Universal AI Art Station: Intel XPU • NVIDIA CUDA • AMD ROCm 🎨

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ArtTic-LAB is a hardware-agnostic, node-based generative AI platform built from the ground up for performance and aesthetics.

While originally forged for Intel® Arc™ GPUs, this iteration leverages Native PyTorch implementations to support NVIDIA (CUDA) and AMD (ROCm) with equal proficiency. It moves away from legacy wrappers (like IPEX) in favor of modern, upstream native support and the SDNQ quantization engine for superior memory efficiency.

Whether you are a developer scripting via the CLI or an artist using the infinite node canvas, ArtTic-LAB removes the friction between idea and image.

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🧭 The Interface

ArtTic-LAB features a responsive, glassmorphic Node-Based UI. Unlike rigid tabbed interfaces, the infinite canvas allows you to arrange your workspace exactly how you want it.

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🔬 Technical Deep Dive

We’ve packed ArtTic-LAB with features designed to maximize performance on consumer hardware.

Feature Group	Description
Universal Core ⚙️	Native XPU/CUDA/ROCm: Auto-detects hardware and utilizes native torch.xpu, torch.cuda, or torch.hip. No heavy external compilation required. PyTorch 2.9+ Ready: Built on the latest nightly builds for maximum stability and speed.
Memory Magic 💧	SDNQ Integration: Built-in support for sdnq quantization. Run massive models like FLUX.1 on cards with limited VRAM (8GB/12GB) without crashing. Smart VRAM Management: Proactive resolution limiting based on available VRAM and reactive OOM handling that auto-clears cache.
Pipeline Mastery 🧠	Auto-Architecture Detection: Simply load a .safetensors file. The core logic analyzes layer keys to automatically distinguish between SD1.5, SD2.1, SDXL, SD3, and FLUX. Hybrid Loading: Automatically fetches required encoder components from HuggingFace while using your local checkpoint weights.
Modern UI/UX ✨	Async Backend: Built on FastAPI and Uvicorn with a WebSocket layer. The UI never freezes during generation. Node Canvas: Draggable, scalable interface nodes for Prompts, Models, Parameters, and Previews. Integrated Gallery: Seamlessly browse, zoom, and manage your creations with embedded metadata reading.

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📸 Creations Gallery

All demo images generated locally using ArtTic-LAB.

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🚀 Installation & Usage

1️⃣ Prerequisites

• Miniconda or Miniforge (Python 3.10+ recommended).
• Git installed and available in PATH.

2️⃣ Quick Install

Clone the repository and run the installer script. It will create a Conda environment named ArtTic-LAB and auto-detect your GPU vendor to install the correct PyTorch version.

Windows:

install.bat

Linux / macOS:

chmod +x install.sh
./install.sh

3️⃣ Launch

Start the server and open the Web UI.

Windows:

start.bat

Linux / macOS:

./start.sh

Note: Access the UI at http://127.0.0.1:7860. To expose a public link via Ngrok, launch with python app.py --share.

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📂 Project Structure

└── 📁ArtTic-LAB
    └── 📁assets
        └── 📁demos
            ├── 1.png ... 10.png
        ├── ArtTic-LAB-CLI.png
        ├── ArtTic-LAB-GUI-Dark.png
        ├── ArtTic-LAB-GUI-Light.png
        ├── Banner.png
        ├── logo.png
    └── 📁core
        ├── __init__.py
        ├── logic.py              # Main business logic & state management
        ├── metadata_handler.py   # PNG Info reader/writer
        ├── prompt_book.py        # TOML prompt management
    └── 📁helpers
        ├── __init__.py
        ├── cli_manager.py        # Logging & System Info
    └── 📁loras
        ├── LORAS.md              # Place .safetensors LoRAs here
    └── 📁models
        ├── CyberRealisticXL.safetensors
        ├── MODELS.md             # Place Checkpoints here
    └── 📁outputs                 # Generated images saved here
    └── 📁pipelines               # Abstracted Diffusion Pipelines
        ├── __init__.py           # Pipeline selector logic
        ├── base_pipeline.py
        ├── flux_pipeline.py
        ├── sd15_pipeline.py
        ├── sd2_pipeline.py
        ├── sd3_pipeline.py
        ├── sdxl_pipeline.py
    └── 📁tests
        ├── init.py
        ├── run_tests.py
        ├── test_core.py
        ├── test_env.py
    └── 📁web
        └── 📁assets
            ├── logo.png
            └── 📁fonts
                ├── Poppins.ttf
                ├── Silkscreen.ttf
            └── 📁icons
                ├── material-symbols-outlined.woff2
                ├── material-symbols-rounded.woff2
                ├── material-symbols-sharp.woff2
        ├── __init__.py
        ├── index.html            # Main Entry Point
        ├── script.js             # Frontend Logic (WebSocket)
        ├── server.py             # FastAPI Server
        ├── style.css             # Glassmorphic Styles
    ├── .gitignore
    ├── .prettierrc
    ├── app.py                    # Launcher Script
    ├── ARC-GPU.sh                # Intel Arc Diagnostics
    ├── How_It_Works.md           # Technical Documentation
    ├── install.bat
    ├── install.ps1
    ├── install.sh
    ├── LICENSE
    ├── prompts.toml              # Prompt Database
    ├── README.md
    ├── requirements.txt
    ├── start.bat
    ├── start.ps1
    ├── start.sh
    └── test.sh

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🤝 License

Distributed under the MIT License. See LICENSE for more information.