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AI Interview

AI-powered interview tool that analyzes answers and provides instant, personalized feedback for effective preparation.

Live Demo GitHub React TypeScript Docker

๐Ÿ“ธ Screenshots

Project Screenshot

Project Screenshot

Project Screenshot

๐ŸŽฏ Overview

AI Interview is a comprehensive interview preparation platform that leverages artificial intelligence to simulate real interview scenarios. The application provides instant feedback on your responses, helping you identify areas for improvement and build confidence for your actual interviews.

โœจ Features

  • ๐Ÿค– AI-Powered Questions - Dynamic question generation based on role and experience level
  • ๐Ÿ“Š Real-time Analysis - Instant feedback on communication skills and answer quality
  • ๐ŸŽ™๏ธ Voice Recognition - Speech-to-text for natural conversation flow
  • ๐Ÿ“ˆ Performance Tracking - Detailed analytics and progress monitoring
  • ๐Ÿ” Secure Authentication - User management with Clerk integration
  • ๐Ÿ’ฌ Real-time Communication - WebSocket integration for seamless interactions
  • ๐ŸŽจ Modern UI/UX - Clean, responsive interface built with Tailwind CSS
  • ๐Ÿ“ฑ Mobile Responsive - Optimized for all devices

๐Ÿ› ๏ธ Tech Stack

Category Technology Purpose
Frontend React 18+ User interface framework
Language TypeScript Type-safe development
Build Tool Vite Fast development and bundling
Styling Tailwind CSS Utility-first styling
State Management Redux Toolkit Predictable state management
Authentication Clerk User authentication & management
Real-time WebSocket Live communication
Validation Zod Runtime type validation
UI Components shadcn/ui Reusable component library
Containerization Docker Application deployment

๐Ÿš€ Quick Start

Prerequisites

  • Node.js 18+ and npm (for local development)
  • Git
  • Docker and Docker Compose (for containerized deployment)

Option 1: Docker Installation (Recommended)

The fastest way to get started is using our pre-built Docker image:

Using Docker Run

  1. Pull and run the Docker image

    docker run -d \
      --name ai-interview \
      -p 3000:80 \
      -e VITE_CLERK_PUBLISHABLE_KEY=your_clerk_key_here \
      -e VITE_API_BASE_URL=your_api_url_here \
      -e VITE_WEBSOCKET_URL=your_websocket_url_here \
      tanish2000/ai-interview:latest
  2. Access the application Open your browser and navigate to http://localhost:3000

Using Docker Compose

  1. Create a docker-compose.yml file

    version: '3.8'
    
    services:
      ai-interview:
        image: tanish2000/ai-interview:latest
        container_name: ai-interview
        ports:
          - "3000:80"
        environment:
          - VITE_CLERK_PUBLISHABLE_KEY=your_clerk_key_here
          - VITE_API_BASE_URL=your_api_url_here
          - VITE_WEBSOCKET_URL=your_websocket_url_here
        restart: unless-stopped
  2. Start the application

    docker-compose up -d
  3. View logs (optional)

    docker-compose logs -f ai-interview

Environment Variables for Docker

Create a .env file for Docker Compose:

VITE_CLERK_PUBLISHABLE_KEY=your_clerk_key_here
VITE_API_BASE_URL=your_api_url_here
VITE_WEBSOCKET_URL=your_websocket_url_here

Then update your docker-compose.yml:

version: '3.8'

services:
  ai-interview:
    image: tanish2000/ai-interview:latest
    container_name: ai-interview
    ports:
      - "3000:80"
    env_file:
      - .env
    restart: unless-stopped

Docker Management Commands

# Pull the latest image
docker pull tanish2000/ai-interview:latest

# Stop the container
docker stop ai-interview

# Start the container
docker start ai-interview

# Remove the container
docker rm ai-interview

# View container logs
docker logs ai-interview

# Execute commands inside the container
docker exec -it ai-interview /bin/sh

Option 2: Local Development Installation

  1. Clone the repository

    git clone https://github.com/devtanish/AI-Interview.git
    cd AI-Interview
  2. Install dependencies

    npm install
  3. Set up environment variables

    cp .env.example .env.local

    Update .env.local with your configuration:

