Open WebUI 本地AI聊天界面
open-webui 是一款MCP 工具，可直接接入 Claude 等 AI 客户端（GitHub 137k⭐）。开源MCP工具：User-friendly AI Interface (Supports Ollama, OpenAI API, ...)。⭐136.8k · Python。配置方法：将 MCP 服务器条目添加至 claude_desktop_config.json，重启 Claude Desktop 即可使用。AI Skill Hub 编辑推荐，适合希望提升 AI 工作流效率的开发者和运营者。
📚 深度解析
**为什么要使用开源工具而非商业 SaaS？**
对于个人开发者和有隐私需求的用户，本地部署的开源工具意味着数据不离本机，不受第三方服务商的数据政策约束。同时，开源工具通常没有使用次数限制和月度费用，一次安装即可长期使用，对于高频使用场景的总拥有成本（TCO）远低于订阅制商业工具。
**安装与环境准备**
Open WebUI 本地AI聊天界面 依赖 Python 运行环境。建议通过 pyenv（Python）或 nvm（Node.js）管理 Python 版本，避免全局环境污染。对于新手用户，推荐先创建虚拟环境（python -m venv venv && source venv/bin/activate），再安装依赖，这样即使出现问题也可以随时删除虚拟环境重新开始，不影响系统稳定性。
**社区与维护**
GitHub Issue 和 Discussion 是获取帮助的最快渠道。在提问前建议先检查 Closed Issues（已关闭的问题），大多数常见问题都已有解答。遇到 Bug 时，提供 pip list 的输出、完整错误堆栈和最小可复现示例，能显著提高开发者响应速度。AI Skill Hub 将持续追踪 Open WebUI 本地AI聊天界面 的版本更新，及时通知重要功能变化。
📋 工具概览
Open WebUI 本地AI聊天界面 是一款基于 Python 开发的开源工具，专注于 Web UI、大模型、本地部署 等核心功能。作为 GitHub 开源项目，它拥有活跃的社区支持和持续的版本迭代，代码完全透明可审计，支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流，都能提供稳定可靠的解决方案。
📖 中文文档
Open WebUI 本地AI聊天界面 是一款基于 Python 开发的开源工具，专注于 Web UI、大模型、本地部署 等核心功能。作为 GitHub 开源项目，它拥有活跃的社区支持和持续的版本迭代，代码完全透明可审计，支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流，都能提供稳定可靠的解决方案。
- 开源免费，支持本地部署，数据完全自主可控
- 活跃的 GitHub 开源社区，持续迭代更新
- 提供详细文档和使用示例，新手友好
- 支持自定义配置，灵活适配不同使用环境
- 可作为基础组件集成进现有技术栈或进行二次开发
- 本地部署运行，保护数据隐私，满足合规要求
- 自定义集成到现有系统，扩展技术栈能力
- 作为开源基础组件进行商业化二次开发
# 方式一：pip 安装（推荐）
pip install open-webui
# 方式二：虚拟环境安装（推荐生产环境）
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install open-webui
# 方式三：从源码安装（获取最新功能）
git clone https://github.com/open-webui/open-webui
cd open-webui
pip install -e .
# 验证安装
python -c "import open_webui; print('安装成功')"
- 访问 GitHub 仓库页面
- 按照 README 文档完成依赖安装
- 根据系统环境完成初始化配置
- 参考官方示例或文档开始使用
- 遇到问题可在 GitHub Issues 中查找解答
# 命令行使用
open-webui --help
# 基本用法
open-webui input_file -o output_file
# Python 代码中调用
import open_webui
# 示例
result = open_webui.process("input")
print(result)
# open-webui 配置文件示例（config.yml） app: name: "open-webui" debug: false log_level: "INFO" # 运行时指定配置文件 open-webui --config config.yml # 或通过环境变量配置 export OPEN_WEBUI_API_KEY="your-key" export OPEN_WEBUI_OUTPUT_DIR="./output"
Open WebUI 👋
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 →
[!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
:ollamaand:cudatagged 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, andOllama 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!
What's Next? 🌟
Discover upcoming features on our roadmap in the Open WebUI Documentation.
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:
pip install open-webui
2. Running Open WebUI: After installation, you can start Open WebUI by executing:
open-webui serve
This will start the Open WebUI server, which you can access at 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 is ready to assist you.
[!WARNING] When using Docker to install Open WebUI, make sure to include the -v open-webui:/app/backend/data in your Docker command. This step is crucial as it ensures your database is properly mounted and prevents any loss of data.
[!TIP] If you wish to utilize Open WebUI with Ollama included or CUDA acceleration, we recommend utilizing our official images tagged with either:cudaor:ollama. To enable CUDA, you must install the Nvidia CUDA container toolkit on your Linux/WSL system.
