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open-webui

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Open WebUI是一款可完全离线自托管的友好型AI操作平台，支持对接Ollama、OpenAI兼容API，内置RAG等能力，可快速搭建企业自用AI服务入口。

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AI 依据上游资料解读 · 2026/8/29

Open WebUI是一款可完全离线自托管的友好型AI操作平台，支持对接Ollama、OpenAI兼容API，内置RAG等能力，可快速搭建企业自用AI服务入口。

解决什么问题
不少企业搭建内部自用AI平台时，面临多厂商大模型对接繁琐、知识库整合成本高、权限管控和团队协作功能缺失、数据上传公共AI服务存在泄露风险等痛点。
适合什么团队
适合有自托管AI服务需求、需要统一多模型入口、要做内部知识库问答、对数据安全性要求高的企业IT部门、业务团队使用。
使用前注意
当前项目未标注开源许可证，商用前需确认授权规则；pip部署需使用Python 3.11版本，部分Docker环境可能需要额外配置。

本页用于缩短初步筛选时间，不构成技术、采购或法律结论。 正式使用前请在真实业务数据上验证，并以官方说明与许可证为准。

项目导读

从官方资料看清能力、部署与采用边界

AI 翻译整理 · 保留官方来源

以下内容依据项目公开 README 或模型卡翻译整理，代码、命令和产品名保持原样。

项目定位

Open WebUI是一款可完全离线自托管的AI操作平台，主打易用性，支持对接多种本地大模型、OpenAI兼容的第三方大模型API，内置RAG能力，可作为企业内部统一的AI服务入口，所有数据可完全保存在企业自有环境中，避免外泄。

核心业务可用能力

  1. 多模型统一接入：可同时对接本地Ollama运行的大模型，以及LMStudio、GroqCloud、Mistral、OpenRouter等符合OpenAI规范的API服务，业务人员无需切换不同平台即可调用不同厂商的大模型能力。
  2. 细粒度权限管控：管理员可自定义角色、用户组和访问权限，不同团队、不同岗位的员工仅能访问授权的模型、知识库和功能，默认采用安全配置。
  3. RAG知识库问答：内置RAG（检索增强生成，可让大模型调用指定的知识库内容生成回答，避免信息偏差）引擎，支持对接9种主流向量数据库，可导入企业内部文档、云存储文件，也支持接入数十种网页搜索来源，让大模型基于企业指定的信息回答问题。
  4. 团队协作功能：提供共享实时空间、笔记专区、公共日历、AI日程调度、定时任务触发等功能，支持团队共同调用AI完成内容创作、方案评审等工作，对话内容可跨会话保存上下文。
  5. 多模态交互：支持语音/视频通话、图片生成与编辑、LaTeX公式渲染等能力，可满足内容创作、代码开发、数据分析等不同场景的交互需求。
  6. 企业级适配：支持LDAP/Active Directory集成、OAuth单点登录、SCIM自动身份同步，可对接Google Drive、OneDrive/SharePoint等企业常用云存储，内置用量统计、模型效果评估看板，方便管理员管理。

典型使用方式

企业部署完成后，可根据业务需求完成配置后交付团队使用：

  • 搭建内部知识库问答平台：上传企业内部制度、产品说明、项目文档等资料，员工可直接提问获取准确答案，减少重复咨询。
  • 多团队AI协作空间：为不同业务组配置独立的模型、知识库权限，团队可在共享空间内共同调用AI完成内容创作、方案打磨等工作。
  • 自定义业务AI助手：基于基础大模型添加专属指令、工具和知识库，搭建面向特定业务场景的AI agent，比如客服助手、代码助手、运营分析助手等。

部署要求

当前提供两种便捷部署方式：

此外也支持Kubernetes部署，可满足企业大规模生产环境的水平扩展需求。

  1. Python pip部署：需提前安装Python 3.11版本，执行pip install open-webui完成安装后，运行open-webui serve即可启动服务，默认访问地址为http://localhost:8080。
  2. Docker部署：可直接使用官方镜像快速部署，部分特殊Docker环境可能需要额外配置，遇到连接问题可参考官方文档排查。

