Verified project record
open-webui/open-webui
A self-hostable web interface for managing and interacting with LLM runners and AI features. It is designed to operate entirely offline and supports various model providers alongside built-in retrieval augmented generation.
Project overview
A self-hostable web interface for managing and interacting with LLM runners and AI features. It is designed to operate entirely offline and supports various model providers alongside built-in retrieval augmented generation.
- Project type
- RAG · Model Runtime
- Use cases
- Chat Assistants · Knowledge Q&A
- Deployment
- Docker / Docker Compose
- License
- License pending
Best for
- General users and developers who require an offline-capable, self-hosted web interface to manage local LLM runners.
- Enterprise teams needing a self-hosted AI platform with granular administrative roles and enterprise authentication integrations.
Key capabilities
- Connect any OpenAI-compatible API alongside local Ollama models, allowing users to mix and match providers freely.
- Extend Open WebUI with Filters, Actions, Pipes, Tools, and Skills, and connect external services through MCP, MCPO, and OpenAPI tool servers.
- Retrieval Augmented Generation backed by 9 vector databases and multiple content-extraction engines, supporting hybrid search with reranking.
- Search the web through dozens of providers and inject results directly into the conversation.
- Pull websites into chat using a URL command or let the model fetch them automatically when needed.
- Create and edit images with multiple engines including OpenAI DALL·E, Gemini, ComfyUI (local), and AUTOMATIC1111 (local).
- Integrated voice and video calls with multiple Speech-to-Text and Text-to-Speech engines.
- Administrators define detailed roles, groups, and permissions, giving each user exactly the access they need securely by default.
Limitations and risks
- Requires Python 3.11 to avoid compatibility issues when installing via pip.
- The :dev branch contains the latest unstable features and may contain bugs or incomplete features.
Getting started
- Installation difficulty is rated as easy, providing a single Docker command installation with bundled Ollama or a straightforward pip install command.
- Begin by installing via pip or Docker, then access the web interface at localhost.
Alternatives and comparisons
- Brings advanced LLM capabilities like RAG, web search, and deep research to any hosted environment via a feature-rich interface and connectors.
- Provides an on-premise generative AI application with an intuitive chat interface, RAG pipelines, and enterprise-grade team management.
Project comparisons
Evidence and sources
- README: Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-c…
- README: 🤝 Broad Model & API Integration: Connect any OpenAI-compatible API alongside local Ollama models. Point the API URL at LMStudio, GroqCloud, Mistral, OpenRouter, vLLM, and more to…
- Release: v0.10.2
- README: Open WebUI can be installed using pip, the Python package installer. Before proceeding, ensure you're using Python 3.11 to avoid compatibility issues.
- README: Effortless Setup: Install seamlessly via pip, uv, Docker, or Kubernetes (kubectl, kustomize, or helm), with :ollama and :cuda tagged images available for container deployments.
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