R Shiny - Rhino Framework - calling user input from view module to logic module

I'm trying to make an R Shiny app with Rhino framework. I want to modify a dataframe in a logic module based on the input from a view module. But I suffered an error:

Loading required package: shiny
Error in box::use(app/main) : 
  i In argument: `season %in% c(season_input())`.
Caused by error in `season_input()`:
! could not find function "season_input"

This is the code in the view module called season_input.R:

box::use(
  shiny[moduleServer, NS, selectInput, reactive],
)

box::use(
  app/logic/init_dfs
)

#' @export
ui <- function(id){
  ns <- NS(id)
  selectInput(
    inputId = "season_year",
    label = "Select Season Year",
    choices = list(
      "seasons" = init_dfs$transfer_df$season |> unique() 
    ), 
    multiple = T, 
    selectize = T
    )
}


#' @export

server <- function(id){
  moduleServer(id, function(input, output, session){
    selected_seasons <- reactive(input$season_year)
  })
}

Below is the logic module that requires input from the previous view module that will use the input to transform a dataframe

box::use(
  dplyr[filter, group_by, summarise, ungroup, arrange, slice_head, left_join]
)

box::use(
  app/logic/init_dfs,
  app/view/season_input
)






transfers_df <- init_dfs$transfer_df |> 
  left_join(init_dfs$longlat_df, by = c("country_2" = "c2_name"), keep = F)

# 1st transform
top10country_byfee_arrivals1 <- 
  transfers_df |> 
  filter(
    season %in% c(season_input()),
    transfer_type == "Arrivals"
  ) |> 
  group_by(country_2) |> 
  summarise(sum_fee = sum(transfer_fee)) |> 
  ungroup() |> 
  arrange(desc(sum_fee)) |> 
  slice_head(n = 10)

top10country_byfee_departures1 <- 
  transfers_df |> 
  filter(
    season %in% c(season_input()),
    transfer_type == "Departures"
  ) |> 
  group_by(country_2) |> 
  summarise(sum_fee = sum(transfer_fee)) |> 
  ungroup() |> 
  arrange(desc(sum_fee)) |> 
  slice_head(n = 10)  

# 2nd transform
top10country_byfee_arrivals2 <- 
  top10country_byfee_arrivals1 %>% 
  left_join(transfers_df %>% filter(transfer_type=="Arrivals"), by = "country_2") %>% 
  select(country_2, centroid_longitude, centroid_latitude, transfer_type, sum_fee) %>% distinct()

top10country_byfee_departures2 <- 
  top10country_byfee_departures1 %>% 
  left_join(transfers_df %>% filter(transfer_type=="Departures"), by = "country_2") %>% 
  select(country_2, centroid_longitude, centroid_latitude, transfer_type, sum_fee) %>% distinct()

# 3rd transform
top10country_byfee <- bind_rows(top10country_byfee_arrivals2, top10country_byfee_departures2) %>% arrange(desc(sum_fee))


#'@export
top10country_byfee