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json-render-generative-ui

by @aradotsov1.0.0
4.1(6)

生成式 UI 框架,通过自然语言生成动态界面,AI 输出 JSON 自动渲染预定义组件,快速构建用户界面

react.jsui-componentsgenerative-aiprototypingfrontend-developmentGitHub
安装方式
npx skills add aradotso/trending-skills --skill json-render-generative-ui
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Before / After 效果对比

1
使用前

手动编写 JSX、配置样式、处理状态管理,构建一个表单页面需要 2-3 小时,修改需求还要重写代码

使用后

描述需求自动生成 UI 组件 JSON,直接渲染可用界面,10 分钟完成复杂表单,修改只需调整描述

description SKILL.md

json-render-generative-ui

json-render Generative UI Framework

Skill by ara.so — Daily 2026 Skills collection.

json-render is a Generative UI framework that lets AI generate dynamic interfaces from natural language prompts, constrained to a predefined component catalog. AI outputs JSON; json-render renders it safely and predictably across any platform.

Installation

# React (core)
npm install @json-render/core @json-render/react

# React + shadcn/ui (36 pre-built components)
npm install @json-render/shadcn

# React Native
npm install @json-render/core @json-render/react-native

# Vue
npm install @json-render/core @json-render/vue

# Svelte
npm install @json-render/core @json-render/svelte

# SolidJS
npm install @json-render/core @json-render/solid

# Video (Remotion)
npm install @json-render/core @json-render/remotion

# PDF
npm install @json-render/core @json-render/react-pdf

# Email
npm install @json-render/core @json-render/react-email @react-email/components @react-email/render

# 3D (React Three Fiber)
npm install @json-render/core @json-render/react-three-fiber @react-three/fiber @react-three/drei three

# OG Images / SVG / PNG
npm install @json-render/core @json-render/image

# State management adapters
npm install @json-render/zustand   # or redux, jotai, xstate

# MCP integration (Claude, ChatGPT, Cursor)
npm install @json-render/mcp

# YAML wire format
npm install @json-render/yaml

Core Concepts

Concept Description

Catalog Defines allowed components and actions (the guardrails for AI)

Spec AI-generated JSON describing which components to render and with what props

Registry Maps catalog component names to actual render implementations

Renderer Platform-specific component that takes a spec + registry and renders UI

Actions Named events AI can trigger (e.g. export_report, refresh_data)

Spec Format

The flat spec format uses a root key + elements map:

const spec = {
  root: "card-1",
  elements: {
    "card-1": {
      type: "Card",
      props: { title: "Dashboard" },
      children: ["metric-1", "metric-2", "button-1"],
    },
    "metric-1": {
      type: "Metric",
      props: { label: "Revenue", value: "124000", format: "currency" },
      children: [],
    },
    "metric-2": {
      type: "Metric",
      props: { label: "Growth", value: "0.18", format: "percent" },
      children: [],
    },
    "button-1": {
      type: "Button",
      props: { label: "Export Report", action: "export_report" },
      children: [],
    },
  },
};

Step 1: Define a Catalog

import { defineCatalog } from "@json-render/core";
import { schema } from "@json-render/react/schema";
import { z } from "zod";

const catalog = defineCatalog(schema, {
  components: {
    Card: {
      props: z.object({ title: z.string() }),
      description: "A card container with a title",
    },
    Metric: {
      props: z.object({
        label: z.string(),
        value: z.string(),
        format: z.enum(["currency", "percent", "number"]).nullable(),
      }),
      description: "Displays a single metric value with optional formatting",
    },
    Button: {
      props: z.object({
        label: z.string(),
        action: z.string(),
      }),
      description: "Clickable button that triggers an action",
    },
    Stack: {
      props: z.object({
        direction: z.enum(["row", "column"]).default("column"),
        gap: z.number().optional(),
      }),
      description: "Layout container that stacks children",
    },
  },
  actions: {
    export_report: { description: "Export the current dashboard to PDF" },
    refresh_data: { description: "Refresh all metric data" },
    navigate: {
      description: "Navigate to a page",
      payload: z.object({ path: z.string() }),
    },
  },
});

Step 2: Define a Registry (React)

import { defineRegistry, Renderer } from "@json-render/react";

function format(value: string, fmt: string | null): string {
  if (fmt === "currency") return `$${Number(value).toLocaleString()}`;
  if (fmt === "percent") return `${(Number(value) * 100).toFixed(1)}%`;
  return value;
}

const { registry } = defineRegistry(catalog, {
  components: {
    Card: ({ props, children }) => (
      <div className="rounded-lg border p-4 shadow-sm">
        <h3 className="text-lg font-semibold mb-3">{props.title}</h3>
        {children}
      </div>
    ),

