vetiver.VetiverAPI#

class vetiver.VetiverAPI(model: vetiver.vetiver_model.VetiverModel, check_prototype: bool = True, app_factory=<class 'fastapi.applications.FastAPI'>, **kwargs)#

Create model aware API

Parameters
  • model (VetiverModel) – Model to be deployed in API

  • check_prototype (bool) – Determine if data prototype should be enforced

  • app_factory – Type of API to be deployed

  • **kwargs (dict) – Deprecated parameters.

Examples

>>> import vetiver as vt
>>> X, y = vt.get_mock_data()
>>> model = vt.get_mock_model().fit(X, y)
>>> v = vt.VetiverModel(model = model, model_name = "my_model", prototype_data = X)
>>> v_api = vt.VetiverAPI(model = v, check_prototype = True)

Notes

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

__init__(model: vetiver.vetiver_model.VetiverModel, check_prototype: bool = True, app_factory=<class 'fastapi.applications.FastAPI'>, **kwargs) None#

Methods

__init__(model[, check_prototype, app_factory])

run([port, host])

Start API

vetiver_post(endpoint_fx[, endpoint_name])

Create new POST endpoint that is aware of model input data

Attributes

app