Prepare foundryR for CRAN release

DESCRIPTION

@@ -1,13 +1,15 @@
 Package: foundryR
 Title: Tibble Workflows for 'Azure AI Foundry'
-Version: 0.0.0.9000
+Version: 0.1.0
 Authors@R:
     person("Alex", "Farach", , "alexfarach@microsoft.com", role = c("aut", "cre", "cph"))
-Description: Work with 'Microsoft Azure AI Foundry' from dataframe-oriented
-    'R' workflows. Returns tibbles for Content Safety, Responses API calls,
-    strict structured extraction, embeddings, files, batch jobs, audio, media,
-    and chat completions. Supports research annotation, safety gates,
-    semantic search, and 'tidymodels' recipes for teams committed to Azure.
+Description: Work with 'Microsoft Azure AI Foundry' from data-frame-oriented
+    'R' workflows. Provides tibble-returning helpers for 'Azure AI Content
+    Safety', 'Azure OpenAI' Responses API calls, strict structured extraction,
+    embeddings, files, batch jobs, audio, media, and chat completions. Supports
+    research annotation, safety gates, semantic search, and 'tidymodels'
+    recipes. Helps teams keep model workflows inside their 'Azure' environment
+    while preserving analyzable outputs.
 License: MIT + file LICENSE
 Depends:
     R (>= 4.1.0)

LICENSE

@@ -1,2 +1,2 @@
-YEAR: 2025
+YEAR: 2026
 COPYRIGHT HOLDER: Alex Farach

NEWS.md

@@ -1,6 +1,6 @@
-# foundryR 0.0.0.9000
+# foundryR 0.1.0
 
-Initial development release of foundryR, a tidy interface to Microsoft Azure AI Foundry.
+Initial CRAN release of foundryR, a tidy interface to Microsoft Azure AI Foundry.
 
 ## New features
 

R/batches.R

@@ -376,6 +376,18 @@ foundry_extract_batch <- function(data,
 #'
 #' @return A one-row tibble with token totals and optional `cost`.
 #' @export
+#'
+#' @examples
+#' responses <- data.frame(
+#'   input_tokens = c(10, 20),
+#'   cached_input_tokens = c(0, 5),
+#'   output_tokens = c(3, 7)
+#' )
+#' foundry_usage(responses)
+#' foundry_usage(
+#'   responses,
+#'   rates = c(input = 0.000001, cached_input = 0.0000001, output = 0.000004)
+#' )
 foundry_usage <- function(x, rates = NULL) {
   if (!is.data.frame(x)) {
     cli::cli_abort("{.arg x} must be a data frame.")

R/codebook.R

@@ -21,7 +21,6 @@
 #' @export
 #'
 #' @examples
-#' \dontrun{
 #' codebook <- foundry_codebook(
 #'   name = "ai-applicability",
 #'   version = "1.0.0",
@@ -34,7 +33,6 @@
 #'     list(text = "Lift a heavy box", ai_applicable = FALSE)
 #'   )
 #' )
-#' }
 foundry_codebook <- function(name,
                              version,
                              instructions,
@@ -76,6 +74,12 @@ foundry_codebook <- function(name,
 #'
 #' @return A JSON Schema fragment represented as an R list.
 #' @name codebook_schema_helpers
+#'
+#' @examples
+#' type_boolean("Whether AI could materially assist the task")
+#' type_enum("Priority label", values = c("low", "medium", "high"))
+#' type_number("Confidence score")
+#' type_string("Short rationale")
 NULL
 
 
@@ -119,9 +123,22 @@ type_string <- function(desc = NULL) {
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' codebook_diff(old_codebook, new_codebook)
-#' }
+#' old <- foundry_codebook(
+#'   name = "support-sentiment",
+#'   version = "1.0.0",
+#'   instructions = "Label the sentiment of support tickets.",
+#'   schema = foundry_schema(sentiment = type_enum(values = c("pos", "neg")))
+#' )
+#' new <- foundry_codebook(
+#'   name = "support-sentiment",
+#'   version = "1.1.0",
+#'   instructions = "Label the sentiment and urgency of support tickets.",
+#'   schema = foundry_schema(
+#'     sentiment = type_enum(values = c("pos", "neg")),
+#'     urgent = type_boolean()
+#'   )
+#' )
+#' codebook_diff(old, new)
 codebook_diff <- function(old, new) {
   foundry_check_codebook(old, "old")
   foundry_check_codebook(new, "new")

