| .. | ||
| README.md | ||
Use Open WebUI with Ollama
Install Open WebUI and use Ollama to chat with models on your Spark
Table of Contents
Overview
Basic idea
Open WebUI is an extensible, self-hosted AI interface that operates entirely offline. This playbook shows you how to deploy Open WebUI with an integrated Ollama server on your DGX Spark device using NVIDIA Sync. The setup creates a secure SSH tunnel that lets you access the web interface from your local browser while the models run on Spark's GPU.
What you'll accomplish
You will have a fully functional Open WebUI installation running on your DGX Spark, accessible through your local web browser via NVIDIA Sync's managed SSH tunneling. The setup includes integrated Ollama for model management, persistent data storage, and GPU acceleration for model inference.
What to know before starting
- How to use NVIDIA Sync to connect to your DGX Spark device
Prerequisites
- DGX Spark device is set up and accessible
- NVIDIA Sync installed and connected to your DGX Spark
- Enough disk space for the Open WebUI container image and model downloads
Time & risk
Duration: 15-20 minutes for initial setup, plus model download time (varies by model size)
Risks:
- Docker permission issues may require user group changes and session restart
- Large model downloads may take significant time depending on network speed
Rollback: Stop and remove Docker containers using provided cleanup commands, remove custom port from NVIDIA Sync settings.
Instructions
Step 1. Configure Docker permissions
To easily manage containers without sudo, you must be in the docker group. If you choose to skip this step, you will need to run Docker commands with sudo.
Open a new terminal and test Docker access. In the terminal, run:
docker ps
If you see a permission denied error (something like permission denied while trying to connect to the Docker daemon socket), add your user to the docker group:
sudo usermod -aG docker $USER
Warning
: After running usermod, you must log out and log back in to start a new session with updated group permissions.
Step 2. Verify Docker setup and pull container
Open a new terminal, pull the Open WebUI container image with integrated Ollama:
docker pull ghcr.io/open-webui/open-webui:ollama
Step 3. Start the Open WebUI container
Start the Open WebUI container by running:
docker run -d -p 8080:8080 --gpus=all \
-v open-webui:/app/backend/data \
-v open-webui-ollama:/root/.ollama \
--name open-webui ghcr.io/open-webui/open-webui:ollama
This will start the Open WebUI container and make it accessible at http://localhost:8080. You can access the Open WebUI interface from your local web browser.
Application data will be stored in the open-webui volume and model data will be stored in the open-webui-ollama volume.
Step 4. Create administrator account
This step sets up the initial administrator account for Open WebUI. This is a local account that you will use to access the Open WebUI interface.
In the Open WebUI interface, click the "Get Started" button at the bottom of the screen.
Fill out the administrator account creation form with your preferred credentials.
Click the registration button to create your account and access the main interface.
Step 5. Download and configure a model
This step downloads a language model through Ollama and configures it for use in Open WebUI. The download happens on your DGX Spark device and may take several minutes.
Click on the "Select a model" dropdown in the top left corner of the Open WebUI interface.
Type gpt-oss:20b in the search field.
Click the "Pull 'gpt-oss:20b' from Ollama.com" button that appears.
Wait for the model download to complete. You can monitor progress in the interface.
Once complete, select "gpt-oss:20b" from the model dropdown.
Step 6. Test the model
This step verifies that the complete setup is working properly by testing model inference through the web interface.
In the chat textarea at the bottom of the Open WebUI interface, enter:
Write me a haiku about GPUs
Press Enter to send the message and wait for the model's response.
Step 7. Troubleshooting
Common issues and their solutions.
| Symptom | Cause | Fix |
|---|---|---|
| Permission denied on docker ps | User not in docker group | Run Step 1 completely, including logging out and logging back in or use sudo |
| Model download fails | Network connectivity issues | Check internet connection, retry download |
| GPU not detected in container | Missing --gpus=all flag |
Recreate container with correct command |
| Port 8080 already in use | Another application using port | Change port in docker command or stop conflicting service |
Step 8. Cleanup and rollback
Steps to completely remove the Open WebUI installation and free up resources:
Warning
: These commands will permanently delete all Open WebUI data and downloaded models.
Stop and remove the Open WebUI container:
docker stop open-webui
docker rm open-webui
Remove the downloaded images:
docker rmi ghcr.io/open-webui/open-webui:ollama
Remove persistent data volumes:
docker volume rm open-webui open-webui-ollama
To rollback permission change: sudo deluser $USER docker
Step 9. Next steps
Try downloading different models from the Ollama library at https://ollama.com/library.
You can monitor GPU and memory usage through the DGX Dashboard available in NVIDIA Sync as you try different models.
If Open WebUI reports an update is available, you can update the container image by running:
docker pull ghcr.io/open-webui/open-webui:ollama
Setup Open WebUI on Remote Spark with NVIDIA Sync
Note
: If you haven't already installed NVIDIA Sync, learn how here.
Step 1. Configure Docker permissions
To easily manage containers using NVIDIA Sync, you must be able to run Docker commands without sudo.
Open the Terminal app from NVIDIA Sync to start an interactive SSH session and test Docker access. In the terminal, run:
docker ps
If you see a permission denied error (something like permission denied while trying to connect to the Docker daemon socket), add your user to the docker group:
sudo usermod -aG docker $USER
Warning
: After running usermod, you must close the terminal window completely to start a new session with updated group permissions.
Step 2. Verify Docker setup and pull container
This step confirms Docker is working properly and downloads the Open WebUI container image. This runs on the DGX Spark device and may take several minutes depending on network speed.
