---

AI RUNNER

v3.0.0.dev5

AI Runner can be compiled with pyinstaller however the current version is not yet stable (check the releases for stable versions).

Version 3.0 is a major upgrade which aims to move the application out of prototype stage and into a more stable and user-friendly state.

It comes with a new UI, new features, and a more robust codebase, security updates, and a more streamlined installation process and much more.

We plan to release future distributions via Snap on Linux.

See Privacy and Security for more information.

---

Stable Diffusion on your own hardware

---

⭐ Features

AI Runner is a multi-modal AI interface which allows you to run open-source large language models and AI image generators on your own hardware.

Feature	Description
🗣️ LLMs and communication
✅ Voice-based chatbot conversations	Have conversations with a chatbot using your voice
✅ Text-to-speech	Convert text to spoken audio
✅ Speech-to-text	Convert spoken audio to text
✅ Vision-to-text	Extract text from images
✅ Text generation with LLMs	Generate text using large language models
✅ RAG on local documents and websites	Interact with your local documents using an LLM
🎨 Image Generation
✅ Stable Diffusion (all versions)	Generate images using Stable Diffusion
🔜 Kandinsky	Generate images using Kandinsky
✅ Near Real-Time Drawing	Draw and generate images in near real-time
✅ Text to Image (aka TextToImage / Txt2Img)	Generate images from textual descriptions
✅ Image to Image (aka ImageToImage / Image2Image)	Generate images based on input images
🖼️ Image Manipulation
✅ Inpaint and Outpaint	Modify parts of an image while maintaining context
✅ Pix2Pix	Transform images from one domain to another
✅ Depth to Image (aka DepthToImage / Depth2Img)	Generate images from depth maps
✅ Controlnet	Control image generation with additional input
✅ LoRA	Efficiently fine-tune models with LoRA
✅ Textual Embeddings	Use textual embeddings for image generation control
🔜 Upscale with GFPGAN	Use textual embeddings for image generation control
🔧 Utility
✅ Run offline, locally	Run on your own hardware without internet
✅ Fast generation	Generate images in ~2 seconds (RTX 2080s)
✅ Run multiple models at once	Utilize multiple models simultaneously
✅ Drawing tools	Built-in tools for drawing and image manipulation
✅ Image filters	Apply various filters to images
✅ Dark mode	Comfortable viewing experience in low-light environments
✅ Infinite scrolling canvas	Seamlessly scroll through generated images
✅ NSFW filter toggle	Help control the visibility of NSFW content
✅ NSFW guardrails	Help prevent generation of harmful content
✅ Standard Stable Diffusion settings	Easily adjust standard Stable Diffusion parameters
✅ Fast load time, responsive interface	Enjoy a smooth and responsive user experience
✅ Pure python	No reliance on a webserver, pure python implementation

---

💻 System Requirements

Minimum system requirements

• Cuda capable GPU
• 6gb of RAM
• 6gb of disc space to install AI Runner

Recommended system specs

• RTX 2080s or higher
• 32gb of RAM
• 100gb disc space

---

🔧 Installation

Linux

1. Open your file explorer and navigate to the directory containing the install.sh script
2. Open the terminal using the keyboard shortcut Ctrl + Alt + T
3. Drag the install.sh script into the terminal and press Enter
4. Follow the on-screen instructions

---

🚀 Running AI Runner

Linux

1. Open the terminal using the keyboard shortcut Ctrl + Alt + T
2. Navigate to the directory containing the run.sh script (cd ~/airunner for example)
3. Run the bin/run.sh script by typing ./bin/run.sh and pressing Enter
4. AI Runner will start and you can begin using it after following the on-screen setup instructions

---

✏️ Using AI Runner

Instructions on how to use AI Runner can be found in the wiki

---

💾 Compiling AI Runner

Clone this repository

git clone https://github.com/Capsize-Games/airunner.git
cd airunner

Build from source

pip install -e .
pip install pyinstaller
bash build.dev.sh

🔬 Unit tests

Run a specific test

python -m unittest src/airunner/tests/test_draggable_pixmap.py

Test coverage is currently low, but the existing tests can be run using the following command:

python -m unittest discover tests

Test coverage

Run tests with coverage tracking:

coverage run --source=src/airunner --omit=__init__.py,*/GFPGAN/*,*/data/*,*/tests/*,*_ui.py,*/enums.py,*/settings.py -m unittest discover src/airunner/tests

To see a report in the terminal, use:

coverage report

For a more detailed HTML report, run:

coverage html

View results in htmlcov/index.html.

---

Privacy and Security

Although AI Runner v3.0 is built with Huggingface libraries, we have taken care to strip the application of any telemetry or tracking features.

The main application itself is unable to access the internet, and we are working towards properly sandboxing certain features to ensure user privacy and security.

As this application evolves we will migrate away from the Huggingface libraries.

Internet access

The core application is incapable of accessing the internet. However there are two features which require internet access. These two features are the setup wizard and the model manager.

Each of these tools are isolated in their own application windows which are capable of directly accessing and downloading files on Huggingface.co and civitai.com (depending on the given URL). Any other URL will be blocked.

The Huggingface Hub library is not used to access these downloads.

For more information see the Darklock and Facehuggershield libraries.

---

Disc access

Write access for the transformers library has been disabled, preventing it from creating a huggingface cache directory at runtime.

The application itself may still access the disc for reading and writing, however we have restricted reads and writes to the user provided airunner directory (by default this is located at ~/.airunner).

All other attempts to access the disc are blocked and logged for your review.

For more information see src/security/restrict_os_access.py.

---

Huggingface Hub

The Huggingface Hub is installed so that Transformers, Diffusers and other Huggingface libraries will continue to function as expected, however it has been neutered to prevent it from accessing the internet.

The security measures taken for this library are as follows

• Prevented from accessing the internet
• Prevented from accessing the disc
• All environment variables set for maximum security
• All telemetry disabled

See Facehuggershield for more information.

---

Planned security measures for Huggingface Libraries

We plant o remove the Huggingface libraries from the application in the future. Although the architecture is currently dependent on these libraries, we will migrate to a better solution in the future.