Lite 模式资源占用低但不支持文档索引,需要 RAG 必须用 Standard 模式;Standard 模式额外依赖向量与关键词索引、后台任务容器、模型推理服务以及 Redis 和 MinIO;需自行选择并配置嵌入模型与 LLM 提供方,本地或第三方均可。

onyx
onyx-dot-app活跃维护开箱即用的开源 AI 对话平台,支持接入任意 LLM,内置 RAG 与企业级搜索,适合团队自建带知识库的聊天助手。
Open Source AI Platform - AI Chat with advanced features that works with every LLM
curl -fsSL https://onyx.app/install_onyx.sh | bashREADME 未给出具体显存或 GPU 型号要求;Lite 模式内存占用低于 1GB,但无法索引文档;Standard 模式需额外运行模型推理服务,可选用本地嵌入模型与 LLM。
自托管团队知识层,把 50+ 应用数据索引成上下文供 LLM 与 Agent 检索
开箱即用的开源 AI 对话平台,支持接入任意 LLM,内置 RAG 与企业级搜索,适合团队自建带知识库的聊天助手。
核心能力
- 连接 50+ 应用索引文档与元数据、权限
- 用混合索引加定制 Agent 框架做 Agentic RAG
- 支持多步 Deep Research 生成深度报告
- 可接入 Serper、Brave、SearXNG 等实时网页搜索
- 提供沙箱执行代码并生成可下载 Artifacts
容易踩的坑
- v5.0.52026-11-09 · 2026-11-09 18:22 UTC
查看更新说明
See the assets to download this version and install.
What's Changed
- fix(tracing): send the Langfuse v4 ingestion header on OTLP exports (#17115) to release v5.0 by @onyx-cherry-pick[bot] in https://github.com/onyx-dot-app/onyx/pull/17129
- fix(craft): backport sandbox browser security to v5.0 by @wenxi-onyx in https://github.com/onyx-dot-app/onyx/pull/17230
- feat(telemetry): report the user count and answer votes to the fleet (#16867) to release v5.0 by @onyx-cherry-pick[bot] in https://github.com/onyx-dot-app/onyx/pull/17486
Full Changelog: https://github.com/onyx-dot-app/onyx/compare/v5.0.4...v5.0.5
- v5.1.1最新正式版2026-11-09 · 2026-11-09 18:21 UTC
See the assets to download this version and install.
What's Changed
- fix(tracing): send the Langfuse v4 ingestion header on OTLP exports (#17115) to release v5.1 by @onyx-cherry-pick[bot] in https://github.com/onyx-dot-app/onyx/pull/17118
- fix(llm): strip Gemini-unsupported tool schema keywords on OpenAI-compatible routes (#17130) to release v5.1 by @devin-ai-integration[bot] in https://github.com/onyx-dot-app/onyx/pull/17159
- feat(telemetry): report the user count and answer votes to the fleet (#16867) to release v5.1 by @onyx-cherry-pick[bot] in https://github.com/onyx-dot-app/onyx/pull/16892
- fix(craft): backport sandbox browser security to v5.1 by @wenxi-onyx in https://github.com/onyx-dot-app/onyx/pull/17488
Full Changelog: https://github.com/onyx-dot-app/onyx/compare/v5.1.0...v5.1.1
- agent-plugin/v0.1.0Onyx agent plugin v0.1.02026-11-09 · 2026-11-09 17:18 UTC
查看更新说明
Install with
/plugin marketplace add https://raw.githubusercontent.com/onyx-dot-app/onyx/main/extensions/agent-plugin/.claude-plugin/marketplace.jsonthen/plugin install onyx@onyx.sha256: 9d880088566ce1e7bfdc3082f0094643351a12273887bb32240205736bfc595d
- helm/onyx-0.9.322026-11-06 · 2026-11-06 22:22 UTC
查看更新说明
Onyx application and Craft sandbox deployment chart
- claude-code-plugin/v0.1.0Onyx plugin for Claude Code v0.1.02026-11-06 · 2026-11-06 18:15 UTC
查看更新说明
Install with
/plugin marketplace add https://raw.githubusercontent.com/onyx-dot-app/onyx/main/extensions/claude-code/.claude-plugin/marketplace.jsonthen/plugin install onyx@onyx.sha256: 365352083ee3d305a92ed111f7272fc5202dedf1e4dade9a4435c58f7b56cfde
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
Onyx - The context layer powered by all your apps
"LLMs know about everything public, but what if it could also know what's going on in our team? I want an AI coworker, not an AI new hire."
Onyx is the knowledge/context layer for your team and AI agents.
Onyx connects to your application to index and surface knowledge from 50+ applications while protecting your data sovereignty through flexible self-hosted deployments.
Beyond search, Onyx enables LLMs with advanced features like web search, sandboxes, skills, and more.
[!TIP] Deploy with a single command:
curl -fsSL https://onyx.app/install_onyx.sh | bash

