Open Webui — AI Agent Review & Live Stats

Live GitHub stats, community sentiment, and trend data for Open Webui. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Apr 1, 2026 • Sentiment updated: Unknown

GitHub Statistics

Why Open Webui Stands Out

Open WebUI stands out from alternatives with its extensible architecture, allowing for seamless integration of various LLM runners and APIs. Its focus on security and customization, with features like granular permissions and user groups, makes it an attractive choice for users who require a high degree of control over their AI environment. Additionally, Open WebUI's support for offline access and PWA capabilities makes it a unique solution for users who need to access their AI models on-the-go. By leveraging its built-in inference engine for RAG, Open WebUI enables users to tap into the potential of Retrieval Augmented Generation, setting it apart from other AI platforms.

Built With

Build a self-hosted AI platform that operates entirely offline — Open WebUI enables this with its extensible and feature-rich architecture, Build a conversational AI model that supports multiple LLM runners like Ollama and OpenAI-compatible APIs — Open WebUI allows for effortless integration of these models, Build a customized AI interface with granular permissions and user groups — Open WebUI provides a secure user environment with detailed user roles and permissions, Build a web-based AI application with responsive design and progressive web app (PWA) capabilities — Open WebUI offers a seamless experience across desktop, laptop, and mobile devices, Build an AI-powered chat environment with hands-free voice and video call features — Open WebUI integrates multiple Speech-to-Text providers and Text-to-Speech engines

Getting Started

  1. Install Open WebUI using Docker or Kubernetes with the command `docker run -p 8000:8000 openwebui/openwebui` or `kubectl apply -f deploy.yaml`
  2. Configure the Open WebUI settings by editing the `config.json` file to customize the AI model and API settings
  3. Integrate OpenAI-compatible APIs by setting the `OPENAI_API_URL` environment variable to your desired API endpoint
  4. Create a new user role and assign permissions using the Open WebUI web interface
  5. Try using the `#` command to load documents directly into chat or add files to your document library to verify that the RAG feature is working

About

User-friendly AI Interface (Supports Ollama, OpenAI API, ...)

Official site: https://openwebui.com

Category & Tags

Category: memory

Tags: ai, llm, llm-ui, llm-webui, llms, mcp, ollama, ollama-webui, open-webui, openai, openapi, rag, self-hosted, ui, webui