⭐ Features
Key Features of Open WebUI ⭐
-
🚀 Effortless Setup: Install seamlessly using Docker, Kubernetes, Podman, Helm Charts (
kubectl,kustomize,podman, orhelm) for a hassle-free experience with support for both:ollamaimage with bundled Ollama and:cudawith CUDA support. -
🛠️ Guided Initial Setup: Complete the setup process with clarity, including an explicit indication of creating an admin account during the first-time setup.
-
🤝 OpenAI API Integration: Effortlessly integrate OpenAI-compatible APIs for versatile conversations alongside Ollama models. The OpenAI API URL can be customized to integrate Open WebUI seamlessly with various third-party applications.
-
🛡️ Granular Permissions and User Groups: By allowing administrators to create detailed user roles, user groups, and permissions across the workspace, we ensure a secure user environment for all users involved. This granularity not only enhances security, but also allows for customized user experiences, fostering a sense of ownership and responsibility amongst users.
-
🔐 SCIM 2.0 Provisioning: Enterprise-grade user and group provisioning through SCIM 2.0 protocol, enabling seamless integration with identity providers like Okta, Azure AD, and Google Workspace for automated user lifecycle management.
-
📱 Responsive Design: Enjoy a seamless experience across desktop PCs, laptops, and mobile devices.
-
📱 Progressive Web App for Mobile: Enjoy a native progressive web application experience on your mobile device with offline access on
localhostor a personal domain, and a smooth user interface. In order for our PWA to be installable on your device, it must be delivered in a secure context. This usually means that it must be served over HTTPS.info- To set up a PWA, you'll need some understanding of technologies like Linux, Docker, and reverse proxies such as
Nginx,Caddy, orTraefik. Using these tools can help streamline the process of building and deploying a PWA tailored to your needs. While there's no "one-click install" option available, and your available option to securely deploy your Open WebUI instance over HTTPS requires user experience, using these resources can make it easier to create and deploy a PWA tailored to your needs.
- To set up a PWA, you'll need some understanding of technologies like Linux, Docker, and reverse proxies such as
-
✒️🔢 Full Markdown and LaTeX Support: Elevate your LLM experience with comprehensive Markdown, LaTex, and Rich Text capabilities for enriched interaction.
-
🧩 Model Builder: Easily create custom models from base Ollama models directly from Open WebUI. Create and add custom characters and agents, customize model elements, and import models effortlessly through Open WebUI Community integration.
-
📚 Advanced RAG Integration with Multiple Vector Databases: Dive into the future of chat interactions with cutting-edge Retrieval Augmented Generation (RAG) technology. Choose from 9 vector database options: ChromaDB (default), PostgreSQL with PGVector, Qdrant, Milvus, Elasticsearch, OpenSearch, Pinecone, S3Vector, and Oracle 23ai. Documents can be loaded into the
Documentstab of the Workspace and accessed using the pound key [#] before a query, or by starting the prompt with [#] followed by a URL for webpage content integration. -
📄 Advanced Document Extraction with Multiple Engines: Extract text and data from various document formats including PDFs, Word documents, Excel spreadsheets, PowerPoint presentations, and more using your choice of extraction engines: Apache Tika, Docling, Azure Document Intelligence, Mistral OCR, or external custom (self-built) content extraction engines/document loaders. Advanced document processing capabilities enable seamless integration with your knowledge base, preserving structure and formatting while supporting OCR for scanned documents and images.
-
🔍 Web Search for RAG with 15+ Providers: Perform web searches using 15+ providers including SearXNG, Google PSE, Brave Search, Kagi, Mojeek, Bocha, Tavily, Perplexity (AI models and Search API), serpstack, serper, Serply, DuckDuckGo, SearchAPI, SerpApi, Bing, Jina, Exa, Sougou, Azure AI Search, and Ollama Cloud, injecting results directly into your local Retrieval Augmented Generation (RAG) experience.
