databricks solutions AI assistants document intelligence information retrieval
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 16 / 25

How are scores calculated?

Stars

16

Forks

6

Language

Python

License

MIT

Last pushed

Apr 29, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/rag/renardeinside/chatten"

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