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JSON Render Shadcn
JSON Render Shadcn
AI-generated UI using @json-render/shadcn. Describe a UI in natural language and watch it render with shadcn components.
Use this when prompts should render only from a fixed catalog of shadcn components provided by the @json-render/shadcn package.
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Problems solved
Technical challenges this implementation handles out of the box.
- Build UIs from natural-language prompts with json-render
- Stream AI-generated component specs into a live preview
- Render shadcn components from a constrained catalog
Use cases
Products and workflows this pattern is designed to support.
- UI playgrounds for prompt-to-interface
- Dashboard builders
- Form generators
- Design-to-shadcn prototyping
Compare with
Similar patterns, and when each one is the better fit.
JSON Render ReactUse this when you want to define your own small component catalog and render streamed JSON specs with the base @json-render React renderer.
JSON Render Three.jsUse this when users describe a 3D scene in plain language and need it streamed as a live React Three Fiber render they can orbit right away.
JSON Render Data TableUse this when you are building a prompt-driven data grid with search, filter, pagination, and bulk action toolbars generated from a json-render spec.
JSON Render ImageUse this when users describe a social card or marketing graphic in plain language and need a downloadable SVG or PNG image as the result.
Setup
Requirements, wiring steps, and what this pattern adds to your project.
Getting started
Pick how you want to pull this pattern in. Then wire env vars and routes the same way.
- 1
Download → Next.js app
Use Download → Next.js app in the preview toolbar. You get a zip scaffold (Pro downloads rewrite preview `/view/.../api/*` paths to `/api/*` automatically).
- 2
Extract the zip and install dependencies
Unzip the archive, then run `pnpm install` (or npm / yarn) in the project folder.
- 3
Fill .env.local
The download includes .env.local placeholders when needed. Add real values for: AI_GATEWAY_API_KEY.
- 4
Customize the agent and tool files
Adapt prompts, tools, and stop conditions in the generated project for your product.
- 5
Run the app and open the pattern route
Run `pnpm dev`, open the setup/checklist page if present, then navigate to the generated pattern route and verify responses.
Environment variables
AI_GATEWAY_API_KEYGet key
Capabilities
AI SDK APIs
streamTextgatewayProviders
OpenAI
External services
Upstash
Files added
10 files
app/page.tsxapp/layout.tsxapp/api/json-render-shadcn/route.tscomponents/json-render-demo.tsxcomponents/empty-state.tsxlib/catalog.tslib/registry.tsxlib/rate-limit.tslib/request-utils.tsREADME.md
Dependencies
15 total
npm packages
11AISDK@json-render/core@json-render/react@json-render/shadcnUpstashlucide-reactNext.jsReactZodmotionsonner
Registry components
buttonemptyinputscroll-area
Critical files
3 files
lib/catalog.tsDefines the json-render catalog using defineCatalog with shadcn component definitions. This is the component registry that maps JSON spec types to renderable shadcn components.
lib/registry.tsxReact component registry mapping json-render component names to actual shadcn/ui React components. Used by the renderer to resolve components at runtime.
json-render-shadcn/route.tsStreaming API endpoint. Uses catalog.prompt() to generate the system prompt, streams AI-generated JSON specs via streamText with gateway('google/gemini-3-flash').
Requirements
- Complexity
- Intermediate
- Setup time
- ~5 minutes
- Node
- 24+
- Memory
- 256MB
Upstash Redis
