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name: onyx-ai description: >- Deploy and configure Onyx, a self-hosted AI chat platform with RAG and 25+ data connectors. Use when: setting up private ChatGPT alternative, connecting AI to company documents, building enterprise AI assistant with Confluence/Slack/Drive access. license: MIT compatibility: "Docker, Python 3.10+" metadata: author: terminal-skills version: "1.0.0" category: data-ai tags: ["self-hosted", "rag", "enterprise-ai"]

Onyx AI

Overview

Onyx (formerly Danswer) is a self-hosted AI platform that connects to your company's data sources and provides ChatGPT-like chat with retrieval-augmented generation. It supports any LLM provider and includes 25+ connectors for Confluence, Slack, Google Drive, GitHub, Notion, and more.

Instructions

Deployment

Deploy Onyx using Docker Compose:

git clone https://github.com/onyx-dot-app/onyx.git
cd onyx/deployment/docker_compose
docker compose up -d

Access the admin panel at http://localhost:3000. Create an admin account on first visit.

Configure LLM Provider

In Admin → LLM Configuration, add your provider:

• OpenAI: Enter API key, select model (gpt-4o recommended)
• Anthropic: Enter API key, select Claude model
• Azure OpenAI: Enter endpoint URL, API key, deployment name
• Ollama: Point to local Ollama instance for fully private setup

Connect Data Sources

In Admin → Connectors, add sources:

1. Confluence: Enter base URL + API token. Onyx indexes all spaces.
2. Slack: Install Onyx Slack app, select channels to index.
3. Google Drive: OAuth connection, select shared drives.
4. GitHub: Personal access token, select repos.
5. Web scraping: Enter URLs to crawl and index.

Each connector runs on a configurable schedule (hourly, daily, weekly).

Create Assistants

Create specialized assistants with different system prompts and document access:

• Engineering Assistant: Access to GitHub + Confluence tech docs
• Sales Assistant: Access to CRM data + product docs
• HR Assistant: Access to policies + handbook (restricted access)

Examples

Example 1: Company knowledge search

User prompt: "What is our refund policy for enterprise customers?"

The assistant searches across Confluence docs and Google Drive, finds the relevant policy document, and responds with the answer including a citation link to the source document.

Example 2: Code question

User prompt: "How does our authentication middleware work?"

The assistant searches GitHub repos, finds the auth middleware files, and explains the implementation with code references.

Guidelines

• Start with 1-2 connectors, verify quality before adding more
• Set document permissions to match your org structure
• Use Ollama for fully air-gapped deployments (no data leaves your network)
• Monitor token usage in Admin → Analytics to control costs
• Schedule connector syncs during off-hours to avoid load spikes
• Test RAG quality with known questions before rolling out to team