import { pageMetadata } from "@/lib/page-metadata" export const metadata = pageMetadata("docs") # Introduction json-render is a framework for **Generative UI** — AI-generated interfaces that are safe, predictable, and render natively on any platform. ## What is Generative UI? Most AI integrations treat the interface as fixed. Developers build layouts ahead of time, and AI fills in the data — a chatbot response, a summary, a recommendation. The UI itself never changes. **Generative UI is different.** The AI generates the interface itself: which components to show, how to arrange them, what data to bind, what actions to wire up. Every response can produce a unique, purpose-built UI tailored to the user's request. The challenge is that unconstrained AI output is unpredictable. It can hallucinate component names, produce invalid structures, or generate unsafe code. You need a way to let AI be creative with layout and composition while keeping it within boundaries you control. That is what json-render does. You define a **catalog** of components and actions. AI generates JSON constrained to that catalog. Your components render the result natively — on web or mobile — with full type safety and no arbitrary code execution. ## How json-render Works ### 1. Define your catalog A catalog declares what AI can use: components with typed props, actions with typed params. ```typescript import { defineCatalog } from '@json-render/core'; import { schema } from '@json-render/react'; import { z } from 'zod'; export const catalog = defineCatalog(schema, { components: { Card: { props: z.object({ title: z.string() }), slots: ["default"], }, Metric: { props: z.object({ label: z.string(), value: z.string(), }), }, }, }); ``` ### 2. AI generates a spec Given a prompt like "show me a revenue dashboard", AI outputs a JSON spec — a flat tree of elements constrained to your catalog: ```json { "root": "card-1", "elements": { "card-1": { "type": "Card", "props": { "title": "Revenue Dashboard" }, "children": ["metric-1", "metric-2"] }, "metric-1": { "type": "Metric", "props": { "label": "Total Revenue", "value": "$48,200" } }, "metric-2": { "type": "Metric", "props": { "label": "Growth", "value": "+12%" } } } } ``` ### 3. Your components render it Map catalog types to real components with a registry, then render the spec: ```tsx import { Renderer, StateProvider, VisibilityProvider } from '@json-render/react'; ``` The result is a native UI built from your own components — not an iframe, not markdown, not generated code. The AI chose the structure; you control everything else. ## Key Concepts - **[Catalog](/docs/catalog)** — Define the components, actions, and validation functions AI can use. This is the contract between your app and the AI. - **[Registry](/docs/registry)** — Map catalog types to platform-specific implementations. React components on web, React Native views on mobile. - **[Specs](/docs/specs)** — The JSON output AI generates. A flat tree of typed elements with props, children, data bindings, and visibility conditions. - **[Streaming](/docs/streaming)** — Render progressively as the AI responds. Each JSONL patch adds to the spec and the UI updates in real time. - **[Data Binding](/docs/data-binding)** — Bind props to runtime data with `$state` paths, repeat elements over arrays, and wire two-way input bindings. - **[Visibility](/docs/visibility)** — Show or hide elements based on state conditions. The AI can generate conditional UIs without writing logic. - **[Generation Modes](/docs/generation-modes)** — Generate standalone UI (playground/builder) or inline UI within a chat conversation. ## Next - [Installation](/docs/installation) — Add json-render to your project - [Quick Start](/docs/quick-start) — Build your first generative UI in 5 minutes