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Smart Todo List with AI Integration

A full-stack web application that combines intelligent task management with AI-powered features for enhanced productivity. Built with Django REST Framework backend and Next.js frontend.

🚀 Features

Core Functionality

  • Task Management: Create, edit, delete, and organize tasks
  • Smart Categorization: Auto-categorize tasks with AI suggestions
  • Priority Management: AI-powered priority scoring (0-100)
  • Deadline Suggestions: Intelligent deadline recommendations
  • Status Tracking: Todo, In Progress, Done status management
  • Tag System: Flexible tagging for better organization

AI-Powered Features

  • Context Analysis: Process daily messages, emails, and notes
  • Task Prioritization: AI ranks tasks based on urgency and context
  • Smart Descriptions: Enhanced task descriptions with context-aware details
  • Deadline Intelligence: Realistic deadline suggestions based on complexity
  • Category Suggestions: Auto-suggest categories and tags
  • Dual AI Support: OpenAI API + Local LLM (LM Studio) support

User Experience

  • Responsive Design: Works seamlessly on desktop and mobile
  • Real-time Updates: Live data synchronization
  • Advanced Filtering: Filter by status, priority, category, and more
  • Search Functionality: Full-text search across tasks
  • Dashboard Analytics: Task completion statistics and insights
  • Dark Mode Ready: Modern UI with Tailwind CSS

🛠 Tech Stack

Backend

  • Django 4.2.7 - Web framework
  • Django REST Framework - API development
  • PostgreSQL - Database (Supabase)
  • OpenAI API - AI integration
  • LM Studio Support - Local LLM hosting

Frontend

  • Next.js 14 - React framework
  • Tailwind CSS - Styling
  • SWR - Data fetching and caching
  • React Hook Form - Form management
  • Lucide React - Icons

AI Integration

  • OpenAI GPT-3.5-turbo - External AI service
  • LM Studio - Local LLM hosting (recommended)
  • Context Processing - Daily context analysis
  • Smart Suggestions - AI-powered task enhancement

🏗️ Project Structure

comata9462-project/
├── backend/                 # Django REST API
│   ├── ai_module/          # AI processing module
│   ├── tasks/              # Task management app
│   ├── smart_todo/         # Django project settings
│   ├── requirements.txt    # Python dependencies
│   └── manage.py          # Django management script
├── frontend/               # Next.js React application
│   ├── components/         # Reusable React components
│   ├── pages/             # Next.js pages and API routes
│   ├── lib/               # Utility functions and API client
│   ├── styles/            # CSS and styling
│   └── package.json       # Node.js dependencies
├── quick-start.sh         # Automated setup script
├── cleanup-production.sh  # Production cleanup script
└── README.md             # This file

📦 Installation & Setup

Prerequisites

  • Python 3.9+
  • Node.js 18+
  • PostgreSQL database (Supabase configured)
  • OpenAI API key (already configured)

Quick Start (OpenHands Environment)

The project is production-ready and pre-configured for the OpenHands runtime environment.

One-Command Setup

# Run the automated setup script
./quick-start.sh

Manual Setup (if needed)

  1. Backend Setup
cd backend
python -m pip install -r requirements.txt
python manage.py makemigrations
python manage.py migrate
python manage.py runserver 0.0.0.0:12000 > backend.log 2>&1 &
  1. Frontend Setup
cd frontend
npm install
echo "NEXT_PUBLIC_BACKEND_URL=https://work-1-zxnbvxythqwtjtxu.prod-runtime.all-hands.dev" > .env.local
echo "NEXT_PUBLIC_API_URL=https://work-1-zxnbvxythqwtjtxu.prod-runtime.all-hands.dev/api" >> .env.local
npm run dev -- --port 12001 --hostname 0.0.0.0 > frontend.log 2>&1 &

Access Points

Production Cleanup

# Remove all unnecessary files for production
./cleanup-production.sh

Local Development Setup

For local development outside OpenHands:

Backend Setup

cd backend

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

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env
# Edit .env with your local configuration

# Setup database
python manage.py makemigrations
python manage.py migrate
python manage.py createsuperuser

# Run server
python manage.py runserver

Frontend Setup

cd frontend

# Install dependencies
npm install

# Configure environment
cp .env.local.example .env.local
# Edit .env.local:
# NEXT_PUBLIC_API_URL=http://localhost:8000/api

