update shiny app

app.R

@@ -1,51 +1,40 @@
 library(shiny)
 library(bslib)
-library(dplyr)
-library(ggplot2)
+library(vetiver)
 
-df <- readr::read_csv("penguins.csv")
-# Find subset of columns that are suitable for scatter plot
-df_num <- df |> select(where(is.numeric), -Year)
+endpoint <- 
+  vetiver_endpoint("https://jameshwade-penguins-model.hf.space/predict")
 
-ui <- page_fillable(theme = bs_theme(bootswatch = "minty"),
-  layout_sidebar(fillable = TRUE,
-    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)
-      ),
-      hr(), # Add a horizontal rule
-      checkboxInput("by_species", "Show species", TRUE),
-      checkboxInput("show_margins", "Show marginal plots", TRUE),
-      checkboxInput("smooth", "Add smoother"),
-    ),
-    plotOutput("scatter")
-  )
+ui <- bslib::page_sidebar(
+  sidebar = sidebar(
+    selectInput("species", "Select Species", 
+                choices = c("Adelie", "Chinstrap", "Gentoo")),
+    sliderInput("bill_length_mm", "Enter Bill Length (mm):",
+                min = 30, max = 60, step = 0.5, value = 45),
+    sliderInput("bill_depth_mm", "Enter Bill Depth (mm):",
+                min = 10, max = 22, step = 0.5, value = 15),
+    sliderInput("flipper_length_mm", "Enter Flipper Length (mm):",
+                min = 170, max = 235, step = 0.5, value = 200),
+    sliderInput("body_mass_g", "Enter Body Mass (g):",
+                min = 2700, max = 6300, step = 10, value = 3500),
+    actionButton("predict", "Predict"), 
+    open = TRUE
+  ),
+  verbatimTextOutput("info")
 )
 
 server <- function(input, output, session) {
-  subsetted <- reactive({
-    req(input$species)
-    df |> filter(Species %in% input$species)
-  })
-  
-  output$scatter <- renderPlot({
-    p <- ggplot(subsetted(), aes(!!input$xvar, !!input$yvar)) + list(
-      theme(legend.position = "bottom"),
-      if (input$by_species) aes(color=Species),
-      geom_point(),
-      if (input$smooth) geom_smooth()
+  observe({
+    new_data <- data.frame(
+      species            = input$species,
+      bill_length_mm     = input$bill_length_mm,
+      bill_depth_mm      = input$bill_depth_mm,
+      flipper_length_mm  = input$flipper_length_mm,
+      body_mass_g        = input$body_mass_g
     )
-
-    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)
+    prediction <- predict(endpoint, new_data)
+    output$info <- renderPrint(prediction)
+  }) |> bindEvent(input$predict)
 }
 
-shinyApp(ui, server)
+shinyApp(ui, server)