Open WebUI
The standard self-hosted chat interface for Ollama and local AI models. Supports OpenAI-compatible APIs, RAG, tool calling, voice, plugins, and multi-user accounts. Runs in Docker
Quick Start
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway ghcr.io/open-webui/open-webui:main Overview
Open WebUI is the standard chat interface for running local AI models. If you have Ollama installed, this is what most people reach for to get a ChatGPT-style UI on top of it. It runs in Docker, connects to Ollama on startup, and gives you conversation history, model switching, document upload, and RAG — all running locally with no data leaving your machine.
The backend support goes beyond Ollama. Open WebUI works with any OpenAI-compatible API, which means you can point it at OpenAI, Anthropic, or a remote vLLM instance and use the same interface for all of them. That makes it practical as a unified front end whether you are running models locally or routing to a hosted API.
The feature set has grown considerably: tool calling, voice input and output, a plugin system, web search integration, multi-user accounts with role-based access, and RAG pipelines backed by a vector database. It is one of the fastest-moving projects in the self-hosted AI space.
The honest constraints: setup requires Docker and some familiarity with the tooling. RAG workloads against large documents are hardware-intensive — a machine with limited RAM will feel it. The default configuration handles small-team use well, but it is not designed for production multi-tenant deployments with many concurrent users. For teams that need governance and workspace isolation without DevOps overhead, AnythingLLM is the closer fit.
For anyone running Ollama who wants a proper interface rather than the API terminal, this is the obvious starting point.
Open WebUI: Pros & Cons
| Pros (The Wins) | Cons (The Friction) |
|---|---|
| Ollama-native: Best integration for local models; connects and discovers on startup. | Technical setup: Requires Docker knowledge; not beginner-friendly to configure. |
| Provider-agnostic: Works with OpenAI, Anthropic, vLLM, and any compatible API. | Hardware demands: RAG with large documents needs significant RAM; GPU helps a lot. |
| Rich feature set: RAG, tool calling, voice, plugins, multi-user — all included. | Not for high concurrency: Default config suits personal or small-team use, not large deployments. |
| 139k GitHub stars: One of the fastest-moving projects in self-hosted AI. | Governance gaps: Team management and audit logs less developed than AnythingLLM. |
Use Cases
Specific ways to use Open WebUI for your workflow.
Deployment Strategy
Recommended ways to host Open WebUI in your own environment.