Merge pull request #15 from edgararuiz/updates

Updates

R/llm-classify.R

@@ -49,7 +49,7 @@
 #'   c("urgent", "not urgent")
 #'   )
 #' 
-#' #' # For character vectors, instead of a data frame, use this function
+#' # To preview the first call that will be made to the downstream R function
 #' llm_vec_classify(
 #'   c("this is important!", "just whenever"), 
 #'   c("urgent", "not urgent"), 

R/llm-custom.R

@@ -9,6 +9,29 @@
 #' @param valid_resps If the response from the LLM is not open, but
 #' deterministic, provide the options in a vector. This function will set to
 #' `NA` any response not in the options
+#' @examples
+#' \dontrun{
+#' library(mall)
+#'
+#' llm_use("ollama", "llama3.1", seed = 100, .silent = TRUE)
+#'
+#' reviews <- data.frame(review = c(
+#'   "This has been the best TV I've ever used. Great screen, and sound.",
+#'   "I regret buying this laptop. It is too slow and the keyboard is too noisy",
+#'   "Not sure how to feel about my new washing machine. Great color, but hard to figure"
+#' ))
+#' 
+#' my_prompt <- paste(
+#'   "Answer a question.",
+#'   "Return only the answer, no explanation",
+#'   "Acceptable answers are 'yes', 'no'",
+#'   "Answer this about the following text, is this a happy customer?:"
+#' )
+#' 
+#' reviews |>
+#'   llm_custom(review, my_prompt)
+#' 
+#' } 
 #' @returns `llm_custom` returns a `data.frame` or `tbl` object.
 #' `llm_vec_custom` returns a vector that is the same length as `x`.
 #' @export

R/llm-extract.R

@@ -11,6 +11,49 @@
 #' `labels` is a named vector, this function will use those names as the
 #' new column names, if not, the function will use a sanitized version of
 #' the content as the name.
+#' @examples
+#' \dontrun{
+#' library(mall) 
+#' 
+#' llm_use("ollama", "llama3.1", seed = 100, .silent = TRUE) 
+#' 
+#' reviews <- data.frame(review = c( 
+#'   "This has been the best TV I've ever used. Great screen, and sound.", 
+#'   "I regret buying this laptop. It is too slow and the keyboard is too noisy", 
+#'   "Not sure how to feel about my new washing machine. Great color, but hard to figure" 
+#' )) 
+#' 
+#' # Use 'labels' to let the function know what to extract
+#' llm_extract(reviews, review, labels = "product")
+#' 
+#' # Use 'pred_name' to customize the new column's name 
+#' llm_extract(reviews, review, "product", pred_name = "prod") 
+#' 
+#' # Pass a vector to request multiple things, the results will be pipe delimeted
+#' # in a single column
+#' llm_extract(reviews, review, c("product", "feelings"))
+#' 
+#' # To get multiple columns, use 'expand_cols'
+#' llm_extract(reviews, review, c("product", "feelings"), expand_cols = TRUE)
+#' 
+#' # Pass a named vector to set the resulting column names
+#' llm_extract(
+#'   .data = reviews,
+#'   col =  review,
+#'   labels =  c(prod = "product", feels = "feelings"),
+#'   expand_cols = TRUE
+#'   )
+#' 
+#' # For character vectors, instead of a data frame, use this function 
+#' llm_vec_extract("bob smith, 123 3rd street", c("name", "address")) 
+#' 
+#' # To preview the first call that will be made to the downstream R function 
+#' llm_vec_extract(
+#'   "bob smith, 123 3rd street", 
+#'   c("name", "address"), 
+#'   preview = TRUE
+#'   ) 
+#' }
 #' @returns `llm_extract` returns a `data.frame` or `tbl` object.
 #' `llm_vec_extract` returns a vector that is the same length as `x`.
 #' @export

R/llm-sentiment.R

@@ -36,7 +36,7 @@
 #' # For character vectors, instead of a data frame, use this function
 #' llm_vec_sentiment(c("I am happy", "I am sad"))
 #' 
-#' #' # For character vectors, instead of a data frame, use this function
+#' # To preview the first call that will be made to the downstream R function
 #' llm_vec_sentiment(c("I am happy", "I am sad"), preview = TRUE)
 #' 
 #' }

