CrackIt.AI

🚀 An AI-powered platform for career development and interview preparation

CrackIt.AI helps job seekers optimize their resumes, LinkedIn profiles, and interview skills through AI-powered tools and personalized feedback.

✨ Features

• 📄 Resume Builder - Create, analyze and optimize your resume with AI-powered feedback
• 👔 LinkedIn Optimizer - Enhance your LinkedIn profile and posts for better engagement
• 🎯 Mock Interviews - Practice with AI-powered interview simulations and get instant feedback
• 📚 Learning Resources - Access curated learning materials for technical and behavioral interviews

🛠️ Tech Stack

• Frontend: React.js, Tailwind CSS, Framer Motion
• Backend: Node.js, Express.js
• Database: MongoDB
• AI: Google Gemini API
• Authentication: JWT

📋 Prerequisites

• Node.js (v14+)
• MongoDB
• Google Gemini API key

🚀 Installation

Clone the repository

git clone https://github.com/yourusername/CrackIt.AI.git
cd CrackIt.AI

Backend setup

cd server
npm install

# Create .env file
cp .env
# Edit .env file with your MongoDB URI, JWT secret, and Gemini API key

Frontend setup

cd client
npm install
# Create .env file
cp  .env
# Add your environment variables

🏃‍♀️ Running the Application

Start the backend server

cd server
node server.js
# Development mode with hot reload
npx nodemon

Start the frontend application

cd client
npm run dev

The application should be running at http://localhost:5173

📁 Project Structure

CrackIt.AI/
├── client/                 # React frontend
│   ├── public/             # Static files
│   └── src/
│       ├── components/     # React components
│       ├── pages/          # Page components
│       ├── services/       # API services
│       └── utils/          # Utility functions
│
└── server/                 # Node.js backend
    ├── config/             # Configuration files
    ├── controllers/        # Request controllers
    ├── middlewares/        # Express middlewares
    ├── models/             # MongoDB models
    ├── routes/             # API routes
    ├── services/           # Business logic
    └── utils/              # Utility functions

🌟 Key Features Explained

Resume Builder

• Upload existing resumes for AI analysis
• Choose from multiple professional templates
• Get ATS compatibility feedback
• Generate optimized content for each section
• Export as PDF

LinkedIn Optimizer

• Analyze and improve your LinkedIn profile
• Get section-by-section recommendations
• Optimize posts for better engagement
• Compare before and after metrics

Mock Interviews

• Practice with AI-powered interviews
• Choose from technical, behavioral, and HR interview types
• Receive feedback using STAR method analysis
• Track progress and improvement areas

Learning Resources

• Access curated topics for interview preparation
• Filter resources by category and difficulty

📝 Environment Variables

Backend (.env)

MONGODB_URI=your_mongodb_connection_string
JWT_SECRET=your_jwt_secret
GEMINI_API_KEY=your_gemini_api_key
PORT=3000

Frontend (.env)

VITE_API_URL=http://localhost:3000/api
VITE_GOOGLE_API_KEY=your_gemini_api_key

💡 Contributing

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

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👥 Authors

• Ananta025

🙏 Acknowledgements

• Google Gemini API
• MongoDB
• React.js
• Framer Motion
• Tailwind CSS