arpan10000/simple-rag-pipeline-demo

🌌 Build a simple RAG pipeline to generate AI-driven answers using Chroma DB for storage and Grok LLM for context-aware response generation.

/ 100

Experimental

No Package No Dependents

Maintenance 13 / 25

Adoption 0 / 25

Maturity 9 / 25

Community 0 / 25

Stars

—

Forks

—

Language

Jupyter Notebook

License

MIT

Category

Last pushed

Mar 13, 2026

Commits (30d)

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/arpan10000/simple-rag-pipeline-demo"

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

Higher-rated alternatives

yichuan-w/LEANN

[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast,...

aws-samples/layout-aware-document-processing-and-retrieval-augmented-generation

Advanced document extraction and chunking techniques for retrieval augmented generation that is...

byerlikaya/SmartRAG

Multi-Modal RAG for .NET — query databases, documents, images and audio in natural language....

mrutunjay-kinagi/ragsearch

This project aims to build a Retrieval-Augmented Generation (RAG) engine to provide...

Omkar-Wagholikar/adora

Python package that makes it easy to spin up a custom Retrieval-Augmented Generation (RAG) pipeline.