R/llm-summarize.R

@@ -6,6 +6,37 @@
 #' @inheritParams llm_classify
 #' @param max_words The maximum number of words that the LLM should use in the
 #' summary. Defaults to 10.
+#' @examples
+#' \dontrun{
+#' library(mall) 
+#' 
+#' llm_use("ollama", "llama3.1", seed = 100, .silent = TRUE) 
+#' 
+#' reviews <- data.frame(review = c( 
+#'   "This has been the best TV I've ever used. Great screen, and sound.", 
+#'   "I regret buying this laptop. It is too slow and the keyboard is too noisy", 
+#'   "Not sure how to feel about my new washing machine. Great color, but hard to figure" 
+#' )) 
+#' 
+#' # Use max_words to set the maximum number of words to use for the summary
+#' llm_summarize(reviews, review, max_words = 5) 
+#' 
+#' # Use 'pred_name' to customize the new column's name 
+#' llm_summarize(reviews, review, 5, pred_name = "review_summary") 
+#' 
+#' # For character vectors, instead of a data frame, use this function 
+#' llm_vec_summarize(
+#'   "This has been the best TV I've ever used. Great screen, and sound.",
+#'   max_words = 5
+#'   ) 
+#' 
+#' # To preview the first call that will be made to the downstream R function
+#' llm_vec_summarize(
+#'   "This has been the best TV I've ever used. Great screen, and sound.",
+#'   max_words = 5, 
+#'   preview = TRUE
+#' ) 
+#' }
 #' @returns `llm_summarize` returns a `data.frame` or `tbl` object.
 #' `llm_vec_summarize` returns a vector that is the same length as `x`.
 #' @export

R/llm-translate.R

@@ -6,6 +6,22 @@
 #'
 #' @inheritParams llm_classify
 #' @param language Target language to translate the text to
+#' @examples
+#' \dontrun{
+#' library(mall)
+#'
+#' llm_use("ollama", "llama3.1", seed = 100, .silent = TRUE)
+#'
+#' reviews <- data.frame(review = c(
+#'   "This has been the best TV I've ever used. Great screen, and sound.",
+#'   "I regret buying this laptop. It is too slow and the keyboard is too noisy",
+#'   "Not sure how to feel about my new washing machine. Great color, but hard to figure"
+#' ))
+#'
+#' # Pass the desired language to translate to
+#' llm_translate(reviews, review, "spanish")
+#' 
+#' }
 #' @returns `llm_translate` returns a `data.frame` or `tbl` object.
 #' `llm_vec_translate` returns a vector that is the same length as `x`.
 #' @export

R/llm-use.R

@@ -15,7 +15,30 @@
 #' the same operation is ran again. To turn off, set this argument to an empty
 #' character: `""`. 'It defaults to '_mall_cache'. If this argument is left
 #' `NULL` when calling this function, no changes to the path will be made.
-#'
+#' @examples
+#' \dontrun{
+#' library(mall)
+#' 
+#' llm_use("ollama", "llama3.1")
+#' 
+#' # Additional arguments will be passed 'as-is' to the 
+#' # downstream R function in this example, to ollama::chat()
+#' llm_use("ollama", "llama3.1", seed = 100, temp = 0.1)
+#' 
+#' # During the R session, you can change any argument 
+#' # individually and it will retain all of previous
+#' # arguments used
+#' llm_use(temp = 0.3)
+#' 
+#' # Use .cache to modify the target folder for caching
+#' llm_use(.cache = "_my_cache")
+#' 
+#' # Leave .cache empty to turn off this functionality 
+#' llm_use(.cache = "")
+#' 
+#' # Use .silent to avoid the print out
+#' llm_use(.silent = TRUE)
+#' }
 #' @returns A `mall_session` object
 #'
 #' @export

README.Rmd

@@ -15,18 +15,18 @@ library(dplyr)
 library(dbplyr)
 library(tictoc)
 library(DBI)
-
 source("utils/knitr-print.R")
-
 mall::llm_use("ollama", "llama3.1", seed = 100, .cache = "_readme_cache")
 ```
 
 # mall
 
+<img src="man/figures/favicon/apple-touch-icon-180x180.png" style="float:right" />
+
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 ## Intro