Installation with Default Configuration
- If Ollama is on your computer, use this command:
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
- If Ollama is on a Different Server, use this command:
To connect to Ollama on another server, change the OLLAMA_BASE_URL to the server's URL:
docker run -d -p 3000:8080 -e OLLAMA_BASE_URL=https://example.com -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
- To run Open WebUI with Nvidia GPU support, use this command:
docker run -d -p 3000:8080 --gpus all --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:cuda
Installation for OpenAI API Usage Only
- If you're only using OpenAI API, use this command:
docker run -d -p 3000:8080 -e OPENAI_API_KEY=your_secret_key -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
Installing Open WebUI with Bundled Ollama Support
This installation method uses a single container image that bundles Open WebUI with Ollama, allowing for a streamlined setup via a single command. Choose the appropriate command based on your hardware setup:
- With GPU Support: Utilize GPU resources by running the following command:
docker run -d -p 3000:8080 --gpus=all -v ollama:/root/.ollama -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:ollama
- For CPU Only: If you're not using a GPU, use this command instead:
docker run -d -p 3000:8080 -v ollama:/root/.ollama -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:ollama
Both commands facilitate a built-in, hassle-free installation of both Open WebUI and Ollama, ensuring that you can get everything up and running swiftly.
After installation, you can access Open WebUI at http://localhost:3000. Enjoy! 😄
Other Installation Methods
We offer various installation alternatives, including non-Docker native installation methods, Docker Compose, Kustomize, and Helm. Visit our Open WebUI Documentation or join our Discord community for comprehensive guidance.
Keeping Your Docker Installation Up-to-Date
Check our Updating Guide available in our Open WebUI Documentation.
Troubleshooting
Encountering connection issues? Our Open WebUI Documentation has got you covered. For further assistance and to join our vibrant community, visit the Open WebUI Discord.
Open WebUI: Server Connection Error
If you're experiencing connection issues, it’s often due to the WebUI docker container not being able to reach the Ollama server at 127.0.0.1:11434 (host.docker.internal:11434) inside the container . Use the --network=host flag in your docker command to resolve this. Note that the port changes from 3000 to 8080, resulting in the link: http://localhost:8080.
Example Docker Command:
docker run -d --network=host -v open-webui:/app/backend/data -e OLLAMA_BASE_URL=http://127.0.0.1:11434 --name open-webui --restart always ghcr.io/open-webui/open-webui:main成熟的开源AI Web UI项目，生态完整、社区活跃、功能丰富。星标高达13.6万，说明认可度极高。适合企业和个人自建AI助手。
- 构建多智能体协作系统的 Agent 开发者
- 构建企业知识库 / RAG 检索应用的团队
- 需要从图片、PDF 提取文字的文档自动化场景
- 跨境业务、多语言内容运营团队
- 做语音类 AI 产品的开发者
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- 本地部署优先选 GGUF 量化模型，节省显存并保持响应速度
- 分块大小建议 256-512 tokens，向量库优选 pgvector 或 Qdrant
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
- embedding 模型与查询模型不一致导致检索失效
- 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
- Python 依赖冲突：建议用 venv / uv 隔离环境
- Docker：open-webui 提供官方镜像，docker compose up 一键启动
- CLI：直接 npm install -g / pip install，命令行调用
- 本地部署：CPU 8GB 起，GPU 推荐 16GB+ 显存
- 云端托管：可放在 Vercel / Railway / Fly.io 等 PaaS 平台
⚡ 核心功能
- 开源免费，支持本地部署，数据完全自主可控
- 活跃的 GitHub 开源社区，持续迭代更新
- 提供详细文档和使用示例，新手友好
- 支持自定义配置，灵活适配不同使用环境
- 可作为基础组件集成进现有技术栈或进行二次开发
- 构建多智能体协作系统的 Agent 开发者
- 构建企业知识库 / RAG 检索应用的团队
- 需要从图片、PDF 提取文字的文档自动化场景
- 跨境业务、多语言内容运营团队
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- 本地部署优先选 GGUF 量化模型，节省显存并保持响应速度
- 分块大小建议 256-512 tokens，向量库优选 pgvector 或 Qdrant
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
- embedding 模型与查询模型不一致导致检索失效
- 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
👥 适合人群
🎯 使用场景
- 本地部署运行，保护数据隐私，满足合规要求
- 自定义集成到现有系统，扩展技术栈能力
- 作为开源基础组件进行商业化二次开发
⚖️ 优点与不足
- +GitHub 136.8k Star，社区高度认可
- +完全开源免费，无授权费用
- +本地部署，数据完全自主可控
- +开发者社区支持，遇问题可查可问
- −安装和初始配置可能需要一定技术基础
- −功能完整性通常不如成熟商业产品
- −技术支持主要依赖开源社区，响应速度不稳定
该工具使用 NOASSERTION 协议，商用场景请仔细阅读协议条款，必要时咨询法律意见。
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。
🔗 相关工具推荐
❓ 常见问题 FAQ
AI Skill Hub 点评：Open WebUI 本地AI聊天界面 的核心功能完整，质量优秀。对于AI 技术爱好者来说，这是一个值得纳入个人工具库的选择。建议先在非生产环境试用，再逐步推广。
| 原始名称 | open-webui |
| 原始描述 | 开源MCP工具：User-friendly AI Interface (Supports Ollama, OpenAI API, ...)。⭐136.8k · Python |
| Topics | Web UI大模型本地部署开源 |
| GitHub | https://github.com/open-webui/open-webui |
| License | NOASSERTION |
| 语言 | Python |
收录时间：2026-05-13 · 更新时间：2026-05-30 · License：NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。