# Run development server
npm run dev

AI Setup Options

Option 1: OpenAI API (Recommended for production)

  1. Get API key from OpenAI Platform
  2. Add to backend .env: OPENAI_API_KEY=your_key_here
  3. Restart backend server

Option 2: Local LLM with LM Studio (Privacy-focused)

  1. Download LM Studio
  2. Install a compatible model (Llama 2, Mistral, etc.)
  3. Start local server in LM Studio
  4. Add to backend .env: LOCAL_LLM_URL=http://127.0.0.1:1234/v1/chat/completions
  5. Restart backend server

🎯 Usage

Getting Started

  1. Access the Application: Open https://work-2-zxnbvxythqwtjtxu.prod-runtime.all-hands.dev in your browser
  2. Dashboard Overview: View your task statistics and recent tasks
  3. Create Tasks: Click "Add Task" to create new tasks with AI assistance
  4. AI Enhancement: Use "Get AI Suggestions" for smart task creation

✅ Verified Working Features

Task Management

  • ✅ Create Tasks: Add new tasks with title, description, priority, and deadlines
  • ✅ AI Suggestions: Get intelligent suggestions for priority, category, tags, and descriptions
  • ✅ Task Status: Track tasks as "To Do", "In Progress", or "Done"
  • ✅ Priority Levels: Set priority from 0-100 with visual indicators
  • ✅ Categories: Organize tasks by Work, Personal, etc.
  • ✅ Tags: Add multiple tags for better organization

AI Features

  • ✅ Smart Suggestions: AI analyzes task titles and provides relevant suggestions
  • ✅ Enhanced Descriptions: AI generates detailed, context-aware task descriptions
  • ✅ Priority Intelligence: AI suggests appropriate priority levels (0-100)
  • ✅ Category Detection: AI recommends suitable categories
  • ✅ Tag Generation: AI suggests relevant tags for better organization

Dashboard Features

  • ✅ Task Statistics: View total, completed, pending, and overdue tasks
  • ✅ Recent Tasks: See your latest tasks with full details
  • ✅ Real-time Updates: Dashboard updates immediately after task creation
  • ✅ Navigation: Easy access to all features via sidebar menu
  • ✅ Responsive Design: Works on desktop and mobile devices

Technical Features

  • ✅ API Integration: Full REST API with Django backend
  • ✅ Database: PostgreSQL with Supabase hosting
  • ✅ AI Integration: OpenAI GPT integration for smart suggestions
  • ✅ CORS Support: Proper cross-origin request handling
  • ✅ Error Handling: Graceful error handling and user feedback

How to Use AI Features

  1. Create a Task: Click "Add Task" and enter a task title
  2. Get AI Suggestions: Click "Get AI Suggestions" button
  3. Apply Suggestions: Use "Apply" buttons to accept AI recommendations for:
    • Priority level (0-100 scale)
    • Category (Work, Personal, etc.)
    • Tags (relevant keywords)
    • Enhanced description (detailed task breakdown)
  4. Save Task: Click "Create Task" to save with AI enhancements

📊 API Documentation

Tasks Endpoints

  • GET /api/tasks/ - List all tasks
  • POST /api/tasks/ - Create new task
  • GET /api/tasks/{id}/ - Get specific task
  • PUT /api/tasks/{id}/ - Update task
  • DELETE /api/tasks/{id}/ - Delete task
  • GET /api/tasks/overdue/ - Get overdue tasks
  • GET /api/tasks/stats/ - Get task statistics

Context Endpoints

  • GET /api/contexts/ - List context entries
  • POST /api/contexts/ - Create context entry
  • POST /api/contexts/bulk_create/ - Create multiple entries

AI Endpoints

  • POST /api/ai/suggestions/ - Get AI task suggestions
  • POST /api/ai/analyze-context/ - Analyze context entries
  • POST /api/ai/enhance-task/{id}/ - Enhance existing task
  • GET /api/ai/health/ - Check AI service health

