https://github.com/amanastel/ai-image-creators
https://github.com/amanastel/ai-image-creators
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/amanastel/ai-image-creators
- Owner: Amanastel
- Created: 2025-04-16T18:32:58.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-04-18T19:12:32.000Z (6 months ago)
- Last Synced: 2025-06-09T08:00:16.542Z (4 months ago)
- Language: Python
- Size: 176 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
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README
# 🎨 AI Creative Pipeline
An advanced AI-powered creative pipeline that transforms text descriptions into stunning images and 3D models, powered by local LLM technology and the Openfabric SDK.
## ✨ Features
- 🤖 **Local LLM Integration**: Uses LLaMA 2 for intelligent prompt expansion
- 🎨 **Text-to-Image Generation**: Creates high-quality images from text descriptions
- 🌟 **Image-to-3D Conversion**: Transforms 2D images into interactive 3D models
- 💾 **Smart Memory System**: Maintains context and history across sessions
- 🔒 **Privacy-Focused**: All processing happens locally
- 🎯 **Multiple Artistic Styles**: Supports realistic, artistic, minimalist, and fantasy styles
- 📊 **Comprehensive Logging**: Detailed execution logs and error tracking
## 🚀 Prerequisites
- Python 3.8 or higher
- Poetry for dependency management
- LLaMA 2 7B Chat model (GGUF format)
- 8GB+ RAM recommended
- NVIDIA GPU (optional, for faster processing)
## 📦 Installation
1. Clone the repository:
```bash
git clone https://github.com/Amanastel/ai-image-creator.git
cd ai-image-creator
```
2. Install dependencies:
```bash
poetry install
```
3. Download the LLaMA 2 7B Chat model:
```bash
mkdir -p models
# Download llama-2-7b-chat.gguf from Hugging Face
# Place it in the models directory
```
4. Create required directories:
```bash
mkdir -p outputs memory
```
## 🛠️ Configuration
1. Environment Setup:
- Copy `.env.example` to `.env`
- Adjust memory settings if needed
- Configure GPU settings (optional)
2. Model Configuration:
- Default model: LLaMA 2 7B Chat
- Supports other GGUF format models
- Configurable inference parameters
## 🖥️ Running the Application
### Method 1: Using Start Script
```bash
./start.sh
```
### Method 2: Using Docker
```bash
docker build -t ai-creative-pipeline .
docker run -p 8888:8888 -v $(pwd)/outputs:/app/outputs -v $(pwd)/memory:/app/memory ai-creative-pipeline
```
Access the application at: http://localhost:8888/swagger-ui/#/App/post_execution
## 📝 Usage Guide
### Basic Usage
1. Access the Swagger UI
2. Navigate to POST /execution endpoint
3. Click "Try it out"
4. Submit a prompt:
```json
{
"prompt": "Make me a glowing dragon standing on a cliff at sunset",
"style": "fantasy",
"dimensions": {
"width": 1024,
"height": 768
},
"quality": 95
}
```
### Advanced Options
- **Styles**:
- `realistic`: Photo-realistic images
- `artistic`: Creative interpretations
- `minimalist`: Clean, simple designs
- `fantasy`: Magical and otherworldly scenes
- **Quality Settings**:
- Resolution: Up to 2048x2048
- Quality: 1-100 scale
- Format: PNG/JPG/JPEG
## 🧠 Memory System
### Short-Term Memory
- Maintains context during interactions
- Enables coherent conversation flow
- Temporary storage in Redis (optional)
### Long-Term Memory
- JSON-based persistent storage
- Searchable history
- Entry format:
```json
{
"timestamp": "2025-04-16T23:33:12.341825",
"original_prompt": "glowing dragon on cliff",
"expanded_prompt": "A majestic dragon...",
"image_path": "outputs/image_20250416_233312.png",
"model_path": "outputs/model_20250416_233312.glb"
}
```
## 📁 Project Structure
```
ai-creative-pipeline/
├── app/
│ ├── core/ # Core application logic
│ ├── models/ # AI models and weights
│ └── utils/ # Utility functions
├── outputs/ # Generated content
│ ├── images/ # 2D image outputs
│ └── models/ # 3D model outputs
├── memory/ # Persistent storage
├── config/ # Configuration files
├── tests/ # Test suite
└── docker/ # Docker configuration
```
## 🐛 Error Handling
- Comprehensive error logging
- Graceful failure recovery
- User-friendly error messages
- Automatic retry mechanism
## 🔒 Security Notes
- Local processing ensures data privacy
- No external API dependencies
- Secure file handling
- Resource usage limits
## 🤝 Contributing
Contributions are welcome! Please read our [Contributing Guide](CONTRIBUTING.md) for details on:
- Code style
- Development process
- Pull request procedure
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 👥 Authors
- **Aman Kumar** - *Initial work* - [Amanastel](https://github.com/Amanastel)
## 🙏 Acknowledgments
- OpenFabric team for the SDK
- LLaMA team for the language model
- Contributors and testers # image-gen-ai
# image-gen-ai
# ai-image-creators