    Metric: ({ props }) => (
      <div className="flex flex-col">
        <span className="text-sm text-gray-500">{props.label}</span>
        <span className="text-2xl font-bold">
          {format(props.value, props.format)}
        </span>
      </div>
    ),

    Button: ({ props, emit }) => (
      <button
        className="px-4 py-2 bg-blue-600 text-white rounded"
        onClick={() => emit("press")}
      >
        {props.label}
      </button>
    ),

    Stack: ({ props, children }) => (
      <div
        style={{
          display: "flex",
          flexDirection: props.direction ?? "column",
          gap: props.gap ?? 8,
        }}
      >
        {children}
      </div>
    ),
  },
});

Step 3: Render the Spec

import { Renderer } from "@json-render/react";

function Dashboard({ spec, onAction }) {
  return (
    <Renderer
      spec={spec}
      registry={registry}
      onAction={(action, payload) => {
        console.log("Action triggered:", action, payload);
        onAction?.(action, payload);
      }}
    />
  );
}

Generating Specs with AI (Vercel AI SDK)

import { generateObject } from "ai";
import { openai } from "@ai-sdk/openai";
import { getCatalogSchema, getCatalogPrompt } from "@json-render/core";

async function generateDashboard(userPrompt: string) {
  const { object: spec } = await generateObject({
    model: openai("gpt-4o"),
    schema: getCatalogSchema(catalog),
    system: getCatalogPrompt(catalog),
    prompt: userPrompt,
  });

  return spec;
}

// Usage
const spec = await generateDashboard(
  "Create a sales dashboard showing revenue, conversion rate, and an export button"
);

Streaming Specs

import { streamObject } from "ai";
import { openai } from "@ai-sdk/openai";
import { getCatalogSchema, getCatalogPrompt, parseSpecStream } from "@json-render/core";
import { Renderer } from "@json-render/react";
import { useState, useEffect } from "react";

function StreamingDashboard({ prompt }: { prompt: string }) {
  const [spec, setSpec] = useState(null);

  useEffect(() => {
    async function stream() {
      const { partialObjectStream } = await streamObject({
        model: openai("gpt-4o"),
        schema: getCatalogSchema(catalog),
        system: getCatalogPrompt(catalog),
        prompt,
      });

      for await (const partial of partialObjectStream) {
        setSpec(partial); // Renderer handles partial specs gracefully
      }
    }
    stream();
  }, [prompt]);

  if (!spec) return <div>Generating UI...</div>;
  return <Renderer spec={spec} registry={registry} />;
}

Using Pre-built shadcn/ui Components

import { defineCatalog } from "@json-render/core";
import { schema } from "@json-render/react/schema";
import { defineRegistry, Renderer } from "@json-render/react";
import { shadcnComponentDefinitions } from "@json-render/shadcn/catalog";
import { shadcnComponents } from "@json-render/shadcn";

// Pick any of the 36 available shadcn components
const catalog = defineCatalog(schema, {
  components: {
    Card: shadcnComponentDefinitions.Card,
    Stack: shadcnComponentDefinitions.Stack,
    Heading: shadcnComponentDefinitions.Heading,
    Text: shadcnComponentDefinitions.Text,
    Button: shadcnComponentDefinitions.Button,
    Badge: shadcnComponentDefinitions.Badge,
    Table: shadcnComponentDefinitions.Table,
    Chart: shadcnComponentDefinitions.Chart,
    Input: shadcnComponentDefinitions.Input,
    Select: shadcnComponentDefinitions.Select,
  },
  actions: {
    submit: { description: "Submit a form" },
    export: { description: "Export data" },
  },
});

const { registry } = defineRegistry(catalog, {
  components: {
    Card: shadcnComponents.Card,
    Stack: shadcnComponents.Stack,
    Heading: shadcnComponents.Heading,
    Text: shadcnComponents.Text,
    Button: shadcnComponents.Button,
    Badge: shadcnComponents.Badge,
    Table: shadcnComponents.Table,
    Chart: shadcnComponents.Chart,
    Input: shadcnComponents.Input,
    Select: shadcnComponents.Select,
  },
});

function AIPage({ spec }) {
  return <Renderer spec={spec} registry={registry} />;
}

