StudySync AI (Citrine & Sage Integration)Tool

This is a full-stack MVP inspired by "NotebookLM", built for the Citrine & Sage assignment. It features RAG-based Q&A, Audio Dialogue generation, and Video Summarization. An AI-powered study companion that transforms textbook chapters and YouTube videos into interactive learning experiences.

Prerequisites

• Node.js (v18+)
• Python (v3.9+)
• OpenAI API Key (Required for RAG & Audio)

🚀 Features

1. AI-Powered RAG Chatbot

• Interactive Q&A: Ask questions about your study material.
• Smart Citations: Citations are granular and specific (e.g., 📺 YouTube (Ec19...), 📚 chapter.pdf).
• Streaming Responses: Real-time, typewriter-style responses for a premium feel.
• Reasoning: Answers are synthesized from both text and video transcripts.

2. Audio Dialogue Generation (Podcast Mode)

• Two-Person Dialogue: Converts dry text into an engaging conversation between two hosts.
• Audio Sync: Generated audio is cached and synchronized with the transcript.

3. Smart Summaries

• Multi-Modal Summary: meaningful summaries derived from both the PDF chapter and related YouTube videos.

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🛠️ Setup Instructions

1. Backend Setup

The backend requires Python 3.8+.

cd backend
# Create virtual environment (optional but recommended)
python -m venv venv
# Windows: venv\Scripts\activate
# Mac/Linux: source venv/bin/activate

# Install dependencies (pinned for stability)
pip install -r requirements.txt

Environment Variables: Create a .env file in backend/ and add your OpenAI Key:

OPENAI_API_KEY=sk-your-key-here

Run the Server:

python main.py

The server will start on http://localhost:5000.

2. Frontend Setup

The frontend uses React + Vite.

cd frontend
npm install
npm run dev

The app will open at http://localhost:5173.

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🔮 Future Roadmap: Dynamic Uploader

I have designed a technical plan to make this tool fully dynamic (NotebookLM style):

• Drag-and-Drop: Upload multiple PDFs.
• YouTube Validation: Add videos by URL (auto-validating for captions).
• Session Support: Create different study sets. (See dynamic_uploader_plan.md in the project files for full architecture)

Tech Stack

• Frontend: React, Vite, TailwindCSS, Lucide Icons
• Backend: Flask, LangChain, FAISS, OpenAI API

Features Implemented

• ✅ Audio Dialogue Mode: Simulated podcast between Teacher and Student.
• ✅ Video/Text Summary: Context-aware summary of the content.
• ✅ Interactive Q&A: Chatbot grounded in the Chapter PDF and Videos.