diff --git a/fedot_ind/api/main.py b/fedot_ind/api/main.py
index 95fc2f5c9..676d24793 100644
--- a/fedot_ind/api/main.py
+++ b/fedot_ind/api/main.py
@@ -175,10 +175,9 @@ def __abstract_predict(self, predict_mode: str):
         custom_predict = self.manager.solver.predict if self.manager.industrial_config.is_default_fedot_context \
             else self.manager.industrial_config.strategy.predict
 
-        predict_function = Either(value=custom_predict,
-                                  monoid=['prob', predict_mode == 'labels']).either(
-            left_function=lambda prob_func: self.manager.solver.predict_proba if have_proba_output else self.manager.solver.predict,
-            right_function=lambda label_func: label_func)
+        predict_function = Either(value=custom_predict, monoid=['prob', predict_mode == 'labels']).either(
+            left_function=lambda prob_func: self.manager.solver.predict_proba
+            if have_proba_output else self.manager.solver.predict, right_function=lambda label_func: label_func)
 
         def _inverse_encoder_transform(predict):
             predicted_labels = self.target_encoder.inverse_transform(predict)
@@ -425,14 +424,20 @@ def save_optimization_history(self, return_history: bool = False):
             f"optimization_history.json")
 
     def save_best_model(self):
-        Either(value=self.manager.solver,
-               monoid=[self.manager.solver, self.manager.condition_check.solver_is_fedot_class(self.manager.solver)]).either(
-            left_function=lambda pipeline: pipeline.save(path=self.manager.output_folder,
-                                                         create_subdir=True,
-                                                         is_datetime_in_path=True),
-            right_function=lambda solver: solver.current_pipeline.save(path=self.manager.output_folder,
-                                                                       create_subdir=True,
-                                                                       is_datetime_in_path=True))
+        Either(
+            value=self.manager.solver,
+            monoid=[
+                self.manager.solver,
+                self.manager.condition_check.solver_is_fedot_class(
+                    self.manager.solver)]).either(
+            left_function=lambda pipeline: pipeline.save(
+                path=self.manager.output_folder,
+                create_subdir=True,
+                is_datetime_in_path=True),
+            right_function=lambda solver: solver.current_pipeline.save(
+                path=self.manager.output_folder,
+                create_subdir=True,
+                is_datetime_in_path=True))
 
     def explain(self, explaing_config: dict = {}):
         """Explain model's prediction via time series points perturbation