leave-one-out cross validation in mixed effects logistic model (lme4)

Hello,

So, I have this (simplified for better understanding) binomial mixed
effects model [library (lme4)]

Mymodel <- glmer(cross.01 ~ stream.01 + width.m + grass.per + (1|
structure.id),
  data = Mydata, family = binomial)

stream is a factor with 2 levels; width.m is continuous; grass.per is a
percentage

Now, a reviewer is asking me to apply "a cross-validation procedure (i.e. a
leave-one-out design coupled with predictive metrics as e.g. AUC) on this
model"

Does anyone have R-code to do this cross validation in my logistic mixed
effects model? In the reviewer words: "the model should be evaluated also
as for their predictive performance, not only for assumptions violation and
for goodness-of-fit" (which I presented already in the reviewed paper draft)

Many thanks in advance,
pedro