🧪 Sample Data

Sample Tasks

{
  "title": "Prepare quarterly presentation",
  "description": "Create slides for Q4 business review meeting",
  "priority": 75,
  "deadline": "2024-01-15T14:00:00Z",
  "category": "Work",
  "tags": ["presentation", "quarterly", "urgent"]
}

Sample Context Entries

{
  "content": "Meeting with client tomorrow at 2 PM to discuss project requirements",
  "source": "email"
}

AI Suggestion Response

{
  "suggestions": {
    "priority": 85,
    "deadline": "2024-01-20T17:00:00Z",
    "category": "Work",
    "tags": ["client", "meeting", "requirements"],
    "enhanced_description": "Prepare for client meeting by reviewing project scope, preparing questions about requirements, and gathering relevant documentation."
  }
}

🔧 Configuration

Environment Variables

Backend (.env)

SECRET_KEY=your-django-secret-key
DEBUG=True
DB_NAME=smart_todo
DB_USER=postgres
DB_PASSWORD=your-password
DB_HOST=localhost
DB_PORT=5432
OPENAI_API_KEY=your-openai-key
LOCAL_LLM_URL=http://127.0.0.1:1234/v1/chat/completions

Frontend (.env.local)

NEXT_PUBLIC_API_URL=http://localhost:8000/api

🚀 Deployment

Current Deployment Status

  • ✅ Backend: Running on OpenHands runtime (port 12000)
  • ✅ Frontend: Running on OpenHands runtime (port 12001)
  • ✅ Database: PostgreSQL hosted on Supabase
  • ✅ AI Service: OpenAI API integration active

Production Deployment

Backend Deployment (Railway/Heroku/Render)

  1. Set environment variables in your hosting platform
  2. Configure PostgreSQL database connection
  3. Run migrations: python manage.py migrate
  4. Collect static files: python manage.py collectstatic
  5. Configure CORS for your frontend domain

Frontend Deployment (Vercel/Netlify)

  1. Set NEXT_PUBLIC_API_URL to your backend URL
  2. Build: npm run build
  3. Deploy build files
  4. Configure environment variables

🔧 Troubleshooting

Common Issues

Backend Not Starting

# Check if port is in use
lsof -i :12000

# Check backend logs
tail -f /workspace/comata9462-project/backend/backend.log

# Restart backend
cd /workspace/comata9462-project/backend
python manage.py runserver 0.0.0.0:12000

Frontend Not Loading

# Check frontend logs
tail -f /workspace/comata9462-project/frontend/frontend.log

# Verify environment configuration
cat /workspace/comata9462-project/frontend/.env.local

# Restart frontend
cd /workspace/comata9462-project/frontend
npm run dev -- --port 12001 --hostname 0.0.0.0

API Connection Issues

# Test backend API
curl -s https://work-1-zxnbvxythqwtjtxu.prod-runtime.all-hands.dev/api/

# Check CORS configuration
grep -r "CORS" /workspace/comata9462-project/backend/

Database Connection Issues

# Test database connection
cd /workspace/comata9462-project/backend
python manage.py dbshell

# Check migrations
python manage.py showmigrations

Environment Variables

Ensure these are properly configured:

Backend (.env)

DEBUG=True
SECRET_KEY=django-insecure-1234567890
ALLOWED_HOSTS=*
CORS_ALLOW_ALL_ORIGINS=True
DB_NAME=postgres
DB_USER=postgres.richcxbjrggbdsbeylzx
DB_PASSWORD=thevectorguy123@
DB_HOST=aws-0-ap-south-1.pooler.supabase.com
DB_PORT=6543
OPENAI_API_KEY=sk-proj-...

Frontend (.env.local)

NEXT_PUBLIC_BACKEND_URL=https://work-1-zxnbvxythqwtjtxu.prod-runtime.all-hands.dev
NEXT_PUBLIC_API_URL=https://work-1-zxnbvxythqwtjtxu.prod-runtime.all-hands.dev/api

🤝 Contributing

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

📝 License

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

🙏 Acknowledgments

  • OpenAI for GPT API
  • LM Studio for local LLM hosting
  • Supabase for database hosting
  • Tailwind CSS for styling
  • Next.js and Django communities

📞 Support

For questions or support, please contact: devgods99@gmail.com

Built with ❤️ for the Full Stack Developer Assignment

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