A modern Django-based web application for weight management and body transformation visualization. Users can input their body metrics (weight, height, age) and upload photos to receive personalized weight loss plans with AI-generated transformation previews.

Features

Core Functionality

  • Health Assessment Survey: Collect user data including weight, height, age, and photos
  • Personalized Weight Loss Plans:
  • Plan 1: Lose 10-15% of current weight
  • Plan 2: Lose 20% of current weight
  • AI Transformation Preview: Generate AI-powered images showing potential transformation results
  • Blog/Post Management: Simple blog functionality to share health and fitness content
  • Admin Dashboard: Django admin interface for content management
  • Media Upload: Support for photo uploads with organized storage

User Interface

  • Modern, responsive design with custom CSS
  • Beautiful form UI with emoji icons
  • Visual feedback for uploaded photos
  • Transformation preview cards
  • Privacy-focused messaging

Tech Stack

Backend

  • Django 5.2.10: Web framework
  • Python 3.x: Programming language
  • SQLite: Database (default)
  • python-dotenv: Environment variable management

Frontend

  • TailwindCSS 4.1.18: Utility-first CSS framework
  • DaisyUI 5.5.16: TailwindCSS component library
  • PostCSS: CSS processing
  • Custom CSS: Additional styling

Additional Dependencies

  • python-dotenv 1.2.1: Environment variable management from .env files
  • Pillow 10.0+: Python Imaging Library for handling image uploads
  • playwright 1.40+: Browser automation for Poe API interactions
  • fastapi-poe 0.0.40+: Poe API client for AI image generation
  • asgiref 3.11.0: ASGI support
  • django-tailwind 4.4.2: Django-Tailwind integration
  • pytailwindcss 0.3.0: Python Tailwind wrapper
  • sqlparse 0.5.5: SQL parser
  • tzdata 2025.3: Timezone data

Project Structure

djangob/
├── core/                          # Main application
│   ├── migrations/                # Database migrations
│   ├── static/                    # Static files (CSS)
│   │   └── core/css/
│   ├── templates/                 # HTML templates
│   │   └── core/
│   │       ├── base.html
│   │       ├── survey.html
│   │       ├── assessment_result.html
│   │       ├── post_list.html
│   │       └── post_detail.html
│   ├── models.py                  # Database models (Post, Assessment)
│   ├── views.py                   # View functions
│   ├── urls.py                    # URL routing
│   └── admin.py                   # Admin configuration
├── first_apps/                    # Django project settings
│   ├── settings.py                # Main settings
│   ├── urls.py                    # Root URL configuration
│   ├── wsgi.py                    # WSGI configuration
│   └── asgi.py                    # ASGI configuration
├── media/                         # User-uploaded files
│   ├── photos/                    # Original photos
│   └── generated/                 # AI-generated images
├── theme/                         # Tailwind theme app
│   ├── static/                    # Compiled CSS
│   └── templates/
├── node_modules/                  # Node.js dependencies
├── manage.py                      # Django management script
├── poe_login.py                   # Playwright script for Poe authentication
├── poe_generate.py                # Playwright script for AI image generation
├── test_poe.py                    # Test script for Poe API integration
├── requirements.txt               # Python dependencies
├── package.json                   # Node.js dependencies
├── db.sqlite3                     # SQLite database
└── .env                           # Environment variables (not tracked)

Installation

Prerequisites

  • Python 3.8 or higher
  • Node.js and npm (for TailwindCSS)
  • Git

Step 1: Clone the Repository

git clone <repository-url>
cd djangob

Step 2: Set Up Python Environment

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On macOS/Linux:
source venv/bin/activate
# On Windows:
venv\Scripts\activate

# Install Python dependencies
pip install -r requirements.txt

Step 3: Set Up Frontend Dependencies

# Install Node.js dependencies
npm install

Step 4: Install Playwright Browsers (if using AI features)

# Install Playwright browser binaries
playwright install

Step 5: Configure Environment Variables

Create a .env file in the project root:

