Creating a Web Endpoint

from beam import endpoint


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

​

Launch a Preview Environment

beam serve monitors changes in your local file system, live-reloads the remote environment as you work, and forwards 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

​

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.

$ beam deploy app.py:multiply --name multiply-numbers

=> Building image
=> Using cached image
=> Syncing files
Reading .beamignore file
=> Files synced
=> Deploying endpoint
=> Deployed 🎉
=> Invocation details

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 '{}'

​

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": ""
}