OpenUI

What is OpenUI?

OpenUI is presented as “the open standard for generative UI.” The site positions it as an open source approach for building AI applications that can respond with a user interface, rather than only plain text.

At a practical level, OpenUI includes a developer CLI and a set of React-oriented primitives for defining components and registering them into a library that an AI app can use as UI building blocks.

Key Features

• Open source tooling for generative UI: The page frames OpenUI as an open standard specifically aimed at making AI app responses take the form of UI.
• CLI for creating projects: The examples show using npx @openuidev/cli@latest create to scaffold a new app/workflow.
• Component definition API: The page shows defineComponent used to name components and describe their input props (including schema definitions).
• Library registration for UI building blocks: The example uses createLibrary and exports library, indicating a way to register components as a reusable set.
• Schema-based props (zod): The example imports zod and defines component props with z.object(...), including URL validation via z.string().url().

How to Use OpenUI

A typical setup shown on the page starts by creating a project with the CLI via npx @openuidev/cli@latest create. After scaffolding, you define UI components with defineComponent, including a prop schema describing what each component expects.

Next, you use createLibrary to register those components into a library object (exported as library). That library can then be referenced by an AI app so responses can be rendered as structured UI using the registered components.

Use Cases

• AI-generated UI sections (e.g., carousels): Define a Carousel component and a CarouselCard component with explicit prop schemas (titles, images, and CTA labels) so the AI can output a UI carousel with consistent structure.
• Structured listings from AI: Use component props (arrays of card definitions, optional fields like descriptions, and validated URLs) to ensure AI-produced UI elements match the expected data shape.
• Building a reusable UI component library for AI apps: Centralize multiple UI components into a single exported library, so teams can grow a shared “UI vocabulary” over time.
• Typed interfaces for UI rendering: Apply schema validation with zod (for example, ensuring imageUrl is a URL string) to reduce the chance that AI output causes UI rendering errors.

FAQ

• Is OpenUI only for React? The provided example uses @openuidev/react-lang and shows React-style component usage, so the site’s examples indicate a React-oriented approach, but the source doesn’t explicitly claim broader framework support.

• How do I start building with OpenUI? The page shows starting with the CLI using npx @openuidev/cli@latest create, then defining components with defineComponent and registering them into a library.

• What does “generative UI” mean in this context? The site describes OpenUI as enabling AI apps to “respond with your UI,” implying AI outputs can be rendered as UI structures built from registered components.

• How are component inputs specified? In the example, component props are defined using zod schemas (e.g., z.object({ ... }) and z.string().url()).

• Do I need to register components before use? The example includes createLibrary and exports library, suggesting that you assemble and register components into a library for the AI app to use.

Alternatives

• Build your own UI-schema + renderer: Instead of adopting an open standard, you can design your own JSON/UI schema and a renderer that converts structured AI output into components. This differs by requiring you to define the end-to-end protocol yourself.
• Use a UI component schema library without an “open standard”: There are approaches that validate AI output and map it to UI components, but may not provide the same “generative UI standard” framing or a dedicated CLI/workflow.
• Generic UI generation frameworks (non-standardized): Tooling that generates UI directly from prompts may be less about registering UI components as a typed library and more about producing code or layouts, changing the workflow from “component library” to “prompt-to-layout/code.”