diff --git a/chatter/info.json b/chatter/info.json
index b79e587..df77ee8 100644
--- a/chatter/info.json
+++ b/chatter/info.json
@@ -17,7 +17,8 @@
     "pytz",
     "https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.3.1/en_core_web_sm-2.3.1.tar.gz#egg=en_core_web_sm",
     "https://github.com/explosion/spacy-models/releases/download/en_core_web_md-2.3.1/en_core_web_md-2.3.1.tar.gz#egg=en_core_web_md",
-    "spacy>=2.3,<2.4"
+    "spacy>=2.3,<2.4",
+    "--no-deps \"chatterbot>=1.1\""
   ],
   "short": "Local Chatbot run on machine learning",
   "end_user_data_statement": "This cog only stores anonymous conversations data; no End User Data is stored.",
diff --git a/chatter/trainers.py b/chatter/trainers.py
index e6eedba..42d6288 100644
--- a/chatter/trainers.py
+++ b/chatter/trainers.py
@@ -4,45 +4,46 @@ from chatterbot.trainers import Trainer
 
 
 class TwitterCorpusTrainer(Trainer):
-    def train(self, *args, **kwargs):
-        """
-        Train the chat bot based on the provided list of
-        statements that represents a single conversation.
-        """
-        import twint
-
-        c = twint.Config()
-        c.__dict__.update(kwargs)
-        twint.run.Search(c)
-
-
-        previous_statement_text = None
-        previous_statement_search_text = ''
-
-        statements_to_create = []
-
-        for conversation_count, text in enumerate(conversation):
-            if self.show_training_progress:
-                utils.print_progress_bar(
-                    'List Trainer',
-                    conversation_count + 1, len(conversation)
-                )
-
-            statement_search_text = self.chatbot.storage.tagger.get_text_index_string(text)
-
-            statement = self.get_preprocessed_statement(
-                Statement(
-                    text=text,
-                    search_text=statement_search_text,
-                    in_response_to=previous_statement_text,
-                    search_in_response_to=previous_statement_search_text,
-                    conversation='training'
-                )
-            )
-
-            previous_statement_text = statement.text
-            previous_statement_search_text = statement_search_text
-
-            statements_to_create.append(statement)
-
-        self.chatbot.storage.create_many(statements_to_create)
\ No newline at end of file
+    pass
+    # def train(self, *args, **kwargs):
+    #     """
+    #     Train the chat bot based on the provided list of
+    #     statements that represents a single conversation.
+    #     """
+    #     import twint
+    #
+    #     c = twint.Config()
+    #     c.__dict__.update(kwargs)
+    #     twint.run.Search(c)
+    #
+    #
+    #     previous_statement_text = None
+    #     previous_statement_search_text = ''
+    #
+    #     statements_to_create = []
+    #
+    #     for conversation_count, text in enumerate(conversation):
+    #         if self.show_training_progress:
+    #             utils.print_progress_bar(
+    #                 'List Trainer',
+    #                 conversation_count + 1, len(conversation)
+    #             )
+    #
+    #         statement_search_text = self.chatbot.storage.tagger.get_text_index_string(text)
+    #
+    #         statement = self.get_preprocessed_statement(
+    #             Statement(
+    #                 text=text,
+    #                 search_text=statement_search_text,
+    #                 in_response_to=previous_statement_text,
+    #                 search_in_response_to=previous_statement_search_text,
+    #                 conversation='training'
+    #             )
+    #         )
+    #
+    #         previous_statement_text = statement.text
+    #         previous_statement_search_text = statement_search_text
+    #
+    #         statements_to_create.append(statement)
+    #
+    #     self.chatbot.storage.create_many(statements_to_create)
\ No newline at end of file