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.
You will need Node.js 18+ and pnpm installed on your local development machine.
npm install ai
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
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();
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.
'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();
}
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.
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,
},
});
import { ReactNode } from 'react';
import { AI } from '@/app/actions';
export default function Layout({ children }: { children: ReactNode }) {
<AI>{children}</AI>;
}
'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>
);
}
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.
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.
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.
This library is created by Vercel and Next.js team members, with contributions from the Open Source Community.