配套生态与商用说明

Open WebUI提供多个周边配套工具扩展能力：

项目当前未标注开源许可证，企业商用前需确认授权规则；官方也提供企业版方案，包含定制化主题、SLA支持、长期维护版本等增值服务，有需求可联系官方团队咨询。

  • oikb：支持从GitHub、Confluence、ServiceNow、Salesforce、Jira、Slack、Notion等45+主流工具同步内容到知识库，无需手动上传。
  • Open Terminal：为AI提供独立的代码运行环境，可在对话内直接完成代码编写、运行、调试。
  • 原生桌面端：支持Windows、macOS、Linux系统，可作为本地应用运行，支持全局唤醒、截图、语音输入等功能。

采用建议

如果你的企业有数据安全要求，需要将AI服务完全部署在自有环境中，同时需要对接多种大模型、整合内部知识库，不需要额外投入大量开发资源搭建AI界面，可优先评估Open WebUI是否符合需求；部署前建议先测试核心功能是否匹配业务场景，商用前确认授权规则。

可核对的事实层

官方资料与来源

查看来源 →
  • ai
  • llm
  • llm-ui
  • llm-webui
  • llms
  • mcp
  • ollama
  • ollama-webui
  • open-webui
  • openai
  • openapi
  • rag
默认分支main
关注仓库649
复刻次数21.9k
开放议题220
近期更新2026/8/27
仓库状态未标记归档
上游部署线索
## How to Install 🚀

### Installation via Python pip 🐍

Open WebUI can be installed using pip, the Python package installer. Before proceeding, ensure you're using **Python 3.11** to avoid compatibility issues.

1. **Install Open WebUI**:
   Open your terminal and run the following command to install Open WebUI:

   ```bash
   pip install open-webui
   ```

2. **Running Open WebUI**:
   After installation, you can start Open WebUI by executing:

   ```bash
   open-webui serve
   ```

This will start the Open WebUI server, which you can access at [http://localhost:8080](http://localhost:8080)

### Quick Start with Docker 🐳

> [!NOTE]  
> Please note that for certain Docker environments, additional configurations might be needed. If you encounter any connection issues, our detailed guide on [Open WebUI Documentation](https://docs.openwebui.com/) is ready to assist you.

> [!WARNING]
> W

该片段来自项目 README，仅用于初步判断；实际部署请以官方文档为准。

项目官网查看 Releases

官方图片与演示已排除二维码、联系方式、赞助付款图和常见徽章
Open WebUI Banner
Open WebUI Banner
Open WebUI Demo
Open WebUI Demo
核对上游原始说明节选

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

Open WebUI 👋

GitHub stars GitHub forks GitHub watchers GitHub repo size GitHub language count GitHub top language GitHub last commit Discord [](https://github.com/sponsors/open-webui)

Open WebUI Banner

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with built-in inference engine for RAG, making it a powerful AI deployment solution.

Passionate about open-source AI? Join our team →

Open WebUI Demo

[!TIP]
Looking for an Enterprise Plan? – Speak with Our Sales Team Today!
Get enhanced capabilities, including custom theming and branding, Service Level Agreement (SLA) support, Long-Term Support (LTS) versions, and more!

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 Kubernetes.
  • 🔄 oikb (open-webui/oikb): Feed your Knowledge Bases from 45+ sources (GitHub, Confluence, ServiceNow, Salesforce, Jira, Slack, SharePoint, Notion, and more), keeping the tools your team already uses continuously in sync.
  • 🖥️ Native Desktop App (open-webui/desktop): Run Open WebUI as a native app on macOS, Windows, and Linux. System-wide Spotlight chat bar with screenshot capture, push-to-talk voice, and optional fully-local inference via a built-in llama.cpp engine.

Want to learn more? Check out our Open WebUI documentation for more details!

---

We are incredibly grateful for the generous support of our sponsors. Their contributions help us to maintain and improve our project, ensuring we can continue to deliver quality work to our community. Thank you!

How to Install 🚀

Installation via Python pip 🐍

Open WebUI can be installed using pip, the Python package installer. Before proceeding, ensure you're using Python 3.11 to avoid compatibility issues.

Open your terminal and run the following command to install Open WebUI:

  1. Install Open WebUI:
   pip install open-webui

After installation, you can start Open WebUI by executing:

  1. Running Open WebUI:
   open-webui serve

This will start the Open WebUI server, which you can access at [http://localhost:8080](http://localhost:808