AI-Powered Learning Assistant

A web application that helps users learn by generating detailed notes and interactive quizzes from text or YouTube videos using AI. Now includes an AI-powered study chatbot with persistent conversation history and LaTeX/Markdown support.

Features

• Note Generation: Generate comprehensive notes from text input or YouTube video transcripts
• Interactive Quizzes: Automatically create multiple-choice quizzes from generated notes
• AI Study Chatbot: Ask questions about your notes with a context-aware AI assistant. Supports Markdown and LaTeX formatting, and saves your chat history per session.
• User Authentication: Secure user registration and login system (JWT-based)
• Dashboard: Track your learning progress, review past notes, quizzes, and chat sessions
• Delete Chat: Easily clear your chat history for any session
• Responsive Design: Works on both desktop and mobile devices

Tech Stack

• Backend: FastAPI (Python)
• Frontend: HTML, CSS, JavaScript (with Jinja2 templating)
• Database: SQLite (via SQLAlchemy, aiosqlite)
• AI/ML: Google Gemini 2.5 Flash model
• Authentication: JWT (JSON Web Tokens)
• Video Processing: YouTubeTranscriptAPI (for YouTube transcription)
• Math/Markdown: MathJax for LaTeX, marked.js for Markdown, highlight.js for code

Prerequisites

• Python 3.8+
• Google AI API key

Installation

1. Clone the repository:

   git clone https://github.com/sheepie20/learnai
   cd learnai

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the project root and add your Google AI API key and other secrets:

   SECRET_KEY=your_secret_key
   GOOGLE_API_KEY=your_google_api_key
   
   MAIL_USERNAME=your_email
   MAIL_PASSWORD=your_email_app_password
   MAIL_FROM=your_email
   MAIL_PORT=your_smtp_port
   MAIL_SERVER=your_smtp_server
   MAIL_STARTTLS=your_starttls
   MAIL_SSL_TLS=your_ssl_tls
   

5. Initialize the database:

   python -c "from database import engine; import asyncio; from models import init_db; asyncio.run(init_db(engine))"

Running the Application

Start the development server:

uvicorn main:app --reload

The application will be available at http://localhost:8000

Or... go to https://learnai.sheepie.dev to use it officially.

API Endpoints

• POST /generate-notes: Generate notes from text or YouTube URL
• POST /generate-quiz: Generate a quiz from notes
• GET /quiz/{quiz_id}: View a specific quiz
• POST /quiz/{quiz_id}: Submit quiz answers
• POST /register: Register a new user
• POST /token: Authenticate and get access token
• GET /dashboards: View user's learning dashboards
• GET /chat/{quiz_id}: Access the AI study chatbot for a quiz/session
• POST /api/chat/{quiz_id}: Interact with the AI chatbot (persistent, context-aware)

Project Structure

• main.py: Main FastAPI application and route handlers
• ai_service.py: Core AI functionality for note taking, quiz generation, and chat
• auth.py: Authentication and user management
• database.py: Database connection and session management
• models.py: SQLAlchemy models
• youtube.py: YouTube video processing utilities
• templates/: HTML templates (dashboard, quiz, chat, etc.)
• static/: Static files (CSS, JavaScript, images)

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Acknowledgments

• Google for the powerful Gemini language models
• FastAPI for the awesome web framework
• The open-source community for various libraries and tools used in this project
• MathJax, marked.js, and highlight.js for rich chat and note formatting