Having an issue getting multiple predicts set up in the same RShiny application. I have 2 different models, one for each work area I am working with (TRN, STR) that I want to have separate predicts set up for that reference their respective models. Apologies for the messy code, and I only included the server portion of the Rshiny code and not all of the dashboarding info. I am not quite sure how to have separate inputs for the 2 different tabs for the separate models.

Thanks in advance!

# R Shiny server
server <- shinyServer(function(input,TRNinput,output,TRNoutput) {
  
  #Prediction model
  #React value when using the action button
  a <- reactiveValues(result = NULL)
  # a_trn <- reactiveValues(result = NULL)
  
  observeEvent(input$cal, {
    #Copy of the test data without the dependent variable
    test_pred <-select(STRtestShiny,Workcenter,Grade,Length,Diameter)
    
    #Dataframe for the single prediction
    values = data.frame(Workcenter = input$p_workcenter, 
                        Length = input$p_length,
                        Grade = input$p_grade,
                        Diameter = input$p_diameter)
    
    #Include the values into the new data
    test_pred <- rbind(test_pred,values)
    
    #Single preiction using the randomforest model
    a$result <-  round(predict(STRModelValidate, 
                               newdata = test_pred[nrow(test_pred),]), 
                       digits = 0)
  })
  
  #OBSERVE EVENT TURNER
  observeEvent(TRNinput$cal, {
    #Copy of the test data without the dependent variable
    test_pred_trn <-select(TRNtestShiny,Workcenter,Grade,Length,Diameter)
    #test_pred$Workcenter<- str_replace(test_pred$Workcenter, "STRAIGHTENER 1 ", "STRAIGHTENER 1 LOAD")
    #test_pred$Workcenter<- str_replace(test_pred$Workcenter, "STRAIGHTENER 2 ", "STRAIGHTENER 2 LOAD")
    #test_pred$Workcenter<- str_replace(test_pred$Workcenter, "STRAIGHTENER 3 ", "STRAIGHTENER 3 LOAD")

    #Dataframe for the single prediction
    values_trn = data.frame(Workcenter = TRNinput$p_workcenter,
                        Length = TRNinput$p_length,
                        Grade = TRNinput$p_grade,
                        Diameter = TRNinput$p_diameter)

    #Include the values into the new data
    test_pred <- rbind(test_pred_trn,values_trn)

    #Single preiction using the randomforest model
    a_trn$result <-  round(predict(TRNModelValidate,
                               newdata = test_pred_trn[nrow(test_pred_trn),]),
                       digits = 0)
  })
  
  
  
  
  output$value <- renderText({
    #Display the prediction value
    paste(a$result)
  })
  
  TRNoutput$value <- renderText({
    #Display the prediction value
    paste(a_trn$result)
  })

  output$range <- renderText({
    #Display the range of prediction value using the MAE value
    input$cal
    isolate(sprintf('(%s) - (%s)', 
                    round(a$result - STRRSS_Predictions, digits = 0),
                    round(a$result + STRRSS_Predictions, digits = 0)))
  })
  
  TRNoutput$range <- renderText({
    #Display the range of prediction value using the MAE value
    TRNinput$cal
    isolate(sprintf('(%s) - (%s)',
                    round(a_trn$result - TRNRSS_Predictions, digits = 0),
                    round(a_trn$result + TRNRSS_Predictions, digits = 0)))
  })
})

shinyApp(ui, server)

I attempted this code above and the error I received was related to the new input/output variables not having default values. I set them up no different to the first set so I was unsure how to tackle this problem