Update app.R

app.R

@@ -1,58 +1,52 @@
 library(shiny)
-library(bslib)
-library(dplyr)
-library(ggplot2)
+library(httr2)
 
-df <- readr::read_csv("penguins.csv")
-# Find subset of columns that are suitable for scatter plot
-df_num <- df |> select(where(is.numeric), -Year)
-
-ui <- page_sidebar(
-  theme = bs_theme(bootswatch = "minty"),
-  title = "Penguins explorer",
-  sidebar = sidebar(
-    varSelectInput("xvar", "X variable", df_num, selected = "Bill Length (mm)"),
-    varSelectInput("yvar", "Y variable", df_num, selected = "Bill Depth (mm)"),
-    checkboxGroupInput("species", "Filter by species",
-      choices = unique(df$Species), selected = unique(df$Species)
+ui <- fluidPage(
+  titlePanel("Chat com NVIDIA NIM via httr2"),
+  sidebarLayout(
+    sidebarPanel(
+      textAreaInput("pergunta", "Digite sua pergunta:", 
+                    "Descreva o package leaflet no R.", rows = 4),
+      actionButton("enviar", "Enviar")
     ),
-    hr(), # Add a horizontal rule
-    checkboxInput("by_species", "Show species", TRUE),
-    checkboxInput("show_margins", "Show marginal plots", TRUE),
-    checkboxInput("smooth", "Add smoother"),
-  ),
-  plotOutput("scatter")
+    mainPanel(
+      h4("Resposta:"),
+      verbatimTextOutput("resposta")
+    )
+  )
 )
 
 server <- function(input, output, session) {
-  subsetted <- reactive({
-    req(input$species)
-    df |> filter(Species %in% input$species)
+  resposta <- reactiveVal("")
+  
+  observeEvent(input$enviar, {
+    req <- request("https://integrate.api.nvidia.com/v1/chat/completions") |>
+      req_headers(
+        Authorization = paste("Bearer", Sys.getenv("OPENAI_API_KEY")),
+        `Content-Type` = "application/json"
+      ) |>
+      req_body_json(list(
+        model = "meta/llama-3.1-70b-instruct",
+        messages = list(
+          list(role = "system", content = "You are a helpful assistant."),
+          list(role = "user",   content = input$pergunta)
+        ),
+        max_tokens = 400
+      ))
+    
+    tryCatch({
+      resp <- req_perform(req)
+      out  <- resp_body_json(resp)
+      resposta(out$choices[[1]]$message$content)
+    }, error = function(e) {
+      resposta(paste("Erro:", e$message))
+    })
+  })
+  
+  output$resposta <- renderText({
+    resposta()
   })
-
-  output$scatter <- renderPlot(
-    {
-      p <- ggplot(subsetted(), aes(!!input$xvar, !!input$yvar)) +
-        theme_light() +
-        list(
-          theme(legend.position = "bottom"),
-          if (input$by_species) aes(color = Species),
-          geom_point(),
-          if (input$smooth) geom_smooth()
-        )
-
-      if (input$show_margins) {
-        margin_type <- if (input$by_species) "density" else "histogram"
-        p <- p |> ggExtra::ggMarginal(
-          type = margin_type, margins = "both",
-          size = 8, groupColour = input$by_species, groupFill = input$by_species
-        )
-      }
-
-      p
-    },
-    res = 100
-  )
 }
 
 shinyApp(ui, server)
+