🤖 QuestRAG: PDF QA and Summarizer Bot

An AI-powered Streamlit web application that allows you to:

• 📄 Upload research PDFs
• 🔍 Ask context-aware questions from the paper
• 🧠 Get automatic summarization using a local RAG (Retrieval-Augmented Generation) pipeline

This mini project was developed as part of the "Project Gen AI Applications with RAG and LangChain" course by IBM on Coursera, with several enhancements for UI, functionality, and offline model usage.

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🚀 Features

• 🧩 LangChain-powered RetrievalQA system
• 📚 Upload any research PDF and extract information
• 🤖 Local inference with Flan-T5-base and MiniLM embeddings
• 💬 Toggle between Question Answering and Summarization
• 📎 Clean and interactive Streamlit interface with logo branding

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📦 Installation

Ensure Python 3.9+ is installed.

git clone https://github.com/YourUsername/QuestRAG.git
cd QuestRAG
pip install -r requirements.txt
streamlit run main.py

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🧠 Model Info

Component	Model Used
Embeddings	sentence-transformers/all-MiniLM-L6-v2
Language Model	google/flan-t5-base
Vector Store	ChromaDB (local)

All models are stored locally for offline use in the saved_model/ directory.

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📝 Sample Questions You Can Ask

• What is the main contribution of the paper?
• How does AI personalize education?
• What role does data play in AI-based learning?
• Which challenges are mentioned in implementing AI in classrooms?

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📸 UI Preview

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🙌 Credits

• 💡 Developed by Noor Jehan
• 🎓 Based on the course "Project Gen AI Applications with RAG and LangChain" by IBM on Coursera