AyorindeTayo/Enterprise-llmops-rag

This project is an end-to-end modular system that enables enterprises to perform question-answering, document retrieval, and AI-powered analysis over large collections of documents (PDFs, text files, or other structured content) using a Retrieval-Augmented Generation (RAG) approach. It is designed for scalable, production-ready deployment

21
/ 100
Experimental
No Package No Dependents
Maintenance 10 / 25
Adoption 0 / 25
Maturity 11 / 25
Community 0 / 25

How are scores calculated?

Stars

Forks

Language

Python

License

MIT

Category

retrieval

Last pushed

Feb 16, 2026

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/rag/AyorindeTayo/Enterprise-llmops-rag"

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