How can I reuse a fable model after fitting the model especially when used in a *new environment*?

I have just recently started using fable and fable.prophet when I have run into a very odd situation. As you can see from the code below, the model runs fine when everything is in the global environment but fails to detect or use the exogenous regressors when the code is in a local environment (like a function):

This code works:

ts2 <- readRDS(url("https://github.com/lbui30/reprexdata/blob/main/ts2.RDS?raw=true"))
testmodel <- readRDS(url("https://github.com/lbui30/reprexdata/blob/main/testmodel.RDS?raw=true"))
sampledata <- ts2 %>% select(!any_of(c("ds"))) %>% filter(station_id %in% c("04"))
myholidays <- readRDS(url("https://github.com/lbui30/reprexdata/blob/main/myholidays.RDS?raw=true"))
myforcast <- testmodel %>%
  forecast(h = "4 weeks")
head(myforcast)
#> # A fable: 4 x 6 [7D]
#> # Key:     battalion, station_id, .model [1]
#>   battalion station_id .model   incident_date   callvolume .mean
#>   <chr>     <chr>      <chr>    <date>              <dist> <dbl>
#> 1 5         04         prophetb 2022-11-20    sample[5000]  47.8
#> 2 5         04         prophetb 2022-11-27    sample[5000]  37.1
#> 3 5         04         prophetb 2022-12-04    sample[5000]  47.6
#> 4 5         04         prophetb 2022-12-11    sample[5000]  47.5

But this code doesn't work:

myprepfunction <- function() {
  ts2 <- readRDS(url("https://github.com/lbui30/reprexdata/blob/main/ts2.RDS?raw=true"))
  testmodel <- readRDS(url("https://github.com/lbui30/reprexdata/blob/main/testmodel.RDS?raw=true"))
  sampledata <- ts2 %>% select(!any_of(c("ds"))) %>% filter(station_id %in% c("04"))
  # simplifying for reprex....
  # myholidays <- create_holidays(sampledata)
  myholidays <- readRDS(url("https://github.com/lbui30/reprexdata/blob/main/myholidays.RDS?raw=true"))
  myforcast <- testmodel %>%
    forecast(h = "4 weeks")
  return(myforcast)
}
forecast = myprepfunction()
#> Error in `mutate()`:
#> ! Problem while computing `prophetb = (function (object, ...) ...`.
#> Caused by error in `value[[3L]]()`:
#> ! object 'myholidays' not found
#>   Unable to compute required variables from provided `new_data`.
#>   Does your model require extra variables to produce forecasts?
#> Backtrace:
#>      ▆
#>   1. ├─global myprepfunction()
#>   2. │ └─testmodel %>% forecast(h = "4 weeks")
#>   3. ├─fabletools::forecast(., h = "4 weeks")
#>   4. ├─fabletools:::forecast.mdl_df(., h = "4 weeks")
#>   5. │ └─dplyr::mutate_at(...)
#>   6. │   ├─dplyr::mutate(.tbl, !!!funs)
#>   7. │   └─dplyr:::mutate.data.frame(.tbl, !!!funs)
#>   8. │     └─dplyr:::mutate_cols(.data, dplyr_quosures(...), caller_env = caller_env())
#>   9. │       ├─base::withCallingHandlers(...)
#>  10. │       └─mask$eval_all_mutate(quo)
#>  11. ├─fabletools (local) `<fn>`(...)
#>  12. └─fabletools:::forecast.lst_mdl(...)
#>  13.   └─fabletools:::mapply_maybe_parallel(...)
#>  14.     └─base::mapply(FUN = .f, ..., MoreArgs = MoreArgs, SIMPLIFY = SIMPLIFY)
#>  15.       ├─fabletools (local) `<fn>`(dots[[1L]][[1L]], dots[[2L]][[1L]], h = "4 weeks", point_forecast = `<named list>`)
#>  16.       └─fabletools:::forecast.mdl_ts(...)
#>  17.         └─base::tryCatch(...)
#>  18.           └─base (local) tryCatchList(expr, classes, parentenv, handlers)
#>  19.             ├─base (local) tryCatchOne(...)
#>  20.             │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
#>  21.             └─base (local) tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
#>  22.               └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
#>  23.                 └─value[[3L]](cond)
#>  24.                   └─rlang::abort(...)

P.S. While the full context of my problem can be found here, I am new to the r-community so I am not sure if my post has shown up yet: https://community.rstudio.com/t/why-wont-my-prophet-fable-model-with-holidays-forecast-in-a-new-r-environment/153767/1

Start at the fabletools::forecast() call in the provided function and trace how the saved fable.prophet model evaluates the myholidays regressor outside the global environment. Compare the global and local execution paths, then verify that forecasting from a locally defined environment resolves the exogenous variable and produces the expected four-week output.