https://github.com/ai-dock/invokeai
InvokeAI docker images for use in GPU cloud and local environments. Includes AI-Dock base for authentication and improved user experience.
https://github.com/ai-dock/invokeai
ai docker image-generation invoke-ai invokeai runpod stable-diffusion vast
Last synced: 12 months ago
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InvokeAI docker images for use in GPU cloud and local environments. Includes AI-Dock base for authentication and improved user experience.
- Host: GitHub
- URL: https://github.com/ai-dock/invokeai
- Owner: ai-dock
- License: other
- Created: 2024-04-05T13:54:55.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-11-18T18:10:05.000Z (over 1 year ago)
- Last Synced: 2025-07-03T17:56:10.494Z (12 months ago)
- Topics: ai, docker, image-generation, invoke-ai, invokeai, runpod, stable-diffusion, vast
- Language: Shell
- Homepage:
- Size: 41 KB
- Stars: 13
- Watchers: 2
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE.md
Awesome Lists containing this project
README
[](https://github.com/ai-dock/stable-diffusion-webui/actions/workflows/docker-build.yml)
# AI-Dock + Invoke AI Docker Image
Run [Invoke AI](https://github.com/invoke-ai/InvokeAI) in a docker container locally or in the cloud.
>[!NOTE]
>These images do not bundle models or third-party configurations. You should use a [provisioning script](https://github.com/ai-dock/base-image/wiki/4.0-Running-the-Image#provisioning-script) to automatically configure your container. You can find examples in `config/provisioning`.
## Documentation
All AI-Dock containers share a common base which is designed to make running on cloud services such as [vast.ai](https://link.ai-dock.org/vast.ai) and [runpod.io](https://link.ai-dock.org/template) as straightforward and user friendly as possible.
Common features and options are documented in the [base wiki](https://github.com/ai-dock/base-image/wiki) but any additional features unique to this image will be detailed below.
>[!NOTE]
>The default provisioning script downloads models to `$WORKSPACE/storage`; You will need to manually scan this directory as symlinks are not yet set for this image.
#### Version Tags
The `:latest` tag points to `:latest-cuda`
Tags follow these patterns:
##### _CUDA_
- `:v2-cuda-[x.x.x]-runtime-[ubuntu-version]-[invokeai-version]`
- `:latest-cuda` → `:v2-cuda-11.8.0-base-22.04-v4.2.5`
##### _ROCm_
- `:v2-rocm-[x.x.x]-runtime-[ubuntu-version]-[invokeai-version]`
- `:latest-rocm` → `:v2-rocm-5.7-runtime-22.04-v4.2.5`
##### _CPU_
- `:v2-cpu-[ubuntu-version]-[invokeai-version]`
- `:latest-cpu` → `:v2-cpu-22.04-v4.2.5`
Browse [here](https://github.com/ai-dock/invokeai/pkgs/container/invokeai) for an image suitable for your target environment.
Supported Python versions: `3.10`
Supported Pytorch versions: `2.2.2`
Supported Platforms: `NVIDIA CUDA`, `AMD ROCm`, `CPU`
## Additional Environment Variables
| Variable | Description |
| ------------------------ | ----------- |
| `AUTO_UPDATE` | Update Invoke AI on startup (default `true`) |
| `INVOKEAI_VERSION` | InvokeAI version tag (default `None`) |
| `INVOKEAI_PORT_HOST` | InvokeAI port (default `9090`) |
| `INVOKEAI_URL` | Override `$DIRECT_ADDRESS:port` with URL for Invoke AI service |
| `INVOKEAI_*` | Invoke AI environment configuration as described in the [project documentation](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/#environment-variables) |
See the base environment variables [here](https://github.com/ai-dock/base-image/wiki/2.0-Environment-Variables) for more configuration options.
### Additional Python Environments
| Environment | Packages |
| -------------- | ----------------------------------------- |
| `invokeai` | Invoke AI and dependencies |
This virtualenv will be activated on shell login.
~~See the base image environments [here](https://github.com/ai-dock/base-image/wiki/1.0-Included-Software#installed-micromamba-environments).~~
## Additional Services
The following services will be launched alongside the [default services](https://github.com/ai-dock/base-image/wiki/1.0-Included-Software) provided by the base image.
### Invoke AI
The service will launch on port `9090` unless you have specified an override with `INVOKEAI_PORT_HOST`.
Invoke AI will be updated to the latest version on container start. You can pin the version to a branch or commit hash by setting the `INVOKEAI_VERSION` variable.
To manage this service you can use `supervisorctl [start|stop|restart] invokeai` or through the [Service Portal](https://github.com/ai-dock/base-image/wiki/1.0-Included-Software#ai-dock-service-portal) process manager tab.
>[!NOTE]
>All services are password protected by default. See the [security](https://github.com/ai-dock/base-image/wiki#security) and [environment variables](https://github.com/ai-dock/base-image/wiki/2.0-Environment-Variables) documentation for more information.
## Pre-Configured Templates
**Vast.ai**
- [InvokeAI:latest-cuda](https://link.ai-dock.org/template-vast-invokeai)
- [InvokeAI:latest-rocm](https://link.ai-dock.org/template-vast-invokeai-rocm)
---
**Runpod.io**
- [InvokeAI:latest](https://link.ai-dock.org/template-runpod-invokeai)
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_The author ([@robballantyne](https://github.com/robballantyne)) may be compensated if you sign up to services linked in this document. Testing multiple variants of GPU images in many different environments is both costly and time-consuming; This helps to offset costs_