tooltip=text does not allow for layers with different alpha values

If ggplotly(tooltip=) is used with a ggplot object that includes 2 layers with different alpha values, then the lower alpha will be used for all layers.

Brief description of the problem

# geom_linerange has a lower alpha (0.3) than geom_point (1)
p = mpg %>%
  group_by(model) %>%
  summarize(mean_mpg = mean(hwy),
            sd_mpg = sd(hwy)) %>%
  ggplot(aes(model, mean_mpg)) +
  geom_linerange(aes(ymin=mean_mpg - sd_mpg, 
                     ymax=mean_mpg + sd_mpg), alpha=0.3) +
  geom_point() +
  theme(
    axis.text.x = element_text(angle=45, hjust=1)
  )
ggplotly(p)

# both layers have an alpha of 0.3
p = mpg %>%
  group_by(model) %>%
  summarize(mean_mpg = mean(hwy),
            sd_mpg = sd(hwy)) %>%
  ggplot(aes(model, mean_mpg, text=model)) +
  geom_linerange(aes(ymin=mean_mpg - sd_mpg, 
                     ymax=mean_mpg + sd_mpg), alpha=0.3) +
  geom_point() +
  theme(
    axis.text.x = element_text(angle=45, hjust=1)
  )
ggplotly(p, tooltip='text')

sessionInfo

R version 4.2.1 (2022-06-23)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Monterey 12.5.1

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] heatmaply_1.3.0   viridis_0.6.2     viridisLite_0.4.1 gtsummary_1.6.1   skimr_2.1.4       plotly_4.10.0     ggplot2_3.3.6    
 [8] tidytable_0.8.1   data.table_1.14.2 dplyr_1.0.10     

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.9          lattice_0.20-45     tidyr_1.2.1         assertthat_0.2.1    digest_0.6.29       foreach_1.5.2      
 [7] utf8_1.2.2          plyr_1.8.7          R6_2.5.1            repr_1.1.4          httr_1.4.4          pillar_1.8.1       
[13] rlang_1.0.5         lazyeval_0.2.2      Matrix_1.4-1        labeling_0.4.2      splines_4.2.1       webshot_0.5.3      
[19] stringr_1.4.1       htmlwidgets_1.5.4   munsell_0.5.0       compiler_4.2.1      xfun_0.32           pkgconfig_2.0.3    
[25] base64enc_0.1-3     mgcv_1.8-40         htmltools_0.5.3     tidyselect_1.1.2    tibble_3.1.8        gridExtra_2.3      
[31] seriation_1.3.6     codetools_0.2-18    dendextend_1.16.0   fansi_1.0.3         crayon_1.5.1        withr_2.5.0        
[37] commonmark_1.8.0    grid_4.2.1          registry_0.5-1      nlme_3.1-157        jsonlite_1.8.0      gtable_0.3.1       
[43] lifecycle_1.0.2     magrittr_2.0.3      scales_1.2.1        cli_3.4.0           stringi_1.7.8       reshape2_1.4.4     
[49] farver_2.1.1        renv_0.15.5         broom.helpers_1.8.0 ellipsis_0.3.2      generics_0.1.3      vctrs_0.4.1        
[55] RColorBrewer_1.1-3  iterators_1.0.14    tools_4.2.1         forcats_0.5.2       glue_1.6.2          purrr_0.3.4        
[61] crosstalk_1.2.0     fastmap_1.1.0       yaml_2.3.5          colorspace_2.0-3    TSP_1.2-1           gt_0.7.0           
[67] knitr_1.40          sass_0.4.2

Start by running the supplied R example with ggplotly(tooltip='text') and compare the rendered alpha values for geom_linerange and geom_point. Trace the ggplotly conversion path for layered plots and verify that each layer preserves its own alpha rather than applying the lowest value to all layers. Done means the two layers render with their specified alpha values.