Open Enthrium AI Platform

Self-Hosted Web-Based AI Platform · Apache-2.0 · Open Source

Run SKILL.md agents · Build an enterprise knowledge base with RAG · Private chat box on your own infrastructure. No code. No LangChain. No Python.

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What is Open Enthrium AI Platform?

A self-hosted, web-based open-source AI platform with three core capabilities:

• SKILL.md agents — run portable, declarative AI agents defined in Markdown. Drop a SKILL.md into any workspace; OE wires it to your connectors and executes it via the built-in runtime. The same skill runs unchanged on Claude, Cursor, Windsurf, or the CLI.
• Enterprise knowledge base with RAG — ingest documents (24+ formats), chunk and embed them into your chosen vector database, and retrieve with cited answers. All on your own infrastructure, no data leaving your network.
• Private chat box — a fully private AI assistant backed by your own LLM, your own knowledge base, and your own connectors. Embed it as a website widget or use it internally across workspaces.

Self-hosted. No call-home. Own your data completely.

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Quick Start

docker run -d \
  -p 3000:3000 \
  -p 3001:3001 \
  -e JWT_SECRET=your-secret \
  -e SUPER_ADMIN_EMAIL=admin@yourdomain.com \
  -e SUPER_ADMIN_PASSWORD=your-password \
  -e LICENSE_TYPE=community \
  -v open-enthrium-data:/app/server/storage \
  jumbocoder/open-enthrium-ai-platform:latest

Open http://localhost:3000 and log in with your super admin credentials. Configure your LLM provider, embedding model, and vector database from the admin panel — no .env changes needed.

Or run from source:

Prerequisites: Node.js v18+, Yarn v1.x

# 1. Clone the repo
git clone https://github.com/enthrium/open-enthrium-ai-platform.git
cd open-enthrium-ai-platform

# 2. Install dependencies
yarn install

# 3. Configure environment
cp server/.env.example server/.env
# Edit server/.env — required variables:
#   JWT_SECRET          — long random string (required)
#   SUPER_ADMIN_EMAIL   — first admin account email
#   SUPER_ADMIN_PASSWORD — first admin account password
#   LICENSE_TYPE        — "community" (default) or "commercial"
# Optional port overrides (defaults shown):
#   FRONTEND_PORT=3000
#   SERVER_PORT=3001
#   PROCESSOR_PORT=3002
#   MCP_PORT=3003

# 4. Set up the database (Prisma)
yarn workspace @open-enthrium/server db:push
yarn workspace @open-enthrium/server db:seed-masters

# 5. Start in development mode (server + processor + frontend)
yarn dev

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Connector Catalog

2,673 connectors across 45+ categories. Databases (PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery), cloud storage (S3, GCS, Azure Blob), communication (Slack, Teams, Gmail, Telegram), developer tools (GitHub, Jira, Linear), CRM (HubSpot, Salesforce), AI media (DALL-E, ElevenLabs, Runway), IoT (MQTT, Kafka), blockchain (Ethereum, Polygon), and more.

All connectors are configurable from the admin panel — no .env changes, no code. The full catalog lives in server/src/data/connectionTypes.json.

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Contributing

Contributions are welcome. Before opening a PR:

1. Open an issue to discuss the change — especially for new features
2. Fork the repository and branch from main
3. Test your changes locally
4. Open a PR with a clear description of what and why

Where contributions are most valuable:

• New connector adapters (server/src/utils/tools/adapters/)
• New connector entries — add to server/src/data/connectionTypes.json and re-run yarn workspace @open-enthrium/server db:seed-masters
• Agent SKILL.md examples for the community marketplace
• Bug fixes with clear reproduction steps

→ See CONTRIBUTING.md for the full guide.

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Community

🌐 Website	Open Enthrium
🐳 Docker Hub	hub.docker.com/r/jumbocoder/open-enthrium-ai-platform
⚡ OE Runtime	open-enthrium-ai-agent-runtime
🔌 OE MCP	open-enthrium-ai-mcp-server
🐛 Issues	github.com/enthrium/open-enthrium-ai-platform/issues

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License

Apache-2.0 — free to use, modify, and deploy for any purpose, including commercial use. No usage limits. No telemetry. No call-home.

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