# Optional: Add your POE API key for AI features
POE_API_KEY=your_api_key_here

Step 6: Initialize the Database

# Run migrations
python manage.py migrate

# Create a superuser for admin access
python manage.py createsuperuser

Step 7: Collect Static Files (Optional for Production)

python manage.py collectstatic

Running the Application

Development Server

# Start the Django development server
python manage.py runserver

The application will be available at http://127.0.0.1:8000/

Available URLs

  • Home/Survey: http://127.0.0.1:8000/ - Main weight management survey
  • Admin Panel: http://127.0.0.1:8000/admin/ - Django admin interface
  • Blog: http://127.0.0.1:8000/blog/ - Blog post listing

Usage

For End Users

  1. Submit Assessment: - Navigate to the homepage - Fill in your weight (kg), height (cm), and age (years) - Upload a recent photo - Click "Calculate My Transformation Plan"

  2. View Results: - See your personalized weight loss plans - View your uploaded photo - Click "Generate AI Transformation" to see potential results

  3. Read Blog Posts: - Visit /blog/ to read health and fitness articles

For Administrators

  1. Access Admin Panel: - Navigate to http://127.0.0.1:8000/admin/ - Log in with your superuser credentials

  2. Manage Content: - Create and edit blog posts - View user assessments - Manage uploaded photos

Database Models

Post

  • title: CharField (max 100 characters)
  • content: TextField
  • created_at: DateTimeField (auto)

Assessment

  • weight: FloatField
  • height: FloatField
  • age: IntegerField
  • photo: ImageField (uploaded to media/photos/)
  • after_plan1: ImageField (AI-generated, optional)
  • after_plan2: ImageField (AI-generated, optional)
  • created_at: DateTimeField (auto)

Development Notes

Security Considerations

  • DEBUG = True is currently enabled - MUST be set to False in production
  • Secret key is exposed in settings.py - MUST be moved to environment variables
  • Update ALLOWED_HOSTS for production deployment
  • Consider using PostgreSQL for production instead of SQLite

AI Image Generation

The project includes Poe API integration for AI-powered image transformation:

Available Scripts: - poe_login.py: First-time authentication script to save login session - poe_generate.py: Automated script to generate images via Poe's Nano-Banana-Pro bot - test_poe.py: Test script for Poe API functionality

Setup: 1. Run poe_login.py once to authenticate and save session 2. Add your POE_API_KEY to the .env file 3. The generate_ai_images function in core/views.py currently uses placeholder logic 4. Integrate the Poe scripts to enable actual AI transformation

TailwindCSS

The project uses TailwindCSS with DaisyUI for styling. To rebuild CSS:

npx tailwindcss -i ./theme/static_src/src/styles.css -o ./theme/static/css/dist/styles.css --watch

Troubleshooting

Common Issues

Issue: ModuleNotFoundError: No module named 'dotenv'

pip install python-dotenv

Issue: ModuleNotFoundError: No module named 'playwright'

pip install playwright
playwright install

Issue: PIL/Pillow not found or Image upload errors

pip install Pillow

Issue: Media files not displaying - Ensure DEBUG = True for development - Check that MEDIA_URL and MEDIA_ROOT are configured correctly - Verify uploaded files exist in the media/ directory

Issue: Database errors

# Reset migrations (warning: deletes all data)
python manage.py migrate --run-syncdb

Future Enhancements

  • [ ] Integrate real AI image generation API
  • [ ] Add user authentication and profiles
  • [ ] Implement progress tracking over time
  • [ ] Add nutrition and exercise recommendations
  • [ ] Export reports as PDF
  • [ ] Multi-language support
  • [ ] Mobile app version

Contributing

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

License

This project is private and proprietary.

Support

For issues, questions, or contributions, please contact the project maintainer.

Note: This is a development version. Do not deploy to production without implementing proper security measures, environment variable management, and production-ready database configuration.