AI Technical Interviewer

A comprehensive AI-powered technical interview platform that conducts real-time interviews with candidates, featuring voice interaction, code assessment, behavioral monitoring, and automated result generation for recruiters.

🚀 Live Demo

Experience the platform with our live demo applications:

Platform	Description	Demo Link
🏢 Job Portal	Complete hiring workflow with job posting and applications	Try Demo →
📅 Interview Scheduler	Schedule and manage AI-powered technical interviews	Try Demo →
💻 Code Analysis	Advanced code assessment and technical evaluation	Try Demo →
🤖 AI Interviewer	Interactive AI-powered candidate interviews	Try Demo →

🎯 Ready to transform your hiring process? Start with our Job Portal Demo to see the complete workflow!

🌟 Features

Core Interview Capabilities

AI-Powered Interviews: GPT-4 driven conversational interviews tailored to candidate profiles
Real-time Voice Interaction: Speech-to-text and text-to-speech for natural conversation flow
Live Coding Assessment: Integrated code editor with multiple programming language support
Behavioral Monitoring: Face detection and object detection to ensure interview integrity

Interview Management

Session Scheduling: Schedule interviews with email notifications
Candidate Profiles: Upload and manage detailed candidate profiles with skills, projects, and experience
Custom Questions: Generate AI-tailored questions based on candidate background
Interview Results: Automated transcription, AI-refined summaries, and recruiter-friendly reports

Technical Monitoring

Video Surveillance: Real-time face and object detection during interviews
Code Editor Integration: Live coding exercises with test case validation
Session Recording: Complete interview transcripts and coding submissions
Email Integration: Automated notifications using Resend API

📸 Platform Screenshots

🏢 Job Portal for Recruiters & Candidates

Comprehensive job portal with role-based access for both recruiters and candidates

👥 Candidate Shortlisting Process

AI-powered candidate evaluation and shortlisting based on skills and experience

📅 AI Interview Scheduler

Intelligent interview scheduling with automated calendar integration

📋 Interview Scheduling Process

Step-by-step interview scheduling workflow with email notifications

🚪 Candidate Entry for Interview Session

Secure candidate authentication and interview session access portal

🤖 AI Interviewer for Candidates

Interactive AI-powered interview interface with real-time conversation

💻 AI-Powered Coding Assessment

Advanced coding challenges with real-time evaluation and feedback

🔍 AI Powered Candidate Project Code Analysis

Intelligent code analysis and technical skill assessment

🚀 Tech Stack

Backend

Node.js with Express.js - RESTful API server
OpenAI GPT-4 - AI interview conductor
MongoDB with Mongoose - Database for profiles and results
Resend - Email service for notifications
CORS - Cross-origin resource sharing

Frontend

React 19 - Modern UI framework
Vite - Fast build tool and development server
TailwindCSS - Utility-first CSS framework
Three.js with @react-three/fiber - 3D avatar rendering
MediaPipe - Face detection capabilities
TensorFlow.js - Object detection models
Lucide React - Modern icon library

📋 Prerequisites

Node.js (v16 or higher)
npm or yarn
MongoDB (optional - falls back to filesystem storage)
OpenAI API Key
Resend API Key (for email features)

🛠️ Installation

1. Clone the Repository

git clone https://github.com/muhammadnavas/AI-Technical-Interviewer.git
cd AI-Technical-Interviewer

2. Install Dependencies

# Install all dependencies (frontend and backend)
cd backend && npm run setup

Or install separately:

# Backend dependencies
cd backend
npm install

# Frontend dependencies
cd ../frontend
npm install

3. Environment Configuration

Copy the environment template:

cd backend
cp .env.example .env

Configure your .env file:

# OpenAI API Configuration (Required)
OPENAI_API_KEY=your_openai_api_key_here

# Email Configuration (Optional)
RESEND_API_KEY=your_resend_api_key_here
FROM_EMAIL=noreply@yourcompany.com

# MongoDB Configuration (Optional - uses filesystem if omitted)
MONGO_URI=mongodb://localhost:27017/ai_interviewer
MONGO_DB_NAME=ai_interviewer

# Frontend URLs
FRONTEND_URL=http://localhost:5173
PRODUCTION_FRONTEND_URL=https://your-production-url.com

# Server Configuration
PORT=3000

4. Start the Application

Development Mode (Both servers):

cd backend
npm run dev:full

Start Individually:

