invokeAI-docs

:fontawesome-brands-docker: Docker

!!! warning “macOS users”

Docker can not access the GPU on macOS, so your generation speeds will be slow. [Install InvokeAI](/invokeAI-docs/installation/INSTALLATION.html) instead.

!!! tip “Linux and Windows Users”

Configure Docker to access your machine's GPU.
Docker Desktop on Windows [includes GPU support](https://www.docker.com/blog/wsl-2-gpu-support-for-docker-desktop-on-nvidia-gpus/).
Linux users should follow the [NVIDIA](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) or [AMD](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html) documentation.

TL;DR

Ensure your Docker setup is able to use your GPU. Then:

```bash
docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
```

Once the container starts up, open http://localhost:9090 in your browser, install some models, and start generating.

Build-It-Yourself

All the docker materials are located inside the docker directory in the Git repo.

```bash
cd docker
cp .env.sample .env
docker compose up
```

We also ship the run.sh convenience script. See the docker/README.md file for detailed instructions on how to customize the docker setup to your needs.

Prerequisites

Install Docker

On the Docker Desktop app, go to Preferences, Resources, Advanced. Increase the CPUs and Memory to avoid this Issue. You may need to increase Swap and Disk image size too.

Setup

Set up your environment variables. In the docker directory, make a copy of .env.sample and name it .env. Make changes as necessary.

Any environment variables supported by InvokeAI can be set here - please see the CONFIGURATION for further detail.

At a minimum, you might want to set the INVOKEAI_ROOT environment variable to point to the location where you wish to store your InvokeAI models, configuration, and outputs.

| Environment-Variable | Default value | Description | | ----------------------------------------------------- | ---------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `INVOKEAI_ROOT` | `~/invokeai` | **Required** - the location of your InvokeAI root directory. It will be created if it does not exist. | `HUGGING_FACE_HUB_TOKEN` | | InvokeAI will work without it, but some of the integrations with HuggingFace (like downloading from models from private repositories) may not work| | `GPU_DRIVER` | `cuda` | Optionally change this to `rocm` to build the image for AMD GPUs. NOTE: Use the `build.sh` script to build the image for this to take effect.

Build the Image

Use the standard docker compose build command from within the docker directory.

If using an AMD GPU: a: set the GPU_DRIVER=rocm environment variable in docker-compose.yml and continue using docker compose build as usual, or b: set GPU_DRIVER=rocm in the .env file and use the build.sh script, provided for convenience

Run the Container

Use the standard docker compose up command, and generally the docker compose CLI as usual.

Once the container starts up (and configures the InvokeAI root directory if this is a new installation), you can access InvokeAI at http://localhost:9090

Troubleshooting / FAQ

• Q: I am running on Windows under WSL2, and am seeing a “no such file or directory” error.
• A: Your docker-entrypoint.sh might have has Windows (CRLF) line endings, depending how you cloned the repository. To solve this, change the line endings in the docker-entrypoint.sh file to LF. You can do this in VSCode (Ctrl+P and search for “line endings”), or by using the dos2unix utility in WSL. Finally, you may delete docker-entrypoint.sh followed by git pull; git checkout docker/docker-entrypoint.sh to reset the file to its most recent version. For more information on this issue, see Docker Desktop documentation

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