import Image from "next/image"

# A2UI - Google's Generative UI Spec

**A2UI** is Google's declarative, LLM-friendly Generative UI specification that enables agents to generate dynamic user interfaces.

<Image
  src="/images/gen-ui-specs-light.png"
  alt="Generative UI Specs"
  width={4096}
  height={2304}
  className="block dark:hidden mb-8"
/>
<Image
  src="/images/gen-ui-specs-dark.png"
  alt="Generative UI Specs"
  width={4096}
  height={2304}
  className="hidden dark:block mb-8"
/>

## What is A2UI?

A2UI is a declarative generative UI specification launched by Google. It's designed to be:

- **JSONL-based** - Uses JSON Lines format for streaming
- **LLM-friendly** - Easy for language models to generate
- **Platform-agnostic** - Can be rendered on any platform
- **Streaming-first** - Built for real-time, progressive rendering

## Why A2UI?

### Declarative Approach
A2UI allows agents to describe UI components declaratively, making it easier for LLMs to generate dynamic interfaces without needing to understand implementation details.

### Streaming Support
Built with streaming in mind, A2UI enables progressive rendering as the agent generates responses, providing a better user experience.

### Platform Agnostic
A2UI specifications can be rendered on web, mobile, or any other platform, making your agent's UI truly universal.


## Setup with CopilotKit

### Backend

Enable A2UI in `CopilotRuntime` and inject a rendering tool (`render_a2ui`) into your agent so it can produce A2UI surfaces:

```ts title="app/api/copilotkit/route.ts"
import { CopilotRuntime } from "@copilotkit/runtime";

const runtime = new CopilotRuntime({
  agents: { default: myAgent },
  a2ui: {
    injectA2UITool: true,
  },
});
```

This applies `A2UIMiddleware` to all registered agents and adds `render_a2ui` to the agent's tool list, along with usage guidelines so the LLM knows how to call it. Scope to specific agents with `a2ui: { injectA2UITool: true, agents: ["my-agent"] }`.

Once configured, any A2UI output returned from your agent will automatically be rendered in the chat interface — no additional frontend code required.

### Frontend

The A2UI renderer activates automatically — no extra configuration needed on the frontend. Optionally, pass a custom theme:

```tsx
import { CopilotKitProvider } from "@copilotkit/react-core/v2";
import "@copilotkit/react-core/v2/styles.css";
import { myCustomTheme } from "@copilotkit/a2ui-renderer";

<CopilotKitProvider runtimeUrl="/api/copilotkit" a2ui={{ theme: myCustomTheme }}>
  {children}
</CopilotKitProvider>
```

The `a2ui` prop on `<CopilotKitProvider>` is only needed if you want to override defaults.

## Custom Components (BYOC)

A2UI ships with a built-in catalog of basic components (Text, Image, Card, etc.). You can extend it with your own components that match your app's design.

### 1. Define component schemas

Create platform-agnostic definitions using Zod. These tell the agent what components and props are available:

```ts title="lib/a2ui/definitions.ts"
import { z } from "zod";

export const myDefinitions = {
  StatusBadge: {
    description: "A colored status badge.",
    props: z.object({
      text: z.string(),
      variant: z.enum(["success", "warning", "error"]).optional(),
    }),
  },
  Metric: {
    description: "A key metric with label and value.",
    props: z.object({
      label: z.string(),
      value: z.string(),
      trend: z.enum(["up", "down"]).optional(),
    }),
  },
};

export type MyDefinitions = typeof myDefinitions;
```

### 2. Create React renderers

Map each definition to a React component. Props are type-checked against the Zod schemas:

```tsx title="lib/a2ui/renderers.tsx"
"use client";

import { createCatalog, type CatalogRenderers } from "@copilotkit/a2ui-renderer";
import { myDefinitions, type MyDefinitions } from "./definitions";

const myRenderers: CatalogRenderers<MyDefinitions> = {
  StatusBadge: ({ props }) => {
    const colors = {
      success: { bg: "#dcfce7", text: "#166534" },
      warning: { bg: "#fef3c7", text: "#92400e" },
      error: { bg: "#fee2e2", text: "#991b1b" },
    };
    const c = colors[props.variant ?? "success"];
    return (
      <span style={{ padding: "2px 8px", borderRadius: 9999, fontSize: "0.75rem", background: c.bg, color: c.text }}>
        {props.text}
      </span>
    );
  },

  Metric: ({ props }) => (
    <div>
      <div style={{ fontSize: "0.75rem", color: "#6b7280" }}>{props.label}</div>
      <div style={{ fontSize: "1.5rem", fontWeight: 700 }}>
        {props.value} {props.trend === "up" ? "↑" : props.trend === "down" ? "↓" : ""}
      </div>
    </div>
  ),
};

export const myCatalog = createCatalog(myDefinitions, myRenderers, {
  catalogId: "my-app-catalog",
  includeBasicCatalog: true, // merges with built-in components
});
```

### 3. Pass the catalog to CopilotKit

```tsx title="app/layout.tsx"
"use client";

import { CopilotKitProvider } from "@copilotkit/react-core/v2";
import "@copilotkit/react-core/v2/styles.css";
import { myCatalog } from "@/lib/a2ui/renderers";

export default function Layout({ children }: { children: React.ReactNode }) {
  return (
    <CopilotKitProvider runtimeUrl="/api/copilotkit" a2ui={{ catalog: myCatalog }}>
      {children}
    </CopilotKitProvider>
  );
}
```

That's it — agents will now see your custom components alongside the built-in ones and can use them in A2UI surfaces.

## Using A2UI with CopilotKit

[Get started with A2UI](/a2a/generative-ui/declarative-a2ui) and A2A with CopilotKit

Check out the [A2UI Composer](https://a2ui-editor.ag-ui.com/gallery) to create and find widgets

## Learn More

- [Generative UI Specs Overview](/learn/generative-ui/specs) - Compare all supported specifications
- [Generative UI Guide](/generative-ui) - Build with Generative UI in CopilotKit
- [A2UI Site](https://a2ui.org/) - Visit the A2UI site
- [AG-UI Protocol](/ag-ui-protocol) - Learn about the protocol that supports A2UI
- [Open-JSON-UI](/learn/generative-ui/specs/open-json-ui) - OpenAI's alternative approach
- [MCP Apps](/learn/generative-ui/specs/mcp-apps) - Iframe-based Generative UI extending MCP
