llmModule 25.06.1: add options that are needed for integration into DataTools (#7)

* add options that are needed for integration into DataTools

* update news.md

* add tests

* fix message

* rename file

* fix output

* update messages

* align argument names

* fix test

* add shinyTryCatch

* update ReadMe

Author: arunge

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: llmModule
 Type: Package
 Title: R Interface for Large Language Model APIs
-Version: 25.06.0
+Version: 25.06.1
 Authors@R: c(
             person("Ricardo", "Fernandes", email = "ldv1452@gmail.com", role = c("aut", "cre")),
             person("Antonia", "Runge", email = "antonia.runge@inwt-statistics.de", role = c("aut"))
@@ -15,11 +15,13 @@ LazyData: true
 Depends: R (>= 3.5.0)
 Imports:
     data.table,
+    futile.logger,
     httr2,
     ollamar,
     shiny,
     shinyAce,
-    shinyjs
+    shinyjs,
+    shinyTools
 Suggests:
     lintr (>= 1.0.2),
     testthat (>= 2.0.0),

NAMESPACE

@@ -14,6 +14,7 @@ S3method(send_prompt,RemoteLlmApi)
 S3method(update,OllamaModelManager)
 export(as_table)
 export(get_llm_models)
+export(has_internet)
 export(llm_generate_prompt_server)
 export(llm_generate_prompt_ui)
 export(new_LlmPromptConfig)
@@ -39,5 +40,7 @@ importFrom(ollamar,list_models)
 importFrom(ollamar,pull)
 importFrom(ollamar,test_connection)
 importFrom(shinyAce,aceEditor)
+importFrom(shinyAce,updateAceEditor)
+importFrom(shinyTools,shinyTryCatch)
 importFrom(shinyjs,disable)
 importFrom(shinyjs,enable)

NEWS.md

@@ -1,3 +1,9 @@
+# llmModule 25.06.1
+
+## New features
+
+* add options to enable integration of `llm_generate_prompt` shiny module into the import module of the `DataTools` package (#3)
+
 # llmModule 25.06.0
 
 ## New features

R/00-LlmApi-helpers.R

@@ -1,3 +1,11 @@
+filter_model_list <- function(models, exclude_pattern) {
+  if (!missing(exclude_pattern) && length(exclude_pattern) > 0 && exclude_pattern != "") {
+    models <- models[!grepl(exclude_pattern, models)]
+  }
+
+  return(models)
+}
+
 categorize_model <- function(id) {
   if (grepl("^gpt-[0-9.]+", id)) {
     match <- regmatches(id, regexpr("^gpt-[0-9.]+", id))

R/00-Namespace.R

@@ -3,7 +3,8 @@
 #' @importFrom data.table data.table rbindlist
 #' @importFrom httr2 req_body_json req_headers req_perform req_timeout request resp_body_json
 #' @importFrom ollamar list_models pull test_connection
-#' @importFrom shinyAce aceEditor
+#' @importFrom shinyAce aceEditor updateAceEditor
 #' @importFrom shinyjs disable enable
+#' @importFrom shinyTools shinyTryCatch
 #'
 NULL

R/00-OllamaModelManager-helpers.R

@@ -76,7 +76,6 @@ is_model_available <- function(manager, model_name) {
 # @param manager An OllamaModelManager object
 # @param model_name Character string of the model name
 # @return An OllamaModel object
-# @export
 pull_model_if_needed <- function(manager, model_name) {
 
   available <- is_model_available(manager, model_name)

R/00-logging.R

@@ -0,0 +1,11 @@
+logging <- function(msg, ...) {
+  futile.logger::flog.info(msg, ...)
+}
+
+logDebug <- function(msg, ...) {
+  futile.logger::flog.debug(msg, ...)
+}
+
+logWarn <- function(msg, ...) {
+  futile.logger::flog.warn(msg, ...)
+}

