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  "Date/Publication": "2026-08-23 16:40:06 UTC",
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    "attach_pkgs",
    "augment",
    "get_vetiver_dashboard_pins",
    "glue_spec_summary",
    "handler_predict",
    "handler_startup",
    "load_pkgs",
    "map_request_body",
    "new_vetiver_model",
    "pin_example_kc_housing_model",
    "required_pkgs",
    "vetiver_api",
    "vetiver_compute_metrics",
    "vetiver_create_description",
    "vetiver_create_meta",
    "vetiver_create_ptype",
    "vetiver_create_rsconnect_bundle",
    "vetiver_dashboard",
    "vetiver_deploy_rsconnect",
    "vetiver_deploy_sagemaker",
    "vetiver_endpoint",
    "vetiver_endpoint_sagemaker",
    "vetiver_meta",
    "vetiver_model",
    "vetiver_pin_metrics",
    "vetiver_pin_read",
    "vetiver_pin_write",
    "vetiver_plot_metrics",
    "vetiver_pr_docs",
    "vetiver_pr_post",
    "vetiver_pr_predict",
    "vetiver_prepare_docker",
    "vetiver_prepare_model",
    "vetiver_ptype",
    "vetiver_python_requirements",
    "vetiver_renviron_requirements",
    "vetiver_sm_build",
    "vetiver_sm_delete",
    "vetiver_sm_endpoint",
    "vetiver_sm_model",
    "vetiver_type_convert",
    "vetiver_write_docker",
    "vetiver_write_plumber"
  ],
  "_help": [
    {
      "page": "api_spec",
      "title": "Update the OpenAPI specification using model metadata",
      "topics": [
        "api_spec",
        "glue_spec_summary",
        "glue_spec_summary.array",
        "glue_spec_summary.data.frame",
        "glue_spec_summary.default"
      ]
    },
    {
      "page": "attach_pkgs",
      "title": "Fully attach or load packages for making model predictions",
      "concept": [
        "namespace"
      ],
      "topics": [
        "attach_pkgs",
        "load_pkgs"
      ]
    },
    {
      "page": "augment.vetiver_endpoint",
      "title": "Post new data to a deployed model API endpoint and augment with predictions",
      "topics": [
        "augment.vetiver_endpoint"
      ]
    },
    {
      "page": "augment.vetiver_endpoint_sagemaker",
      "title": "Post new data to a deployed SageMaker model endpoint and augment with predictions",
      "topics": [
        "augment.vetiver_endpoint_sagemaker"
      ]
    },
    {
      "page": "handler_startup",
      "title": "Model handler functions for API endpoint",
      "topics": [
        "handler_predict",
        "handler_predict.default",
        "handler_predict.gam",
        "handler_predict.glm",
        "handler_predict.int_conformal_cv",
        "handler_predict.int_conformal_full",
        "handler_predict.int_conformal_quantile",
        "handler_predict.int_conformal_split",
        "handler_predict.keras.engine.training.Model",
        "handler_predict.kproto",
        "handler_predict.Learner",
        "handler_predict.lm",
        "handler_predict.luz_module_fitted",
        "handler_predict.model_stack",
        "handler_predict.ranger",
        "handler_predict.recipe",
        "handler_predict.train",
        "handler_predict.workflow",
        "handler_predict.xgb.Booster",
        "handler_startup",
        "handler_startup.default",
        "handler_startup.gam",
        "handler_startup.int_conformal_cv",
        "handler_startup.int_conformal_full",
        "handler_startup.int_conformal_quantile",
        "handler_startup.int_conformal_split",
        "handler_startup.keras.engine.training.Model",
        "handler_startup.Learner",
        "handler_startup.luz_module_fitted",
        "handler_startup.model_stack",
        "handler_startup.ranger",
        "handler_startup.recipe",
        "handler_startup.train",
        "handler_startup.workflow",
        "handler_startup.xgb.Booster"
      ]
    },
    {
      "page": "map_request_body",
      "title": "Identify data types for each column in an input data prototype",
      "topics": [
        "map_request_body"
      ]
    },
    {
      "page": "predict.vetiver_endpoint",
      "title": "Post new data to a deployed model API endpoint and return predictions",
      "topics": [
        "predict.vetiver_endpoint"
      ]
    },
    {
      "page": "predict.vetiver_endpoint_sagemaker",
      "title": "Post new data to a deployed SageMaker model endpoint and return predictions",
      "topics": [
        "predict.vetiver_endpoint_sagemaker"
      ]
    },
    {
      "page": "vetiver_api",
      "title": "Create a Plumber API to predict with a deployable 'vetiver_model()' object",
      "topics": [
        "vetiver_api",
        "vetiver_pr_docs",
        "vetiver_pr_post"
      ]
    },
    {
      "page": "vetiver_compute_metrics",
      "title": "Aggregate model metrics over time for monitoring",
      "topics": [
        "vetiver_compute_metrics"
      ]
    },
    {
      "page": "vetiver_create_description",
      "title": "Model constructor methods",
      "topics": [
        "vetiver_create_description",
        "vetiver_create_description.default",
        "vetiver_create_description.gam",
        "vetiver_create_description.glm",
        "vetiver_create_description.int_conformal_cv",
        "vetiver_create_description.int_conformal_full",
        "vetiver_create_description.int_conformal_quantile",
        "vetiver_create_description.int_conformal_split",
        "vetiver_create_description.keras.engine.training.Model",
        "vetiver_create_description.kproto",
        "vetiver_create_description.Learner",
        "vetiver_create_description.lm",
        "vetiver_create_description.luz_module_fitted",
        "vetiver_create_description.model_stack",
        "vetiver_create_description.ranger",
        "vetiver_create_description.recipe",
        "vetiver_create_description.train",
        "vetiver_create_description.workflow",
        "vetiver_create_description.xgb.Booster",
        "vetiver_prepare_model",
        "vetiver_prepare_model.default",
        "vetiver_prepare_model.gam",
        "vetiver_prepare_model.glm",
        "vetiver_prepare_model.int_conformal_cv",
        "vetiver_prepare_model.int_conformal_full",
        "vetiver_prepare_model.int_conformal_quantile",
        "vetiver_prepare_model.int_conformal_split",
        "vetiver_prepare_model.keras.engine.training.Model",
        "vetiver_prepare_model.kproto",
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        "vetiver_prepare_model.luz_module_fitted",
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