CV - AI-Powered Chat & Learning Platform

🌐 Website: https://gaile.ee/

A comprehensive web application featuring AI-powered chat, language learning tools, and various interactive features. Built with Spring Boot, Angular, and integrated with Ollama for AI capabilities.

🚀 Features

• AI Chat System: Interactive chat with AI models supporting English and Estonian languages
• Language Learning: English vocabulary building and grammar checking
• Speech Processing: Text-to-speech and speech-to-text capabilities
• Blog System: Content management and publishing
• Proxy Management: Proxy list management and monitoring
• Statistics: Visit statistics and user analytics
• Interactive Games: Minesweeper and learning-to-count modules
• User Authentication: Secure JWT-based authentication system

🛠 Technologies

Backend

• Java 25 with Spring Boot 4.0.5
• Spring Security - JWT authentication
• Spring Data JPA - Database access
• Spring WebFlux - Reactive programming
• Liquibase - Database migrations
• PostgreSQL with pgvector extension - Vector database for AI embeddings
• Ollama - AI model integration (GPU & CPU versions)
• MapStruct - Bean mapping
• Lombok - Code generation
• Apache POI - Document processing
• Swagger/OpenAPI - API documentation

Frontend

• Angular 21 with Angular Material
• Bootstrap 5 - UI framework
• Socket.IO - Real-time communication
• Chart.js - Data visualization
• ngx-translate - Internationalization

Infrastructure

• Docker & Docker Compose - Containerization
• Nginx - Reverse proxy and static file serving
• PostgreSQL Backup - Automated database backups

📋 Prerequisites

• Java 25 or higher
• Maven 3.8+
• Node.js 22+ and npm
• Docker and Docker Compose
• PostgreSQL 18 with pgvector extension
• NVIDIA GPU (for GPU-accelerated Ollama, optional)

🏗 Project Structure

CV/
├── common/              # Shared utilities and models
├── persistence/         # Database layer (entities, repositories)
├── security/            # Security configuration and JWT
├── services/            # Business logic layer
│   ├── blog/           # Blog service
│   ├── chat/           # AI chat service
│   ├── email/          # Email service
│   ├── english/        # English learning service
│   ├── proxy/          # Proxy management
│   ├── statistics/     # Statistics service
│   └── user/           # User management
├── web-api/             # REST API controllers
├── frontend/            # Angular application
├── docker-compose.yml   # Docker services configuration
├── Dockerfile           # Backend Docker image
└── pom.xml             # Maven configuration

🔧 Installation

1. Clone the repository

git clone <repository-url>
cd CV

2. Configure environment variables

Create a .env file in the root directory:

# Database
SPRING_DATASOURCE_URL=jdbc:postgresql://cv-postgres/db
SPRING_DATASOURCE_USERNAME=your_username
SPRING_DATASOURCE_PASSWORD=your_password
POSTGRES_DB=cv_db

# Security
SECURITY_JWT_KEY=your_jwt_secret_key

# Email (optional)
SPRING_MAIL_USERNAME=your_email@gmail.com
SPRING_MAIL_PASSWORD=your_app_password

# Ollama
OLLAMA_MODEL=hf.co/kyx0r/L3-Evil-Stheno-v3.2-8B-GGUF:Q8_0
OLLAMA_MODEL_EMBEDDING=qwen3-embedding:4b

3. Create Docker network

docker network create kokoro-net

4. Build and start services

docker-compose up -d

🚀 Running the Application

Using Docker Compose (Recommended)

# Start all services
docker-compose up -d

# View logs
docker-compose logs -f

# Stop services
docker-compose down

Manual Development Setup

Backend

# Build the project
mvn clean install

# Run the application
cd web-api
mvn spring-boot:run

The backend API will be available at http://localhost:8399/api/v1

Frontend

cd frontend

# Install dependencies
npm install --legacy-peer-deps

# Start development server
npm start

The frontend will be available at http://localhost:4405

Access Points

• Frontend: http://localhost:4488 (HTTP) or https://localhost:4489 (HTTPS)
• Backend API: http://localhost:8399/api/v1
• API Documentation: http://localhost:8399/api/v1/swagger-ui.html
• PostgreSQL: localhost:5442
• Ollama GPU: http://localhost:11434
• Ollama CPU: http://localhost:11435

📚 API Documentation

The application uses Swagger/OpenAPI for API documentation. Once the backend is running, access the Swagger UI at:

http://localhost:8399/api/v1/swagger-ui.html

Main API Endpoints

• Authentication: /api/v1/auth/*
• Chat: /api/v1/chat/*
• Blog: /api/v1/blog/*
• User: /api/v1/user/*
• Statistics: /api/v1/statistics/*
• Proxy: /api/v1/proxy/*

🔐 Security

• JWT-based authentication
• Token expiration: 30 minutes (access token), 60 minutes (refresh token)
• Password encryption
• CORS configuration
• Role-based access control

🗄 Database

Database Migrations

The project uses Liquibase for database migrations. Migration files are located in:

persistence/src/main/resources/db/changelog/

Backup Strategy

Automatic backups are scheduled daily at 2:00 AM (Europe/Tallinn timezone) and retained for 60 days.

🧪 Testing

Backend Tests

mvn test

Frontend Tests

cd frontend
npm test

📦 Building for Production

Backend

mvn clean package -Dmaven.test.skip

The executable JAR will be created at web-api/target/cv-exec.jar

Frontend

cd frontend
npm run build --configuration production

The production build will be in the dist/ directory.

Docker Images

# Build backend image
docker build -t cv-app:latest .

# Build frontend image
cd frontend
docker build -t cv-ui:latest .

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 Configuration

Application Properties

Main configuration is in web-api/src/main/resources/application.properties:

• Server Port: 8399
• Context Path: /api/v1
• File Upload Limit: 20MB
• Database: PostgreSQL with connection pooling
• Async Request Timeout: 600 seconds (for AI operations)

Ollama Configuration

• GPU Instance: Supports NVIDIA GPUs with CUDA
• CPU Instance: Fallback for systems without GPU
• Parallel Requests: 4 concurrent requests
• Thread Count: 8 threads
• Model Keep Alive: 30 minutes

🔍 Troubleshooting

Common Issues

1. Port already in use: Change ports in docker-compose.yml
2. Database connection failed: Check PostgreSQL container logs
3. Ollama not responding: Verify Ollama container is running and model is downloaded
4. Frontend build fails: Try using --legacy-peer-deps flag with npm install

Viewing Logs

# All services
docker-compose logs

# Specific service
docker-compose logs cv-app
docker-compose logs cv-postgres
docker-compose logs cv-ollama

📄 License

This project is licensed under the MIT License.

👥 Authors

• Gaile - Project Owner

🙏 Acknowledgments

• Spring Boot team
• Angular team
• Ollama project
• PostgreSQL community
• All open-source contributors