Streaming React Components

The RSC API allows you to stream React components from the server to the client with the streamUI function. This is useful when you want to go beyond raw text and stream components to the client in real-time.

Similar to AI SDK Core APIs (like streamText and streamObject , streamUI provides a single function to call a model and allow it to respond with React Server Components. It supports the same model interfaces as AI SDK Core APIs.

Concepts

To give the model the ability to respond to a user's prompt with a React component, you can leverage tools.

With the streamUI function, you provide tools that return React components. With the ability to stream components, the model is akin to a dynamic router that is able to understand the user's intention and display relevant UI.

At a high level, the streamUI works like other AI SDK Core functions: you can provide the model with a prompt or some conversation history and, optionally, some tools. If the model decides, based on the context of the conversation, to call a tool, it will generate a tool call. The streamUI function will then run the respective tool, returning a React component. If the model doesn't have a relevant tool to use, it will return a text generation, which will be passed to the text function, for you to handle (render and return as a React component).

const result = await streamUI({
  model: openai('gpt-4o'),
  prompt: 'Get the weather for San Francisco',
  text: ({ content }) => <div>{content}</div>,
  tools: {},
});

This example calls the streamUI function using OpenAI's gpt-4o model, passes a prompt, specifies how the model's plain text response (content) should be rendered, and then provides an empty object for tools. Even though this example does not define any tools, it will stream the model's response as a div rather than plain text.

Adding A Tool

Using tools with streamUI is similar to how you use tools with generateText and streamText. A tool is an object that has:

• description: a string telling the model what the tool does and when to use it
• parameters: a Zod schema describing what the tool needs in order to run
• generate: an asynchronous function that will be run if the model calls the tool. This must return a React component

Let's expand the previous example to add a tool.

const result = await streamUI({
  model: openai('gpt-4o'),
  prompt: 'Get the weather for San Francisco',
  text: ({ content }) => <div>{content}</div>,
  tools: {
    getWeather: {
      description: 'Get the weather for a location',
      parameters: z.object({ location: z.string() }),
      generate: async function* ({ location }) {
        yield <LoadingComponent />;
        const weather = await getWeather(location);
        return <WeatherComponent weather={weather} location={location} />;
      },
    },
  },
});

This tool would be run if the user asks for the weather for their location. If the user hasn't specified a location, the model will ask for it before calling the tool. When the model calls the tool, the generate function will initially return a loading component. This component will show until the awaited call to getWeather is resolved, at which point, the model will stream the <WeatherComponent /> to the user.

Using streamUI with Next.js

Let's see how you can use the example above in a Next.js application.

To use streamUI in a Next.js application, you will need two things:

1. A Server Action (where you will call streamUI)
2. A page to call the Server Action and render the resulting components

Step 1: Create a Server Action

Create a Server Action at app/actions.tsx and add the following code:

'use server';

import { streamUI } from 'ai/rsc';
import { openai } from '@ai-sdk/openai';
import { z } from 'zod';

const LoadingComponent = () => (
  <div className="animate-pulse p-4">getting weather...</div>
);

const getWeather = async (location: string) => {
  await new Promise(resolve => setTimeout(resolve, 2000));
  return '82°F️ ☀️';
};

interface WeatherProps {
  location: string;
  weather: string;
}

const WeatherComponent = (props: WeatherProps) => (
  <div className="border border-neutral-200 p-4 rounded-lg max-w-fit">
    The weather in {props.location} is {props.weather}
  </div>
);

export async function streamComponent() {
  const result = await streamUI({
    model: openai('gpt-4o'),
    prompt: 'Get the weather for San Francisco',
    text: ({ content }) => <div>{content}</div>,
    tools: {
      getWeather: {
        description: 'Get the weather for a location',
        parameters: z.object({
          location: z.string(),
        }),
        generate: async function* ({ location }) {
          yield <LoadingComponent />;
          const weather = await getWeather(location);
          return <WeatherComponent weather={weather} location={location} />;
        },
      },
    },
  });

  return result.value;
}

The getWeather tool should look familiar as it is identical to the example in the previous section. In order for this tool to work:

1. First define a LoadingComponent, which renders a pulsing div that will show some loading text.
2. Next, define a getWeather function that will timeout for 2 seconds (to simulate fetching the weather externally) before returning the "weather" for a location. Note: you could run any asynchronous TypeScript code here.
3. Finally, define a WeatherComponent which takes in location and weather as props, which are then rendered within a div.

Your Server Action is an asynchronous function called streamComponent that takes no inputs, and returns a ReactNode. Within the action, you call the streamUI function, specifying the model (gpt-4o), the prompt, the component that should be rendered if the model chooses to return text, and finally, your getWeather tool. Last but not least, you return the resulting component generated by the model with result.value.

To call this Server Action and display the resulting React Component, you will need a page.

Step 2: Create a Page

Create or update your root page (app/page.tsx) with the following code:

'use client';

import { useState } from 'react';
import { Button } from '@/components/ui/button';
import { streamComponent } from './actions';

export default function Page() {
  const [component, setComponent] = useState<React.ReactNode>();

  return (
    <div>
      <form
        onSubmit={async e => {
          e.preventDefault();
          setComponent(await streamComponent());
        }}
      >
        <Button>Stream Component</Button>
      </form>
      <div>{component}</div>
    </div>
  );
}

This page is first marked as a client component with the "use client"; directive given it will be using hooks and interactivity. On the page, you render a form. When that form is submitted, you call the streamComponent action created in the previous step (just like any other function). The streamComponent action returns a ReactNode that you can then render on the page using React state (setComponent).

Going beyond a single prompt

You can now allow the model to respond to your prompt with a React component. However, this example is limited to a static prompt that is set within your Server Action. You could make this example interactive by turning it into a chatbot.

Learn how to stream React components with the Next.js App Router using streamUI with this example.