R/content-safety-extra.R

@@ -78,6 +78,13 @@ foundry_moderate_image <- function(image,
 #'
 #' @return A tibble with one row per input text.
 #' @export
+#'
+#' @examples
+#' if (interactive() &&
+#'     nzchar(Sys.getenv("AZURE_CONTENT_SAFETY_ENDPOINT")) &&
+#'     nzchar(Sys.getenv("AZURE_CONTENT_SAFETY_KEY"))) {
+#'   foundry_protected_material("A short text sample.")
+#' }
 foundry_protected_material <- function(text,
                                        endpoint = NULL,
                                        api_key = NULL,
@@ -126,6 +133,21 @@ foundry_protected_material <- function(text,
 #'
 #' @return A tibble with blocklist or blocklist-item metadata.
 #' @name foundry_blocklists
+#'
+#' @examples
+#' if (interactive() &&
+#'     nzchar(Sys.getenv("AZURE_CONTENT_SAFETY_ENDPOINT")) &&
+#'     nzchar(Sys.getenv("AZURE_CONTENT_SAFETY_KEY"))) {
+#'   foundry_blocklists()
+#'   foundry_blocklist_create("example-blocklist", description = "Example")
+#'   foundry_blocklist_get("example-blocklist")
+#'   items <- foundry_blocklist_add_items("example-blocklist", "blocked phrase")
+#'   foundry_blocklist_items("example-blocklist")
+#'   if (nrow(items) > 0 && !is.na(items$item_id[[1]])) {
+#'     foundry_blocklist_remove_items("example-blocklist", items$item_id)
+#'   }
+#'   foundry_blocklist_delete("example-blocklist")
+#' }
 NULL
 
 

R/conversations.R

@@ -13,6 +13,21 @@
 #'
 #' @return A tibble with conversation metadata or conversation items.
 #' @name foundry_conversations
+#'
+#' @examples
+#' if (interactive() &&
+#'     nzchar(Sys.getenv("AZURE_FOUNDRY_ENDPOINT")) &&
+#'     nzchar(Sys.getenv("AZURE_FOUNDRY_KEY"))) {
+#'   conversation <- foundry_conversation_create(
+#'     metadata = list(example = "cran")
+#'   )
+#'   id <- conversation$conversation_id[[1]]
+#'   foundry_conversations(limit = 10)
+#'   foundry_conversation_get(id)
+#'   foundry_conversation_update(id, metadata = list(example = "updated"))
+#'   foundry_conversation_items(id)
+#'   foundry_conversation_delete(id)
+#' }
 NULL
 
 

R/schema.R

@@ -50,6 +50,14 @@ foundry_schema <- function(...,
 #'
 #' @return A JSON Schema fragment represented as an R list.
 #' @name schema_constructors
+#'
+#' @examples
+#' schema_string("Free-text label")
+#' schema_enum(c("positive", "negative", "neutral"))
+#' schema_object(
+#'   sentiment = schema_enum(c("positive", "negative", "neutral")),
+#'   confidence = schema_number()
+#' )
 NULL
 
 
@@ -168,6 +176,10 @@ schema_object <- function(...,
 #'
 #' @return A JSON Schema represented as an R list.
 #' @export
+#'
+#' @examples
+#' schema <- foundry_schema(label = schema_string())
+#' as_foundry_schema(schema)
 as_foundry_schema <- function(x) {
   if (inherits(x, "ellmer::Type")) {
     return(foundry_preserve_schema_arrays(ellmer_type_to_schema(x)))

R/utils-pipe.R

@@ -11,4 +11,6 @@
 #' @param lhs A value or the magrittr placeholder.
 #' @param rhs A function call using the magrittr semantics.
 #' @return The result of calling `rhs(lhs)`.
+#' @examples
+#' 1:3 %>% sum()
 NULL

R/validation.R

@@ -121,6 +121,14 @@ foundry_consistency <- function(text, schema, n = 3L, ...) {
 #'
 #' @return A one-row tibble.
 #' @export
+#'
+#' @examples
+#' schema <- foundry_schema(label = schema_string())
+#' foundry_provenance(
+#'   model = "gpt-5-nano",
+#'   schema = schema,
+#'   metadata = list(run = "pilot")
+#' )
 foundry_provenance <- function(model, schema, metadata = NULL) {
   foundry_check_character_scalar(model, "model")
   schema <- as_foundry_schema(schema)

