from beam import endpoint


@endpoint(
    cpu=1.0,
    memory=128,
)
def multiply(**inputs):
    result = inputs["x"] * 2
    return {"result": result}

Serve

beam serve functions like an Ngrok server that live-reloads as you work. Beam monitors changes in your local file system and forwards the remote container logs to your local shell.

Serve is great for prototyping. You can develop in a containerized cloud environment in real-time, with adjustable CPU, memory, GPU resources.

It’s also great for testing an app before deploying it. Served functions are orchestrated identically to deployments, which means you can test your Beam workflow end-to-end before deploying.

To start an ephemeral serve session, you’ll use the serve command:

beam serve app.py:func
Sessions end automatically after 10 minutes of inactivity.

By default, Beam will sync all the files in your working directory to the remote container. This allows you to use the files you have locally while developing. If you want to prevent some files from getting uploaded, you can create a .beamignore.

Deploying the API

To deploy the app, enter your shell and run this command from the working directory:

beam deploy [FILE.PY]:[ENTRY-POINT] --name [NAME]

After running this command, you’ll see some logs in the console that show the progress of your deployment.

Calling the API

After deploying the API, you’ll be able to copy a cURL request to hit the API. In your app dashboard, click Call API.

Example Request

curl -X POST 'https://app.beam.cloud/endpoint/multiply-numbers/v1' \
-H 'Accept: */*' \
-H 'Accept-Encoding: gzip, deflate' \
-H 'Connection: keep-alive' \
-H 'Authorization: Bearer [YOUR_AUTH_TOKEN]' \
-H 'Content-Type: application/json' \
-d '{"x": 10}'

Example Response

{
  "result": {
    "result": 20
  },
  "msg": "",
  "error_msg": ""
}