> ## Documentation Index
> Fetch the complete documentation index at: https://docs.luly.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Send 1000 phone calls

<RequestExample>
  ```javascript Sendcall.js
  // Headers
  const headers = {
    authorization: "YOUR-API-KEY-HERE",
  };

  // Data
  const data = {
    base_prompt:
      "You are calling {{business}} to renew their subscription to {{service}} before it expires on {{date}}.",
    call_data: [
      {
        phone_number: "1234567890",
        business: "ABC co.",
        service: "Netflix",
        date: "September 4th",
      },
      {
        phone_number: "32176540987",
        business: "XYZ inc.",
        service: "Window Cleaning",
        date: "December 20th",
      },
    ],
    label: "Renewal Reminder - Wednesday Afternoon with female voice",
    voice_id: 0,
    max_duration: 10,
    reduce_latency: true,
    wait_for_greeting: true,
  };

  // API request
  await axios.post("https://api.luly.ai/v1/batches", data, { headers });

  ```
</RequestExample>

<img src="https://mintlify.s3.us-west-1.amazonaws.com/developersden/images/sendfirstcall.png" />

## Step 1: Setup Your Authorization

To initiate a batch call, you must first authenticate your request. Ensure you have your API key from signing up on the [developer portal](https://portal.luly.ai/).

## Step 2: Prepare the Call Data

Craft a base prompt that will be common across all calls in the batch. Use placeholders `{{curly_braces}}` for dynamic content.

Example:

```
"You are calling {{business}} to renew their subscription to {{service}} before it expires on {{date}}.";
```

## Step 3: Define the Call Data

Specify the list of calls in the `call_data` array. Each call must have a `phone_number`and can include other properties corresponding to placeholders in your base prompt.

Example

```JSON
[
  {
    phone_number: "1234567890",
    business: "ABC co.",
    service: "Netflix",
    date: "September 4th",
  },
  {
    phone_number: "32176540987",
    business: "XYZ inc.",
    service: "Window Cleaning",
    date: "December 20th",
  },
];
```

Step 4: Additional Configuration

* `label` : Assign a label to your batch for easy tracking.
* `campaign_id` : Organize related batches under a campaign.
* `test_mode` : Set to true for testing with the first call only.
* `batch_id` : Manually set or auto-generated for tracking.
* `voice_id` : Select a voice for the batch.
* `reduce_latency` : Reduce latency for faster processing.
* `Language` : Select a language for the batch.
* `request_data` : Assign a label to your batch for easy tracking.
* Voice and Language Settings: Select `voice_id`,`reduce_latency`, and `Language`

## Step 5: Send the API Request

Use the provided JavaScript or Python code snippet to make the API request.

## Step 6: Handle the Response

After sending the batch request, you’ll receive a response with a `message` and the `batch_id`. Monitor the progress of your calls and any responses via your specified webhook.

Here’s what an example response might look like:

```JSON
{
  "message": "success",
  "batch_id": "3p$7rQ3p9sT5bzmF-gen-batch"
}
```

## Step 7: Monitoring and Analytics

Track the performance and outcomes of your batch calls through the provided `batch_id` and campaign analytics. Adjust future batches based on the insights gained.