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Open WebUI

Self‑hosted AI platform with offline LLM, RAG, and extensible UI

AI Personal Assistant Software

Open WebUI delivers a feature‑rich, offline‑first AI interface supporting Ollama, OpenAI‑compatible APIs, RAG, and customizable plugins, with easy Docker, pip, or Kubernetes deployment.

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Overview

Overview

Open WebUI is a self‑hosted AI platform designed for teams that require data privacy and offline operation. It supports local model runners such as Ollama and any OpenAI‑compatible API, letting you run diverse large language models behind your firewall.

Capabilities & Extensibility

The UI includes full Markdown and LaTeX rendering, voice/video calls, PWA support, and integrated Retrieval‑Augmented Generation that can pull from local documents or web searches. Granular role‑based access control, SCIM 2.0 provisioning, and a plugin‑based pipeline framework let you add custom Python tools, rate limiting, translation, or any bespoke logic.

Deployment Options

Install with a single pip install open-webui command, launch via Docker images, or orchestrate with Kubernetes (helm, kustomize, or plain manifests). The platform ships with ready‑to‑use images for both CPU and CUDA environments, making scaling from a laptop to a cluster straightforward.

Highlights

One‑click deployment via Docker, pip, or Kubernetes
Integrated RAG with local document upload and web search
Granular RBAC with SCIM 2.0 for enterprise identity providers
Plugin and pipeline framework for custom Python functions

Pros

  • Operates fully offline, preserving data privacy
  • Broad model support including Ollama and OpenAI‑compatible APIs
  • Rich interactive UI with markdown, LaTeX, voice/video, and PWA
  • Strong security controls through RBAC and SCIM provisioning

Considerations

  • Self‑hosting requires infrastructure management
  • Advanced enterprise features are gated behind a paid plan
  • Feature‑dense UI may have a learning curve for newcomers
  • Limited official support compared to commercial SaaS alternatives

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Fit guide

Great for

  • Organizations that need on‑premise AI for privacy compliance
  • Teams managing heterogeneous model stacks across environments
  • Developers building custom AI workflows with Python extensions
  • Edge deployments where internet connectivity is unreliable

Not ideal when

  • Hobbyists without access to Docker or Kubernetes resources
  • Projects that prefer a turnkey cloud SaaS solution
  • Environments lacking GPU or sufficient compute for local models
  • Users requiring out‑of‑the‑box analytics dashboards

How teams use it

Internal Knowledge Base Assistant

Employees retrieve company documents via RAG‑enhanced chat

Multilingual Customer Support Bot

Real‑time translation and responses using integrated language models

Prototype Voice‑Enabled AI Agent

Hands‑free interaction through built‑in voice and video calls

Custom Function Calling Service

Deploy pure Python functions as LLM tools via the BYOF framework

Tech snapshot

JavaScript32%
Svelte31%
Python29%
TypeScript5%
CSS3%
Shell1%

Tags

openapiaiself-hostedllmsollama-webuillmollamaragmcpuillm-uiwebuillm-webuiopenaiopen-webui

Frequently asked questions

How can I install Open WebUI?

You can install via pip (`pip install open-webui`), Docker images, or Kubernetes manifests (helm, kustomize, or plain yaml).

Can Open WebUI run completely offline?

Yes, when using local model runners like Ollama you can operate without any external internet connection.

What authentication and user management options are available?

Open WebUI offers role‑based access control, granular permissions, and SCIM 2.0 integration for automated provisioning with IdPs such as Okta or Azure AD.

How do I add external models?

Configure an OpenAI‑compatible API URL to connect to services like LMStudio, GroqCloud, Mistral, or OpenRouter, or use Ollama for local models.

Is there an enterprise offering?

Yes, the enterprise plan provides custom theming, SLA support, long‑term support versions, and additional capabilities.

Project at a glance

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