Vue Renderer

import { h, defineComponent } from "vue";
import { defineCatalog } from "@json-render/core";
import { schema } from "@json-render/vue/schema";
import { defineRegistry, Renderer } from "@json-render/vue";
import { z } from "zod";

const catalog = defineCatalog(schema, {
  components: {
    Card: {
      props: z.object({ title: z.string() }),
      description: "Card container",
    },
    Button: {
      props: z.object({ label: z.string() }),
      description: "Button",
    },
  },
  actions: {
    click: { description: "Button clicked" },
  },
});

const { registry } = defineRegistry(catalog, {
  components: {
    Card: ({ props, children }) =>
      h("div", { class: "card" }, [
        h("h3", null, props.title),
        children,
      ]),
    Button: ({ props, emit }) =>
      h("button", { onClick: () => emit("click") }, props.label),
  },
});

// In your Vue SFC:
// <template>
//   <Renderer :spec="spec" :registry="registry" />
// </template>

React Native Renderer

import { defineCatalog } from "@json-render/core";
import { schema } from "@json-render/react-native/schema";
import {
  standardComponentDefinitions,
  standardActionDefinitions,
} from "@json-render/react-native/catalog";
import { defineRegistry, Renderer } from "@json-render/react-native";

// 25+ standard mobile components out of the box
const catalog = defineCatalog(schema, {
  components: { ...standardComponentDefinitions },
  actions: standardActionDefinitions,
});

const { registry } = defineRegistry(catalog, {
  components: {}, // use all standard implementations
});

export function AIScreen({ spec }) {
  return <Renderer spec={spec} registry={registry} />;
}

PDF Generation

import { renderToBuffer } from "@json-render/react-pdf";

const invoiceSpec = {
  root: "doc",
  elements: {
    doc: {
      type: "Document",
      props: { title: "Invoice #1234" },
      children: ["page-1"],
    },
    "page-1": {
      type: "Page",
      props: { size: "A4" },
      children: ["heading-1", "table-1"],
    },
    "heading-1": {
      type: "Heading",
      props: { text: "Invoice #1234", level: "h1" },
      children: [],
    },
    "table-1": {
      type: "Table",
      props: {
        columns: [
          { header: "Item", width: "60%" },
          { header: "Amount", width: "40%", align: "right" },
        ],
        rows: [
          ["Widget A", "$10.00"],
          ["Widget B", "$25.00"],
          ["Total", "$35.00"],
        ],
      },
      children: [],
    },
  },
};

// Returns a Buffer you can send as a response
const buffer = await renderToBuffer(invoiceSpec);

// In a Next.js route handler:
export async function GET() {
  const buffer = await renderToBuffer(invoiceSpec);
  return new Response(buffer, {
    headers: { "Content-Type": "application/pdf" },
  });
}

Email Generation

import { renderToHtml } from "@json-render/react-email";
import { schema, standardComponentDefinitions } from "@json-render/react-email";
import { defineCatalog } from "@json-render/core";

const catalog = defineCatalog(schema, {
  components: standardComponentDefinitions,
});

const emailSpec = {
  root: "html-1",
  elements: {
    "html-1": {
      type: "Html",
      props: { lang: "en" },
      children: ["head-1", "body-1"],
    },
    "head-1": { type: "Head", props: {}, children: [] },
    "body-1": {
      type: "Body",
      props: { style: { backgroundColor: "#f6f9fc" } },
      children: ["container-1"],
    },
    "container-1": {
      type: "Container",
      props: { style: { maxWidth: "600px", margin: "0 auto" } },
      children: ["heading-1", "text-1", "button-1"],
    },
    "heading-1": {
      type: "Heading",
      props: { text: "Welcome aboard!" },
      children: [],
    },
    "text-1": {
      type: "Text",
      props: { text: "Thanks for signing up. Click below to get started." },
      children: [],
    },
    "button-1": {
      type: "Button",
      props: { text: "Get Started", href: "https://example.com" },
      children: [],
    },
  },
};

const html = await renderToHtml(emailSpec);

MCP Integration (Claude, ChatGPT, Cursor)

import { createMCPServer } from "@json-render/mcp";

const server = createMCPServer({
  catalog,
  name: "my-ui-server",
  version: "1.0.0",
});

server.start();

State Management Integration

import { create } from "zustand";
import { createZustandAdapter } from "@json-render/zustand";

const useStore = create((set) => ({
  data: {},
  setData: (data) => set({ data }),
}));

const stateStore = createZustandAdapter(useStore);

// Pass to Renderer for action handling with state
<Renderer spec={spec} registry={registry} stateStore={stateStore} />;

YAML Wire Format

import { parseYAML, toYAML } from "@json-render/yaml";

