---
title: Workers Bindings
description: Create an AI binding to connect your Cloudflare Worker to Workers AI.
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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# Workers Bindings

## Workers

[Workers](https://developers.cloudflare.com/workers/) provides a serverless execution environment that allows you to create new applications or augment existing ones.

To use Workers AI with Workers, you must create a Workers AI [binding](https://developers.cloudflare.com/workers/runtime-apis/bindings/). Bindings allow your Workers to interact with resources, like Workers AI, on the Cloudflare Developer Platform. You create bindings on the Cloudflare dashboard or by updating your [Wrangler file](https://developers.cloudflare.com/workers/wrangler/configuration/).

To bind Workers AI to your Worker, add the following to the end of your Wrangler file:

* [  wrangler.jsonc ](#tab-panel-11635)
* [  wrangler.toml ](#tab-panel-11636)

JSONC

```
{  "ai": {    "binding": "AI" // i.e. available in your Worker on env.AI  }}
```

TOML

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

## Pages Functions

[Pages Functions](https://developers.cloudflare.com/pages/functions/) allow you to build full-stack applications with Cloudflare Pages by executing code on the Cloudflare network. Functions are Workers under the hood.

To configure a Workers AI binding in your Pages Function, you must use the Cloudflare dashboard. Refer to [Workers AI bindings](https://developers.cloudflare.com/pages/functions/bindings/#workers-ai) for instructions.

## Methods

### async env.AI.run()

`async env.AI.run()` runs a model. Takes a model as the first parameter, and an object as the second parameter.

JavaScript

```
const answer = await env.AI.run('@cf/meta/llama-3.1-8b-instruct', {    prompt: "What is the origin of the phrase 'Hello, World'"});
```

**Parameters**

* `model` ` string ` required

  * The model to run.

**Supported options**

  * `stream` ` boolean ` optional  
    * Returns a stream of results as they are available.

JavaScript

```
const answer = await env.AI.run('@cf/meta/llama-3.1-8b-instruct', {    prompt: "What is the origin of the phrase 'Hello, World'",    stream: true});
return new Response(answer, {    headers: { "content-type": "text/event-stream" }});
```

```json
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```