How to Deploy Open WebUI on a VPS

copyapt update && apt upgrade -y
adduser deploy
usermod -aG sudo deploy

copyufw allow OpenSSH
ufw allow 80
ufw allow 443
ufw enable

copycurl -fsSL https://get.docker.com | sh
usermod -aG docker deploy

#Install Open WebUI

Create a working directory:

copymkdir ~/open-webui && cd ~/open-webui

Create a compose file:

copyservices:
  open-webui:
    image: ghcr.io/open-webui/open-webui:main
    restart: unless-stopped
    ports:
      - "127.0.0.1:3000:8080"
    volumes:
      - open-webui_data:/app/backend/data
    environment:
      - OLLAMA_BASE_URL=http://host.docker.internal:11434
    extra_hosts:
      - "host.docker.internal:host-gateway"

volumes:
  open-webui_data:

The OLLAMA_BASE_URL tells Open WebUI where to find Ollama. If Ollama runs on the same server, host.docker.internal reaches it via Docker's internal network. If Ollama is on a different server, replace it with the actual URL (e.g., http://ollama-server:11434).

Start it:

copydocker compose up -d

Open WebUI listens on port 3000 (mapped to 8080 inside the container). The 127.0.0.1 bind keeps it private — a reverse proxy handles public access.

#Connect to Ollama

If Ollama isn't running yet, install it first — see Deploy Ollama on a VPS for the full setup. The quick version:

copy# In a separate directory
mkdir ~/ollama && cd ~/ollama
cat > compose.yaml <<EOF
services:
  ollama:
    image: ollama/ollama:latest
    restart: unless-stopped
    ports:
      - "127.0.0.1:11434:11434"
    volumes:
      - ollama_data:/root/.ollama
volumes:
  ollama_data:
EOF
docker compose up -d

Pull a model so Ollama has something to serve:

copydocker exec -it ollama ollama pull llama3.2

Once Ollama is running and has at least one model, Open WebUI should detect it automatically. Load the web interface and you'll see the model in the dropdown.

#HTTPS + domain

Open WebUI needs HTTPS for production use — especially if you're enabling user accounts or accessing it remotely. Point a reverse proxy at 127.0.0.1:3000 and terminate HTTPS on 443.

The simplest path is Automatic HTTPS with Caddy. Point an A record for your hostname (say chat.example.com) at the server's public IP, then have Caddy reverse-proxy that hostname to 127.0.0.1:3000.

If you're using the Caddy container approach, put Open WebUI and Caddy in the same compose file and proxy to the Open WebUI service name:

reverse_proxy open-webui:8080

#First-run setup

Load https://chat.example.com in your browser. On a fresh install, Open WebUI shows an admin account setup screen.

Create the admin account immediately. Like most self-hosted tools, the setup screen is open until the first account exists — whoever registers first becomes the admin. Set your email and a strong password before you do anything else.

Once you're in:

1. Check the model dropdown — it should show models from your Ollama instance. If it's empty, verify Ollama is running and the OLLAMA_BASE_URL is correct.
2. Send a test message — type something and confirm you get a response. This verifies the full chain: browser → Open WebUI → Ollama → model → response.
3. Upload a document — try uploading a PDF or text file and ask a question about it. This tests the RAG (retrieval-augmented generation) pipeline, which indexes documents and retrieves relevant chunks for the model.

If the model dropdown is empty, check the Open WebUI logs:

copydocker compose logs open-webui | tail -20

Common issues: Ollama not reachable (wrong URL), Ollama not running, or firewall blocking the connection.

#Multi-user setup

Open WebUI supports multiple users with role-based access. After creating the admin account:

1. Disable open registration (Settings → General → "Allow New Sign Ups") once you've created all the accounts you need. Leaving registration open means anyone who finds your URL can create an account.
2. Create user accounts (Admin Panel → Users → Add User) for each person who needs access.
3. Set default models (Settings → General → "Default Model") to control which model new conversations start with.

Users get their own conversation history and settings, but they all share the same Ollama backend and its models. There's no per-user model isolation — everyone sees the same models.

#Backups

The important data lives in the Open WebUI volume:

copydocker run --rm -v open-webui_data:/data -v $(pwd):/backup alpine \
  tar czf /backup/open-webui-$(date +%F).tar.gz -C /data .

This backs up conversation history, user accounts, settings, and indexed documents. The backup is self-contained — restore it to a fresh Open WebUI instance and everything comes back.

For Ollama, see Deploy Ollama on a VPS for backup instructions.

#Upgrades

Pull the newer image and recreate:

copydocker compose pull
docker compose up -d

Open WebUI runs database migrations automatically on startup, so upgrades are usually seamless. Check the Open WebUI changelog for any breaking changes before a major version bump.

#Troubleshooting

Model dropdown is empty. Ollama isn't reachable. Check that Ollama is running (docker compose ps in the Ollama directory) and that the OLLAMA_BASE_URL is correct. If both are on the same server, http://host.docker.internal:11434 should work.

Responses are very slow. Open WebUI is waiting for Ollama, which is doing CPU inference. This is expected without a GPU. Check Ollama's logs for model loading errors.

"Unauthorized" errors when chatting. Your session may have expired, or you may have disabled registration before creating your account. If you're locked out, you can reset the admin password by setting ADMIN_EMAIL and ADMIN_PASSWORD environment variables in the compose file and restarting.

Document upload fails. Check disk space — RAG indexing stores embeddings locally. Also verify the file isn't corrupted or too large (there's a per-file size limit in the settings).

Can't register new users. Registration is disabled in the admin settings. Log in as admin and enable "Allow New Sign Ups" in Settings → General.

#Verification + next steps

You're done when you can: load the web interface over HTTPS, sign in as admin, send a message and get a response from Ollama, upload a document and ask questions about it, and create additional user accounts.

From here, connect Ollama with additional models (pull different sizes for different use cases), enable image generation if you have a Stable Diffusion backend, or integrate Open WebUI with other self-hosted tools via its API. For a document-focused AI workspace, see AnythingLLM. A 2 vCPU / 4 GB box handles the UI alone; step up to 8 vCPU / 16 GB for the Ollama backend with 7B models. See Best VPS for AI & ML Workloads for the ranked picks.