    VITE_CLERK_PUBLISHABLE_KEY=your_clerk_key_here
    VITE_API_BASE_URL=your_api_url_here
    VITE_WEBSOCKET_URL=your_websocket_url_here
  4. Start the development server ```bash npm run dev ```

  5. Open your browser Navigate to http://localhost:5173

๐Ÿ“ Project Structure

AI-Interview/
โ”œโ”€โ”€ public/                 # Static assets
โ”œโ”€โ”€ src/
โ”‚   โ”œโ”€โ”€ components/        # Reusable UI components
โ”‚   โ”‚   โ”œโ”€โ”€ ui/           # shadcn/ui components
โ”‚   โ”‚   โ”œโ”€โ”€ interview/    # Interview-specific components
โ”‚   โ”‚   โ””โ”€โ”€ common/       # Shared components
โ”‚   โ”œโ”€โ”€ pages/            # Application pages/routes
โ”‚   โ”œโ”€โ”€ hooks/            # Custom React hooks
โ”‚   โ”œโ”€โ”€ store/            # Redux store configuration
โ”‚   โ”‚   โ”œโ”€โ”€ slices/      # Redux slices
โ”‚   โ”‚   โ””โ”€โ”€ api/         # API slice definitions
โ”‚   โ”œโ”€โ”€ lib/             # Utility libraries
โ”‚   โ”œโ”€โ”€ types/           # TypeScript type definitions
โ”‚   โ”œโ”€โ”€ schemas/         # Zod validation schemas
โ”‚   โ””โ”€โ”€ styles/          # Global styles
โ”œโ”€โ”€ package.json
โ”œโ”€โ”€ tsconfig.json
โ”œโ”€โ”€ tailwind.config.js
โ”œโ”€โ”€ vite.config.ts
โ””โ”€โ”€ README.md

๐Ÿ”ง Available Scripts

# Development
npm run dev          # Start development server
npm run build        # Build for production  
npm run preview      # Preview production build locally

# Code Quality
npm run lint         # Run ESLint
npm run lint:fix     # Fix ESLint issues
npm run type-check   # Run TypeScript compiler

# Testing
npm run test         # Run tests
npm run test:ui      # Run tests with UI

# Docker (if building locally)
docker build -t ai-interview .                    # Build Docker image
docker run -p 3000:80 ai-interview             # Run Docker container

Custom Domain Setup

To use a custom domain with Lovable:

  1. Go to Project โ†’ Settings โ†’ Domains
  2. Click Connect Domain
  3. Follow the DNS configuration steps

๐ŸŽฎ Usage

  1. Sign Up/Login - Create an account or sign in with existing credentials
  2. Choose Interview Type - Select from technical, behavioral, or custom interviews
  3. Set Parameters - Configure difficulty level, duration, and focus areas
  4. Start Interview - Begin your AI-powered interview session
  5. Review Feedback - Analyze your performance and improvement suggestions
  6. Track Progress - Monitor your improvement over time

๐Ÿณ Docker Hub

The application is available as a Docker image on Docker Hub:

Pull the image directly: ```bash docker pull tanish2000/ai-interview:latest ```

๐Ÿค Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

Development Workflow

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/amazing-feature
  3. Make your changes and add tests
  4. Commit your changes: git commit -m 'Add amazing feature'
  5. Push to the branch: git push origin feature/amazing-feature
  6. Open a Pull Request

Code Style

  • Use TypeScript for all new code
  • Follow the existing ESLint configuration
  • Write meaningful commit messages
  • Add tests for new features

๐Ÿ› Issues & Support

๐Ÿ“„ License

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

๐Ÿ‘จโ€๐Ÿ’ป Author

Tanish

๐Ÿ™ Acknowledgments

  • React - The foundation of our UI
  • Clerk - Authentication made simple
  • shadcn/ui - Beautiful component library
  • Tailwind CSS - Utility-first CSS framework
  • Lovable - Rapid development platform
  • Docker - Containerization platform

๐Ÿ“ˆ Roadmap

  • Multi-language support
  • Video interview simulation
  • Advanced analytics dashboard
  • Integration with job platforms
  • Mobile app development
  • AI interviewer personality customization
  • Kubernetes deployment support
  • Multi-architecture Docker images

โญ Star this repo if you found it helpful!

Made with โค๏ธ by Tanish

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AI-powered interview tool, analyzes answers, provides instant, personalized feedback for effective preparation.

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