Skip to content

README.md

Latest commit

 

History

History
66 lines (50 loc) · 2.51 KB

README.md

File metadata and controls

66 lines (50 loc) · 2.51 KB

PrepAI — AI-Powered Interview Preparation Platform

PrepAI is an intelligent web application designed to help students and job seekers master their interview skills. By leveraging the power of Gemini AI, PrepAI provides personalized resume feedback, ATS scoring, and realistic mock interview simulations with qualitative evaluations.

🚀 Features

  • AI Resume Analysis: Upload your PDF resume to get an instant ATS score, strengths/weaknesses breakdown, and actionable formatting tips.
  • Personalized Interview Generator: Generate tailored interview questions based on your target role, tech stack, and experience level.
  • Interactive Mock Interviews: Submit your answers via text and receive real-time AI feedback on clarity, technical accuracy, and communication.
  • Smart Dashboard: Track your progress over time, view your analysis history, and get smart tips to boost your employability.
  • Secure Authentication: Protected accounts using JWT and bcrypt password hashing.

🛠 Tech Stack

  • Frontend: React (Vite), TailwindCSS, React Router, Motion (Animations), Axios
  • Backend: Node.js, Express.js
  • Database: MongoDB (Mongoose)
  • AI: Google Gemini AI (@google/genai)
  • File Handling: Multer & pdf-parse

⚙️ Setup Instructions

Prerequisites

  • Node.js (v18+)
  • MongoDB (Local or Atlas URI)
  • Gemini API Key (from Google AI Studio)

Installation

  1. Clone the repository.
  2. Install dependencies: 
    npm install
  3. Create a .env file in the root directory (use .env.example as a template): 
    MONGODB_URI=your_mongodb_uri
JWT_SECRET=your_jwt_secret
GEMINI_API_KEY=your_gemini_api_key
  4. Start the development server: 
    npm run dev

📜 Deployment

The application is structured to be easily deployable:

  • Frontend: Can be deployed as a static site (after npm run build) or served via the Express backend.
  • Backend: Deployable to platforms like Render, Railway, or Heroku.
  • Environment Variables: Ensure NODE_ENV is set to production to serve static files correctly.

🏗 Architecture Overview

PrepAI follows a full-stack architecture where the Express server acts as both the API provider and the static file server in production. Gemini AI calls are handled securely on the server side to protect API keys.

Frontend (React) <---> Backend (Express) <---> MongoDB
                          |
                          v
                      Gemini AI

Built with ❤️ by the PrepAI Team.