R/vector-stores.R

@@ -20,6 +20,26 @@
 #'
 #' @return A tibble with vector store, file, or search-result metadata.
 #' @name foundry_vector_stores
+#'
+#' @examples
+#' if (interactive() &&
+#'     nzchar(Sys.getenv("AZURE_FOUNDRY_ENDPOINT")) &&
+#'     nzchar(Sys.getenv("AZURE_FOUNDRY_KEY"))) {
+#'   store <- foundry_vector_store_create("example-store")
+#'   id <- store$vector_store_id[[1]]
+#'   foundry_vector_stores(limit = 10)
+#'   foundry_vector_store_get(id)
+#'   foundry_vector_store_modify(id, name = "renamed-example-store")
+#'   foundry_vector_store_files(id)
+#'   file_id <- Sys.getenv("AZURE_FOUNDRY_FILE_ID")
+#'   if (nzchar(file_id)) {
+#'     foundry_vector_store_file_add(id, file_id)
+#'     foundry_vector_store_file_remove(id, file_id)
+#'     foundry_vector_store_file_batch(id, file_id)
+#'     foundry_vector_search(id, "example query")
+#'   }
+#'   foundry_vector_store_delete(id)
+#' }
 NULL
 
 
@@ -260,6 +280,9 @@ foundry_vector_search <- function(vector_store_id,
 #'
 #' @return A Responses API tool definition list.
 #' @export
+#'
+#' @examples
+#' foundry_tool_file_search("vs_abc123", max_num_results = 3)
 foundry_tool_file_search <- function(vector_store_ids, max_num_results = NULL) {
   if (!is.character(vector_store_ids) || length(vector_store_ids) == 0L ||
       any(is.na(vector_store_ids))) {

README.Rmd

@@ -38,7 +38,7 @@ if (run_api) {
 }
 ```
 
-# foundryR <a href="https://farach.github.io/foundryR/"><img src="man/figures/logo.svg" align="right" height="138" alt="foundryR website" /></a>
+# foundryR <a href="https://farach.github.io/foundryR/"><img src="https://raw.githubusercontent.com/farach/foundryR/main/man/figures/logo.svg" align="right" height="138" alt="foundryR website" /></a>
 
 <!-- badges: start -->
 [![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
@@ -57,6 +57,12 @@ Its strongest path is dataframe in, dataframe out.
 
 ## Installation
 
+Install the released version from CRAN:
+
+```r
+install.packages("foundryR")
+```
+
 Install the development version from GitHub:
 
 ```r

README.md

@@ -3,7 +3,7 @@
 <!-- Executable chunks replay recorded, credential-free API fixtures.        -->
 <!-- Regenerate with: source("data-raw/record-doc-outputs.R")               -->
 
-# foundryR <a href="https://farach.github.io/foundryR/"><img src="man/figures/logo.svg" align="right" height="138" alt="foundryR website" /></a>
+# foundryR <a href="https://farach.github.io/foundryR/"><img src="https://raw.githubusercontent.com/farach/foundryR/main/man/figures/logo.svg" align="right" height="138" alt="foundryR website" /></a>
 
 <!-- badges: start -->
 
@@ -34,6 +34,12 @@ Its strongest path is dataframe in, dataframe out.
 
 ## Installation
 
+Install the released version from CRAN:
+
+``` r
+install.packages("foundryR")
+```
+
 Install the development version from GitHub:
 
 ``` r

cran-comments.md

@@ -1,3 +1,11 @@
+## Submission
+
+This is the first CRAN submission for foundryR.
+
+## Test environments
+
+- Local Windows 11 x64, R 4.5.2
+
 ## R CMD check results
 
 0 errors | 0 warnings | 0 notes

inst/extdata/samples/README

@@ -0,0 +1,11 @@
+jfk.wav
+=======
+
+jfk.wav is a short excerpt from John F. Kennedy's January 20, 1961
+inaugural address, included as a small speech-recognition example. The
+address is a U.S. federal government work and is in the public domain in
+the United States under 17 U.S.C. 105.
+
+Source recording: John F. Kennedy Presidential Library and Museum,
+"The Inaugural Address":
+https://www.jfklibrary.org/learn/about-jfk/historic-speeches/the-inaugural-address