Open WebUI
Open WebUI is a home for AI, a self-hosted platform that's extensible, feature-rich, user-friendly, and built to run entirely offline. With support for Ollama and OpenAI-compatible APIs, it gives you a powerful, provider-agnostic platform for both local and cloud-based models.
Quick Start
- Docker
- pip
- uv
- Desktop
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:mainThen open http://localhost:3000.

For GPU support, Docker Compose, and more → Full Docker guide
pip install open-webui
open-webui serveThen open http://localhost:8080.
curl -LsSf https://astral.sh/uv/install.sh | sh
DATA_DIR=~/.open-webui uvx --python 3.11 open-webui@latest serveThen open http://localhost:8080.
Download the desktop app from github.com/open-webui/desktop. It runs Open WebUI natively on your system without Docker or manual setup.
For production deployments, install via Docker or Python.
Installed Open WebUI but not sure where to start? The Essentials for Open WebUI guide covers the six things every new user needs to know: plugins, tool calling, task models, context management, RAG, and Open Terminal.
Getting Started
- Quick Start: Docker, Python, Kubernetes install options
- Connect a Provider: Ollama, OpenAI, Anthropic, vLLM, and more
- Essentials for Open WebUI: Start here after your first install. Plugins, tool calling, task models, context management, RAG, Open Terminal.
- Connect an Agent: Open WebUI Computer, Hermes Agent, OpenClaw, and other autonomous AI agents
- Updating: Keep your instance current
- Development Branch: Help test the latest changes before stable release
- Advanced Topics: Scaling, logging, and advanced configuration
Explore
- Features: Discover what Open WebUI can do
- Tutorials: Step-by-step guides
- FAQ: Common questions answered
- Troubleshooting: Fix common issues
- Reference: Environment variables and API details
Open WebUI Computer
Open WebUI Computer is an agent harness that runs on your real machine. You install one app, add AI (an API key, a local model, or a coding-agent subscription you already have like Claude Code or Codex), and it works on your actual files and projects, from research and writing to code, with approvals and plan mode. It doesn't spin up a throwaway sandbox and hand you a diff. The file the agent edits is the file on your disk.
Because it's your whole machine, you get the rest for free: files, editor, terminal, and git in any browser, from your desk or your phone; an assistant you can message from Telegram or WhatsApp; scheduled agents that report back to you. Everything runs locally on hardware you own, nothing hosted elsewhere.
Computer and Open WebUI are one ecosystem moving at two speeds, on purpose. Open WebUI is the stable platform: enterprise-ready, multi-user, what teams and organizations deploy and rely on. Computer moves faster: new capabilities are built and shipped there first, hardened in daily use, and graduated into Open WebUI where they fit. If you want the bleeding edge of what we're building, it lands in Computer first.
- New to it? What is Computer? · Quickstart · Use cases
- Already run Open WebUI? Use a Computer workspace as a model in Open WebUI
Also by Open WebUI
- open-terminal: Give your AI a real computer. Sandboxed terminal, file browser, and code execution for Open WebUI.
- oikb: Keep your Open WebUI knowledge bases in sync. Watches local folders, GitHub repos, S3 buckets, Confluence, and 40+ other sources.
- mcpo: MCP-to-OpenAPI proxy. Use any MCP tool server with Open WebUI (or any OpenAPI client) without custom glue code.
Enterprise
Need custom branding, SLA support, or Long-Term Support (LTS) versions? → Learn about Enterprise plans
Get Involved
- Contributing: Help build Open WebUI
- Development Setup: Run the project locally from source
- Discord: Join the community
- GitHub: Report issues, submit PRs
- Careers: Join our team
Sponsors
Acknowledgements
For LLMs and coding agents
Machine-readable entry points to this documentation:
- llms.txt: curated index of every docs page with short descriptions.
- llms-full.txt: every docs page concatenated into a single Markdown file.
- agents.txt: concise instructions for agents using these docs.
- api/search?q=YOUR_QUERY: deterministic docs search.
All files are generated fresh on every deploy.


