Open WebUI

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted WebUI designed to operate entirely offline. It supports various LLM runners, including Ollama and OpenAI-compatible APIs.

Key Features of Open WebUI ⭐

🚀 Effortless Setup: Install seamlessly using Docker or Kubernetes (kubectl, kustomize or helm) for a hassle-free experience with support for both :ollama and :cuda tagged images.

🤝 Ollama/OpenAI API Integration: Effortlessly integrate OpenAI-compatible APIs for versatile conversations alongside Ollama models. Customize the OpenAI API URL to link with LMStudio, GroqCloud, Mistral, OpenRouter, and more.

🛡️ Granular Permissions and User Groups: By allowing administrators to create detailed user roles and permissions, we ensure a secure user environment. This granularity not only enhances security but also allows for customized user experiences, fostering a sense of ownership and responsibility amongst users.

📱 Responsive Design: Enjoy a seamless experience across Desktop PC, Laptop, and Mobile devices.

📱 Progressive Web App (PWA) for Mobile: Enjoy a native app-like experience on your mobile device with our PWA, providing offline access on localhost and a seamless user interface.

✒️🔢 Full Markdown and LaTeX Support: Elevate your LLM experience with comprehensive Markdown and LaTeX capabilities for enriched interaction.

🎤📹 Hands-Free Voice/Video Call: Experience seamless communication with integrated hands-free voice and video call features, allowing for a more dynamic and interactive chat environment.

🛠️ Model Builder: Easily create Ollama models via the Web UI. Create and add custom characters/agents, customize chat elements, and import models effortlessly through Open WebUI Community integration.

🐍 Native Python Function Calling Tool: Enhance your LLMs with built-in code editor support in the tools workspace. Bring Your Own Function (BYOF) by simply adding your pure Python functions, enabling seamless integration with LLMs.

📚 Local RAG Integration: Dive into the future of chat interactions with groundbreaking Retrieval Augmented Generation (RAG) support. This feature seamlessly integrates document interactions into your chat experience. You can load documents directly into the chat or add files to your document library, effortlessly accessing them using the # command before a query.

🔍 Web Search for RAG: Perform web searches using providers like SearXNG, Google PSE, Brave Search, serpstack, serper, Serply, DuckDuckGo, TavilySearch, SearchApi and Bing and inject the results directly into your chat experience.

🌐 Web Browsing Capability: Seamlessly integrate websites into your chat experience using the # command followed by a URL. This feature allows you to incorporate web content directly into your conversations, enhancing the richness and depth of your interactions.

🎨 Image Generation Integration: Seamlessly incorporate image generation capabilities using options such as AUTOMATIC1111 API or ComfyUI (local), and OpenAI’s DALL-E (external), enriching your chat experience with dynamic visual content.

⚙️ Many Models Conversations: Effortlessly engage with various models simultaneously, harnessing their unique strengths for optimal responses. Enhance your experience by leveraging a diverse set of models in parallel.

🔐 Role-Based Access Control (RBAC): Ensure secure access with restricted permissions; only authorized individuals can access your Ollama, and exclusive model creation/pulling rights are reserved for administrators.

🌐🌍 Multilingual Support: Experience Open WebUI in your preferred language with our internationalization (i18n) support. Join us in expanding our supported languages! We’re actively seeking contributors!

🧩 Pipelines, Open WebUI Plugin Support: Seamlessly integrate custom logic and Python libraries into Open WebUI using Pipelines Plugin Framework. Launch your Pipelines instance, set the OpenAI URL to the Pipelines URL, and explore endless possibilities. Examples include Function Calling, User Rate Limiting to control access, Usage Monitoring with tools like Langfuse, Live Translation with LibreTranslate for multilingual support, Toxic Message Filtering and much more.

🌟 Continuous Updates: We are committed to improving Open WebUI with regular updates, fixes, and new features.

Creating an App using the Control Panel

Click the Deploy to DigitalOcean button to create a Droplet based on this 1-Click App. If you aren’t logged in, this link will prompt you to log in with your DigitalOcean account.

Creating an App using the API

In addition to creating a Droplet from the Open WebUI 1-Click App using the control panel, you can also use the DigitalOcean API. As an example, to create a 4GB Open WebUI Droplet in the SFO2 region, you can use the following curl command. You need to either save your API access token) to an environment variable or substitute it in the command below.

curl -X POST -H 'Content-Type: application/json' \
         -H 'Authorization: Bearer '$TOKEN'' -d \
        '{"name":"choose_a_name","region":"sfo2","size":"s-2vcpu-4gb","image": "sharklabs-openwebui"}' \
        "https://api.digitalocean.com/v2/droplets"

Getting Started After Deploying Open WebUI

Prerequisites

• A DigitalOcean Cloud account.
• A HUGS GPU Droplet deployed and running.
• The Open WebUI marketplace droplet 1-click running and configured to connect to the HUGS droplet.

Step 1 - Create and Access Your GPU Droplet

1. Set up the Droplet:

Go to DigitalOcean’s Droplets page and create a new GPU Droplet. Under the Choose an Image tab, please select 1-Click Models and use one of the available Hugging Face images. 2. Access the Console:

Once your Droplet is ready, click on its name in the Droplets section and select Launch Web Console. 3. Please note the Message of the Day (MOTD): This contains the bearer token and inference endpoint for API access, which you’ll need later.

Step 2 - Connect Open WebUI to the HUGs droplet

1. Open Settings:

In Open WebUI, click your user icon at the bottom left, then click Settings.

Go to Admin: 2. Navigate to the Admin tab, then select Connections. 3. Set the Inference Endpoint:

In the API link field, enter your Droplet’s IP followed by /v1. If a specific port is required, include it, e.g., http:///v1.

Use the API token from the MOTD for authentication.

Verify Connection: 4. Click Verify Connection. A green light confirms a successful connection. Open WebUI will then auto-detect available models, such as hfhgus/Meta-Llama.