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

# Async requests

> Execute calls to a Cerebrium app to be run asynchronously

Many apps require asynchronous execution of functions in a "fire-and-forget" fashion
to work optimally. In this scenario, you hand off execution of a function to be Cerebrium's
responsibility, while you as the developer are responsible for ensuring that data is able to leave the function.

You can enable your function to execute asynchronously by adding the `async` query parameter to your request and setting it to `true`. This would look something like this:

```bash theme={null}
curl -X POST https://api.aws.us-east-1.cerebrium.ai/v4/<YOUR-PROJECT-ID>/<YOUR-APP>/run?async=true'\
       -H 'Content-Type: application/json'\
       -H 'Authorization: Bearer <YOUR-JWT-TOKEN>\
       --data '{"param": "hello world"}'
```

This would *immediately* return a response akin to the following, with a body that only specifies a `run_id`:

```bash theme={null}
HTTP/1.1 202 Accepted
Connection: close
Content-Length: 50
Content-Type: application/json
Date: Tue, 12 Nov 2024 03:13:25 GMT
Server: envoy
Vary: Origin
X-Envoy-Upstream-Service-Time: 2
X-Request-Id: 21eb3b98-4b10-9ad6-8681-a47172828024

{"run_id":"21eb3b98-4b10-9ad6-8681-a47172828024"}
```

Async functions will run for a maximum of **12 hours** however will obey a maximum running time of based what is set in your cerebrium.toml file as the `response_grace_period`.
This defaults to 15 minutes so max sure to update it to the maximum time your task needs.

In the background, Cerebrium will now run this HTTP request for you.
Your function is still expected to behave in a **synchronous** manner. That is, it must execute a body of work and return a result once it is done.
If you terminate your function early and return a response while the application is still doing work, the Cerebrium
system will begin to terminate the application. Therefore, you should only return a response once the container
has finished processing the task, and not earlier.

To use async execution effectively, you must ensure that your function exports any relevant data you
need, since you will no longer be able to receive a request. An easy way to achieve this would be to combine
async execution with a specified `webhookEndpoint`, to have Cerebrium automatically forward the body of
the function response once it has returned:

```bash theme={null}
curl -X POST <https://api.aws.us-east-1.cerebrium.ai/v4/><YOUR-PROJECT-ID>/<YOUR-APP>/run?async=true&webhookEndpoint=https%3A%2F%2Fwebhook.site%2F'\
 -H 'Content-Type: application/json'\
 -H 'Authorization: Bearer <YOUR-JWT-TOKEN>\
 --data '{"param": "hello world"}'
```

As with webhooks, this a feature of our proxy, and you will not need to modify any part of your code to use the webhook
functionality. In your dashboard, your function will be marked as **async**, but will still show the status of the internal synchronous call
that was made (in other words, if the call to your function failed, the state of your async request would be `failure` etc.)