RijuSaha-01/RAG-Document-Assistant-with-Azure-Cosmos-DB

A RAG pipeline implementation using Azure Cosmos DB (MongoDB vCore) and OpenAI to answer questions from PDF/Docx files.

/ 100

Experimental

No Package No Dependents

Maintenance 6 / 25

Adoption 0 / 25

Maturity 9 / 25

Community 0 / 25

Stars

—

Forks

—

Language

HTML

License

MIT

Category

Last pushed

Dec 31, 2025

Commits (30d)

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/RijuSaha-01/RAG-Document-Assistant-with-Azure-Cosmos-DB"

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

Higher-rated alternatives

Siddhant-K-code/distill

Reliable LLM outputs start with clean context. Deterministic deduplication, compression, and...

louisbrulenaudet/ragoon

High level library for batched embeddings generation, blazingly-fast web-based RAG and quantized...

pesu-dev/ask-pesu

A RAG pipeline for question answering about PES University

namtroi/RAGBase

Open Source RAG ETL Platform. Turns PDFs, Docs & Slides into queryable vectors. Features a...

B-A-M-N/FlockParser

Distributed document RAG system with intelligent GPU/CPU orchestration. Auto-discovers...