Open WebUI

Use Ollama and OpenAI-compatible backends through one model-facing interface

Open WebUI supports Ollama alongside OpenAI-compatible APIs, allowing backends such as LM Studio, vLLM, OpenRouter, Mistral, and Groq to be presented through the same workspace. Multi-model conversations can involve several models in parallel, while the Models feature can wrap a base model with custom instructions, tools, and knowledge to publish purpose-specific agents. This makes it possible to mix local and cloud inference without giving every user a different application for each provider.

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Connect chat to RAG, web search, MCP, and operational tools

Its local RAG stack supports multiple vector databases and document extraction engines, including hybrid BM25 plus vector search and reranking. Web search can be connected through providers such as SearXNG, Brave, Kagi, Tavily, Perplexity, and Firecrawl. Extensibility includes Filters, Actions, Pipes, Tools, and Skills, plus MCP, MCPO, and OpenAPI tool servers, so an installation can connect models to internal APIs, knowledge sources, and automated workflows instead of remaining a standalone chat surface.

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From a private local-AI setup to a managed internal AI portal

Open WebUI fits individuals who want to run Ollama on their own hardware without sending conversations to a cloud service, as well as organizations that want one entry point for multiple LLMs, internal documents, search, and business tools. RBAC, user groups, LDAP/Active Directory, OAuth, and SCIM make it possible to grow beyond a single-user chat UI. It is particularly useful when administrators want to publish curated agents and knowledge rather than exposing raw model endpoints directly to every user.

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Its broad feature surface needs operational design, and the current license includes branding restrictions

Self-hosting Open WebUI does not automatically make every connected capability private or free. Cloud LLMs, speech services, image generators, and web-search providers retain their own data-handling and pricing terms. A fully offline deployment requires local choices for inference, embeddings, extraction, and any speech or image features that are used. Team deployments also introduce model permissions, external tools, knowledge sources, SSO, storage, and observability decisions beyond simply starting the Docker container.

The current Open WebUI License is not the project's earlier MIT license and contains additional conditions. In deployments or distributions with more than 50 direct end users within a rolling 30-day period, removing or altering Open WebUI branding is generally prohibited unless prior written permission or an enterprise license permits it. Earlier code remains subject to prior licenses as recorded in LICENSE_HISTORY, so white-labeling, redistribution, and commercial embedding should be evaluated against the exact revision being used.

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