Docker image for InvokeAI

Installs

Ubuntu 22.04 LTS
CUDA 12.1
Python 3.11.9
Torch 2.2.2
xformers 0.0.25.post1
Jupyter Lab
code-server
InvokeAI v4.2.7post1
runpodctl
OhMyRunPod
RunPod File Uploader
croc
rclone
Application Manager
CivitAI Downloader

Available on RunPod

This image is designed to work on RunPod. You can use my custom RunPod template to launch it on RunPod.

Building the Docker image

Note

You will need to edit the docker-bake.hcl file and update REGISTRY_USER, and RELEASE. You can obviously edit the other values too, but these are the most important ones.

Important

In order to cache the models, you will need at least 32GB of CPU/system memory (not VRAM) due to the large size of the models. If you have less than 32GB of system memory, you can comment out or remove the code in the Dockerfile that caches the models.

# Clone the repo
git clone https://github.com/ashleykleynhans/invokeai-docker.git

# Log in to Docker Hub
docker login

# Build the image, tag the image, and push the image to Docker Hub
docker buildx bake -f docker-bake.hcl --push

# Same as above but customize registry/user/release:
REGISTRY=ghcr.io REGISTRY_USER=myuser RELEASE=my-release docker buildx \
    bake -f docker-bake.hcl --push

Running Locally

Install Nvidia CUDA Driver

Start the Docker container

docker run -d \
  --gpus all \
  -v /workspace \
  -p 2999:2999 \
  -p 3000:3001 \
  -p 7777:7777 \
  -p 8000:8000 \
  -p 8888:8888 \
  -e JUPYTER_PASSWORD=Jup1t3R! \
  ashleykza/invokeai:latest

You can obviously substitute the image name and tag with your own.

Ports

Connect Port	Internal Port	Description
3000	3001	InvokeAI
7777	7777	Code Server
8000	8000	Application Manager
8888	8888	Jupyter Lab
2999	2999	RunPod File Uploader

Environment Variables

Variable	Description	Default
JUPYTER_LAB_PASSWORD	Set a password for Jupyter lab	not set - no password
DISABLE_AUTOLAUNCH	Disable application from launching automatically	(not set)
DISABLE_SYNC	Disable syncing if using a RunPod network volume	(not set)

Logs

InvokeAI creates a log file, and you can tail it instead of killing the service to view the logs

Application	Log file
InvokeAI	/workspace/logs/invokeai.log

Acknowledgements

A special word of thanks to Madiator2011 for advice and suggestions on improving these images, as well as all of the code for the code-server which was borrowed from his madiator-docker-runpod GitHub repository.

Community and Contributing

Pull requests and issues on GitHub are welcome. Bug fixes and new features are encouraged.

ashleykleynhans/invokeai-docker