🎓 AI StudyBuddy

An advanced, full-stack AI-driven educational platform that transforms static lecture videos into interactive, dynamic learning environments. Built with a highly user friendly frontend, the application automatically indexes video transcripts to generate comprehensive lesson summaries, dynamic quiz assessments, and an interactive context-aware AI co-pilot.

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✨ Key Features

• Premium Dark UI Dashboard: Features a clean, accessible layout featuring high-fidelity styling built with Tailwind CSS.
• Lecture Synthesis & Roadmap: Replaces arbitrary timeline segments with an AI-generated academic overview, review time allocation budget, and a curated key takeaways panel.
• Dynamic Knowledge Assessment: Generates customized multiple-choice questions with real-time semantic feedback loops (correct options highlight in emerald; incorrect choices flash in rose).
• Interactive AI Assistance: A vector-indexed contextual assistant sitting side-by-side with an embedded YouTube stream player, allowing students to query specifics across long-form lectures.
• Auto-Curriculum Exploration: Every suggested forward topic features an automated external search component mapping directly into live YouTube search indexes via encoded URI protocols.

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🛠️ Technology Stack

Frontend Canvas

• React.js (Vite) — Single Page Application structural foundation.
• Tailwind CSS — Declarative layout and interaction engines.
• PostCSS & Autoprefixer — Cross-browser style parsing automation.

Backend Infrastructure

• FastAPI — High-performance execution router framework.
• LangChain — LLM chaining architecture and document loader ecosystem.
• ChatGroq model: llama-3.3-70b-versatile — Structured JSON schematic execution layer.
• ChromaDB — Local standalone vector database instance storage (data/chroma_db).

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📁 Project Structure

ai-studybuddy/
├── backend/
│   ├── app/
│   │   ├── main.py             # FastAPI core engine and global CORS router config
│   │   └── services/
│   │       ├── videoprocessor.py # YouTube Loader and transcript parsing
│   │       ├── quizgen.py       # Pydantic structured quiz generation logic
│   │       └── planner.py       # Synthesis, takeaways, and milestone recommendations
│   ├── .env                    # System environmental authentication keys
│   └── requirements.txt        # Python library dependencies
│
└── frontend/
    ├── src/
    │   ├── features/
    │   │   ├── Dashboard.jsx    # Central nexus orchestrator 
    │   │   ├── StudyPlanner.jsx # Study Roadmap and YouTube redirect links
    │   │   ├── QuizDashboard.jsx# Real-time evaluation button state matrix
    │   │   └── VideoChat.jsx    # Stream player & context-aware chat logs 
    │   ├── App.jsx             # Top-level viewport element loader
    │   └── index.css           # Global Tailwind compiler directive configurations
    ├── tailwind.config.js      # Workspace utility routing scanner
    └── package.json            # Node package configurations

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📸 Model in Action

Below are the interface states of the AI StudyBuddy Workspace processing an active lecture vector index:

1. Active Dashboard Entry

2. Synthesis & Curriculum Planner View

3. Dynamic Knowledge Assessment (Quiz)

4. Vector Contextual AI Assistance Chat

⚙️ Local Setup Instructions

Follow these steps to get the project running smoothly on your local machine.

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📋 Prerequisites

Make sure the following are installed:

• Node.js (v18 or higher)
• Python (v3.9 or higher)
• Git

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📥 Clone the Repository

git clone https://github.com/Anwesha28S/StudyBuddy.git
cd StudyBuddy

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🖥️ Backend Setup (FastAPI)

Navigate to the backend directory:

cd backend

Create a Virtual Environment

python -m venv venv

Activate the Virtual Environment

Windows (Command Prompt)

venv\Scripts\activate

Windows (PowerShell)

.\venv\Scripts\Activate.ps1

Mac/Linux

source venv/bin/activate

Install Dependencies

pip install -r requirements.txt

Configure Environment Variables

Create a .env file inside the backend/ directory:

GROQ_API_KEY=your_groq_api_key_here
HF_token=your_hftoken_here

Start the Backend Server

uvicorn app.main:app --reload

The backend will be available at:

http://localhost:8000

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🎨 Frontend Setup (React + Vite)

Open a new terminal and navigate to the frontend directory:

cd frontend

Install Dependencies

npm install

Configure Environment Variables

Create a .env file inside the frontend/ directory:

VITE_API_URL=http://localhost:8000

Start the Development Server

npm run dev -- --force

The frontend will be available at:

http://localhost:5173

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🚀 Running the Application

1. Start the FastAPI backend server.
2. Start the Vite frontend server.
3. Open your browser and visit:

http://localhost:5173

Paste a YouTube URL and start generating summaries, quizzes, and study plans.

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Transcript Extraction Errors

Transcript extraction depends on YouTube captions.

✅ Ensure the selected video has captions (CC) enabled.

Videos without captions may not generate summaries, quizzes, or study materials correctly.

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🎉 You're Ready!

Once both servers are running, you can start using AI StudyBuddy locally.