# Backend server
cd backend
npm run dev

# Frontend development server (in new terminal)
cd frontend
npm run dev

🎯 Usage Guide

For Recruiters

1. Candidate Profile Management

Upload candidate profiles via JSON files
Create detailed profiles with skills, experience, and project details
Generate AI-tailored interview questions automatically

2. Interview Setup

Schedule interviews with automatic email notifications
Configure custom questions and coding challenges
Set interview parameters (duration, difficulty level)

3. Session Management

Access live interviews for monitoring
Review real-time candidate performance
Export interview results and assessments

For Candidates

1. Interview Access

Join interviews using session ID and access token
Complete pre-interview setup and equipment checks
Participate in voice-based technical discussions

2. Coding Assessments

Solve programming challenges in integrated code editor
Multiple language support (JavaScript, Python, Java, etc.)
Real-time code execution and test validation

3. Behavioral Monitoring

Face detection ensures candidate presence
Object detection maintains interview integrity
3D avatar provides engaging interview experience

🏗️ Project Structure

AI-Technical-Interviewer/
├── backend/
│   ├── models/
│   │   └── InterviewSession.js    # MongoDB schema for sessions
│   ├── routes/
│   │   ├── sessions.js            # Interview session routes
│   │   ├── email.js               # Email notification routes
│   │   ├── integrations.js        # External integrations
│   │   └── scheduledSessions.js   # Session scheduling
│   ├── utils/
│   │   ├── emailService.js        # Email service utilities
│   │   └── sessionScheduler.js    # Session scheduling logic
│   ├── candidate-profiles/        # Candidate profile storage
│   ├── interview-results/         # Interview result storage
│   ├── server.js                  # Main server file
│   ├── package.json               # Backend dependencies
│   └── .env.example               # Environment template
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── InterviewSession.jsx    # Main interview interface
│   │   │   ├── AIAvatar3D.jsx          # 3D avatar component
│   │   │   ├── FaceDetector.jsx        # Face detection monitoring
│   │   │   ├── ObjectDetector.jsx      # Object detection monitoring
│   │   │   ├── VideoMonitor.jsx        # Video monitoring panel
│   │   │   ├── MonitoringPanel.jsx     # Behavioral monitoring
│   │   │   └── SessionScheduler.jsx    # Interview scheduling
│   │   ├── pages/
│   │   │   ├── HomePage.jsx            # Landing page
│   │   │   └── InterviewSetup.jsx      # Interview configuration
│   │   ├── App.jsx                     # Main application component
│   │   ├── config.js                   # Frontend configuration
│   │   └── main.jsx                    # Application entry point
│   ├── package.json                    # Frontend dependencies
│   ├── vite.config.js                  # Vite configuration
│   ├── tailwind.config.js              # TailwindCSS configuration
│   └── index.html                      # HTML template
└── README.md                           # Project documentation

🤝 Contributing

Fork the repository
Create a feature branch: git checkout -b feature/amazing-feature
Commit your changes: git commit -m 'Add amazing feature'
Push to the branch: git push origin feature/amazing-feature
Open a Pull Request

Development Guidelines

Follow ESLint configuration for code style
Add tests for new features
Update documentation for API changes
Ensure cross-browser compatibility

📧 Support

For questions, issues, or feature requests:

GitHub Issues: Create an issue

🔮 Roadmap

Video recording and playback
Advanced analytics dashboard
Multi-language interview support
Integration with ATS systems
Mobile application support
Real-time collaboration features
Advanced code assessment metrics
Machine learning bias detection

👥 Collaborators

Contributor	GitHub Profile
Muhammad Navas
Sanketh Shetty
Samarth Hegde

🤝 How to Contribute

We welcome contributions from the community! Whether you're fixing bugs, adding features, or improving documentation, your help is appreciated.

Ways to contribute:

🐛 Report bugs and issues
💡 Suggest new features
🔧 Submit pull requests
📚 Improve documentation
⭐ Star the repository to show support

Built with ❤️ by Muhammad Navas and the amazing contributors above

Transform your technical hiring process with AI-powered interviews that provide comprehensive, unbiased, and detailed candidate assessments.

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frontend		frontend
README.md		README.md

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