Docker¶

Quick Start¶

Requires Docker and an NVIDIA GPU.

docker run --gpus all -p 8188:8188 -v comfyui:/data ghcr.io/umeairt/comfyui:latest

Open http://localhost:8188 — ComfyUI is ready.

That's it. All your data (models, custom nodes, outputs) is stored in the comfyui volume and persists between container restarts or removal.

Windows

Docker Desktop with WSL2 handles GPU passthrough automatically — no extra setup needed with recent NVIDIA drivers (≥ 525.x).

Data Storage¶

You have two options for where your data lives:

Option 1: Docker Volume (recommended)¶

docker run --gpus all --name comfyui -p 8188:8188 -v comfyui:/data ghcr.io/umeairt/comfyui:latest

Docker manages the storage. Data persists until you explicitly delete the volume. Simple and cross-platform.

Option 2: Local Folder¶

docker run --gpus all --name comfyui -p 8188:8188 -v ./comfyui_data:/data ghcr.io/umeairt/comfyui:latest

Data lives in ./comfyui_data/ on your disk — you can see and edit the files directly:

./comfyui_data/
├── models/          ← drop .safetensors files here
├── custom_nodes/    ← installed automatically at first boot
├── output/          ← your generated images
├── input/           ← images you upload to ComfyUI
└── user/            ← ComfyUI settings

Note

If no -v is specified, Docker still creates an anonymous volume automatically (thanks to VOLUME /data in the Dockerfile), so you won't lose data accidentally — but finding that anonymous volume later is harder.

Customization¶

Custom Node Bundles¶

Control which nodes get installed with the NODE_TIER environment variable:

Tier	What's installed	Use Case
`minimal`	ComfyUI-Manager only	Quick testing
`umeairt`	+ UmeAiRT Sync/Toolkit + essentials	UmeAiRT workflows
`full`	+ all community nodes (~34)	Default

docker run --gpus all -p 8188:8188 -v comfyui:/data -e NODE_TIER=minimal ghcr.io/umeairt/comfyui:latest

Change tiers by restarting with a different value — no rebuild needed.

JupyterLab (Cloud / RunPod)¶

A cloud variant adds JupyterLab for remote development:

docker run --gpus all -p 8188:8188 -p 8888:8888 -v comfyui:/data \
  -e JUPYTER_ENABLE=true -e JUPYTER_TOKEN=mysecrettoken \
  ghcr.io/umeairt/comfyui:latest-cloud

ComfyUI → :8188
JupyterLab → :8888

All Environment Variables¶

Variable	Default	Description
`NODE_TIER`	`full`	Custom node bundle (`minimal`, `umeairt`, `full`)
`JUPYTER_ENABLE`	`false`	Start JupyterLab (cloud variant only)
`JUPYTER_TOKEN`	(empty)	JupyterLab access token
`JUPYTER_PORT`	`8888`	JupyterLab listening port

Docker Compose¶

If you prefer docker compose, clone the repo and use the included docker-compose.yml:

git clone https://gitlab.com/UmeAiRT-Studio/ComfyUI-Auto_installer-Python.git
cd ComfyUI-Auto_installer-Python
docker compose up -d

Edit docker-compose.yml to customize environment variables or switch between Docker volume and local folder storage.

Building Locally¶

# Standard image
docker build -t umeairt/comfyui:latest .

# Cloud image (with JupyterLab)
docker build --build-arg VARIANT=cloud -t umeairt/comfyui:cloud .

Troubleshooting¶

GPU not detected¶

Verify Docker can see your GPU:

docker run --rm --gpus all nvidia/cuda:13.0.2-cudnn-runtime-ubuntu24.04 nvidia-smi

`bash\r: No such file or directory`¶

Shell scripts have Windows line endings. The Dockerfile fixes this automatically, but if you edited entrypoint.sh locally, ensure it uses LF endings.