Is it possible to arrange graphs and filters in an R plot output?

Question

I have created a small dashboard using bscols( from the crosstalkpackage. It consists of plotly graphs and their respective filter_checkboxes.

It looks pretty messy now, as the filters are not vertically aligned with their corresponding plots.

HTML_graphic

As indicated, I would like the first two checkbox sets to appear next to the second line graph (nothing to appear next to the first line graph); and the second two checkbox sets to appear next to the third line graph.

Also, I would like to create some vertical space between the three elements, as indicated by the brown and black horizontal lines.

The best solution would be to set the height of the html elements inside the bscols() command. Because in the future, I would like to programmatically save multiple of these outputs using htmltools::save_html. The next best would be to have the output of that command somehow converted to html and add html code like line breaks or heights. Neither I know how to do.

I came across this related question but it is unanswered: Arrange crosstalk graphs via bscols

Any suggestions on how to solve my problem?

My code

{r 002_Auto App Doc Vol_Invoice group delta plot - plot code, echo = FALSE}

# Setup of the legend for invoice plot
invoice_plot_legend <- list(
  font = list(
    family = "sans-serif",
    size = 12,
    color = "#000"),
  title = list(text="<b> Delta previous month by division </b>"),
  bgcolor = "#E2E2E2",
  bordercolor = "#FFFFFF",
  borderwidth = 2,
  layout.legend = "constant",
  traceorder = "grouped")

# The Shared Data format is needed for crosstalk to be able to filter the dataset upon clicking the checkboxes (division filters):
shared_invoice <- SharedData$new(Auto_App_Doc_Vol_invoiceg_plotting_tibble)
shared_invoice_KPI <- SharedData$new(Auto_App_Doc_Vol_KPI)

shared_abs <- SharedData$new(Auto_App_Doc_Vol_plotting_tibble_diff_abs)


# Setup of a bscols html widget; widths determines the widths of the input lists (here, 2: the filters, 10: the plot and legend)

# Overall KPI and invoice group plot

library(htmlwidgets)
crosstalk::bscols(
  widths = c(2, 10),
    list(
      crosstalk::filter_checkbox("Division", 
                                 label = "Division",
                                 sharedData = shared_invoice, 
                                 group = ~Division),
      crosstalk::filter_checkbox("Rechnungsgruppe", 
                                 label = "Invoice group",
                                 sharedData = shared_invoice, 
                                 group = ~Rechnungsgruppe),
      crosstalk::filter_checkbox("Rechnungsgruppe", 
                                 label = "Invoice group",
                                 sharedData = shared_abs, 
                                 group = ~Rechnungsgruppe),
      crosstalk::filter_checkbox("Division", 
                                 label = "Division",
                                 sharedData = shared_abs, 
                                 group = ~Division)
    )

    ,
  list(
   plot_ly(data = shared_invoice_KPI, x = ~Freigabedatum_REAL_YM, y = ~KPI_current_month, meta = ~Division,
           type = "scatter",
           mode = "lines+text",
           text = ~KPI_current_month,
           textposition='top center',
           hovertemplate = "%{meta}",
           color = ~Diff_KPI_pp)
    %>% 
   layout(legend = invoice_plot_legend,
         title = "Automatically Approved Document Volume",
         xaxis = list(title = 'Release date'),
         yaxis = list(title = '%'))
   ,
   plot_ly(data = shared_invoice, x = ~Freigabedatum_REAL_YM, y = ~n,
           type = "scatter",
           mode = "lines",
           text = ~Rechnungsgruppe_effort,
           hoverinfo = "y+text",
           color = ~Difference_inline
   )
  %>%
   layout(legend = invoice_plot_legend,
         title = " ",
         xaxis = list(title = 'Release date'),
         yaxis = list(title = '# of Approved Documents'))
  ,
   plot_ly(data = shared_abs, x = ~Freigabedatum_REAL_YM, y = ~n,
            type = "scatter",
            mode = "lines",
            text = ~Lieferantenname,
            hoverinfo = "y+text",
            color = ~Lieferantenname_text
    )
    %>%
      layout(legend = vendor_plot_legend,
             title = "by vendor absolute delta previous month all documents",
             xaxis = list(title = 'Release date'),
             yaxis = list(title = '# of Approved Documents w/ & w/o effort')
      )
  
  )
  ) 

Thank you so much!