JobHelper - AI-Powered Resume Assistant

A comprehensive platform for creating, enhancing, and managing resumes with AI assistance.

Project Structure

├── backend/          # .NET backend API
├── client/           # Next.js frontend application
└── AI2/             # Python AI services

Deployment Information

Production URLs

• Frontend: local
• Backend API: https://job-helper-app.azurewebsites.net
• Python AI Services: https://jobhelper-py.azurewebsites.net

Backend (.NET API)

Local Development

Prerequisites:

• .NET 9.0 SDK
• SQL Server or compatible database

Setup:

cd backend
dotnet restore
dotnet build

Configuration: Edit appsettings.Development.json with your local database connection string and configuration.

Run:

dotnet run

The API will be available at https://localhost:5001 (or the port specified in launchSettings.json).

Deployment to Azure

The backend is deployed to Azure Web Apps at: https://job-helper-app.azurewebsites.net

Deployment Steps:

1. Build the application:

   cd backend
   dotnet publish -c Release -o ./publish

2. Deploy via Azure CLI:

   az login
   az webapp deployment source config-zip --resource-group <resource-group> --name job-helper-app --src ./publish.zip

3. Or deploy via Visual Studio:

   • Right-click the project → Publish
   • Select Azure → Azure App Service (Windows)
   • Choose the existing job-helper-app service

Configuration:

• Set connection strings and app settings in Azure Portal under Configuration
• Enable Application Insights for monitoring
• Configure CORS settings to allow frontend domain

Frontend (Next.js)

Local Development

Prerequisites:

• Node.js 18+ and npm

Setup:

cd client
npm install

Environment Variables: Create a .env.local file with:

NEXT_PUBLIC_API_URL=http://localhost:5001
NEXT_PUBLIC_PYTHON_API_URL=http://localhost:8000
# Add other environment variables as needed

Run Development Server:

npm run dev

Open http://localhost:3000 in your browser.

Build for Production

npm run build
npm start

Python AI Services

Local Development

Prerequisites:

• Python 3.9+
• pip

Setup:

cd AI2
pip install -r requirements.txt

Environment Variables: Create a .env file with necessary API keys:

OPENAI_API_KEY=your_key_here
# Add other required keys

Run:

python main.py

Or with uvicorn for FastAPI:

uvicorn main:app --reload --port 8000

The service will be available at http://localhost:8000.

Deployment to Azure

The Python services are deployed to Azure Web Apps at: https://jobhelper-py.azurewebsites.net

Deployment Steps:

1. Prepare requirements: Ensure requirements.txt is up to date:

   cd AI2
   pip freeze > requirements.txt

2. Deploy via Azure CLI:

   az webapp up --name jobhelper-py --resource-group <resource-group> --runtime "PYTHON:3.9"

3. Or deploy via GitHub Actions: Configure workflow for automatic deployment on push.

Configuration in Azure:

• Set Python version in Azure Portal → Configuration → General Settings
• Add environment variables (API keys) in Configuration → Application Settings
• Enable Always On for production workloads
• Configure startup command if needed (e.g., gunicorn -w 4 -k uvicorn.workers.UvicornWorker main:app)

Docker Deployment

For detailed Docker setup instructions, see DOCKER_SETUP.md.

Architecture

• Backend: RESTful API built with .NET, handles user authentication, resume CRUD operations
• Frontend: Next.js React application with TypeScript, provides user interface
• Python Services: AI-powered features including CV enhancement, chat assistance, and quiz generation

Features

• 📝 Resume creation and management
• 🤖 AI-powered CV enhancement
• 💬 Interactive chat assistant
• 📊 Skills assessment quizzes
• 🌍 Multi-language support (EN, UA, RU)
• 🔐 Secure authentication
• 📱 Responsive design

API Documentation

• Backend API: Access Swagger documentation at https://job-helper-app.azurewebsites.net/swagger
• Python API: Access API docs at https://jobhelper-py.azurewebsites.net/docs

Monitoring & Logs

• View application logs in Azure Portal → Log Stream
• Use Application Insights for performance monitoring
• Check deployment status in Deployment Center

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

Support

For issues and questions, please open an issue in the repository.