Type: Package
Title: Interface to the 'ValidMind' Platform
Version: 2.12.5
Maintainer: Andres Rodriguez <andres@validmind.ai>
Description: Deploy, execute, and analyze the results of models hosted on the 'ValidMind' Platform https://validmind.ai. This package interfaces with the 'Python' Library API in order to allow advanced diagnostics and insight into trained models all from an 'R' environment.
License: AGPL-3
Encoding: UTF-8
URL: https://github.com/validmind/validmind-library
BugReports: https://github.com/validmind/validmind-library/issues
RoxygenNote: 7.3.3
Imports: glue, reticulate, dplyr, plotly, htmltools, rmarkdown, DT, base64enc
NeedsCompilation: no
Packaged: 2026-03-25 22:49:05 UTC; andres
Author: Andres Rodriguez [aut, cre, cph]
Repository: CRAN
Date/Publication: 2026-03-25 23:00:02 UTC

Build an R Plotly figure from a JSON representation

Description

Build an R Plotly figure from a JSON representation

Usage

build_r_plotly(plotly_figure)

Arguments

plotly_figure

A nested list containing plotly elements

Value

An R Plotly object derived from the JSON representation

Produce RMarkdown-compatible output of all results

Description

Produce RMarkdown-compatible output of all results

Usage

display_report(processed_results)

Arguments

processed_results

A list of processed result objects

Value

A formatted list of RMarkdown widgets

Examples

## Not run: 
vm_dataset = vm_r$init_dataset(
  dataset=data,
  target_column="Exited",
  class_labels=list("0" = "Did not exit", "1" = "Exited")
)

tabular_suite_results <- vm_r$run_test_suite("tabular_dataset", dataset=vm_dataset)

processed_results <- process_result(tabular_suite_results)
all_widgets <- display_report(processed_results)
for (widget in all_widgets) {
  print(widget)
}

## End(Not run)

Description

Print a summary table of the ValidMind results

Usage

print_summary_tables(result_summary)

Arguments

result_summary

A summary of the results

Value

A data frame containing the summary of the ValidMind results

Process a set of ValidMind results into parseable data

Description

Process a set of ValidMind results into parseable data

Usage

process_result(results)

Arguments

results

A list of ValidMind result objects

Value

A nested list of ValidMind results (dataframes, plotly plots, and matplotlib plots)

Examples

## Not run: 
vm_dataset = vm_r$init_dataset(
  dataset=data,
  target_column="Exited",
  class_labels=list("0" = "Did not exit", "1" = "Exited")
)

tabular_suite_results <- vm_r$run_test_suite("tabular_dataset", dataset=vm_dataset)

processed_results <- process_result(tabular_suite_results)
processed_results

## End(Not run)

Run a Python expression and display its print() output in R

Description

Wraps a Python call with reticulate::py_capture_output() and displays the result with cat(). Useful in R Jupyter notebooks where Python print() output is not displayed automatically.

Usage

py_print(expr)

Arguments

expr

A Python expression to evaluate

Details

Note: Python logging output (e.g. from run_documentation_tests) is not captured due to reticulate limitations.

Register a Custom Test Function in ValidMind

Description

Registers an R function as a custom test within the ValidMind Library, allowing it to be used as a custom metric for model validation.

Usage

register_custom_test(
  func,
  test_id = NULL,
  description = NULL,
  required_inputs = NULL
)

Arguments

func

An R function to be registered as a custom test.

test_id

A unique identifier for the test. If NULL, a default ID is generated based on the function name.

description

A description of the test. If NULL, the function's description attribute is used. Defaults to "No description" if not available.

required_inputs

A character vector specifying the required inputs for the test. If NULL, the function's formal argument names are used.

Details

The provided R function is converted into a Python callable using r_to_py. A Python class is then defined, inheriting from ValidMind's Metric class, which wraps this callable. This custom test is registered within ValidMind's test store and can be used in the library for model validation purposes.

Value

The test store object containing the newly registered custom test.

See Also

r_to_py, import_main, py_run_string

Examples

## Not run: 
# Define a custom test function in R
my_custom_metric <- function(predictions, targets) {
  # Custom metric logic
  mean(abs(predictions - targets))
}

# Register the custom test
register_custom_test(
  func = my_custom_metric,
  test_id = "custom.mae",
  description = "Custom Mean Absolute Error",
  required_inputs = c("predictions", "targets")
)

## End(Not run)

Run a Custom Test using the ValidMind Framework

Description

This function runs a custom test using the ValidMind Library through Python's 'validmind.vm_models'. It retrieves a custom test by 'test_id', executes it with the provided 'inputs', and optionally displays the result. The result is also logged.

Usage

run_custom_test(test_id, inputs, test_registry, show = FALSE)

Arguments

test_id

A string representing the ID of the custom test to run.

inputs

A list of inputs required for the custom test.

test_registry

A reference to the test register object which provides the custom test class.

show

A logical value. If TRUE, the result will be displayed. Defaults to FALSE.

Value

An object representing the result of the test, with an additional log function.

Examples

## Not run: 
result <- run_custom_test("test123", my_inputs, test_registry, show = TRUE)

## End(Not run)

Save an R model to a temporary file

Description

This function saves a given R model object to a randomly named '.RData' file in the '/tmp/' directory. The file is saved with a unique name generated using random letters.

Usage

save_model(model)

Arguments

model

The R model object to be saved.

Value

A string representing the full file path to the saved '.RData' file.

Examples

model <- lm(mpg ~ cyl, data = mtcars)
file_path <- save_model(model)

Provide a summarization of a single metric result

Description

Provide a summarization of a single metric result

Usage

summarize_metric_result(result)

Arguments

result

The ValidMind result object

Value

A list containing the summary of the ValidMind results

Provide a summarization of a single result (test or metric)

Description

Provide a summarization of a single result (test or metric)

Usage

summarize_result(result)

Arguments

result

The ValidMind result object

Value

Based on the type of 'result', either A list containing the summary of the ValidMind results, or a list containing the summary of the ValidMind results

Provide a summarization of a single test result

Description

Provide a summarization of a single test result

Usage

summarize_test_result(result)

Arguments

result

The ValidMind result object

Value

A list containing the summary of the ValidMind test results

Retrieve a validmind (vm) connection object using reticulate

Description

Retrieve a validmind (vm) connection object using reticulate

Usage

vm(
  api_key,
  api_secret,
  model,
  python_version = Sys.getenv("VALIDMIND_PYTHON", Sys.which("python")),
  api_host = "http://localhost:3000/api/v1/tracking",
  document = NULL
)

Arguments

api_key

The ValidMind API key

api_secret

The ValidMind API secret

model

The ValidMind model

python_version

The path to the Python binary to use. Defaults to the VALIDMIND_PYTHON environment variable, or the system Python.

api_host

The ValidMind host, defaulting to local

document

The document type to associate with this session (e.g. "documentation", "validation-report"). Defaults to NULL.

Value

A validmind connection object, obtained from 'reticulate', which orchestrates the connection to the ValidMind API

Examples

## Not run: 
vm_r <- vm(
   api_host="https://app.prod.validmind.ai/api/v1/tracking",
   api_key="<your_api_key_here>",
   api_secret="<your_api_secret_here>",
   model="<your_model_id_here>",
   document="documentation"
 )

## End(Not run)