Once the endpoint has finished updating:
endpoint.update(model_version, strategy, wait=True)
Users can make queries to it. This tutorial will explore several ways to do this, using the client and CLI.
Given an endpoint (which has a model deployed to it), we can make queries as follows:
deployed_model = endpoint.get_deployed_model()results = deployed_model.predict(test_data)
We can also make queries via cURL requests. An example request is given in the string representation of the endpoint object:
print(endpoint)# This should print out similar to:# path: <some-path># id: <some-id># curl: curl -X POST <prediction-url> -d '' -H "Content-Type: application/json"# ...
Verta's CLI also has a
predict command for querying an endpoint:
verta deployment predict endpoint /some-path --data '[0, 1, 1, 1]'
The input passed to
data option must have JSON format.