Open-webui
by open-webui
Self-Hosted AI Chat Interface with Multi-Model Support
Deploy your own ChatGPT-like interface supporting Ollama, OpenAI, and multiple LLM providers with RAG capabilities and model customization.
- 121,330+ GitHub stars
- Built with Python
- Multi-provider support for Ollama, OpenAI, and other LLM backends
- Other license
About This Project
Open WebUI transforms how developers and teams interact with large language models by providing a polished, self-hosted chat interface that works seamlessly with multiple AI backends. Whether you're running local models through Ollama or connecting to cloud APIs like OpenAI, this platform gives you complete control over your AI infrastructure without vendor lock-in.
Built with privacy and flexibility in mind, the project enables Retrieval-Augmented Generation (RAG) for grounding responses in your own documents, multi-user authentication, and conversation management. The intuitive interface mirrors familiar chat applications while adding powerful features like prompt templates, model parameter tuning, and API integrations through the Model Context Protocol (MCP).
What sets this solution apart is its production-ready architecture combined with ease of deployment. Run it locally with Docker, host it on your infrastructure, or scale it for team use. The active community and extensive plugin ecosystem make it adaptable to workflows ranging from personal AI assistants to enterprise knowledge bases.
With over 120,000 stars, Open WebUI has become the go-to choice for developers who want a professional AI interface without sacrificing control, customization, or data sovereignty.
Key Features
- Multi-provider support for Ollama, OpenAI, and other LLM backends
- Built-in RAG system for document-based question answering
- Self-hosted deployment with Docker and authentication management
- Model Context Protocol (MCP) integration for extended capabilities
- Customizable prompts, model parameters, and conversation workflows
How You Can Use It
Building private AI assistants for sensitive business data without cloud dependencies
Creating internal knowledge bases with RAG to query company documentation
Running local LLM experiments with Ollama while maintaining a clean UI
Deploying team-wide AI tools with role-based access and conversation history
Prototyping AI applications with switchable models and prompt engineering tools
Who Is This For?
Developers, DevOps engineers, and organizations seeking self-hosted AI solutions with multi-model flexibility and privacy control