Marginal plots cause error using different approaches

[InkaSpy]

Hello,
thank you in advance for having a look at it. We are currently writing functions for internal use, that can plot the model predicitions considering only a single independent variable to vary. I understand that modelbased is providing these functions already, but I am having some issues when trying them.

According to my understanding the above described intention should be carried out accordingly:

fit <- lm(mpg ~ cyl + disp + gear, data = mtcars)
result <-  estimate_means(fit, by = "disp", fixed = c("cyl", "gear"))
plot(result)

Unfortunately, when I run this I get the following error:
Error in rlang::sym():
! Can't convert a character vector to a symbol.

I tried other plotting options like:

result <- estimate_relation(fit)
plot(result)

where I get the following error:
Error in geom_from_list():
! Problem while computing aesthetics.
ℹ Error occurred in the 2nd layer.
Caused by error:
! object 'interaction(gear, disp)' not found

Of course the plot cannot easily depict the prediction with respect to four variables, but I cannot find out how to select the variables that should be considered for plotting.

Another approach I tried is:

result <- estimate_expectation(fit)
plot(result)

where I get the same error as before:
Error in geom_from_list():
! Problem while computing aesthetics.
ℹ Error occurred in the 2nd layer.
Caused by error:
! object 'interaction(gear, disp)' not found

I find it kind strange that for the last two examples the interaction(gear,disp) object is required even though my model does not contain any interactions and I am also wondering why it is focusing on only this interaction.

I look forward to your response!