VerQ - AI-Powered Mock Interview Platform

VerQ is an AI-powered mock interview platform that generates personalized interview questions based on a user's resume and target role, captures voice responses, and provides AI feedback.

Links

FRONTEND, BACKEND, PPT

Features

• Resume-based interview question generation
• Voice response recording and transcription
• AI-powered feedback and evaluation
• Real-time interview experience
• Multiple AI model support (OpenAI GPT-4, Google Gemini)
• Text-to-speech capabilities

Tech Stack

Frontend

• React + Vite
• Tailwind CSS
• Framer Motion
• React Router
• Firebase Authentication
• Web Speech API

Backend

• Node.js + Express
• MongoDB
• Google Gemini API
• Deepgram API
• Firebase Admin SDK

Project Structure

verq/
├── frontend/          # React frontend application
├── backend/           # Node.js backend server
├── PLANNING.md        # Project planning and roadmap
└── TASKS.md          # Task tracking and management

Environment Variables Setup

Backend Environment Variables

Create a .env file in the backend directory (verq/backend/.env):

# Server Configuration
PORT=3000
NODE_ENV=development

# Database Configuration
MONGODB_URI=your_mongodb_connection_string

# JWT Configuration
JWT_SECRET=your_jwt_secret_here
JWT_EXPIRES_IN=24h

# File Upload Configuration
UPLOAD_DIR=uploads
MAX_FILE_SIZE=5242880  # 5MB in bytes

# AI Configuration
OPENAI_API_KEY=your_openai_api_key_here
GEMINI_API_KEY=your_gemini_api_key_here
DEEPGRAM_API_KEY=your_deepgram_api_key_here

# Firebase Admin SDK Configuration
FIREBASE_TYPE=service_account
FIREBASE_PROJECT_ID=your_project_id
FIREBASE_PRIVATE_KEY_ID=your_private_key_id
FIREBASE_PRIVATE_KEY="your_private_key_here"
FIREBASE_CLIENT_EMAIL=your_client_email
FIREBASE_CLIENT_ID=your_client_id
FIREBASE_AUTH_URI=https://accounts.google.com/o/oauth2/auth
FIREBASE_TOKEN_URI=https://oauth2.googleapis.com/token
FIREBASE_AUTH_PROVIDER_X509_CERT_URL=https://www.googleapis.com/oauth2/v1/certs
FIREBASE_CLIENT_X509_CERT_URL=your_client_x509_cert_url

Frontend Environment Variables

Create a .env file in the frontend directory (verq/frontend/.env):

# Firebase Configuration
VITE_FIREBASE_API_KEY=your_firebase_api_key_here
VITE_FIREBASE_AUTH_DOMAIN=your_project_id.firebaseapp.com
VITE_FIREBASE_PROJECT_ID=your_project_id
VITE_FIREBASE_STORAGE_BUCKET=your_project_id.appspot.com
VITE_FIREBASE_MESSAGING_SENDER_ID=your_messaging_sender_id
VITE_FIREBASE_APP_ID=your_firebase_app_id

# API Configuration
VITE_API_BASE_URL=http://localhost:3000

Getting API Keys

1. Google Gemini API Key:

   • Visit Google AI Studio
   • Create a new API key
   • Add the key to backend/.env as GEMINI_API_KEY

2. Deepgram API Key:

   • Visit Deepgram Console
   • Create an account and generate an API key
   • Add the key to backend/.env as DEEPGRAM_API_KEY

3. Firebase Configuration:

   • Create a project in Firebase Console
   • Add a web app to your project
   • Copy the configuration object
   • Add the values to both frontend/.env and backend/.env
   • For backend, download the service account key and add its values to backend/.env

4. MongoDB Connection String:

   • Create a cluster in MongoDB Atlas
   • Get the connection string
   • Add it to backend/.env as MONGODB_URI

Getting Started

Backend Setup

1. Navigate to the backend directory:

   cd backend

2. Install dependencies:

   npm install

3. Create and configure the .env file as described above

4. Start the backend server:

   npm run dev

Frontend Setup

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install

3. Create and configure the .env file as described above

4. Start the development server:

   npm run dev

Available Scripts

Backend

• npm start - Start the production server
• npm run dev - Start the development server with auto-reload
• npm run test-pdf - Test PDF processing functionality
• npm run extract-pdf - Extract text from PDF
• npm run test-tts - Test text-to-speech functionality
• npm run generate-question-tts - Generate question and convert to speech
• npm run interview - Run the interview workflow

Frontend

• npm run dev - Start the development server
• npm run build - Build for production
• npm run lint - Run ESLint
• npm run preview - Preview production build
• npm test - Run tests
• npm run test:watch - Run tests in watch mode
• npm run test:coverage - Generate test coverage report

API Endpoints

Interview Flow

• POST /api/resume - Submit resume text and job role
• POST /api/questions - Generate interview questions
• POST /api/answers - Submit voice answer transcript
• POST /api/feedback - Get AI evaluation of answer

License

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

Acknowledgments

• Google for Gemini API
• Deepgram for Text-to-Speech API
• Firebase for Authentication and Storage
• MongoDB for Database