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Michelangelo UI

Michelangelo's User Interface (UI) provides a standard, code free ML development experience. It guides users through five phases in the ML development lifecycle, from developing your first model to productionization.

Getting Started​

Deploy to Kubernetes​

Production deployment using sandbox manifests as templates for your infrastructure.

  • For: Platform operators
  • Use case: Full ML platform deployment with UI

→ Deploying Michelangelo UI

Integrate with Existing React App​

Add Michelangelo components to your existing React application as npm dependencies that connect to your infrastructure.

  • For: Frontend developers, application teams
  • Use case: Separate frontend/backend infrastructure, or embedding ML capabilities in existing developer tools

→ React Library Integration

Local Development​

Set up a development environment for contributing to the UI codebase.

  • For: Contributors, UI developers
  • Use case: UI development and contributions

→ Local Development Setup

Architecture​

The Michelangelo UI is built with React and communicates with the Michelangelo API server through gRPC-Web. The UI supports two main consumption methods:

  • Containerized deployment: Complete UI deployed to Kubernetes clusters
  • Component integration: Individual React components embedded in existing applications

For internal architecture documentation (providers, hooks, types, and component patterns), see the UI Developer Reference.