# Multilingual RAG System

A multilingual retrieval-augmented Q&A system that answers Bengali and English queries from HSC Bangla 1st Paper textbooks with source citations.

## Context
Bengali textbook question answering needs both meaningful text comprehension and a traceable connection to the source material.

## Engineering
- Processed textbook PDFs using PDFMiner and OCR.
- Built a retrieval pipeline with LangChain, ChromaDB, and the OpenAI API.
- Served Bengali and English questions through FastAPI, with Redis and Docker in the stack.

## Outcomes
- Bengali and English query support
- Source-cited answers from textbook content
- A working application of low-resource NLP

## Technologies
Python, LangChain, ChromaDB, FastAPI, Redis, Docker