📚 3Ts Study Assistant - Personal AI Study Assistant

AI-powered study assistant that helps students learn from their textbooks using RAG (Retrieval-Augmented Generation).

Deployed on:
After deploying on HuggingFace got port's conflict. Therefore staying with HF
Streamlit URL not working: 3tinfotinker-3ts-studyassistant-app-pk.streamlit.app/

HuggingFace:https://huggingface.co/spaces/3T-InfoTinker/3Ts_Study_Assistant

✨ Features

• 📤 Upload PDF or image-based textbooks
• 💬 Natural conversation with your books
• 📝 Generate practice quizzes
• 📖 Summarize topics/chapters
• 💡 Explain concepts simply
• 💾 Persistent chat history
• 🗃 Record Manager-Storage & Data
• 🎨 Dark mode UI
• video demo: https://youtu.be/QCcdvMNnWBc?si=t3Dl3utKpbOxpYKv

🛠️ Tech Stack

• Frontend : Streamlit
• LLM : Google Gemini 2.0 Flash
• Vector DB : FAISS
• Embeddings: Sentence-Transformers (all-MiniLM-L6-v2)
• OCR : Tesseract + PyMuPDF

🚀 Quick Start

1. Clone the repository:

git clone https://github.com/3TInfoTinker/3Ts_StudyAssistant
cd 3Ts_StudyAssistant

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables:

echo "GOOGLE_API_KEY=your_api_key_here" > .env

4. Run the app:

streamlit run app.py

📋 Requirements

See requirements.txt for full list. Main dependencies:

• streamlit
• google-generativeai
• faiss-cpu
• sentence-transformers
• pytesseract
• PyMuPDF
• python-dotenv

🎯 Usage

1. Upload your textbook (PDF/images) via sidebar
2. Click "Process & Build Index"
3. Use Quick Actions Dashboard or chat naturally
4. Get instant answers with page citations

🏗️ Architecture

app.py (UI) → agent.py (Logic) → vector_store.py (Search)
                                    → hybrid_processor.py (OCR)

📝 License

MIT License - Feel free to use for educational purposes

💝 Acknowledgments

Built for [Kaggle - Agents Intensive - Capstone Project]

Powered by:

• Google Gemini API
• FAISS (Meta AI)
• Sentence-Transformers
• Streamlit
• HuggingFace