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Open WebUI can be easily deployed using Docker. This guide covers various Docker deployment scenarios including standalone, with bundled Ollama, and GPU support.

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Prerequisites

When using Docker to install Open WebUI, make sure to include the -v open-webui:/app/backend/data in your Docker command. This step is crucial as it ensures your database is properly mounted and prevents any loss of data.

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Quick Start

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If Ollama is on Your Computer

Connect to Ollama running on the same machine: 
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
Access Open WebUI at http://localhost:3000

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If Ollama is on a Different Server

Connect to Ollama on another server by setting the OLLAMA_BASE_URL: 
docker run -d -p 3000:8080 -e OLLAMA_BASE_URL=https://example.com -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main

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OpenAI API Only

If you’re only using OpenAI API without Ollama: 
docker run -d -p 3000:8080 -e OPENAI_API_KEY=your_secret_key -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main

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GPU Support

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NVIDIA GPU with CUDA

Run Open WebUI with NVIDIA GPU support: 
docker run -d -p 3000:8080 --gpus all --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:cuda

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Bundled Ollama Installation

These images bundle Open WebUI with Ollama in a single container: 
docker run -d -p 3000:8080 --gpus=all -v ollama:/root/.ollama -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:ollama

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Docker Compose

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Basic Setup

Create a docker-compose.yaml file:
docker-compose.yaml
services:
  ollama:
    volumes:
      - ollama:/root/.ollama
    container_name: ollama
    pull_policy: always
    tty: true
    restart: unless-stopped
    image: ollama/ollama:${OLLAMA_DOCKER_TAG-latest}

  open-webui:
    build:
      context: .
      dockerfile: Dockerfile
    image: ghcr.io/open-webui/open-webui:${WEBUI_DOCKER_TAG-main}
    container_name: open-webui
    volumes:
      - open-webui:/app/backend/data
    depends_on:
      - ollama
    ports:
      - ${OPEN_WEBUI_PORT-3000}:8080
    environment:
      - 'OLLAMA_BASE_URL=http://ollama:11434'
      - 'WEBUI_SECRET_KEY='
    extra_hosts:
      - host.docker.internal:host-gateway
    restart: unless-stopped

volumes:
  ollama: {}
  open-webui: {}
Run with: 
docker compose up -d

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GPU Support with Docker Compose

Create docker-compose.gpu.yaml to extend the base configuration:
docker-compose.gpu.yaml
services:
  ollama:
    # GPU support
    deploy:
      resources:
        reservations:
          devices:
            - driver: ${OLLAMA_GPU_DRIVER-nvidia}
              count: ${OLLAMA_GPU_COUNT-1}
              capabilities:
                - gpu
Run with GPU support: 
docker compose -f docker-compose.yaml -f docker-compose.gpu.yaml up -d

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Available Docker Images

Open WebUI provides several image tags:
TagDescription
mainLatest stable release
devDevelopment branch (unstable)
cudaCUDA GPU support
ollamaBundled with Ollama
For CUDA acceleration, use the :cuda tag. For bundled Ollama, use the :ollama tag.

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Network Configuration

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Host Network Mode

If you’re experiencing connection issues, use host networking: 
docker run -d --network=host -v open-webui:/app/backend/data -e OLLAMA_BASE_URL=http://127.0.0.1:11434 --name open-webui --restart always ghcr.io/open-webui/open-webui:main
With --network=host, the port changes from 3000 to 8080, so access at http://localhost:8080

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Build Arguments

When building from the Dockerfile, you can use these build arguments: 
docker build \
  --build-arg USE_CUDA=false \
  --build-arg USE_OLLAMA=false \
  --build-arg USE_SLIM=false \
  --build-arg USE_CUDA_VER=cu128 \
  --build-arg USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 \
  --build-arg USE_RERANKING_MODEL="" \
  --build-arg BUILD_HASH=dev-build \
  -t open-webui .

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Build Arguments Reference

  • USE_CUDA: Enable CUDA support (default: false)
  • USE_OLLAMA: Bundle Ollama in the image (default: false)
  • USE_SLIM: Use slim build without downloading models (default: false)
  • USE_CUDA_VER: CUDA version - cu121 for CUDA 12, cu128 for CUDA 12.8 (default: cu128)
  • USE_EMBEDDING_MODEL: Sentence transformer model (default: sentence-transformers/all-MiniLM-L6-v2)
  • USE_RERANKING_MODEL: Optional reranking model
  • USE_AUXILIARY_EMBEDDING_MODEL: Auxiliary embedding model (default: TaylorAI/bge-micro-v2)
  • BUILD_HASH: Build version hash
  • UID / GID: User and group IDs (default: 0 for root)
If you change the embedding model, you won’t be able to use RAG Chat with your previous documents. You’ll need to re-embed them.

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Container Environment

The container runs on port 8080 internally and includes:
  • Python 3.11.14
  • Node.js 22 (for frontend build)
  • FFmpeg for media processing
  • Pandoc for document conversion

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Health Check

The container includes a health check that verifies the service is running: 
curl --silent --fail http://localhost:8080/health | jq -ne 'input.status == true'

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Offline Mode

For offline environments, set the HF_HUB_OFFLINE environment variable: 
docker run -d -p 3000:8080 -e HF_HUB_OFFLINE=1 -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main

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Next Steps

Environment Variables

Configure Open WebUI with environment variables

Reverse Proxy

Set up nginx or Apache reverse proxy

Updating

Keep your installation up-to-date

Kubernetes

Deploy on Kubernetes