-
🌐 Web Browsing Capabilities: Integrate websites seamlessly into your chat experience by using the
#command followed by a URL. This feature enables the incorporation of web content directly into your conversations, thereby enhancing the richness and depth of your interactions. -
🎨 Image Generation & Editing Integration: Seamlessly create and edit images using multiple engines including OpenAI's DALL-E (generation and editing), Gemini (generation and editing), ComfyUI (local, generation and editing), and AUTOMATIC1111 (local, generation). Support for both text-to-image generation and prompt-based image editing workflows with dynamic visual content.
-
⚙️ Concurrent Model Utilization: Effortlessly engage with multiple models simultaneously, harnessing their unique strengths for optimal responses. Leverage a diverse set of model modalities in parallel to enhance your experience.
-
🔐 Role-Based Access Control (RBAC): Ensure secure access with restricted permissions. Only authorized individuals can access your Ollama, while model creation and pulling rights are exclusively reserved for administrators.
-
🌐🌍 Multilingual Support: Experience Open WebUI in your preferred language with our internationalization (
i18n) support. We invite you to join us in expanding our supported languages! We're actively seeking contributors! -
💾 Persistent Artifact Storage: Built-in key-value storage API for artifacts, enabling features like journals, trackers, leaderboards, and collaborative tools with both personal and shared data scopes that persist across sessions.
-
☁️ Cloud Storage Integration: Native support for cloud storage backends including Amazon S3 (with S3-compatible providers), Google Cloud Storage, and Microsoft Azure Blob Storage for scalable file storage and data management.
-
☁️ Enterprise Cloud Integration: Seamlessly import documents from Google Drive and OneDrive/SharePoint directly through the file picker interface, enabling smooth workflows with enterprise cloud storage solutions.
-
📊 Production Observability with OpenTelemetry: Built-in OpenTelemetry support for comprehensive monitoring with traces, metrics, and logs export to your existing observability stack (Prometheus, Grafana, Jaeger, etc.), enabling production-grade monitoring and debugging.
-
🔒 Encrypted Database Support: Optional at-rest encryption for SQLite databases using SQLCipher, providing enhanced security for sensitive data in smaller deployments without requiring PostgreSQL infrastructure.
-
⚖️ Horizontal Scalability for Production: Redis-backed session management and WebSocket support enabling multi-worker and multi-node deployments behind load balancers for high-availability production environments.
-
🌟 Continuous Updates: We are committed to improving Open WebUI with regular updates, fixes, and new features.
And many more remarkable features including... ⚡️
🔧 Pipelines Support
-
🔧 Pipelines Framework: Seamlessly integrate and customize your Open WebUI experience with our modular plugin framework for enhanced customization and functionality (https://github.com/open-webui/pipelines). Our framework allows for the easy addition of custom logic and integration of Python libraries, from AI agents to home automation APIs.
-
📥 Upload Pipeline: Pipelines can be uploaded directly from the
Admin Panel>Settings>Pipelinesmenu, streamlining the pipeline management process.
The possibilities with our Pipelines framework knows no bounds and are practically limitless. Start with a few pre-built pipelines to help you get started!
-
🔗 Function Calling: Integrate Function Calling seamlessly through Pipelines to enhance your LLM interactions with advanced function calling capabilities.
-
📚 Custom RAG: Integrate a custom Retrieval Augmented Generation (RAG) pipeline seamlessly to enhance your LLM interactions with custom RAG logic.
-
📊 Message Monitoring with Langfuse: Monitor and analyze message interactions in real-time usage statistics via Langfuse pipeline.
-
⚖️ User Rate Limiting: Manage API usage efficiently by controlling the flow of requests sent to LLMs to prevent exceeding rate limits with Rate Limit pipeline.
-
🌍 Real-Time LibreTranslate Translation: Integrate real-time translations into your LLM interactions using LibreTranslate pipeline, enabling cross-lingual communication.
- Please note that this pipeline requires further setup with LibreTranslate in a Docker container to work.
-
🛡️ Toxic Message Filtering: Our Detoxify pipeline automatically filters out toxic messages to maintain a clean and safe chat environment.
