Open WebUI

Beautiful ChatGPT-like interface for running LLMs on CLORE.AI GPUs.

All examples can be run on GPU servers rented through CLORE.AI Marketplace.

Why Open WebUI?

• ChatGPT-like UI - Familiar, polished interface

• Multi-model - Switch between models easily

• RAG built-in - Upload documents for context

• User management - Multi-user support

• History - Conversation persistence

• Ollama integration - Works out of the box

Quick Deploy on CLORE.AI

Docker Image:

ghcr.io/open-webui/open-webui:cuda

Ports:

22/tcp
8080/http

Command:

# Start Ollama in background
ollama serve &
sleep 5
ollama pull llama3.2

# Start Open WebUI (connects to Ollama automatically)
# Note: The Docker image handles this

Accessing Your Service

After deployment, find your http_pub URL in My Orders:

1. Go to My Orders page

2. Click on your order

3. Find the http_pub URL (e.g., abc123.clorecloud.net)

Use https://YOUR_HTTP_PUB_URL instead of localhost in examples below.

Verify It's Working

# Check health
curl https://your-http-pub.clorecloud.net/health

# Get version
curl https://your-http-pub.clorecloud.net/api/version

Response:

{"version": "0.7.2"}

If you get HTTP 502, wait 1-2 minutes - the service is still starting.

Installation

With Ollama (Recommended)

# Start Ollama first
docker run -d --gpus all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

# Pull a model
docker exec -it ollama ollama pull llama3.2

# Start Open WebUI
docker run -d -p 8080:8080 \
  --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

All-in-One (Bundled Ollama)

docker run -d -p 8080:8080 \
  --gpus all \
  -v ollama:/root/.ollama \
  -v open-webui:/app/backend/data \
  --name open-webui \
  ghcr.io/open-webui/open-webui:ollama

First Setup

1. Open http://your-server:8080

2. Create admin account (first user becomes admin)

3. Go to Settings → Models → Pull a model

4. Start chatting!

Features

Chat Interface

• Markdown rendering

• Code highlighting

• Image generation (with compatible models)

• Voice input/output

• File attachments

Model Management

• Pull models directly from UI

• Create custom models

• Set default model

• Model-specific settings

RAG (Document Chat)

1. Click "+" in chat

2. Upload PDF, TXT, or other documents

3. Ask questions about the content

User Management

• Multiple users

• Role-based access

• API key management

• Usage tracking

Configuration

Environment Variables

docker run -d \
  -e OLLAMA_BASE_URL=http://ollama:11434 \
  -e WEBUI_AUTH=True \
  -e WEBUI_NAME="My AI Chat" \
  -e DEFAULT_MODELS="llama3.2" \
  ghcr.io/open-webui/open-webui:main

Key Settings

Variable	Description	Default
OLLAMA_BASE_URL	Ollama API URL	http://localhost:11434
WEBUI_AUTH	Enable authentication	True
WEBUI_NAME	Instance name	Open WebUI
DEFAULT_MODELS	Default model	-
ENABLE_RAG_WEB_SEARCH	Web search in RAG	False

Connect to Remote Ollama

docker run -d -p 8080:8080 \
  -e OLLAMA_BASE_URL=http://remote-server:11434 \
  ghcr.io/open-webui/open-webui:main

Docker Compose

version: '3.8'

services:
  ollama:
    image: ollama/ollama
    container_name: ollama
    volumes:
      - ollama:/root/.ollama
    ports:
      - "11434:11434"
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]

  open-webui:
    image: ghcr.io/open-webui/open-webui:main
    container_name: open-webui
    volumes:
      - open-webui:/app/backend/data
    ports:
      - "8080:8080"
    environment:
      - OLLAMA_BASE_URL=http://ollama:11434
    depends_on:
      - ollama

volumes:
  ollama:
  open-webui:

docker-compose up -d

API Reference

Open WebUI provides several API endpoints:

Endpoint	Method	Description
/health	GET	Health check
/api/version	GET	Get Open WebUI version
/api/config	GET	Get configuration
/ollama/api/tags	GET	List Ollama models (proxied)
/ollama/api/chat	POST	Chat with Ollama (proxied)

Check Health

curl https://your-http-pub.clorecloud.net/health

Response: true

Get Version

curl https://your-http-pub.clorecloud.net/api/version

Response:

{"version": "0.7.2"}

List Models (via Ollama proxy)

curl https://your-http-pub.clorecloud.net/ollama/api/tags

Most API operations require authentication. Use the web UI to create an account and manage API keys.

Tips

Faster Responses

1. Use quantized models (Q4_K_M)

2. Enable streaming in settings

3. Reduce context length if needed

Better Quality

1. Use larger models (13B+)

2. Use Q8 quantization

3. Adjust temperature in model settings

Save Resources

1. Set OLLAMA_KEEP_ALIVE=5m

2. Unload unused models

3. Use smaller models for testing

GPU Requirements

Same as Ollama.

Open WebUI itself uses minimal resources (~500MB RAM).

Troubleshooting

Can't connect to Ollama

# Check Ollama is running
curl http://localhost:11434/api/tags

# If using Docker, use host networking or correct URL
docker run --network=host ghcr.io/open-webui/open-webui:main

Models not showing

1. Check Ollama connection in Settings

2. Refresh model list

3. Pull models via CLI: ollama pull modelname

Slow performance

1. Check GPU is being used: nvidia-smi

2. Try smaller/quantized models

3. Reduce concurrent users

Cost Estimate

Setup	GPU	Hourly
Basic (7B)	RTX 3060	~$0.03
Standard (13B)	RTX 3090	~$0.06
Advanced (34B)	RTX 4090	~$0.10
Enterprise (70B)	A100	~$0.17

Next Steps

• Ollama - CLI usage

• LocalAI - More backends

• RAG + LangChain - Advanced RAG