// AI can output YAML instead of JSON (often more token-efficient)
const yamlSpec = `
root: card-1
elements:
  card-1:
    type: Card
    props:
      title: Hello World
    children: [button-1]
  button-1:
    type: Button
    props:
      label: Click Me
    children: []
`;

const spec = parseYAML(yamlSpec);

Full Next.js App Router Example

// app/dashboard/page.tsx
import { generateObject } from "ai";
import { openai } from "@ai-sdk/openai";
import { getCatalogSchema, getCatalogPrompt } from "@json-render/core";
import { DashboardRenderer } from "./DashboardRenderer";
import { catalog } from "@/lib/catalog";

export default async function DashboardPage({
  searchParams,
}: {
  searchParams: { q?: string };
}) {
  const prompt = searchParams.q ?? "Show me a sales overview dashboard";

  const { object: spec } = await generateObject({
    model: openai("gpt-4o"),
    schema: getCatalogSchema(catalog),
    system: getCatalogPrompt(catalog),
    prompt,
  });

  return <DashboardRenderer spec={spec} />;
}

// app/dashboard/DashboardRenderer.tsx
"use client";
import { Renderer } from "@json-render/react";
import { registry } from "@/lib/registry";
import { useRouter } from "next/navigation";

export function DashboardRenderer({ spec }) {
  const router = useRouter();

  return (
    <Renderer
      spec={spec}
      registry={registry}
      onAction={(action, payload) => {
        switch (action) {
          case "navigate":
            router.push(payload.path);
            break;
          case "export_report":
            window.open("/api/export", "_blank");
            break;
          case "refresh_data":
            router.refresh();
            break;
        }
      }}
    />
  );
}

Common Patterns

Conditional Component Availability

// Restrict catalog based on user role
function getCatalogForRole(role: "admin" | "viewer") {
  const base = { Card, Stack, Heading, Text, Metric };
  const adminOnly = role === "admin" ? { Button, Form, Table } : {};
  const adminActions = role === "admin"
    ? { export: { description: "Export data" } }
    : {};

  return defineCatalog(schema, {
    components: { ...base, ...adminOnly },
    actions: adminOnly ? adminActions : {},
  });
}

Dynamic Props with Runtime Data

// Components can fetch their own data
const { registry } = defineRegistry(catalog, {
  components: {
    LiveMetric: ({ props }) => {
      const { data } = useSWR(`/api/metrics/${props.metricId}`);
      return (
        <div>
          <span>{props.label}</span>
          <span>{data?.value ?? "..."}</span>
        </div>
      );
    },
  },
});

Type-Safe Action Handling

import { type ActionHandler } from "@json-render/core";

const handleAction: ActionHandler<typeof catalog> = (action, payload) => {
  // action and payload are fully typed based on your catalog definition
  if (action === "navigate") {
    router.push(payload.path); // payload.path is typed as string
  }
};

Troubleshooting

Problem Cause Fix

AI generates unknown component type Component not in catalog Add component to defineCatalog or update AI prompt

Props validation error AI hallucinated a prop Tighten Zod schema, add .strict() or .describe() hints

Renderer shows nothing root key doesn't match an elements key Check spec structure; root must reference a valid element ID

Partial spec renders incorrectly Streaming not handled Use parseSpecStream utility or check for null elements before render

Actions not firing onAction not passed to Renderer Pass onAction prop to <Renderer>

shadcn components unstyled Missing Tailwind config Ensure @json-render/shadcn paths are in tailwind.config.js content array

TypeScript errors in registry Catalog/registry mismatch Ensure defineRegistry(catalog, ...) uses the same catalog instance

Environment Variables

# For AI generation (use your preferred provider)
OPENAI_API_KEY=your_key_here
ANTHROPIC_API_KEY=your_key_here

# For MCP server
MCP_SERVER_PORT=3001

Key API Reference

// Core
defineCatalog(schema, { components, actions })  // Define guardrails
getCatalogSchema(catalog)                        // Get Zod schema for AI
getCatalogPrompt(catalog)                        // Get system prompt for AI

// React
defineRegistry(catalog, { components })          // Create typed registry
<Renderer spec={spec} registry={registry} onAction={fn} />

// Core utilities
parseSpecStream(stream)    // Parse streaming partial specs
toYAML(spec)              // Convert spec to YAML
parseYAML(yaml)           // Parse YAML spec to JSON

// PDF
renderToBuffer(spec)       // → Buffer
renderToStream(spec)       // → ReadableStream

// Email
renderToHtml(spec)         // → HTML string
renderToText(spec)         // → plain text string

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统计数据

安装量398
评分4.1 / 5.0
版本1.0.0
更新日期2026年3月24日
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创建2026年3月24日
最后更新2026年3月24日