PomoTask

A Pomodoro timer with intelligent task management and AI-powered features. Built with React, Vite, and a Node.js backend.

Features

• Pomodoro Timer: Customizable 25-minute focus sessions with break tracking
• Smart Task Management: Add, edit, delete, and organize your tasks with drag-and-drop
• AI-Powered Task Analysis: Get intelligent task breakdowns including time estimates, prerequisites, and optimal scheduling
• Motivational Quotes: AI-generated motivational messages to keep you inspired
• Task Context: Automatic task categorization with metadata like energy levels, best times, and required tools
• Responsive Design: Clean, minimal UI that works on all devices
• Local Storage: Persistent task and timer state across sessions

Tech Stack

Frontend:

• React 19 with Vite
• CSS Modules for styling
• React Icons and React Tooltip for enhanced UX
• Axios for API communication

Backend:

• Node.js with Express
• AI integration via Hugging Face (DeepSeek-V3 model)
• CORS enabled for cross-origin requests

Requirements

• Node.js 18+ (recommended LTS)
• npm 9+ (or use pnpm/yarn if preferred)

Getting Started

Prerequisites

• Node.js 18+ (recommended LTS)
• npm 9+ (or use pnpm/yarn if preferred)

Installation

1. Clone the repository

   git clone https://github.com/itsleonbro/PomoTask.git
   cd PomoTask

2. Install frontend dependencies

   npm install

3. Install backend dependencies

   cd backend
   npm install
   cd ..

4. Set up environment variables Create a .env file in the backend/ directory with your Hugging Face API configuration:

   HUGGINGFACE_API_KEY=your_api_key_here
   PORT=3000
   

Running the Application

1. Start the backend server

   cd backend
   npm run dev

   The backend will run on http://localhost:3000

2. Start the frontend development server (in a new terminal)

   npm run dev

   The frontend will be available at http://localhost:5173

API Endpoints

The backend provides several AI-powered endpoints:

• POST /api/clarify: Analyze tasks and provide metadata (time estimates, prerequisites, etc.)
• GET /api/motivate: Generate motivational quotes for completed tasks
• POST /api/categorize: Categorize tasks

Development Notes

• Frontend uses CSS Modules for component-scoped styles
• React Fast Refresh is enabled via Vite for a smooth dev experience
• Backend uses Express with CORS for cross-origin requests
• AI features powered by Hugging Face's DeepSeek-V3 model
• Local storage persists task and timer state across sessions

Deployment

Frontend: The built output is static and can be deployed to platforms like Vercel, Netlify, GitHub Pages, or any static host.

Backend: Deploy the Express server to platforms like Railway, Render, Heroku, or your preferred Node.js hosting service. Ensure environment variables are properly configured.

A live deployed version of the application is also available!
Check out the latest deployment here.

Contributing

Issues and pull requests are welcome. If you’re proposing a significant change, please open an issue first to discuss what you’d like to change.

Acknowledgements

Created by the CloudCTRL team.

Team Members:

• Leon Hlabathi
• Mmela Dyantyi
• Boipelo Ngakane