How does Onyx work
Onyx creates a representation of knowledge across all connected sources. It pulls data along with metadata, permissions, etc. and ingests it so that the information is easily accessible for downstream use cases.
Compared to MCP based searches and index-free approaches, Onyx provides a more reliable, low latency, and low cost context for any given query whether it's a simple keyword query or a complex research task.
Instead of an agent coordinating and iteratively searching dozens of MCP and burning many thousands of tokens, Onyx fetches the context across its internal representation instantly and filters down to only the most relevant ground truth documents.
⭐ Features
- 🔍 Agentic RAG: Get best in class search and answer quality based on hybrid index + a custom agent harness tuned for information retrieval.
- 🔬 Deep Research: Get in depth reports with a multi-step research flow.
- 🤖 Custom Agents: Build AI Agents with unique subsets of knowledge, custom instructions, and the ability to take actions.
- 🌍 Web Search: Augment internal knowledge with live web search.
- Supports Serper, Google PSE, Brave, SearXNG, and others.
- Comes with an in house web crawler and support for Firecrawl/Exa.
- ▶️ External Actions & MCP: Let Onyx agents take actions in external applications to complete tasks end to end.
- 💻 Secure Sandbox: Execute code and work with intermediate artifacts in a sandbox for complex workflows.
- 📄 Artifacts: Generate documents, graphics, and other downloadable artifacts.
- 🎙️ Voice Mode: Interact with Onyx via text-to-speech and speech-to-text.
Onyx supports all major LLM providers, both self-hosted (like Ollama, LiteLLM, vLLM, etc.) and proprietary (like Anthropic, OpenAI, Gemini, etc.).
To learn more - check out our docs!
Security and Data Processing

When connecting up your organization's knowledge, it's critical that this sensitive IP is not leaked to the wrong parties both external and internal.
Onyx provides an air-gappable, self-hosted deployment where the document index, database, and processing all happen within a self-contained set of services.
You can also choose a trusted embedding model and LLM provider (both of which can also run locally).
Access Onyx from anywhere
The same security and fine grained permissions apply no matter where the question comes from.
- Web and desktop app - Ask questions, interface with Onyx AI agents, and everything else in the feature list above.
- Slack and Discord bot - Get answers directly in Slack or Discord from a bot connected to your org's knowledge.
- MCP server - Point Claude Code, Open Code, Codex, or any MCP client at Onyx. Your AI agents get company context with the same access controls as the person running them.
- Chrome extension - Query Onyx from any tab with context from the page, directly in Chrome.
- Embeddable Widget - Easily add Onyx functionality to your app or website.
🚀 Deployment Modes
Onyx supports deployments in Docker, Kubernetes, Helm/Terraform and provides guides for major cloud providers. Detailed deployment guides found here.
Onyx supports two separate deployment options: standard and lite.
Standard Onyx
The complete feature set of Onyx which is recommended for serious users and larger teams. Additional components not included in Lite mode:
- Vector + Keyword index for RAG.
- Background containers to run job queues and workers for syncing knowledge from connectors.
- AI model inference servers to run deep learning models used during indexing and inference.
- Performance optimizations for large scale use via in memory cache (Redis) and blob store (MinIO).
Onyx Lite
The Lite mode can be thought of as a lightweight AI Chat UI. It requires less resources (under 1GB memory) and runs a less complex stack but is not capable of indexing documents. It is great for users who want to test out the Onyx UI quickly or for teams who are only interested in the Chat UI and Agents functionalities.
[!TIP]
To try Onyx for free without deploying, visit Onyx Cloud.
🏢 Onyx for Enterprise
Onyx is built for teams of all sizes, from individual users to the largest global enterprises:
- 👥 Collaboration: Share chats and agents with other members of your organization.
- 🔐 Single Sign On: SSO via Google OAuth, OIDC, or SAML. Group syncing and user provisioning via SCIM.
- 🛡️ Role Based Access Control: RBAC for sensitive resources like access to agents, actions, etc.
- 📊 Analytics: Usage graphs broken down by teams, LLMs, or agents.
- 🕵️ Query History: Audit usage to ensure safe adoption of AI in your organization.
- 💻 Custom code: Run custom code to remove PII, reject sensitive queries, or to run custom analysis.
- 🎨 Whitelabeling: Customize the look and feel of Onyx with custom naming, icons, banners, and more.
📚 Licensing
There are two editions of Onyx:
- Onyx Community Edition (CE) is available freely under the MIT license and covers all of the core features for RAG, AI Chat, Agents, and Actions.
- Onyx Enterprise Edition (EE) includes extra features that are primarily useful for larger organizations.
For feature details, check out our website.
👪 Community
Join our open source community on Discord!
💡 Contributing
Looking to contribute? Please check out the Contribution Guide for more details.