-
🔒 LLM-Guard: Ensure secure LLM interactions with LLM-Guard pipeline, featuring a Prompt Injection Scanner that detects and mitigates crafty input manipulations targeting large language models. This protects your LLMs from data leakage and adds a layer of resistance against prompt injection attacks.
-
🕒 Conversation Turn Limits: Improve interaction management by setting limits on conversation turns with Conversation Turn Limit pipeline.
-
📈 OpenAI Generation Stats: Our OpenAI pipeline provides detailed generation statistics for OpenAI models.
-
🚀 Multi-Model Support: Our seamless integration with various AI models from various providers expands your possibilities with a wide range of language models to select from and interact with.
In addition to the extensive features and customization options, we also provide a library of example pipelines ready to use along with a practical example scaffold pipeline to help you get started. These resources will streamline your development process and enable you to quickly create powerful LLM interactions using Pipelines and Python. Happy coding! 💡
🖥️ User Experience
-
🖥️ Intuitive Interface: The chat interface has been designed with the user in mind, drawing inspiration from the user interface of ChatGPT.
-
⚡ Swift Responsiveness: Enjoy reliably fast and responsive performance.
-
🎨 Splash Screen: A simple loading splash screen for a smoother user experience.
-
🌐 Personalized Interface: Choose between a freshly designed search landing page and the classic chat UI from Settings > Interface, allowing for a tailored experience.
-
📦 Pip Install Method: Installation of Open WebUI can be accomplished via the command
pip install open-webui, which streamlines the process and makes it more accessible to new users. For further information, please visit: https://pypi.org/project/open-webui/. -
🌈 Theme Customization: Personalize your Open WebUI experience with a range of options, including a variety of solid, yet sleek themes, customizable chat background images, and three mode options: Light, Dark, or OLED Dark mode - or let Her choose for you! ;)
-
🖼️ Custom Background Support: Set a custom background from Settings > Interface to personalize your experience.
-
📝 Rich Banners with Markdown: Create visually engaging announcements with markdown support in banners, enabling richer and more dynamic content.
-
💻 Code Syntax Highlighting: Our syntax highlighting feature enhances code readability, providing a clear and concise view of your code.
-
🗨️ Markdown Rendering in User Messages: User messages are now rendered in Markdown, enhancing readability and interaction.
-
🎨 Flexible Text Input Options: Switch between rich text input and legacy text area input for chat, catering to user preferences and providing a choice between advanced formatting and simpler text input.
-
👆 Effortless Code Sharing : Streamline the sharing and collaboration process with convenient code copying options, including a floating copy button in code blocks and click-to-copy functionality from code spans, saving time and reducing frustration.
-
🎨 Interactive Artifacts: Render web content and SVGs directly in the interface, supporting quick iterations and live changes for enhanced creativity and productivity.
-
🖊️ Live Code Editing: Supercharged code blocks allow live editing directly in the LLM response, with live reloads supported by artifacts, streamlining coding and testing.
-
🔍 Enhanced SVG Interaction: Pan and zoom capabilities for SVG images, including Mermaid diagrams, enable deeper exploration and understanding of complex concepts.
-
🔍 Text Select Quick Actions: Floating buttons appear when text is highlighted in LLM responses, offering deeper interactions like "Ask a Question" or "Explain", and enhancing overall user experience.
-
↕️ Bi-Directional Chat Support: You can easily switch between left-to-right and right-to-left chat directions to accommodate various language preferences.
-
📱 Mobile Accessibility: The sidebar can be opened and closed on mobile devices with a simple swipe gesture.
-
🤳 Haptic Feedback on Supported Devices: Android devices support haptic feedback for an immersive tactile experience during certain interactions.
-
🔍 User Settings Search: Quickly search for settings fields, improving ease of use and navigation.
-
📜 Offline Swagger Documentation: Access developer-friendly Swagger API documentation offline, ensuring full accessibility wherever you are.
