---
title: Workers Binding · Cloudflare Workers AI docs
description: You can use Workers Bindings to interact with the Batch API.
lastUpdated: 2025-04-10T22:24:36.000Z
source_url:
  html: https://zt-dark-mode-changelog.preview.developers.cloudflare.com/workers-ai/features/batch-api/workers-binding/index.md
  md: https://zt-dark-mode-changelog.preview.developers.cloudflare.com/workers-ai/features/batch-api/workers-binding/
---

You can use Workers Bindings to interact with the Batch API.

## Send a Batch request

Send your initial batch inference request by composing a JSON payload containing an array of individual inference requests and the `queueRequest: true` property (which is what controlls queueing behavior).

Note

Ensure that the total payload is under 10 MB.

```ts
export interface Env {
  AI: Ai;
}
export default {
  async fetch(request, env): Promise<Response> {
    const embeddings = await env.AI.run(
      "@cf/baai/bge-m3",
      {
        requests: [
          {
            query: "This is a story about Cloudflare",
            contexts: [
              {
                text: "This is a story about an orange cloud",
              },
              {
                text: "This is a story about a llama",
              },
              {
                text: "This is a story about a hugging emoji",
              },
            ],
          },
        ],
      },
      { queueRequest: true },
    );


    return Response.json(embeddings);
  },
} satisfies ExportedHandler<Env>;
```

```json
{
  "status": "queued",
  "model": "@cf/baai/bge-m3",
  "request_id": "000-000-000"
}
```

You will get a response with the following values:

* **`status`**: Indicates that your request is queued.
* **`request_id`**: A unique identifier for the batch request.
* **`model`**: The model used for the batch inference.

Of these, the `request_id` is important for when you need to [poll the batch status](#poll-batch-status).

### Poll batch status

Once your batch request is queued, use the `request_id` to poll for its status. During processing, the API returns a status `queued` or `running` indicating that the request is still in the queue or being processed.

```typescript
export interface Env {
  AI: Ai;
}


export default {
  async fetch(request, env): Promise<Response> {
    const status = await env.AI.run("@cf/baai/bge-m3", {
      request_id: "000-000-000",
    });


    return Response.json(status);
  },
} satisfies ExportedHandler<Env>;
```

```json
{
  "responses": [
    {
      "id": 0,
      "result": {
        "response": [
          { "id": 0, "score": 0.73974609375 },
          { "id": 1, "score": 0.642578125 },
          { "id": 2, "score": 0.6220703125 }
        ]
      },
      "success": true,
      "external_reference": null
    }
  ],
  "usage": { "prompt_tokens": 12, "completion_tokens": 0, "total_tokens": 12 }
}
```

When the inference is complete, the API returns a final HTTP status code of `200` along with an array of responses. Each response object corresponds to an individual input prompt, identified by an `id` that maps to the index of the prompt in your original request.
