Creating a Web Endpoint

from beta9 import endpoint


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

​

Serve

beta9 serve functions like an Ngrok server that live-reloads as you work. Beta9 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 Beta9 workflow end-to-end before deploying.

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

beta9 serve app.py:func

​

Deploying the API

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

beta9 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.

$ beta9 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": ""
}