api_spec                Update the OpenAPI specification using model
                        metadata
attach_pkgs             Fully attach or load packages for making model
                        predictions
augment.vetiver_endpoint
                        Post new data to a deployed model API endpoint
                        and augment with predictions
augment.vetiver_endpoint_sagemaker
                        Post new data to a deployed SageMaker model
                        endpoint and augment with predictions
handler_startup.train   Model handler functions for API endpoint
map_request_body        Identify data types for each column in an input
                        data prototype
predict.vetiver_endpoint
                        Post new data to a deployed model API endpoint
                        and return predictions
predict.vetiver_endpoint_sagemaker
                        Post new data to a deployed SageMaker model
                        endpoint and return predictions
vetiver_api             Create a Plumber API to predict with a
                        deployable 'vetiver_model()' object
vetiver_compute_metrics
                        Aggregate model metrics over time for
                        monitoring
vetiver_create_description.train
                        Model constructor methods
vetiver_create_meta.train
                        Metadata constructors for 'vetiver_model()'
                        object
vetiver_create_rsconnect_bundle
                        Create an Posit Connect bundle for a vetiver
                        model API
vetiver_dashboard       R Markdown format for model monitoring
                        dashboards
vetiver_deploy_rsconnect
                        Deploy a vetiver model API to Posit Connect
vetiver_deploy_sagemaker
                        Deploy a vetiver model API to Amazon SageMaker
vetiver_endpoint        Create a model API endpoint object for
                        prediction
vetiver_endpoint_sagemaker
                        Create a SageMaker model API endpoint object
                        for prediction
vetiver_model           Create a vetiver object for deployment of a
                        trained model
vetiver_pin_metrics     Update model metrics over time for monitoring
vetiver_pin_write       Read and write a trained model to a board of
                        models
vetiver_plot_metrics    Plot model metrics over time for monitoring
vetiver_prepare_docker
                        Generate files necessary to build a Docker
                        container for a vetiver model
vetiver_ptype.train     Create a vetiver input data prototype
vetiver_sm_build        Deploy a vetiver model API to Amazon SageMaker
                        with modular functions
vetiver_sm_delete       Delete Amazon SageMaker model, endpoint, and
                        endpoint configuration
vetiver_type_convert    Convert new data at prediction time using input
                        data prototype
vetiver_write_docker    Write a Dockerfile for a vetiver model
vetiver_write_plumber   Write a deployable Plumber file for a vetiver
                        model
