mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
79 lines
3.1 KiB
Markdown
79 lines
3.1 KiB
Markdown
# InvokeAI Containerized
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All commands are to be run from the `docker` directory: `cd docker`
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#### Linux
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1. Ensure builkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
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2. Install the `docker compose` plugin using your package manager, or follow a [tutorial](https://docs.docker.com/compose/install/linux/#install-using-the-repository).
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- The deprecated `docker-compose` (hyphenated) CLI continues to work for now.
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3. Ensure docker daemon is able to access the GPU.
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- You may need to install [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
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#### macOS
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1. Ensure Docker has at least 16GB RAM
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2. Enable VirtioFS for file sharing
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3. Enable `docker compose` V2 support
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This is done via Docker Desktop preferences
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## Quickstart
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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:
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a. the desired location of the InvokeAI runtime directory, or
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b. an existing, v3.0.0 compatible runtime directory.
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1. Execute `run.sh`
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The image will be built automatically if needed.
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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.
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### Use a GPU
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- Linux is *recommended* for GPU support in Docker.
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- WSL2 is *required* for Windows.
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- only `x86_64` architecture is supported.
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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.
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## Customize
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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.
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You can also set these values in `docker-compose.yml` directly, but `.env` will help avoid conflicts when code is updated.
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Example (values are optional, but setting `INVOKEAI_ROOT` is highly recommended):
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```bash
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INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
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HUGGINGFACE_TOKEN=the_actual_token
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CONTAINER_UID=1000
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GPU_DRIVER=cuda
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```
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Any environment variables supported by InvokeAI can be set here - please see the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
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## Even Moar Customizing!
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See the `docker-compose.yml` file. The `command` instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
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### Reconfigure the runtime directory
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Can be used to download additional models from the supported model list
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In conjunction with `INVOKEAI_ROOT` can be also used to initialize a runtime directory
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```yaml
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command:
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- invokeai-configure
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- --yes
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```
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Or install models:
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```yaml
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command:
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- invokeai-model-install
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```
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