67ed4a0245
CONTAINER_UID is used for the user ID within the container, however I noticed the UID was hard coded to 1000 in the Dockerfile chown -R command. This leaves the default as 1000, but allows it to be overrriden by setting CONTAINER_UID. |
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.. | ||
.env.sample | ||
build.sh | ||
docker-compose.yml | ||
docker-entrypoint.sh | ||
Dockerfile | ||
README.md | ||
run.sh | ||
runpod-readme.md |
InvokeAI Containerized
All commands are to be run from the docker
directory: cd docker
Linux
- Ensure builkit is enabled in the Docker daemon settings (
/etc/docker/daemon.json
) - Install the
docker compose
plugin using your package manager, or follow a tutorial.- The deprecated
docker-compose
(hyphenated) CLI continues to work for now.
- The deprecated
- Ensure docker daemon is able to access the GPU.
- You may need to install nvidia-container-toolkit
macOS
- Ensure Docker has at least 16GB RAM
- Enable VirtioFS for file sharing
- Enable
docker compose
V2 support
This is done via Docker Desktop preferences
Quickstart
- Make a copy of
env.sample
and name it.env
(cp env.sample .env
(Mac/Linux) orcopy example.env .env
(Windows)). Make changes as necessary. SetINVOKEAI_ROOT
to an absolute path to: a. the desired location of the InvokeAI runtime directory, or b. an existing, v3.0.0 compatible runtime directory. docker compose up
The image will be built automatically if needed.
The runtime directory (holding models and outputs) will be created in the location specified by INVOKEAI_ROOT
. The default location is ~/invokeai
. The runtime directory will be populated with the base configs and models necessary to start generating.
Use a GPU
- Linux is recommended for GPU support in Docker.
- WSL2 is required for Windows.
- only
x86_64
architecture is supported.
The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing nvidia-docker-runtime
and configuring the nvidia
runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
Customize
Check the .env.sample
file. It contains some environment variables for running in Docker. Copy it, name it .env
, and fill it in with your own values. Next time you run docker compose up
, your custom values will be used.
You can also set these values in docker-compose.yml
directly, but .env
will help avoid conflicts when code is updated.
Example (values are optional, but setting INVOKEAI_ROOT
is highly recommended):
INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
HUGGINGFACE_TOKEN=the_actual_token
CONTAINER_UID=1000
GPU_DRIVER=cuda
Any environment variables supported by InvokeAI can be set here - please see the Configuration docs for further detail.
Even Moar Customizing!
See the docker-compose.yml
file. The command
instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
Reconfigure the runtime directory
Can be used to download additional models from the supported model list
In conjunction with INVOKEAI_ROOT
can be also used to initialize a runtime directory
command:
- invokeai-configure
- --yes
Or install models:
command:
- invokeai-model-install