https://github.com/nandhu-44/lumina
🎨 Modern AI art generator with real-time prompt enhancement and progress tracking. Built with Stable Diffusion, FastAPI, and Next.js
https://github.com/nandhu-44/lumina
ai content-filtering image-generation nextjs14 prompt-engineering stable-diffusion websocket
Last synced: 4 months ago
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🎨 Modern AI art generator with real-time prompt enhancement and progress tracking. Built with Stable Diffusion, FastAPI, and Next.js
- Host: GitHub
- URL: https://github.com/nandhu-44/lumina
- Owner: nandhu-44
- Created: 2024-12-25T09:25:21.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-25T09:42:07.000Z (over 1 year ago)
- Last Synced: 2024-12-25T10:26:50.963Z (over 1 year ago)
- Topics: ai, content-filtering, image-generation, nextjs14, prompt-engineering, stable-diffusion, websocket
- Language: JavaScript
- Homepage:
- Size: 256 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
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README
# Lumina - AI Art Generator
> 🎨 A modern AI art generator with real-time prompt enhancement and generation progress tracking. Built with Stable Diffusion, FastAPI, and Next.js. Features GPT-4/Gemini Pro prompt enhancement, WebSocket updates, and content safety validation.
Lumina is an AI-powered image generation system that uses Stable Diffusion with prompt enhancement capabilities.
## Features
- Advanced prompt enhancement using GPT-4 OR Gemini Pro
- Real-time generation progress updates via WebSocket
- Content safety validation for both prompts and generated images
- Customizable generation parameters
- Modern responsive UI with animations
## Prerequisites
- Python 3.10+ _(Python 3.12.0)_
- Node.js 18+ _(v22.12.0)_
- CUDA-compatible GPU (recommended)
- API Keys:
- OpenAI API key
- Google Gemini API key
- Hugging Face token
## Backend Setup
1. Clone the repository:
```bash
git clone https://github.com/nandhu-44/Lumina.git
cd Lumina
```
2. Create and activate a virtual environment:
```bash
python -m venv venv
# Windows
.\venv\Scripts\activate
# Linux/MacOS
source venv/bin/activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Install PyTorch with CUDA support (if you have a compatible GPU) from the [pytorch official website](https://pytorch.org/get-started/locally/)
```bash
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu124
```
5. Create a `.env` file in the root directory:
```env
OPENAI_API_KEY=your_openai_key
GEMINI_API_KEY=your_gemini_key
HF_TOKEN=your_huggingface_token
```
6. Start the backend server:
```bash
uvicorn main:app
```
The server will start at `http://localhost:8000`
## Frontend Setup
For frontend setup instructions, please refer to the [web/README.md](web/README.md) file.
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