Clarifying how to calculate predicted response values from fit model

After some more troubleshooting and finding this helpful answer on a related post from @bwiernik here, I am suspicious that the right answer is just that re_formula = NA instead of Null will do what I want? So something like this?

x <- df %>%
    # dplyr::filter(!is.na(site), !is.na(week)) %>%
    modelr::data_grid(year, site, week) %>%
    tidybayes::add_epred_draws(bayes_fit, re_formula = NA)

 ggplot(x, aes(x = .epred, y = year, fill = year)) +
        tidybayes::stat_halfeye(.width = 0.95) +
        scale_fill_manual(values = c(rep("lightpink", 16))) +
        labs(
            x = "Count", y = "Year",
            subtitle = "Posterior predictions"
        ) +
        theme(legend.position = "bottom") +
        theme_bw()

which gives this:

Which feels right??