-
💾 Performance Optimizations: Lazy loading of large dependencies minimizes initial memory usage, boosting performance and reducing loading times.
-
🚀 Persistent and Scalable Configuration: Open WebUI configurations are stored in a database (webui.db), allowing for seamless load balancing, high-availability setups, and persistent settings across multiple instances, making it easy to access and reuse your configurations.
-
🔄 Portable Import/Export: Easily import and export Open WebUI configurations, simplifying the process of replicating settings across multiple systems.
-
❓ Quick Access to Documentation & Shortcuts: The question mark button located at the bottom right-hand corner of the main UI screen (available on larger screens like desktop PCs and laptops) provides users with easy access to the Open WebUI documentation page and available keyboard shortcuts.
-
📜 Changelog & Check for Updates: Users can access a comprehensive changelog and check for updates in the
Settings>About>See What's Newmenu, which provides a quick overview of the latest features, improvements, and bug fixes, as well as the ability to check for updates.
💬 Conversations
-
💬 True Asynchronous Chat: Enjoy uninterrupted multitasking with true asynchronous chat support, allowing you to create chats, navigate away, and return anytime with responses ready.
-
🔔 Chat Completion Notifications: Stay updated with instant in-UI notifications when a chat finishes in a non-active tab, ensuring you never miss a completed response.
-
🌐 Notification Webhook Integration: Receive timely updates for long-running chats or external integration needs with configurable webhook notifications, even when your tab is closed.
-
📚 Channels (Beta): Explore real-time collaboration between users and AIs with Discord/Slack-style chat rooms, build bots for channels, and unlock asynchronous communication for proactive multi-agent workflows.
-
🖊️ Typing Indicators in Channels: Enhance collaboration with real-time typing indicators in channels, keeping everyone engaged and informed.
-
👤 User Status Indicators: Quickly view a user's status by clicking their profile image in channels, providing better coordination and availability insights.
-
💬 Chat Controls: Easily adjust parameters for each chat session, offering more precise control over your interactions.
-
💖 Favorite Response Management: Easily mark and organize favorite responses directly from the chat overview, enhancing ease of retrieval and access to preferred responses.
-
📌 Pinned Chats: Support for pinned chats, allowing you to keep important conversations easily accessible.
-
🔍 RAG Embedding Support: Change the Retrieval Augmented Generation (RAG) embedding model directly in the
Admin Panel>Settings>Documentsmenu, enhancing document processing. This feature supports Ollama and OpenAI models. -
📜 Citations in RAG Feature: The Retrieval Augmented Generation (RAG) feature allows users to easily track the context of documents fed to LLMs with added citations for reference points.
-
🌟 Enhanced RAG Pipeline: A togglable hybrid search sub-feature for our RAG embedding feature that enhances the RAG functionality via
BM25, with re-ranking powered byCrossEncoder, and configurable relevance score thresholds. -
📹 YouTube RAG Pipeline: The dedicated Retrieval Augmented Generation (RAG) pipeline for summarizing YouTube videos via video URLs enables smooth interaction with video transcriptions directly.
-
📁 Comprehensive Document Retrieval: Toggle between full document retrieval and traditional snippets, enabling comprehensive tasks like summarization and supporting enhanced document capabilities.
-
🌟 RAG Citation Relevance: Easily assess citation accuracy with the addition of relevance percentages in RAG results.
-
🗂️ Advanced RAG: Improve RAG accuracy with smart pre-processing of chat history to determine the best queries before retrieval.
-
📚 Inline Citations for RAG: Benefit from seamless inline citations for Retrieval-Augmented Generation (RAG) responses, improving traceability and providing source clarity for newly uploaded files.
-
📁 Large Text Handling: Optionally convert large pasted text into a file upload to be used directly with RAG, keeping the chat interface cleaner.
-
🔄 Multi-Modal Support: Effortlessly engage with models that support multi-modal interactions, including images (
e.g., LLaVA). -
🤖 Multiple Model Support: Quickly switch between different models for diverse chat interactions.

