[opensourcedex]

Open WebUI is a free, open source ai interaction & interfaces project written in Python and released under a custom open-source licence. It has 152,394 GitHub stars, 22,296 forks and 294 open issues, and was last pushed 21 hours ago. On this registry it ranks #3 of 76 tracked projects in AI Interaction & Interfaces, and is listed as an open source replacement for 1 paid product, with 5 head-to-head comparisons available. It gained 625 stars over the last 6 tracked days.

Open WebUI — One interface for every AI model you run or connect

What is Open WebUI?

What it is

Open WebUI is a self-hosted, open-source AI interface that unifies access to local and cloud-based large language models. It runs entirely in a web browser and supports Ollama for local model hosting alongside any OpenAI-compatible API, including services like LMStudio, GroqCloud, Mistral, and OpenRouter. Built in Python, it functions as a drop-in replacement for proprietary AI platforms, giving users full control over their model infrastructure and data.

It solves the fragmentation problem in AI tooling by providing a single, consistent interface to manage models, tools, agents, and workflows—regardless of where the models are hosted. Users no longer need separate dashboards or SDK integrations for each provider; Open WebUI abstracts API differences and offers shared features like persistent memory, plugins, and scheduling across all connected services.

Key capabilities

  • Connect local Ollama models and any OpenAI-compatible API in the same workspace
  • Granular role-based access control (RBAC) with user groups and custom permissions
  • Plugin system supporting Filters, Actions, Pipes, Tools, and Skills via MCP/MCPO/OpenAPI
  • Build and deploy custom agents by wrapping base models with instructions, tools, and knowledge
  • Persistent memory that carries user-specific context across conversations
  • Real-time shared collaboration spaces called Channels with threads, reactions, and access control
  • Built-in calendar, scheduling, and automation engine with recurring prompt execution

Who uses it and how

  • Developers self-host Open WebUI to test and iterate on local models using Ollama without cloud dependency
  • Teams deploy it internally to standardize AI workflows across departments with shared Channels and RBAC
  • Enterprises use it to integrate proprietary APIs (e.g., vLLM, Mistral) with on-prem models under one UI
  • Individual users run it as a PWA on mobile or desktop for offline, private AI interaction
  • Researchers configure custom agents and automations for repeated experimentation and data logging

Getting started

Install via Docker using openwebui/openwebui:ollama or openwebui/openwebui:cuda tags, or deploy with pip, uv, or Kubernetes using Helm/Kustomize. A hosted option is available at https://openwebui.com.

When to use it — and when not to

Use Open WebUI when you need a unified, self-hosted interface for mixed local/cloud models and want features like persistent memory, plugins, and RBAC without vendor lock-in. Avoid it if you require minimal resource usage—self-hosting demands a database, storage, and optionally SMTP for notifications. It does not replace model inference infrastructure (e.g., you still need Ollama or an API endpoint), and its active development means some features may shift before stable release.

project readme (upstream, from github) — read inline

Open WebUI 👋

GitHub stars GitHub forks GitHub watchers GitHub repo size GitHub language count GitHub top language GitHub last commit Discord

Open WebUI is a home for AI, a self-hosted AI 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 interface for both local and cloud-based models.

Passionate about open-source AI? Join our team →

Open WebUI Demo

[!TIP]
Looking for an Enterprise Plan? – Speak with Our Sales Team Today!

For more information, be sure to check out our Open WebUI Documentation.

Key Features of Open WebUI ⭐

  • 🚀 Effortless Setup: Install seamlessly via pip, uv, Docker, or Kubernetes (kubectl, kustomize, or helm), with :ollama and :cuda tagged images available for container deployments.

  • 🤝 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 mix and match providers freely.

  • 🔐 Granular RBAC & User Groups: Administrators define detailed roles, groups, and permissions, giving each user exactly the access they need. Secure by default, with tailored experiences per group.

  • 🧩 Plugin Support: Extend Open WebUI with Filters, Actions, Pipes, Tools, and Skills. Connect external services through MCP, MCPO, and OpenAPI tool servers. Build custom integrations, rate limits, approval flows, data connections, and more.

  • 🤖 Models & Agents: Wrap any base model with custom instructions, tools, and knowledge to build specialized agents. Supports dynamic variables, per-user/group access control, and community preset imports via Open WebUI Community.

  • 📝 Notes: A dedicated workspace for content outside conversations. Draft with a rich editor, use AI to rewrite selected text, and attach notes to any chat for full-context injection.

  • 📢 Channels: Real-time shared spaces where your team and AI models collaborate in one timeline. Tag models to draft or critique, with threads, reactions, pins, and access control.

  • 🧠 Persistent Memory: The AI remembers facts about you across conversations, carrying context from one chat to the next.

  • ✅ Live Workflow & Message Flow: Watch the AI build and work through checklists in real time. Queue messages while the AI is still responding; they send automatically when it's ready.

  • 📅 Calendar & AI Scheduling: Built-in personal and shared calendars with month/week/day views, recurring events, color coding, attendees, and reminders. Models manage your schedule conversationally through native function calling.

  • ⏱️ Automations: Schedule prompts to run on recurring schedules, with runs surfaced on your calendar and each completed run linking back to the chat it produced.

