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Wilson E. Alvarez 296060db63 Add cpu and rocm profiles. Let invokeai-nvidia service be the default.
2023-12-13 23:23:43 -05:00
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.env.sample Fix ROCm support in Docker container 2023-11-06 13:47:08 -08:00
docker-compose.yml Add cpu and rocm profiles. Let invokeai-nvidia service be the default. 2023-12-13 23:23:43 -05:00
docker-entrypoint.sh feat(docker): update docker image, etc. to python3.11+ubuntu23.04 2023-10-19 11:26:16 -04:00
Dockerfile Add container GID 2023-12-11 14:30:40 -05:00
README.md Simplify docker compose setup 2023-12-13 23:23:43 -05:00
run.sh Add cpu and rocm profiles. Let invokeai-nvidia service be the default. 2023-12-13 23:23:43 -05:00
runpod-readme.md (docker) add README used by the Runpod template 2023-07-12 16:51:15 -04:00

README.md

InvokeAI Containerized

All commands are to be run from the docker directory: cd docker

Linux

  1. Ensure builkit is enabled in the Docker daemon settings (/etc/docker/daemon.json)
  2. Install the docker compose plugin using your package manager, or follow a tutorial.
    • The deprecated docker-compose (hyphenated) CLI continues to work for now.
  3. Ensure docker daemon is able to access the GPU.

macOS

  1. Ensure Docker has at least 16GB RAM
  2. Enable VirtioFS for file sharing
  3. Enable docker compose V2 support

This is done via Docker Desktop preferences

Quickstart

  1. Make a copy of env.sample and name it .env (cp env.sample .env (Mac/Linux) or copy example.env .env (Windows)). Make changes as necessary. Set INVOKEAI_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.
  2. Execute run.sh

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 run.sh, 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