how to pass categorical features names or indices to learner

Dear, first of all thanks so much again for You awesome project and support.

I have thought to increase score best learner passing the features categorical information to the learner capable to manage categorical features.
I rearrange Your extra argument example:

from flaml.data import load_openml_dataset
from flaml import AutoML
import numpy as np

X_train, X_test, y_train, y_test = load_openml_dataset(dataset_id=1169, data_dir="./")

cat_feat_index_list = np.where(X_train.dtypes != float) [0]
cat_feat_index_list = cat_feat_index_list.astype(np.int32)
cat_feat_names_list = X_train.iloc[:,cat_feat_index_list].columns.to_list()

automl = AutoML()
automl_settings = {
"task": "classification",
"time_budget": 60,
"estimator_list": "auto",
"fit_kwargs_by_estimator": {
"catboost": {
"cat_features": cat_feat_index_list,
}
},
}
automl.fit(X_train=X_train, y_train=y_train, **automl_settings)

but get the following error:

TypeError: catboost.core.CatBoostClassifier.fit() got multiple values for keyword argument 'cat_features'.

I tried a lot workarounds but nothing.......no way.

Please could You kindly help me.

Thanks in advance.

luigi