Open a new Terminal app from NVIDIA Sync and pull the Open WebUI container image with integrated Ollama:
docker pull ghcr.io/open-webui/open-webui:ollama
Once the container image is downloaded, continue to setup NVIDIA Sync.
Step 3. Open NVIDIA Sync Settings
Click on the NVIDIA Sync icon in your system tray or taskbar to open the main application window.
Click the gear icon in the top right corner to open the Settings window.
Click on the "Custom" tab to access Custom Ports configuration.
Step 4. Add Open WebUI custom port
This step creates a new entry in NVIDIA Sync that will manage the Open WebUI container and create the necessary SSH tunnel.
Click the "Add New" button in the Custom section.
Fill out the form with these values:
Name: Open WebUI
Port: 12000
Auto open in browser at the following path: Check this checkbox
Start Script: Copy and paste this entire script:
#!/usr/bin/env bash
set -euo pipefail
NAME="open-webui"
IMAGE="ghcr.io/open-webui/open-webui:ollama"
cleanup() {
echo "Signal received; stopping ${NAME}..."
docker stop "${NAME}" >/dev/null 2>&1 || true
exit 0
}
trap cleanup INT TERM HUP QUIT EXIT
## Ensure Docker CLI and daemon are available
if ! docker info >/dev/null 2>&1; then
echo "Error: Docker daemon not reachable." >&2
exit 1
fi
## Already running?
if [ -n "$(docker ps -q --filter "name=^${NAME}$" --filter "status=running")" ]; then
echo "Container ${NAME} is already running."
else
# # Exists but stopped? Start it.
if [ -n "$(docker ps -aq --filter "name=^${NAME}$")" ]; then
echo "Starting existing container ${NAME}..."
docker start "${NAME}" >/dev/null
else
# # Not present: create and start it.
echo "Creating and starting ${NAME}..."
docker run -d -p 12000:8080 --gpus=all \
-v open-webui:/app/backend/data \
-v open-webui-ollama:/root/.ollama \
--name "${NAME}" "${IMAGE}" >/dev/null
fi
fi
echo "Running. Press Ctrl+C to stop ${NAME}."
## Keep the script alive until a signal arrives
while :; do sleep 86400; done
Click the "Add" button to save configuration.
Step 5. Launch Open WebUI
This step starts the Open WebUI container on your DGX Spark and establishes the SSH tunnel. The browser will open automatically if configured correctly.
Click on the NVIDIA Sync icon in your system tray or taskbar to open the main application window.
Under the "Custom" section, click on "Open WebUI".
Your default web browser should automatically open to the Open WebUI interface at http://localhost:12000.
Step 6. Create administrator account
This step sets up the initial administrator account for Open WebUI. This is a local account that you will use to access the Open WebUI interface.
In the Open WebUI interface, click the "Get Started" button at the bottom of the screen.
Fill out the administrator account creation form with your preferred credentials.
Click the registration button to create your account and access the main interface.
Step 7. Download and configure a model
This step downloads a language model through Ollama and configures it for use in Open WebUI. The download happens on your DGX Spark device and may take several minutes.
Click on the "Select a model" dropdown in the top left corner of the Open WebUI interface.
Type gpt-oss:20b in the search field.
Click the "Pull 'gpt-oss:20b' from Ollama.com" button that appears.
Wait for the model download to complete. You can monitor progress in the interface.
Once complete, select "gpt-oss:20b" from the model dropdown.
Step 8. Test the model
This step verifies that the complete setup is working properly by testing model inference through the web interface.
In the chat textarea at the bottom of the Open WebUI interface, enter:
Write me a haiku about GPUs
Press Enter to send the message and wait for the model's response.
Step 9. Stop the Open WebUI
When you are finished with your session and want to stop the Open WebUI server and reclaim resources, close the Open WebUI from NVIDIA Sync.
Click on the NVIDIA Sync icon in your system tray or taskbar to open the main application window.
Under the "Custom" section, click the x icon on the right of the "Open WebUI" entry.
This will close the tunnel and stop the Open WebUI docker container.
Step 10. Troubleshooting
Common issues and their solutions.
| Symptom | Cause | Fix |
|---|---|---|
| Permission denied on docker ps | User not in docker group | Run Step 1 completely, including terminal restart |
| Browser doesn't open automatically | Auto-open setting disabled | Manually navigate to localhost:12000 |
| Model download fails | Network connectivity issues | Check internet connection, retry download |
| GPU not detected in container | Missing --gpus=all flag |
Recreate container with correct start script |
| Port 12000 already in use | Another application using port | Change port in Custom App settings or stop conflicting service |
Step 11. Cleanup and rollback
Steps to completely remove the Open WebUI installation and free up resources:
Warning
: These commands will permanently delete all Open WebUI data and downloaded models.
Stop and remove the Open WebUI container:
docker stop open-webui
docker rm open-webui
Remove the downloaded images:
docker rmi ghcr.io/open-webui/open-webui:ollama
Remove persistent data volumes:
docker volume rm open-webui open-webui-ollama
To rollback permission change: sudo deluser $USER docker
Remove the Custom App from NVIDIA Sync by opening Settings > Custom tab and deleting the entry.
Step 12. Next steps
Try downloading different models from the Ollama library at https://ollama.com/library.
You can monitor GPU and memory usage through the DGX Dashboard available in NVIDIA Sync as you try different models.
If Open WebUI reports an update is available, you can update the container image by running:
docker pull ghcr.io/open-webui/open-webui:ollama
After the update, launch Open WebUI again from NVIDIA Sync.