AI Interview Coach

An AI-powered interview practice platform that provides real-time feedback on body language, speech, and answer quality using computer vision and AI.

🎯 Features

• Real-Time Body Language Analysis

  • Eye contact tracking
  • Posture detection
  • Fidgeting and gesture analysis

• Speech Analysis

  • Automatic transcription using OpenAI Whisper
  • Filler word detection ("um", "uh", "like")
  • Speaking pace analysis

• AI-Powered Feedback

  • Answer quality evaluation using Claude AI
  • STAR format detection
  • Personalized improvement suggestions

• Progress Tracking

  • Dashboard with performance metrics
  • Improvement trends over time
  • Session history and reports

🏗️ Tech Stack

Backend

• FastAPI - Modern Python web framework
• SQLAlchemy - Database ORM
• MediaPipe - Face and pose detection
• OpenAI Whisper - Speech-to-text
• Anthropic Claude - AI evaluation
• SQLite - Database (PostgreSQL for production)

Frontend

• React 18 - UI library
• Vite - Build tool
• TailwindCSS - Styling
• React Query - Data fetching
• React Router - Navigation
• MediaPipe (Browser) - Client-side face detection

📁 Project Structure

ai-interview-coach/
├── backend/
│   ├── app/
│   │   ├── api/routes/          # API endpoints
│   │   ├── analyzers/           # Analysis logic
│   │   ├── database/            # Models and DB config
│   │   └── utils/               # Helper functions
│   ├── requirements.txt
│   └── .env.example
├── frontend/
│   ├── src/
│   │   ├── components/          # React components
│   │   ├── pages/               # Page components
│   │   └── services/            # API services
│   └── package.json
└── data/
    ├── videos/                  # Interview recordings
    └── reports/                 # Generated reports

🚀 Getting Started

Prerequisites

• Python 3.11+
• Node.js 18+
• npm or yarn

Backend Setup

1. Navigate to backend directory:

cd backend

2. Create virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Create .env file:

cp .env.example .env

5. Add your Anthropic API key to .env:

ANTHROPIC_API_KEY=your_api_key_here

6. Run the server:

cd app
python -m uvicorn main:app --reload

Backend will be available at http://localhost:8000

Frontend Setup

1. Navigate to frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Start development server:

npm run dev

Frontend will be available at http://localhost:5173

📅 Development Roadmap

Sprint 1: Foundation (Days 1-5) ✅ DONE

• Project structure
• Backend API setup
• Frontend React setup
• Database models
• Video recording
• Face detection integration

Sprint 2: Analysis (Days 6-10)

• Eye contact tracking
• Posture analysis
• Speech-to-text integration
• Filler word detection
• Claude AI integration

Sprint 3: Reports (Days 11-15)

• Report generation
• Dashboard with charts
• PDF export
• Progress tracking

Sprint 4: Deployment (Days 16-20)

• Docker setup
• Deploy backend
• Deploy frontend
• Documentation
• Demo video

🔑 Getting Anthropic API Key

1. Go to https://console.anthropic.com/
2. Sign up (get $5 free credit)
3. Navigate to "API Keys"
4. Create new key
5. Add to .env file

📊 Database Schema

InterviewSession

• Stores overall interview data
• Tracks scores and metrics
• Links to video recordings

Question

• Interview question bank
• Categorized by type and difficulty

InterviewAnswer

• Individual answers within sessions
• Detailed metrics per answer

UserProgress

• Long-term progress tracking
• Improvement metrics

🧪 Testing the API

Once backend is running, visit:

• API Docs: http://localhost:8000/docs
• Health Check: http://localhost:8000/api/health

📝 API Endpoints

Interviews

• POST /api/interviews/start - Start new session
• GET /api/interviews/{id} - Get session details
• GET /api/interviews/ - List all sessions
• POST /api/interviews/{id}/upload-video - Upload video
• POST /api/interviews/{id}/complete - Complete session

Analysis

• POST /api/analysis/analyze - Analyze session
• GET /api/analysis/real-time/{id} - Real-time metrics

Reports

• GET /api/reports/{id} - Get detailed report
• GET /api/reports/{id}/pdf - Download PDF
• GET /api/reports/progress/summary - Progress summary

🎨 UI Screenshots

🤝 Contributing

This is a personal portfolio project, but suggestions are welcome!

📄 License

MIT License - feel free to use for your own learning

👤 Author

Ege Karaca

• LinkedIn: www.linkedin.com/in/ege-karaca
• GitHub: www.github.com/egekaraca

🙏 Acknowledgments

• MediaPipe by Google
• Anthropic Claude API
• OpenAI Whisper
• FastAPI community

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Status: 🚧 In Development (Day 2/20 Complete)