Decomp to get utterances list

handler.py

@@ -215,22 +215,10 @@ class EndpointHandler():
                               {'speaker': utterance.speaker, 'data': utterance.text, 'time': utterance.starttime}]}])
         return formatted
 
-    def __call__(self, data: str) -> List[Dict[str, Any]]:
-        ''' data_file is a str pointing to filename of type .vtt '''
-
-        # deserialize incoming request
-        data_file = data.pop("data_file", None)
-        model_id = data.pop("model_id", None)
-
-        if data_file is None:
-            raise ValueError("no data file provided")
-
-        full_transcript = self.process_vtt_transcript(data_file)
-        utterances_list = []
-        utterances_indexes = [] # entry corresponds to utterance in full_transcript
+    def get_utterances_list(self, full_transcript, utterances_list, utterances_indexes, model_id):
         for i in range(len(full_transcript)):
             utterance = full_transcript[i]
-            #TODO: filter out to only have SL utterances
+            #TODO: filter out to only have SL utterances                                                                                                                                                   
             if model_id == 'eliciting':
                 utterance_str, is_list = self.eliciting_utterance_to_str(utterance)
             elif model_id == 'connecting':
@@ -241,7 +229,7 @@ class EndpointHandler():
                 utterance_str, is_list = self.adding_on_utterance_to_str(utterance)
             else:
                 raise ValueError("model id not found")
-                
+
             if is_list == 'list':
                 utterances_list.extend(utterance_str)
                 for j in range(len(utterance_str)):
@@ -249,7 +237,22 @@ class EndpointHandler():
             else:
                 utterances_list.append(utterance_str)
                 utterances_indexes.append(i)
+        return utterances_list, utterances_indexes
 
+    def __call__(self, data: str) -> List[Dict[str, Any]]:
+        ''' data_file is a str pointing to filename of type .vtt '''
+
+        # deserialize incoming request
+        data_file = data.pop("data_file", None)
+        model_id = data.pop("model_id", None)
+
+        if data_file is None:
+            raise ValueError("no data file provided")
+
+        full_transcript = self.process_vtt_transcript(data_file)
+        # utterances_indexes entry corresponds to utterance in full_transcript
+        utterances_list, utterances_indexes = self.get_utterances_list(full_transcript, [], [], model_id)
+        
         talk_move = ""
         cuda_available = torch.cuda.is_available()
         if model_id == 'eliciting':