VetiverAPI
VetiverAPI(self, model, show_prototype=True, check_prototype=True, app_factory=FastAPI, **kwargs)
Create model aware API
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
model |
VetiverModel | Model to be deployed in API | required |
show_prototype |
bool | True |
|
check_prototype |
bool | Determine if data prototype should be enforced | True |
app_factory |
Type of API to be deployed | FastAPI |
|
**kwargs |
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
This generates an API with either 3 or 4 GET endpoints and 1 POST endpoint.
├──/ping (GET)
├──/metadata (GET)
├──/prototype (GET)
├──/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 |
|---|---|
| vetiver.VetiverAPI.run | Start API |
| vetiver.VetiverAPI.vetiver_post | Create new POST endpoint that is aware of model input data |