Generate map only when selectInput is selected

I create a shiny app that generates a cluster map based on the VIKOR multicriteria method. In this sense, I made two selecInput for the user to select whether to maximize (max) or minimize (min) a certain criterion. In this case I have two criteria. The code below works as it is, as I didn't remove maxmin <- c('min','max') from the code. However, if I withdraw, I cannot generate the map. But the idea is that max and min are selected by selecInput. How to adjust this?

Executable code below:

library(shiny)
library(rdist)
library(geosphere)
library(shinythemes)
library(leaflet)
library(shinyjs)
library(MCDM)

function.cl<-function(df,k,maxmin){
  
  #database df
  df<-structure(list(Properties = c(1,2,3,4,5,6,7), 
                     Latitude = c(-23.8, -23.8, -23.9, -23.9, -23.9,-23.4,-23.5), 
                     Longitude = c(-49.6, -49.3, -49.4, -49.8, -49.6,-49.4,-49.2), 
                     Coverage = c (1526, 2350, 3526, 2469, 1285, 2433, 2456),
                     Production = c(526, 350, 526, 469, 285, 433, 456)), class = "data.frame", row.names = c(NA, -7L))
  
  #Vikor
  df1 <- df[c(4:5)]
  df1<-data.matrix(df1)
  
  weights <- c(0.5,0.5) 
  
  maxmin <- c('min','max')
  
  v <- 0.5
  
  scaled<-VIKOR(df1,weights,maxmin,v)
  
  k<-subset(scaled, Ranking==2)$Alternatives #cluster number
  
  
  #clusters
  coordinates<-df[c("Latitude","Longitude")]
  d<-as.dist(distm(coordinates[,2:1]))
  fit.average<-hclust(d,method="average") 
  clusters<-cutree(fit.average, k) 
  nclusters<-matrix(table(clusters))  
  df$cluster <- clusters 
  df1<-df[c("Latitude","Longitude")]
  
  
  #Color and Icon for map
  ai_colors <-c("red","gray","blue","orange","green","beige")
  
  clust_colors <- ai_colors[df$cluster]
  icons <- awesomeIcons(
    icon = 'ios-close',
    iconColor = 'black',
    library = 'ion',
    markerColor =  clust_colors)
  
  # Map for all clusters:
  m1<-leaflet(df1) %>% addTiles() %>%
    addMarkers(~Longitude, ~Latitude) %>%
    addAwesomeMarkers(lat=~df$Latitude, lng = ~df$Longitude, icon=icons, label=~as.character(df$cluster)) %>% 
    addLegend( position = "topright", title="Cluster", colors = ai_colors[1:max(df$cluster)],labels = unique(df$cluster))
  
  plot1<-m1
  
  return(list(
    "Plot1" = plot1
  ))
}

ui <- bootstrapPage(
  useShinyjs(),
  navbarPage(theme = shinytheme("flatly"), collapsible = TRUE,
             "Cl", 
             tabPanel("Solution",
                      sidebarLayout(
                        sidebarPanel(
                          
                        selectInput("maxmin1", label = h5("Maximize or Minimize?"),
                                      choices = list("","max " = "1", "min" = "2"), selected = "1"),

                        selectInput("maxmin2", label = h5("Maximize or Minimize?"),
                                      choices = list("","max " = "1", "min" = "2"), selected = "2")),
 
                        
                        mainPanel(
                          tabsetPanel(      
                            tabPanel("Solution", (leafletOutput("Leaf1",width = "95%", height = "600")))))
                        
                      ))))

server <- function(input, output, session) {
  
  Modelcl<-reactive({
    function.cl(df,k,maxmin=c(input$maxmin1, input$maxmin2))
  })
  
  output$Leaf1 <- renderLeaflet({
    req(maxmin=c(input$maxmin1, input$maxmin2))
    Modelcl()[[1]]
  })
  
}

shinyApp(ui = ui, server = server)

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