R ensemble stacking using caret: the right way to establish index for LOOCV

Question

Im trying to stack ensemble of predictions using caretStack and applying LOOCV. Here is my script:

library(readr)
library(caretEnsemble)

# Using wine quality dataset as an example:
raw <- read_delim('https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv',
                   delim = ";", escape_double = FALSE, trim_ws = TRUE)

df<-raw[c(1:10),] # reducing observations to 10 rows

Since LOOCV method is not explicitly offered in the trainControl function, I have to specify index and indexOut arguments. I came up with the following:

holdout<-list()

for(i in 1:nrow(df)){
  holdout[[i]]<-i
}


my_control <- trainControl(
  savePredictions = 'final',
  classProbs = F,
  index = rep(list(seq(1,nrow(df))),times=nrow(df)),
  indexOut = holdout
)

model_list <- caretList(
  quality~.,
  data=df,
  trControl=my_control,
  methodList=c('glm',"gaussprLinear")
   
)

Here however I get the warning:

Warning message:
In nominalTrainWorkflow(x = x, y = y, wts = weights, info = trainInfo,  :
  There were missing values in resampled performance measures

And when running caretStack, I get an error:

glm_ensemble <- caretStack(
  model_list,
  method="glm",
  metric="Rsquared",
  trControl=my_control
)

Something is wrong; all the Rsquared metric values are missing:
      RMSE           Rsquared        MAE        
 Min.   :0.4614   Min.   : NA   Min.   :0.4614  
 1st Qu.:0.4614   1st Qu.: NA   1st Qu.:0.4614  
 Median :0.4614   Median : NA   Median :0.4614  
 Mean   :0.4614   Mean   :NaN   Mean   :0.4614  
 3rd Qu.:0.4614   3rd Qu.: NA   3rd Qu.:0.4614  
 Max.   :0.4614   Max.   : NA   Max.   :0.4614  
                  NA's   :1                     
Error: Stopping
In addition: Warning message:
In nominalTrainWorkflow(x = x, y = y, wts = weights, info = trainInfo,  :
  There were missing values in resampled performance measures.

I assume there is smth wrong with the way I set up the index and index_Out arguments, but Im not sure. Any help would be appreciated.