feat: propagate streaming to rest of functions

NAMESPACE

@@ -3,6 +3,7 @@
 export(add_roxygen_addin)
 export(addin_run_scrape_pkgs)
 export(addin_run_select_pkgs)
+export(chat)
 export(chat_with_context)
 export(chat_with_retrieval)
 export(collect_dataframes)

R/embedding.R

@@ -225,6 +225,7 @@ create_index <- function(domain,
 get_top_matches <- function(index, query_embedding, k = 5) {
   k <- min(k, nrow(index))
   index |>
+    tibble::as_tibble() |>
     dplyr::mutate(
       similarity = purrr::map_dbl(embedding, \(x) {
         lsa::cosine(query_embedding, unlist(x))

R/gpt-query.R

@@ -43,7 +43,7 @@ gpt_chat <- function(instructions,
     purrr::map_chr(.f = "content") |>
     paste(collapse = "\n\n")
 
-  answer <- gptstudio::chat(
+  answer <- chat(
     prompt = simple_prompt,
     service = service,
     model = model,

R/history.R

@@ -177,6 +177,8 @@ check_context <- function(context) {
 #' @param local Whether to use the local model or not. Default is FALSE.
 #' @param embedding_model A model object to use for embedding. Only needed if
 #' local is TRUE. Default is NULL.
+#' @param stream Whether to stream the response or not. Default is FALSE.
+#' @param rv A reactive value to store the response. Default is NULL.
 #'
 #' @return A list containing the prompt, context, and answer.
 #' @export
@@ -190,7 +192,7 @@ chat_with_context <- function(query,
                               model = "gpt-4-turbo-preview",
                               index = NULL,
                               add_context = TRUE,
-                              check_context = FASLE,
+                              check_context = FALSE,
                               chat_history = NULL,
                               history_name = "chat_history",
                               session_history = NULL,
@@ -201,7 +203,9 @@ chat_with_context <- function(query,
                               save_history = TRUE,
                               overwrite = FALSE,
                               local = FALSE,
-                              embedding_model = NULL) {
+                              embedding_model = NULL,
+                              stream = FALSE,
+                              rv = NULL) {
   arg_match(task, c("Context Only", "Permissive Chat"))
 
   if (rlang::is_true(check_context)) {
@@ -352,12 +356,33 @@ chat_with_context <- function(query,
   cli_alert_info("Service: {service}")
   cli_alert_info("Model: {model}")
 
-  answer <- gptstudio::chat(
-    prompt = simple_prompt,
-    service = service,
-    model = model,
-    stream = FALSE
-  )
+  cli_alert_info("Stream: {stream}")
+
+  if (rlang::is_true(stream)) {
+    cli_alert_info("Attempting to stream chat.")
+    if (rlang::is_null(rv)) {
+      answer <-
+        stream_chat_openai(
+          prompt = simple_prompt,
+          element_callback = create_stream_handler()
+        )
+    } else {
+      stream_chat_shiny(
+        prompt = simple_prompt,
+        service = service,
+        r = rv,
+        output_id = "streaming"
+      )
+      answer <- rv$response
+    }
+  } else {
+    answer <- chat(
+      prompt = simple_prompt,
+      service = service,
+      model = model,
+      stream = FALSE
+    )
+  }
 
   if (save_history) {
     purrr::map(prompt, \(x) {
@@ -406,7 +431,7 @@ is_context_needed <- function(user_prompt,
                Respond ONLY with TRUE or FALSE.
                \n\n{user_prompt}")
 
-  gptstudio::chat(
+  chat(
     prompt = prompt,
     service = service,
     model = model,

R/index.R

@@ -161,10 +161,17 @@ delete_index <- function() {
 
 combine_index <- function(dir_name) {
   dir <- glue('{tools::R_user_dir("gpttools", which = "data")}/{dir_name}')
-  arrow::open_dataset(
-    sources = dir,
-    factory_options = list(selector_ignore_prefixes = "local")
-  ) |>
+  indices <- list_index(dir_name, full_path = FALSE)
+  if ("All" %in% indices) {
+    cli_abort(
+      c(
+        "!" = "All.parquet already exists in the directory.",
+        "-" = "Please remove it with `delete_index` before combining indexes."
+      )
+    )
+  }
+  list_index(dir_name, full_path = TRUE) |>
+    arrow::open_dataset() |>
     tibble::as_tibble() |>
     arrow::write_parquet(sink = glue::glue("{dir}/All.parquet"))
 }

inst/rstudio/addins.dcf

@@ -37,3 +37,4 @@ Name: Scrape Packages
 Description: Scrape packages for use in Chat with Retrieval app
 Binding: addin_run_scrape_pkgs
 Interactive: true
+

inst/streaming_example.R

@@ -0,0 +1,36 @@
+library(httr2)
+library(shiny)
+library(bslib)
+
+ui <- fluidPage(
+  theme = bslib::bs_theme(version = 5),
+  shinyjs::useShinyjs(),
+  textInput("message", label = "Ask away", placeholder = "Simple ggplot2, be brief."),
+  actionButton("send", "Send"),
+  # div(id = "response"),
+  bslib::card(
+    bslib::card_header("Response"),
+    textOutput(outputId = "response"),
+    h3("some text")
+  )
+)
+
+server <- function(input, output, session) {
+  rv <- reactiveValues(response = NULL)
+  rv$response <- NULL
+  observeEvent(input$send, {
+    req(input$message)
+    shinyjs::show("response")
+    stream_chat_openai(
+      prompt = input$message,
+      element_callback = create_stream_handler_for_shiny(rv, "response")
+    )
+    shinyjs::hide("response")
+  })
+
+  output$response2 <- renderText({
+    rv$response
+  })
+}
+
+shinyApp(ui, server)