VetiverAPI

VetiverAPI(
    self,
    model: VetiverModel,
    show_prototype: bool = True,
    check_prototype: bool = True,
    app_factory,
    **kwargs,
)

Create model aware API

Parameters

model : VetiverModel

Model to be deployed in API

show_prototype : bool = True

Whether or not to show the data prototype in the API

check_prototype : bool = True

Determine if data prototype should be enforced

app_factory : = FastAPI

Type of API to be deployed

****kwargs** : = {}

Deprecated parameters.

Examples

from vetiver import mock, VetiverModel, VetiverAPI
X, y = mock.get_mock_data()
model = mock.get_mock_model().fit(X, y)

v = VetiverModel(model = model, model_name = "my_model", prototype_data = X)
api = VetiverAPI(model = v, check_prototype = True)

Notes

This generates an API with 2-4 GET endpoints and 1 POST endpoint.

├──/ping (GET)
├──/metadata (GET)
├──/prototype (GET, if `show_prototype` is True)
├──/pin-url (GET, if VetiverModel metadata `url` field is not None)
└──/predict (POST)

Parameter check_ptype was changed to check_prototype. Handling of check_ptype will be removed in a future version.

Methods

Name	Description
run	Start API
vetiver_post	Create new POST endpoint that is aware of model input data