test

.Rbuildignore

@@ -34,3 +34,8 @@ docs
 tests/testthat/.rds
 t_dm_slide_FAS.rds
 tmp.pptx
+
+# Keys
+.*_KEY
+DEEPSEEK_KEY
+PORTKEY_KEY

.gitignore

@@ -6,3 +6,6 @@ tests/testthat/Rplots.pdf
 tests/testthat/t_dm_output.rds
 tests/testthat/srep.pptx
 docs/
+*_KEY
+PORTKEY_KEY
+DEEPSEEK_KEY

NAMESPACE

@@ -9,6 +9,7 @@ S3method(to_flextable,default)
 S3method(to_flextable,dgtsummary)
 S3method(to_flextable,dlisting)
 S3method(to_flextable,gtsummary)
+export(adding_ai_footnotes)
 export(autoslider_dose_format)
 export(autoslider_error)
 export(autoslider_format)
@@ -37,6 +38,8 @@ export(g_vs_slide)
 export(generate_output)
 export(generate_outputs)
 export(generate_slides)
+export(get_ellmer_chat)
+export(get_prompt_list)
 export(gt_t_dm_slide)
 export(l_ae_slide)
 export(lyt_to_side_by_side)

R/ai.R

@@ -0,0 +1,71 @@
+get_deepseek_key <- function(filename = "DEEPSEEK_KEY"){
+  scan(filename, what = "character", sep = NULL)
+}
+
+get_portkey_key <- function(filename = "PORTKEY_KEY"){
+  scan(filename, what = "character", sep = NULL)
+}
+
+get_system_prompt <- function(text = "you are a Clinical data scientist expert"){
+  return(text)
+}
+
+#'
+#' @export
+#'
+get_ellmer_chat <- function(platform = "deepseek",
+                            base_url = "https://api.deepseek.com",
+                            api_key = get_deepseek_key(),
+                            model = "deepseek-chat") {
+  chat <- NULL
+  if (platform == "deepseek") {
+    chat <- ellmer::chat_deepseek(
+      system_prompt = get_system_prompt(),
+      base_url = base_url,
+      api_key = api_key,
+      model=model)
+  } else if (platform == "galileo"){
+    chat <- chat_portkey(system_prompt = get_system_prompt(),
+                 base_url = base_url,
+                 api_key = api_key,
+                 model = model)
+  }
+  return(chat)
+}
+
+#' @export
+get_prompt_list <- function(filename){
+  prompt <- yaml::read_yaml(filename, eval.expr = TRUE)
+  structure(
+    .Data = prompt,
+    names = map_chr(prompt, `[[`, "output"),
+    class = union("spec", class(prompt))
+  )
+}
+
+
+integrate_prompt <- function(base_prompt, tlg) {
+  # let's do figures in the future
+  ret <- gsub("\\{table_text\\}", export_as_txt(tlg), base_prompt)
+  ret
+}
+
+#' @export
+adding_ai_footnotes <- function(outputs, prompt_list, platform, base_url, api_key, model){
+  chat <- get_ellmer_chat(platform, base_url, api_key, model)
+  names_outputs <- names(outputs)
+  ret <- lapply(names_outputs, function(output_name) {
+    output <- outputs[[output_name]]
+    if (is(output, "autoslider_error")) {
+      return(output)
+    }
+    if (output_name %in% names(prompt_list)){
+      current_prompt <- integrate_prompt(prompt_list[[output_name]]$prompt, output@tbl)
+      output@footnotes <- c(output@footnotes, chat$chat(current_prompt)) #gather_ai_feedback()
+    }
+    output
+  })
+  print(ret)
+  names(ret) <- names_outputs
+  return(ret)
+}

autoslider.core.Rproj

@@ -1,5 +1,5 @@
 Version: 1.0
-ProjectId: 05146cdf-6682-48bb-8f33-b4232d5de690
+ProjectId: 9f3c33a8-faa3-4d7f-bb54-3995f3ae6b2b
 
 RestoreWorkspace: Default
 SaveWorkspace: Default

inst/prompt.yml

@@ -4,7 +4,7 @@ As a Clinical data scientist expert, here is a demographic summary table from a
 
 {table_text}
 
-Please analyze the 'Race' category in this table. Specifically, compare the distribution of races between the '{group1_name}' column and the '{group2_name}' column.
+Please analyze the 'Race' category in this table. Specifically, compare the distribution of races between the Placebo column and the treatment column.
 
 Focus only on describing any noticeable differences or similarities in the counts and percentages for each race listed between these two specific groups, based *directly* on the data presented in the table text provided above.
 

tests/testthat/test_ai.R

@@ -0,0 +1,41 @@
+test_that("Listing print correctly", {
+  testthat::skip_if_not_installed("filters")
+  testthat::skip_if_not_installed("ellmer")
+
+  # skip_if_too_deep(1)
+  filters::load_filters(file.path(
+    system.file(package = "autoslider.core"),
+    "filters.yml"
+  ), overwrite = TRUE)
+
+  spec_file <- file.path(system.file(package = "autoslider.core"), "spec.yml")
+
+  full_spec <- spec_file %>%
+    read_spec()
+
+  outputs <- full_spec %>%
+    filter_spec(., program %in% c(
+      "t_dm_slide"
+    )) %>%
+    generate_outputs(datasets = testdata) %>%
+    decorate_outputs(
+      version_label = NULL,
+      for_test = TRUE
+    )
+  prompt_list <- get_prompt_list(filename = "~/autoslider.core/inst/prompt.yml")
+  outputs <- adding_ai_footnotes(outputs, prompt_list,
+                                 platform = "deepseek",
+                                 base_url = "https://api.deepseek.com",
+                                 api_key = get_deepseek_key("~/autoslider.core/DEEPSEEK_KEY"),
+                                 model = "deepseek-chat")
+  output_dir <- tempdir()
+  testthat::expect_output({
+    outputs %>%
+      generate_slides(outfile = paste0(output_dir, "/srep.pptx"), t_cpp = 250, t_lpp = 50)
+  })
+
+  testthat::expect_no_error({
+    outputs %>%
+      save_outputs(outfolder = output_dir)
+  })
+})