AI Playground

This example is based on the xpu implementation of Intel Arc A-Series dGPU and Ultra iGPU

Welcome to AI Playground beta open source project and AI PC starter app for doing AI image creation, image stylizing, and chatbot on a PC powered by an Intel® Arc™ GPU. AI Playground leverages libraries from GitHub and Huggingface which may not be available in all countries world-wide.

README.md

• English (readme.md)

Min Specs

AI Playground beta is currently available as a packaged installer, or available as a source code from our Github repository. To run AI Playground you must have a PC that meets the following specifications

• Windows OS
• Intel Core Ultra-H Processor, Intel Core Ultra 200V series processor OR Intel Arc GPU (discrete) with 8GB of vRAM

Installation - Packaged Installer:

AI Playground has multiple packaged installers, each specific to the hardware. These packages make it easier for an end user to install AI Playground and get it running on their PC. Please note while this does make the process much easier, this is open source beta software, where components and version can have conflicts. Check the Troubleshooting section for known issues.

1. Choose the correct installer (for Desktop systems with Intel Arc GPUs,or for Intel Core Ultra-H systems), download to your PC then run the installer.
2. The installer will have two phases. It will first install components and environment from the installer. The second phase will pull in components from their source. This second phase of installation will take several minutes and require a steady internet connection.
3. On first run, the load screen will take up to a minute
4. Download the Users Guide for application information

• AI Playground 1.22b for Intel Core Ultra 200V (LNL) - Release Notes | Download

• AI Playground 1.22b for Intel Core Ultra-H (MTL) - Release Notes | Download

• AI Playground 1.22b for Desktop-dGPU (ACM) - Release Notes | Download

• AI Playground Users Guide

TROUBLESHOOTING INSTALLATION:

1. Be sure your system has an Intel Arc GPU. Go to your Windows Start Menu. Type "Device Manager" Under Display Adapters look at the name of your GPU device. It should describe an an Intel Arc GPU. If it says "Intel(R) Graphics" your system does not have a built-in Intel Arc GPU and does not meet minimum specifications
2. Interrupted Installation: The online installation portion can be interuppted or blocked by an IT network, firewall, or sleep settings. Be sure to be on an open network, with firewall off, and set sleep settings to stay awake when powered on.
3. Some Windows systems may be missing needed libraries. This can be fixed by installing the 64bit VC++ redistribution from Microsoft here https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170
4. There have been reports of an Huggingface version error. This is due to a 3rd party component changing a version. This issue is corrected in our v1.22b mid November release.

Project Development

Checkout Source Code

git clone -b dev https://github.com/intel/AI-Playground.git
cd AI-Playground

Dev Environment Setup (backend, python)

1. Create and switch the conda environment and go to the service directory.

conda create -n aipg_xpu python=3.11 -y
conda activate aipg_xpu
conda install libuv -y

cd service

@REM for Desktop-dGPU (e.g. A770)
pip install -r requirements-arc.txt

@REM for Intel Core Ultra-H (MTL)
pip install -r requirements-ultra.txt

2. Check whether the XPU environment is correct

python -c "import torch; import intel_extension_for_pytorch as ipex; print(torch.__version__); print(ipex.__version__); [print(f'[{i}]: {torch.xpu.get_device_properties(i)}') for i in range(torch.xpu.device_count())];"

Example output:

2.1.0.post3+cxx11.abi
2.1.40+xpu
[0]: _DeviceProperties(name='Intel(R) Arc(TM) Graphics', platform_name='Intel(R) Level-Zero', dev_type='gpu', driver_version='1.3.29283', has_fp64=1, total_memory=14765MB, max_compute_units=112, gpu_eu_count=112)

Linking Dev Environment to Project Environment

1. Switch to the root directory of the project. (AI-Playground)

2. Run the following command to view the path of the conda virtual environment

on windows

conda env list|findstr aipg_xpu

3. Based on the obtained environment path, run the following command to create an env file link on windows

mklink /J "./env" "{aipg_xpu_env_path}"

WebUI (nodejs + electron)

1. Install Nodejs development environment, you can get it from https://nodejs.org/en/download.

2. Switch to the WebUI directory and install all Nodejs dependencies.

npm install

3. In the WebUI directory, run the below command to get started with development

npm run dev

Model Support

AI Playground supports PyTorch LLM, SD1.5, and SDXL models. AI Playground does not ship with any models but does make models available for all features either directly from the interface or indirectly by the users downloading models from HuggingFace.co or CivitAI.com and placing them in the appropriate model folder.

Models currently linked from the application

Model	License	Background Information/Model Card
Dreamshaper 8 Model	license	site
Dreamshaper 8 Inpainting Model	license	site
JuggernautXL v9 Model	license	site
Phi3-mini-4k-instruct	license	site
bge-large-en-v1.5	license	site
Latent Consistency Model (LCM) LoRA: SD1.5	license	site
Latent Consistency Model (LCM) LoRA:SDXL	license	site

Be sure to check license terms for any model used in AI Playground especially taking note of any restrictions.

Use Alternative Models

Check the User Guide for details or watch this video on how to add alternative Stable Diffusion models to AI Playground

Notices and Disclaimers:

For information on AI Playground terms, license and disclaimers, visit the project and files on GitHub repo:
License | Notices & Disclaimers

The software may include third party components with separate legal notices or governed by other agreements, as may be described in the Third Party Notices file accompanying the software.