Fixed ValueError

Added a try except block for the functions to see if a value error is brought up since it's only for that instance.

runCorpus.py

@@ -133,19 +133,25 @@ class CorpusTrainer:
 
 						data = [input_text, target_text]
 
-						# User Choices
-						if user_choice in self.choices_yes and play_notification in self.choices_yes:
-							self.user_yes(speaker=speaker, data=data, limit=limit, play_notification=play_notification)
+						try:
+							# User Choices
+							if user_choice in self.choices_yes and play_notification in self.choices_yes:
+								self.user_yes(speaker=speaker, data=data, limit=limit, play_notification=play_notification)
 
 
-						elif user_choice in self.choices_yes and play_notification not in self.choices_yes:
-							self.user_yes(speaker=speaker, data=data, limit=limit, play_notification=play_notification)
+							elif user_choice in self.choices_yes and play_notification not in self.choices_yes:
+								self.user_yes(speaker=speaker, data=data, limit=limit, play_notification=play_notification)
 
 
-						elif user_choice not in self.choices_yes and play_notification not in self.choices_yes:
-							self.user_no(speaker=speaker, data=data, limit=limit, play_notification=play_notification)
+							elif user_choice not in self.choices_yes and play_notification not in self.choices_yes:
+								self.user_no(speaker=speaker, data=data, limit=limit, play_notification=play_notification)
 
+						except ValueError:
+							print("Skipped Conversation {speaker}... Trying again...")
+							continue
 
+						except Exception as e:
+							print(e)
 
 	def user_yes(self, data, speaker, limit, play_notification):
 		self.chatbot_trainer.train_model(data[0], data[1], str(self.conversation_id), speaker)
@@ -355,11 +361,13 @@ class CorpusTrainer:
 
 		print(f"Logged {num_failures} failures.")
 
+def run():
+	app = CorpusTrainer()
+	user_choice = input(f"Run Supervised?({app.chatbot_trainer.model_filename})\n>")
+	play_notification = input(f"Would you like to play a notification after each training?\nHelps with manual stopping before max_vocabulary reached...  \n>")
+	app.main(chatbot_trainer=app.chatbot_trainer, user_choice=user_choice, dialog_data=dialog_data, play_notification=play_notification)
+
 
 if __name__ == "__main__":
 	while True:
-		app = CorpusTrainer()
-		user_choice = input(f"Run Supervised?({app.chatbot_trainer.model_filename})\n>")
-		play_notification = input(f"Would you like to play a notification after each training?\nHelps with manual stopping before max_vocabulary reached...  \n>")
-		app.main(chatbot_trainer=app.chatbot_trainer, user_choice=user_choice, dialog_data=dialog_data, play_notification=play_notification)
-
+		run()