Vercel AI SDK

The Vercel AI SDK is a TypeScript toolkit designed to help you build AI-powered applications using popular frameworks like Next.js, React, Svelte, Vue and runtimes like Node.js.

To learn more about how to use the Vercel AI SDK, check out our API Reference and Documentation.

Installation

You will need Node.js 18+ and pnpm installed on your local development machine.

npm install ai

Usage

AI SDK Core

The AI SDK Core module provides a unified API to interact with model providers like OpenAI, Anthropic, Google, and more.

You will then install the model provider of your choice.

npm install @ai-sdk/openai

@/index.ts (Node.js Runtime)

import { generateText } from 'ai';
import { openai } from '@ai-sdk/openai'; // Ensure OPENAI_API_KEY environment variable is set

async function main() {
  const { text } = await generateText({
    model: openai('gpt-4-turbo'),
    system: 'You are a friendly assistant!',
    prompt: 'Why is the sky blue?',
  });

  console.log(text);
}

main();

AI SDK UI

The AI SDK UI module provides a set of hooks that help you build chatbots and generative user interfaces. These hooks are framework agnostic, so they can be used in Next.js, React, Svelte, Vue, and SolidJS.

@/app/page.tsx (Next.js App Router)

'use client';

import { useChat } from 'ai/react';

export default function Page() {
  const { messages, input, handleSubmit, handleInputChange, isLoading } =
    useChat();

  return (
    <div>
      {messages.map(message => (
        <div key={message.id}>
          <div>{message.role}</div>
          <div>{message.content}</div>
        </div>
      ))}

      <form onSubmit={handleSubmit}>
        <input
          value={input}
          placeholder="Send a message..."
          onChange={handleInputChange}
          disabled={isLoading}
        />
      </form>
    </div>
  );
}

@/app/api/chat/route.ts (Next.js App Router)

import { CoreMessage, streamText } from 'ai';
import { openai } from '@ai-sdk/openai';

export async function POST(req: Request) {
  const { messages }: { messages: CoreMessage[] } = await req.json();

  const result = await streamText({
    model: openai('gpt-4'),
    system: 'You are a helpful assistant.',
    messages,
  });

  return result.toAIStreamResponse();
}

AI SDK RSC

The AI SDK RSC module provides an alternative API that also helps you build chatbots and generative user interfaces for frameworks that support React Server Components (RSC).

This API leverages the benefits of Streaming and Server Actions offered by RSC, thus improving the developer experience of managing states between server/client and building generative user interfaces.

@/app/actions.tsx (Next.js App Router)

import { streamUI } from 'ai/rsc';
import { z } from 'zod';

async function submitMessage() {
  'use server';

  const stream = await streamUI({
    model: openai('gpt-4-turbo'),
    messages: [
      { role: 'system', content: 'You are a friendly bot!' },
      { role: 'user', content: input },
    ],
    text: ({ content, done }) => {
      return <div>{content}</div>;
    },
    tools: {
      deploy: {
        description: 'Deploy repository to vercel',
        parameters: z.object({
          repositoryName: z
            .string()
            .describe('The name of the repository, example: vercel/ai-chatbot'),
        }),
        generate: async function* ({ repositoryName }) {
          yield <div>Cloning repository {repositoryName}...</div>;
          await new Promise(resolve => setTimeout(resolve, 3000));
          yield <div>Building repository {repositoryName}...</div>;
          await new Promise(resolve => setTimeout(resolve, 2000));
          return <div>{repositoryName} deployed!</div>;
        },
      },
    },
  });

  return {
    ui: stream.value,
  };
}

export const AI = createAI({
  initialAIState: {},
  initialUIState: {},
  actions: {
    submitMessage,
  },
});

@/app/layout.tsx (Next.js App Router)

import { ReactNode } from 'react';
import { AI } from '@/app/actions';

export default function Layout({ children }: { children: ReactNode }) {
  <AI>{children}</AI>;
}

@/app/page.tsx (Next.js App Router)

'use client';

import { useActions } from 'ai/rsc';
import { ReactNode, useState } from 'react';

export default function Page() {
  const [input, setInput] = useState('');
  const [messages, setMessages] = useState<ReactNode[]>([]);
  const { submitMessage } = useActions();

  return (
    <div>
      <input
        value={input}
        onChange={event => {
          setInput(event.target.value);
        }}
      />
      <button
        onClick={async () => {
          const { ui } = await submitMessage(input);
          setMessages(currentMessages => [...currentMessages, ui]);
        }}
      >
        Submit
      </button>
    </div>
  );
}

Templates

We've built templates that include AI SDK integrations for different use cases, providers, and frameworks. You can use these templates to get started with your AI-powered application.

Community

The Vercel AI SDK community can be found on GitHub Discussions where you can ask questions, voice ideas, and share your projects with other people.

Contributing

Contributions to the Vercel AI SDK are welcome and highly appreciated. However, before you jump right into it, we would like you to review our Contribution Guidelines to make sure you have smooth experience contributing to Vercel AI SDK.

Authors

This library is created by Vercel and Next.js team members, with contributions from the Open Source Community.

import { generateText } from 'ai'; import { openai } from '@ai-sdk/openai'; // Ensure OPENAI_API_KEY environment variable is set async function main() { const { text } = await generateText({ model: openai('gpt-4-turbo'), system: 'You are a friendly assistant!', prompt: 'Why is the sky blue?', }); console.log(text); } main();

'use client'; import { useChat } from 'ai/react'; export default function Page() { const { messages, input, handleSubmit, handleInputChange, isLoading } = useChat(); return ( <div> {messages.map(message => ( <div key={message.id}> <div>{message.role}</div> <div>{message.content}</div> </div> ))} <form onSubmit={handleSubmit}> <input value={input} placeholder="Send a message..." onChange={handleInputChange} disabled={isLoading} /> </form> </div> ); }

import { CoreMessage, streamText } from 'ai'; import { openai } from '@ai-sdk/openai'; export async function POST(req: Request) { const { messages }: { messages: CoreMessage[] } = await req.json(); const result = await streamText({ model: openai('gpt-4'), system: 'You are a helpful assistant.', messages, }); return result.toAIStreamResponse(); }

import { streamUI } from 'ai/rsc'; import { z } from 'zod'; async function submitMessage() { 'use server'; const stream = await streamUI({ model: openai('gpt-4-turbo'), messages: [ { role: 'system', content: 'You are a friendly bot!' }, { role: 'user', content: input }, ], text: ({ content, done }) => { return <div>{content}</div>; }, tools: { deploy: { description: 'Deploy repository to vercel', parameters: z.object({ repositoryName: z .string() .describe('The name of the repository, example: vercel/ai-chatbot'), }), generate: async function* ({ repositoryName }) { yield <div>Cloning repository {repositoryName}...</div>; await new Promise(resolve => setTimeout(resolve, 3000)); yield <div>Building repository {repositoryName}...</div>; await new Promise(resolve => setTimeout(resolve, 2000)); return <div>{repositoryName} deployed!</div>; }, }, }, }); return { ui: stream.value, }; } export const AI = createAI({ initialAIState: {}, initialUIState: {}, actions: { submitMessage, }, });

'use client'; import { useActions } from 'ai/rsc'; import { ReactNode, useState } from 'react'; export default function Page() { const [input, setInput] = useState(''); const [messages, setMessages] = useState<ReactNode[]>([]); const { submitMessage } = useActions(); return ( <div> <input value={input} onChange={event => { setInput(event.target.value); }} /> <button onClick={async () => { const { ui } = await submitMessage(input); setMessages(currentMessages => [...currentMessages, ui]); }} > Submit </button> </div> ); }