Skip to content

Handling vetiver objects

A vetiver_model() collects the information needed to store, version, and deploy a trained model.

vetiver_model() new_vetiver_model()
Create a vetiver object for deployment of a trained model
vetiver_pin_write() vetiver_pin_read()
Read and write a trained model to a board of models
vetiver_api() vetiver_pr_post() vetiver_pr_docs()
Create a Plumber API to predict with a deployable vetiver_model() object
vetiver_write_plumber()
Write a deployable Plumber file for a vetiver model
vetiver_write_docker()
Write a Dockerfile for a vetiver model
vetiver_prepare_docker()
Generate files necessary to build a Docker container for a vetiver model
vetiver_endpoint()
Create a model API endpoint object for prediction
predict(<vetiver_endpoint>)
Post new data to a deployed model API endpoint and return predictions
augment(<vetiver_endpoint>)
Post new data to a deployed model API endpoint and augment with predictions

Posit Connect

Deploy your vetiver model to Posit Connect.

vetiver_deploy_rsconnect()
Deploy a vetiver model API to Posit Connect
vetiver_create_rsconnect_bundle()
Create an Posit Connect bundle for a vetiver model API

SageMaker

Deploy your vetiver model to Amazon SageMaker.

vetiver_deploy_sagemaker()
Deploy a vetiver model API to Amazon SageMaker
vetiver_endpoint_sagemaker()
Create a SageMaker model API endpoint object for prediction
predict(<vetiver_endpoint_sagemaker>)
Post new data to a deployed SageMaker model endpoint and return predictions
augment(<vetiver_endpoint_sagemaker>)
Post new data to a deployed SageMaker model endpoint and augment with predictions
vetiver_sm_build() vetiver_sm_model() vetiver_sm_endpoint()
Deploy a vetiver model API to Amazon SageMaker with modular functions
vetiver_sm_delete()
Delete Amazon SageMaker model, endpoint, and endpoint configuration

Monitoring deployed models

Monitor a deployed vetiver_model() with a dashboard.

vetiver_compute_metrics()
Aggregate model metrics over time for monitoring
vetiver_pin_metrics()
Update model metrics over time for monitoring
vetiver_plot_metrics()
Plot model metrics over time for monitoring
vetiver_dashboard() get_vetiver_dashboard_pins() pin_example_kc_housing_model()
R Markdown format for model monitoring dashboards

Developer functions

These functions are helpful for developers extending vetiver for other types of models.

api_spec() glue_spec_summary()
Update the OpenAPI specification using model metadata
attach_pkgs() load_pkgs()
Fully attach or load packages for making model predictions
handler_startup() handler_predict()
Model handler functions for API endpoint
map_request_body()
Identify data types for each column in an input data prototype
vetiver_create_description() vetiver_prepare_model()
Model constructor methods
vetiver_meta() vetiver_create_meta()
Metadata constructors for vetiver_model() object
vetiver_ptype() vetiver_create_ptype()
Create a vetiver input data prototype
vetiver_type_convert()
Convert new data at prediction time using input data prototype