R/01-LlmPromptConfig-class.R

@@ -4,7 +4,8 @@
 #' making requests to Large Language Models (LLMs) such as OpenAI's GPT models and DeepSeek models.
 #'
 #' @param prompt_content character string containing the primary instruction or query for the model. This serves as the main input to the LLM.
-#' @param model Character string specifying the model to use (e.g., `'gpt-4-turbo'` for OpenAI or `'deepseek-chat'` for DeepSeek). To retrieve a list of valid models for each LLM, use the \code{get_llm_models()} function.
+#' @param model Character string specifying the model to use (e.g., `'gpt-4.1'` for OpenAI or `'deepseek-chat'` for DeepSeek).
+#'  To retrieve a list of valid models for each LLM, use the \code{get_llm_models()} method
 #'
 #' See the following documentation for valid models:
 #' - \href{https://platform.openai.com/docs/models}{OpenAI model list}
@@ -30,10 +31,10 @@
 #' models <- get_llm_models(api)
 #' }
 #'
-#' # Create a parameter object for OpenAI GPT-4 Turbo
+#' # Create a parameter object for OpenAI GPT-4.1
 #' params <- new_LlmPromptConfig(
 #'   prompt_content = 'Explain entropy in simple terms.',
-#'   model = 'gpt-4-turbo',
+#'   model = 'gpt-4.1',
 #'   temperature = 0.7,
 #'   max_tokens = 150
 #' )

R/01-LlmResponse-class.R

@@ -52,10 +52,8 @@ new_LlmResponse <- function(api, prompt_config) {
     error = function(e) e
   )
 
-  if (inherits(content, "error")) {
-    response <- list()
-    attr(response, "error") <- content$message
-    return(response)
+  if (!is.null(attr(content, "error"))) {
+    return(content)
   }
 
   response <- structure(

R/01-LocalLlmApi-class.R

@@ -3,13 +3,16 @@
 #' @param manager An OllamaModelManager object
 #' @param new_model Character, model name input from user (can be partial) of the model to pull
 #' @param base_url Local Ollama base URL
+#' @param exclude_pattern  Character, a regex pattern to exclude certain models from the list of
+#'   available models, e.g. "babbage|curie|dall-e|davinci|text-embedding|tts|whisper"
 #'
 #' @return An object of class LocalLlmApi, or a list with an "error" attribute if construction fails.
 #' @export
 new_LocalLlmApi <- function(
     manager,
     new_model = "",
-    base_url = Sys.getenv("OLLAMA_BASE_URL", unset = "http://localhost:11434")
+    base_url = Sys.getenv("OLLAMA_BASE_URL", unset = "http://localhost:11434"),
+    exclude_pattern = ""
 ) {
   if (!is_ollama_running(url = base_url)) {
     api <- list()
@@ -45,7 +48,8 @@ new_LocalLlmApi <- function(
     list(
       url = base_url,
       provider = "Ollama",
-      manager = manager
+      manager = manager,
+      exclude_pattern = exclude_pattern
     ),
     class = c("LocalLlmApi", "LlmApi")
   )
@@ -84,10 +88,17 @@ print.LocalLlmApi <- function(x, ...) {
 #' @export
 get_llm_models.LocalLlmApi <- function(x, ...) {
   local_models <- x$manager$local_models
+  exclude_pattern <- x$exclude_pattern
 
-  # Extract categories
-  categories <- vapply(local_models, function(x) categorize_model(x), character(1))
+  # Extract models
   models <- vapply(local_models, function(x) x, character(1))
+
+  # Filter models
+  models <- models |> filter_model_list(exclude_pattern = exclude_pattern)
+
+  # Extract categories
+  categories <- vapply(models, function(x) categorize_model(x), character(1))
+
   models_list <- extract_named_model_list(models, categories)
 
   return(models_list)
@@ -127,11 +138,14 @@ send_prompt.LocalLlmApi <- function(api, prompt_config) {
     body$num_predict <- prompt_config$max_tokens
   }
 
-  req <- httr2::request(paste0(api$url, "/api/generate")) |>
-    httr2::req_body_json(body) |>
-    httr2::req_perform()
+  resp <- request(paste0(api$url, "/api/generate")) |>
+    req_body_json(body) |>
+    try_send_request()
 
-  resp <- httr2::resp_body_json(req)
+  # return early if there was an error
+  if (!is.null(attr(resp, "error"))) {
+    return(resp)
+  }
 
   result <- list(
     choices = list(