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docs: overhaul Docker documentation, add to main README
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Eugene Brodsky
@ -1,41 +1,75 @@
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# InvokeAI Containerized
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# Invoke in Docker
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All commands should be run within the `docker` directory: `cd docker`
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- Ensure that Docker can use the GPU on your system
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- This documentation assumes Linux, but should work similarly under Windows with WSL2
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- We don't recommend running Invoke in Docker on macOS at this time. It works, but very slowly.
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## Quickstart :rocket:
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## Quickstart :lightning:
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On a known working Linux+Docker+CUDA (Nvidia) system, execute `./run.sh` in this directory. It will take a few minutes - depending on your internet speed - to install the core models. Once the application starts up, open `http://localhost:9090` in your browser to Invoke!
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No `docker compose`, no persistence, just a simple one-liner using the official images:
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For more configuration options (using an AMD GPU, custom root directory location, etc): read on.
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**CUDA:**
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## Detailed setup
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```bash
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docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
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```
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**ROCm:**
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```bash
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docker run --device /dev/kfd --device /dev/dri --publish 9090:9090 ghcr.io/invoke-ai/invokeai:main-rocm
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```
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Open `http://localhost:9090` in your browser once the container finishes booting, install some models, and generate away!
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> [!TIP]
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> To persist your data (including downloaded models) outside of the container, add a `--volume/-v` flag to the above command, e.g.: `docker run --volume /some/local/path:/invokeai <...the rest of the command>`
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## Customize the container
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We ship the `run.sh` script, which is a convenient wrapper around `docker compose` for cases where custom image build args are needed. Alternatively, the familiar `docker compose` commands work just as well.
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```bash
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cd docker
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cp .env.sample .env
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# edit .env to your liking if you need to; it is well commented.
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./run.sh
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```
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It will take a few minutes to build the image the first time. Once the application starts up, open `http://localhost:9090` in your browser to invoke!
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## Docker setup in detail
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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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- The deprecated `docker-compose` (hyphenated) CLI probably won't work. Update to a recent version.
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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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- [NVIDIA docs](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
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- [AMD docs](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html)
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#### macOS
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> [!TIP]
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> You'll be better off installing Invoke directly on your system, because Docker can not use the GPU on macOS.
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If you are still reading:
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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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This is done via Docker Desktop preferences.
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### Configure Invoke environment
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### Configure the Invoke Environment
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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. 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 the desired location of the InvokeAI runtime directory. It may be an existing directory from a previous installation (post 4.0.0).
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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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The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. Navigate to the Model Manager tab and install some models before generating.
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### Use a GPU
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@ -43,9 +77,9 @@ The runtime directory (holding models and outputs) will be created in the locati
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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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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/NVIDIA/AMD documentation for the most up-to-date instructions for using your GPU with Docker.
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To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file.
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To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file before running `./run.sh`.
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## Customize
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@ -59,10 +93,10 @@ Values are optional, but setting `INVOKEAI_ROOT` is highly recommended. The defa
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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=nvidia
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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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Any environment variables supported by InvokeAI can be set here. See the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
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## Even More Customizing!
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