thendralmagudapathi/RAG-for-NCERT
A professional-grade Retrieval-Augmented Generation (RAG) system designed for intelligent question-answering over NCERT textbooks of Class 11 and 12. This project integrates LangChain, Qdrant vector store, Dockerized LLM backend using Ollama, and PDF data pipelines to deliver accurate and contextual answers to academic questions.
No commits in the last 6 months.
Stars
—
Forks
—
Language
Python
License
MIT
Last pushed
Jun 08, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/thendralmagudapathi/RAG-for-NCERT"
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...