Smart Tutor AI - AI-Powered Learning Platform

A comprehensive Next.js learning platform with AI-powered content generation, user authentication, and progress tracking.

Features

• 🧠 AI-Powered Learning: Generate explanations and quizzes using Google Gemini AI
• 📚 Quick Learn: Get concise explanations with interactive quizzes
• 🎯 Deep Learn: Comprehensive learning modules with structured sections
• 👤 User Authentication: Firebase-based user management
• 📊 Progress Tracking: Track learning streaks, quiz scores, and study sessions
• 🌙 Dark Mode: Complete theme system with user preference persistence
• 📱 Responsive Design: Works seamlessly across all devices

Tech Stack

• Frontend: Next.js 14, React, TypeScript, Tailwind CSS
• Backend: Next.js API Routes
• Database: Firebase Firestore
• Authentication: Firebase Auth
• AI: Google Gemini API
• Deployment: Vercel

Quick Start

Prerequisites

• Node.js 18+
• npm or yarn
• Firebase project
• Google Gemini API key

Installation

1. Clone the repository:

git clone <repository-url>
cd smartutor

2. Install dependencies:

npm install

3. Set up environment variables: Create a .env.local file in the root directory:

GEMINI_API_KEY=your_gemini_api_key
NEXT_PUBLIC_FIREBASE_API_KEY=your_firebase_api_key
NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN=your_project.firebaseapp.com
NEXT_PUBLIC_FIREBASE_PROJECT_ID=your_project_id
NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET=your_project.appspot.com
NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID=your_sender_id
NEXT_PUBLIC_FIREBASE_APP_ID=your_app_id

4. Run the development server:

npm run dev

5. Open http://localhost:3000 in your browser.

Deployment on Vercel

One-Click Deploy

Manual Deploy

1. Install Vercel CLI:

npm i -g vercel

2. Login to Vercel:

vercel login

3. Deploy:

vercel

4. Set environment variables in Vercel dashboard:
   • Go to your project settings
   • Add all environment variables from .env.local
   • Redeploy if necessary

Environment Variables for Vercel

Set these in your Vercel project settings:

• GEMINI_API_KEY
• NEXT_PUBLIC_FIREBASE_API_KEY
• NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN
• NEXT_PUBLIC_FIREBASE_PROJECT_ID
• NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET
• NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID
• NEXT_PUBLIC_FIREBASE_APP_ID

Firebase Setup

1. Create a Firebase project at Firebase Console
2. Enable Authentication with Email/Password
3. Create a Firestore database
4. Set up Firestore security rules:

rules_version = '2';
service cloud.firestore {
  match /databases/{database}/documents {
    // Users can only access their own data
    match /users/{userId} {
      allow read, write: if request.auth != null && request.auth.uid == userId;
    }
    
    // Study sessions - users can only access their own
    match /studySessions/{sessionId} {
      allow read, write: if request.auth != null && request.auth.uid == resource.data.userId;
    }
    
    // Quiz results - users can only access their own
    match /quizResults/{resultId} {
      allow read, write: if request.auth != null && request.auth.uid == resource.data.userId;
    }
  }
}

Google Gemini API Setup

1. Go to Google AI Studio
2. Create an API key
3. Add the key to your environment variables as GEMINI_API_KEY

Project Structure

smartutor/
├── app/                    # Next.js app directory
│   ├── api/               # API routes
│   ├── dashboard/         # Dashboard page
│   ├── learn/            # Quick learn page
│   ├── deep-learn/       # Deep learn page
│   ├── progress/         # Progress tracking page
│   └── profile/          # User profile page
├── components/           # React components
├── lib/                 # Utility libraries
│   ├── firebase.ts      # Firebase configuration
│   ├── firestore.ts     # Firestore functions
│   └── gemini.ts        # Gemini AI integration
└── public/              # Static assets

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

License

This project is licensed under the MIT License.