  • 📱 Responsive Design & PWA: Seamless experience across desktop, laptop, and mobile, with a Progressive Web App for native app-like feel and offline access on localhost.

  • ✒️🔢 Full Markdown and LaTeX Support: Comprehensive Markdown and LaTeX capabilities for enriched interaction.

  • 🎤📹 Hands-Free Voice/Video Call: Integrated voice and video calls with multiple Speech-to-Text providers (Local Whisper, OpenAI, Deepgram, Azure) and Text-to-Speech engines (Azure, ElevenLabs, OpenAI, Transformers, WebAPI).

  • 💾 Persistent Artifact Storage: Built-in key-value storage API for artifacts, enabling journals, trackers, leaderboards, and collaborative tools with personal and shared data scopes.

  • 📚 Local RAG Integration: Retrieval Augmented Generation backed by 9 vector databases and multiple content-extraction engines (Tika, Docling, Document Intelligence, Mistral OCR, PaddleOCR-vl, external loaders). Supports hybrid search (BM25 + vector) with reranking and full-context mode. Load documents into chat or pull them from your library with the # command.

  • 🔍 Web Search for RAG: Search the web through dozens of providers including SearXNG, Google PSE, Brave Search, Kagi, Mojeek, Tavily, Perplexity, Firecrawl, serpstack, serper, Serply, DuckDuckGo, SearchApi, SerpApi, Bing, Jina, Exa, Sougou, Azure AI Search, and Ollama Cloud, injecting results directly into the conversation.

  • 🌐 Web Browsing Capability: Pull websites into chat with the # command followed by a URL, or let the model fetch them on its own when needed.

  • 🎨 Image Generation & Editing: Create and edit images with multiple engines including OpenAI DALL·E, Gemini, ComfyUI (local), and AUTOMATIC1111 (local), supporting both generation and prompt-based editing.

  • ⚙️ Multi-Model Conversations: Engage several models at once, harnessing their individual strengths in parallel for the best possible responses.

  • 📊 Usage Analytics & Model Evaluation: Admin dashboards track message volume, token consumption, and cost across users and models. Evaluate models with a built-in arena, A/B testing, and ELO-based leaderboards.

  • 🗄️ Flexible Database & Storage: Choose SQLite (with optional encryption) or PostgreSQL, and store files locally or on S3, Google Cloud Storage, or Azure Blob Storage.

  • 🧬 Advanced Vector Database Support: Pick from 9 vector databases: ChromaDB, PGVector, Qdrant, Milvus, Elasticsearch, OpenSearch, Pinecone, S3Vector, and Oracle 23ai.

  • 🪪 Enterprise Authentication & Provisioning: Full LDAP/Active Directory integration, SSO via trusted headers and OAuth providers, and SCIM 2.0 automated provisioning for identity providers like Okta, Azure AD, and Google Workspace.

  • ☁️ Cloud-Native File Integration: Native Google Drive and OneDrive/SharePoint file picking for seamless document import from enterprise cloud storage.

  • 🔭 Production Observability: Built-in OpenTelemetry support for traces, metrics, and logs, plugging into your existing monitoring stack.

  • ⚖️ Horizontal Scalability: Redis-backed session management and WebSocket support for multi-worker, multi-node deployments behind load balancers.

  • 🌐🌍 Multilingual Support: Use Open WebUI in your preferred language with i18n support. We're actively seeking contributors to expand language coverage!

  • 🌟 Continuous Updates: We're committed to improving Open WebUI with regular updates, fixes, and new features.

  • 🛡️ Transparent Security Process: Security reports are triaged, fixed, and published as open advisories through a documented responsible-disclosure process. See our Security Policy.

Want to learn more about Open WebUI's features? Check out our Open WebUI documentation for a comprehensive overview!

The Open WebUI Ecosystem 🌐

Open WebUI is the core, surrounded by companion apps and infrastructure that extend what your AI can do, where it can reach, and how you run it:

  • 💻 Open WebUI Computer (open-webui/computer): A standalone, mobile-first computer and coding agent that runs on the machine you own. Files, terminal, and git in a browser tab, reachable from your phone. Connect it into Open WebUI as a model, or reach it from Telegram, WhatsApp, and more.

  • ⚡ Open Terminal and Terminals (Enterprise) (open-webui/open-terminal & open-webui/terminals): A self-hosted computing environment that plugs into Open WebUI, giving the AI a place to write code, run it, read output, fix errors, and iterate inside the chat. Terminals gives you per-user isolated containers with separate credentials, resource limits, and network rules. Automatic lifecycle management on Docker or Kuberne

readme truncated — read the full docs on github

Frequently asked questions

Is Open WebUI free to use?

Open WebUI is open source. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does Open WebUI do?

One interface for every AI model you run or connect

What is Open WebUI written in?

Open WebUI is primarily written in Python. Its source is publicly available at https://github.com/open-webui/open-webui, and it has 152,394 GitHub stars.

What is a good open source alternative to OpenAI API?

Open WebUI is one of the open source options listed as an alternative to OpenAI API. Compare licences, stars and activity side by side on the Open WebUI profile.