---
title: Vercel AI SDK
description: Use Workers AI with the Vercel AI SDK for streaming text generation, tool calls, and structured output.
image: https://developers.cloudflare.com/dev-products-preview.png
---

> Documentation Index  
> Fetch the complete documentation index at: https://developers.cloudflare.com/workers-ai/llms.txt  
> Use this file to discover all available pages before exploring further. 

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# Vercel AI SDK

Workers AI can be used with the [Vercel AI SDK ↗](https://sdk.vercel.ai/) for JavaScript and TypeScript codebases.

## Setup

Install the [workers-ai-provider provider ↗](https://sdk.vercel.ai/providers/community-providers/cloudflare-workers-ai):

 npm  yarn  pnpm  bun 

```
npm i workers-ai-provider
```

```
yarn add workers-ai-provider
```

```
pnpm add workers-ai-provider
```

```
bun add workers-ai-provider
```

Then, add an AI binding in your Workers project Wrangler file:

TOML

```
[ai]binding = "AI"
```

## Models

The AI SDK can be configured to work with [any AI model](https://developers.cloudflare.com/workers-ai/models/).

JavaScript

```
import { createWorkersAI } from "workers-ai-provider";
const workersai = createWorkersAI({ binding: env.AI });
// Choose any model: https://developers.cloudflare.com/workers-ai/models/const model = workersai("@cf/meta/llama-3.1-8b-instruct", {});
```

## Generate Text

Once you have selected your model, you can generate text from a given prompt.

JavaScript

```
import { createWorkersAI } from 'workers-ai-provider';import { generateText } from 'ai';
type Env = {  AI: Ai;};
export default {  async fetch(_: Request, env: Env) {    const workersai = createWorkersAI({ binding: env.AI });    const result = await generateText({      model: workersai('@cf/meta/llama-2-7b-chat-int8'),      prompt: 'Write a 50-word essay about hello world.',    });
    return new Response(result.text);  },};
```

## Stream Text

For longer responses, consider streaming responses to provide as the generation completes.

JavaScript

```
import { createWorkersAI } from 'workers-ai-provider';import { streamText } from 'ai';
type Env = {  AI: Ai;};
export default {  async fetch(_: Request, env: Env) {    const workersai = createWorkersAI({ binding: env.AI });    const result = streamText({      model: workersai('@cf/meta/llama-2-7b-chat-int8'),      prompt: 'Write a 50-word essay about hello world.',    });
    return result.toTextStreamResponse({      headers: {        // add these headers to ensure that the        // response is chunked and streamed        'Content-Type': 'text/x-unknown',        'content-encoding': 'identity',        'transfer-encoding': 'chunked',      },    });  },};
```

## Generate Structured Objects

You can provide a Zod schema to generate a structured JSON response.

JavaScript

```
import { createWorkersAI } from 'workers-ai-provider';import { generateObject } from 'ai';import { z } from 'zod';
type Env = {  AI: Ai;};
export default {  async fetch(_: Request, env: Env) {    const workersai = createWorkersAI({ binding: env.AI });    const result = await generateObject({      model: workersai('@cf/meta/llama-3.1-8b-instruct'),      prompt: 'Generate a Lasagna recipe',      schema: z.object({        recipe: z.object({          ingredients: z.array(z.string()),          description: z.string(),        }),      }),    });
    return Response.json(result.object);  },};
```

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```