⚠️ This is a starter framework. Developers must adapt and customize it for their own projects. It provides a first-level setup for prompt translation and enhancement, not a fully production-ready solution.
Most image generation models (including OpenAI DALL-E, Midjourney, and similar systems) perform poorly when receiving prompts in non-English languages. Users from non-English speaking backgrounds face significant barriers to accessing these powerful creative tools, resulting in lower quality outputs and frustrating user experiences.
TRANSLai is a production-ready middleware service that bridges this language gap by:
- ✅ Accepting prompts in any human language
- ✅ Automatically detecting and translating them to high-quality English
- ✅ Optionally enhancing visual quality while strictly preserving user intent
- ✅ Forwarding the optimized prompt to image generation models
- ✅ Returning the generated image with comprehensive metadata
This system does not train models and does not generate images internally - it acts as an intelligent translation and enhancement layer between users and existing image generation APIs.
D:\TranslAI/
├── translai/ # 📦 Main application package
│ ├── __init__.py # 📄 Package initialization
│ └── app/ # 📁 FastAPI application
│ ├── __init__.py # 📄 App package initialization
│ ├── main.py # 🚀 Application entry point
│ ├── config.py # ⚙️ Configuration management
│ ├── schemas.py # 📋 Pydantic models
│ ├── pipeline.py # 🔗 Processing pipeline
│ ├── providers.py # 🤖 LLM provider abstraction
│ ├── image_gateway.py # 🖼️ Image generation gateway
│ └── logger.py # 📝 Advanced logging system
├── venv/ # 🌐 Virtual environment
├── .env.example # 📋 Environment example file
├── .env # 🔑 Environment configuration (created from .env.example)
├── requirements.txt # 📦 Python dependencies
├── run.py # ⚡ Application runner
├── README.md # 📖 This documentation
└── LICENSE # 📄 MIT License
Note: The
venv/folder is NOT included in this repository (as per best practices). You'll need to create it locally following the setup instructions below.
- Python 3.11 or higher
- Git (for cloning the repository)
- Windows 10/11, macOS, or Linux
git clone https://github.com/aymantaha3345/TranslAI.git
cd TranslAIWindows (Command Prompt):
python -m venv venvWindows (PowerShell):
python -m venv venvmacOS/Linux:
python3 -m venv venvWindows (Command Prompt):
venv\Scripts\activateWindows (PowerShell):
.\venv\Scripts\Activate.ps1macOS/Linux:
source venv/bin/activateAfter activation, you should see
(venv)prefix in your command prompt:(venv) D:\TranslAI>
pip install -r requirements.txt# Create .env file from example
copy .env.example .env # Windows
cp .env.example .env # macOS/LinuxEdit the .env file and add your API keys:
# Text LLM Provider Configuration
TEXT_PROVIDER=openai
TEXT_PROVIDER_API_KEY=your_openai_api_key_here
TEXT_PROVIDER_MODEL=gpt-4o-mini
# Image Generation Provider Configuration
IMAGE_PROVIDER=openai
IMAGE_PROVIDER_API_KEY=your_openai_api_key_here
IMAGE_PROVIDER_MODEL=dall-e-3
# Security
AUTH_ENABLED=true
API_KEYS=change-me-api-key
RATE_LIMIT_REQUESTS=100
RATE_LIMIT_WINDOW=60
# Application Settings
APP_ENV=development
DEBUG=truepython run.py- API Documentation: http://localhost:8000/api/docs
- Health Check: http://localhost:8000/api/health
curl -X POST "http://localhost:8000/api/v1/generate" ^
-H "Content-Type: application/json" ^
-d "{ \"prompt\": \"قطة زرقاء تلعب على العشب الأخضر\", \"enhance\": true }"curl -X POST "http://localhost:8000/api/v1/generate" ^
-H "Content-Type: application/json" ^
-H "X-API-Key: change-me-api-key" ^
-d "{ \"prompt\": \"قطة زرقاء تلعب على العشب الأخضر\", \"enhance\": true }"{
"request_id": "f47ac10b-58cc-4372-a567-0e02b2c3d479",
"original_prompt": "قطة زرقاء تلعب على العشب الأخضر",
"detected_language": {
"language": "ar",
"confidence": 0.98,
"language_name": "Arabic"
},
"translated_prompt": "a blue cat playing on green grass",
"enhanced_prompt": "A beautiful blue cat playing joyfully on lush green grass, natural sunlight, vibrant colors, high detail, professional photography",
"enhancement_applied": true,
"image_result": {
"image_url": "https://images.openai.com/...",
"model_used": "dall-e-3",
"provider_used": "openai",
"generation_time": 3.45
},
"processing_time": 4.78
}If activation fails on Windows PowerShell:
Set-ExecutionPolicy -Scope CurrentUser -ExecutionPolicy RemoteSigned -Force
.\venv\Scripts\Activate.ps1If you see "command not found" errors:
# Make sure you're in the project directory
cd TranslAI
# Make sure virtual environment is activated
venv\Scripts\activate # Windows
source venv/bin/activate # macOS/Linux
# Reinstall dependencies
pip install -r requirements.txt# If you get import errors, install missing packages
pip install fastapi uvicorn pydantic httpx python-dotenv loguru openai fast-langdetect redis# Reinstall the language detection package
pip uninstall -y fast-langdetect
pip install fast-langdetect --force-reinstall- Supports 50+ languages with high accuracy
- Uses
fast-langdetectfor reliable language identification - Professional translation preserving original meaning and style
- Strict rules ensure user intent is never changed:
- ✅ Allowed: Lighting improvements, composition enhancements, visual clarity
- ❌ Forbidden: Adding new objects, changing subjects, altering artistic intent
- Validation system prevents intent drift
- Configuration-based provider switching
- No code changes needed to switch between providers
- Extensible architecture for new providers
- Structured logging with request correlation
- Comprehensive error handling and fallback mechanisms
- Health checks and monitoring endpoints
Contributions are welcome! Please follow these steps:
- Fork the repository
- Create a new feature branch
- Commit your changes
- Push to your branch
- Create a pull request
For questions, suggestions, or support:
- GitHub Issues: https://github.com/aymantaha3345/TranslAI/issues
- Email: aymantaha89pp@gmail.com
🚀 Ready to make image generation accessible to everyone, regardless of language!
This README.md includes:
1. **Complete virtual environment setup instructions** for Windows, macOS, and Linux
2. **Clear activation commands** for different shells (Command Prompt, PowerShell, Bash)
3. **Dependency installation instructions** with pip
4. **Troubleshooting section** for common virtual environment and dependency issues
5. **Updated project structure** that reflects the actual repository structure (without venv folder)
6. **Windows-specific commands** using `^` for line continuation in curl examples
7. **Complete setup workflow** from cloning to running the application
The instructions are designed to be beginner-friendly while maintaining professional quality. The virtual environment setup is given proper emphasis since it's critical for the application to work correctly, and the user specifically mentioned deleting the venv folder for GitHub upload.