AI Interview Prep Platform

🌟 Live Demo: https://interview-prep-1-5dz1.onrender.com

An intelligent, full-stack application designed to help job seekers prepare for interviews by leveraging the power of Generative AI. The platform analyzes resumes against job descriptions to generate tailored ATS-friendly resumes, comprehensive interview reports, technical/behavioral questions, and personalized preparation plans.

🚀 Features

• Resume Analysis: Upload a PDF resume and a target job description to get a detailed match score.
• ATS Resume Tailoring: Generate a cleanly formatted, ATS-optimized HTML/PDF resume tailored specifically to the job description you are targeting.
• AI Mock Interview Generation: Receive a customized interview report containing:
  • Technical & Behavioral Questions
  • Ideal Answers & Interviewer Intentions
  • Identified Skill Gaps and their Severities
  • A structured Day-by-Day Preparation Plan
• Robust Architecture: Powered by Google's latest Gemini AI models (gemini-2.5-flash-lite), featuring automatic retry loops and fallback mechanisms to ensure high availability.
• Secure Authentication: User authentication and protected routes to manage personal interview reports securely.

💻 Tech Stack

Frontend

• Framework: React.js
• Styling: SCSS (with a responsive, modern dark/light mode UI)
• Routing: React Router

Backend

• Server: Node.js with Express.js
• Database: MongoDB (via Mongoose)
• AI Integration: Google Generative AI SDK (@google/genai)
• PDF Processing: pdf-parse (v2), puppeteer (for HTML-to-PDF conversion)
• File Uploads: Multer

🛠️ Setup & Installation

Prerequisites

• Node.js (v18 or higher recommended)
• MongoDB running locally or a MongoDB Atlas URI
• Google Gemini API Key

1. Clone the Repository

git clone https://github.com/Jatzz26/Interview-Prep.git
cd Interview-Prep

2. Backend Setup

cd Backend
npm install

Create a .env file in the Backend directory:

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

Start the backend server:

npm run dev

3. Frontend Setup

cd ../Frontend
npm install

Create a .env file in the Frontend directory (if required) and configure your backend API URL.

Start the frontend development server:

npm run dev

🧠 How the AI Works

The platform utilizes Google's Gemini 2.5 Flash Lite model. To ensure strict JSON formatting and avoid schema-parsing errors, the backend utilizes explicit structured-prompt engineering. A built-in automatic retry mechanism intercepts 503 High Demand errors to provide a seamless, robust user experience even during peak API traffic times.

📄 License

This project is open-source and available under the MIT License.