AI-powered iOS app icon generation with localization support, using OpenAI's DALL-E and GPT-Image models via ai_proxy_core.

Modular, composable architecture following Single Responsibility Principle:

src/
├── icon_generator.py         # Main orchestrator
├── ai_generator.py           # AI image generation (DALL-E, GPT-Image)
├── image_processor.py        # iOS icon processing (12 sizes + Contents.json)
├── prompt_builder.py         # Cultural prompt construction (25+ locales)
└── ios_localization_reader.py # iOS project file reader (.strings files)

• 🎨 AI Models: DALL-E 3, DALL-E 2, GPT-Image-1
• 🌍 Localization: Reads InfoPlist.strings and Localizable.strings
• 🎯 Cultural Context: Design aesthetics for 25+ locales
• 📱 iOS Ready: Generates all 12 required sizes + Contents.json
• 🔧 Composable: Use modules independently or together
• 🚀 Batch Generation: Generate icons for all locales at once

pip install -r requirements.txt

Requirements:

• Python 3.8+
• OpenAI API key
• ai_proxy_core 0.4.3

from src import IconGenerator

generator = IconGenerator()
generator.generate_icon(
    app_name="MyApp",
    colors=('#FF6B6B', '#4ECDC4'),
    output_dir=Path('./output'),
    model='dalle-3'
)

Automatically reads localization files and generates culturally appropriate icons:

from src import IconGenerator
from pathlib import Path

generator = IconGenerator()
generator.generate_from_ios_project(
    ios_project_path=Path('/path/to/iOS/app'),
    output_dir=Path('./output'),
    model='dalle-3'
)

Each module can be used independently:

from src import (
    AIIconGenerator,
    IOSIconProcessor, 
    PromptBuilder,
    IOSLocalizationReader
)

# Read iOS localization
reader = IOSLocalizationReader()
context = reader.get_app_context_from_project(ios_path, 'en')

# Build culturally-aware prompt
builder = PromptBuilder()
prompt = builder.build_prompt(
    app_name="MyApp",
    locale='ja',
    cultural_style='Japanese minimalist design'
)

# Generate AI image
ai_gen = AIIconGenerator()
image = ai_gen.generate(prompt, model='dalle-3')

# Process for iOS
processor = IOSIconProcessor()
processor.save_ios_iconset(image, output_dir)

The generator includes cultural design context for:

• 🇺🇸 English (en)
• 🇯🇵 Japanese (ja)
• 🇨🇳 Chinese Simplified (zh-Hans)
• 🇹🇼 Chinese Traditional (zh-Hant)
• 🇰🇷 Korean (ko)
• 🇪🇸 Spanish (es)
• 🇲🇽 Spanish Mexico (es-MX)
• 🇫🇷 French (fr)
• 🇩🇪 German (de)
• 🇮🇹 Italian (it)
• 🇵🇹 Portuguese (pt-BR)
• 🇷🇺 Russian (ru)
• 🇸🇦 Arabic (ar)
• 🇮🇳 Hindi (hi)
• 🇹🇭 Thai (th)
• 🇻🇳 Vietnamese (vi)
• 🇮🇩 Indonesian (id)
• 🇹🇷 Turkish (tr)
• 🇳🇱 Dutch (nl)
• 🇵🇱 Polish (pl)
• 🇸🇪 Swedish (sv)
• 🇳🇴 Norwegian (no)
• 🇩🇰 Danish (da)
• 🇫🇮 Finnish (fi)
• 🇬🇷 Greek (el)
• 🇮🇱 Hebrew (he)

• 20pt: @2x (40×40), @3x (60×60)
• 29pt: @2x (58×58), @3x (87×87)
• 40pt: @2x (80×80), @3x (120×120)
• 60pt: @2x (120×120), @3x (180×180)
• 76pt: @1x (76×76), @2x (152×152)
• 83.5pt: @2x (167×167)
• 1024pt: @1x (1024×1024) - App Store

Set your OpenAI API key:

export OPENAI_API_KEY='your-api-key'
# or create .env file
echo "OPENAI_API_KEY=your-api-key" > .env

from src import IconGenerator

generator = IconGenerator()

locales = ['en', 'ja', 'zh-Hans', 'es-MX']
for locale in locales:
    generator.generate_icon(
        app_name="SleepCycles",
        locale=locale,
        output_dir=Path(f'./icons/{locale}')
    )

generator.generate_icon(
    app_name="MyApp",
    colors=('#1E3A8A', '#60A5FA'),
    style='minimalist',
    icon_elements=['moon', 'stars', 'clouds'],
    app_description='Sleep tracking app',
    target_audience='Health-conscious individuals',
    cultural_style='Silicon Valley tech aesthetic'
)

# Test with English locale
python test_en_locale.py

# Test replacing actual app icons
python test_replace_actual.py

ios-icon-generator/
├── src/                    # Core modules
│   ├── __init__.py
│   ├── icon_generator.py
│   ├── ai_generator.py
│   ├── image_processor.py
│   ├── prompt_builder.py
│   └── ios_localization_reader.py
├── legacy/                 # Previous monolithic version
├── example_batch.py        # Batch generation example
├── test_*.py              # Test scripts
├── requirements.txt
├── README.md
└── .gitignore

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

MIT

Built with ai_proxy_core for OpenAI API integration.