AI & Machine Learning

RAG-Powered PDF Question Answering Assistant

  • AI
  • GEN AI
  • RAG
RAG-Powered PDF Question Answering Assistant
overview

About this engagement

RAG-Powered PDF Question Answering Assistant

Built an intelligent question-answering assistant using Retrieval-Augmented Generation (RAG) with LangChain, FAISS, and OpenAI GPT. Users can upload PDF documents and ask natural language questions to receive context-aware answers sourced directly from the uploaded document.

Key Features

  • PDF ingestion and intelligent text chunking
  • Vector embeddings stored in a FAISS database
  • Semantic document retrieval based on user queries
  • Context-aware answer generation using LangChain and OpenAI GPT
  • Interactive Streamlit web application

Tools & Technologies

Python • LangChain • FAISS • Streamlit • OpenAI API • PyMuPDF • python-dotenv

Links

Live Demo:
https://rag-assistant-project-eeyp5rpbdh6cpgy4x5kmbb.streamlit.app/

GitHub Repository:
https://github.com/Chizzy0428/RAG-Assistant-Project

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