Car Rental Application

A full-stack car rental application with admin dashboard and client interface built with Next.js, Express, and MongoDB.

Project Structure

car-rental/
├── backend/                     # Express.js API backend
│   ├── src/
│   │   ├── config/              # Configuration files
│   │   ├── controllers/         # API controllers
│   │   ├── middlewares/         # Express middleware
│   │   ├── models/              # Mongoose models
│   │   ├── public/              # Static assets
│   │   ├── routes/              # API routes
│   │   ├── services/            # Business logic services
│   │   ├── utils/               # Utility functions
│   │   ├── seed-data.js         # Sample data for database seeding
│   │   ├── seed-data-runner.js  # Script to run database seeding
│   │   ├── app.js               # Express app setup
│   │   └── server.js            # Server entry point
│   ├── .env                     # Environment variables
│   └── package.json             # Backend dependencies
│
├── frontend-admin/              # Next.js admin dashboard
│   ├── src/
│   │   ├── app/                 # Next.js app router pages
│   │   ├── components/          # React components
│   │   ├── lib/                 # Utility functions and API
│   │   └── public/              # Static assets
│   └── package.json             # Frontend dependencies
│
└── frontend-client/             # Next.js client website
    ├── src/
    │   ├── app/                 # Next.js app router pages 
    │   ├── components/          # React components
    │   └── lib/                 # Utility functions and API
    ├── public/                  # Static assets
    └── package.json             # Frontend dependencies

Getting Started

Backend Setup

# Navigate to backend directory
cd backend

# Install dependencies
npm install

# Setup environment variables (copy from .env.example and modify as needed)
cp .env.example .env

# Seed the database with initial data
npm run seed

# Run in development mode
npm run dev

# Run in production mode
npm start

Admin Dashboard Setup

# Navigate to admin dashboard directory
cd frontend-admin

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build for production
npm run build

Client Website Setup

# Navigate to client website directory
cd frontend-client

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build for production
npm run build

Features

Admin Dashboard

• User management (customers, staff, admins)
• Car inventory management
• Booking management and status updates
• Analytics and reporting
• Notifications system

Client Website

• Car browsing and filtering
• Booking system
• User registration and profile management
• Responsive design for all devices

API Routes

• /api/auth - Authentication (login, register, reset password)
• /api/users - User management (CRUD operations)
• /api/cars - Car management (CRUD operations)
• /api/bookings - Booking management
• /api/categories - Car categories management
• /api/website - Website content management
• /api/dashboard - Admin dashboard statistics
• /api/upload - File upload functionality
• /api/notifications - User notifications
• /api/statistics - Detailed statistics for analytics

Database Seeding

The project includes a comprehensive data seeding system to populate the database with sample data for testing and development:

# Run the seeding script
npm run seed

The seed data includes:

• User accounts (admin, staff, regular users)
• Car categories
• Car listings with details and images
• Sample bookings
• Website content and FAQs
• Statistics for the dashboard
• Notifications

Default Admin User

After running the seed script, you can log in with the following credentials:

• Email: admin@carental.com
• Password: Admin123!

AI-Powered Chatbot with Google Gemini

This application includes an AI-powered chatbot that uses Google's Gemini API to provide intelligent responses to customer inquiries. The chatbot can:

• Answer questions about rental policies, car availability, and booking procedures
• Search for cars based on user requirements (type, brand, price range)
• Maintain conversation context for more natural interactions
• Fall back to pre-defined responses when AI is unavailable

Setting up Gemini AI

1. Get a Gemini API key from Google AI Studio
2. Add the API key to your environment files:
   • For the frontend: NEXT_PUBLIC_GEMINI_API_KEY in frontend-client/.env.local
   • For the backend: GEMINI_API_KEY in backend/.env

Chatbot Fallback Mechanism

The chatbot is designed to gracefully degrade functionality:

1. First tries to match against known FAQs
2. Then searches for car-related queries
3. Uses Gemini AI for complex or unknown questions
4. Falls back to rule-based responses if AI is unavailable

The chat experience remains functional even without an API key, making it suitable for development and testing environments.

License

This project is licensed under the MIT License.