only run reasoning for non-teacher utterances

handler.py

@@ -256,11 +256,11 @@ class ReasoningModel:
         self.model = BertForSequenceClassification.from_pretrained(path)
         self.model.to(self.device)
 
-    def run_inference(self, transcript, min_num_words=8):
+    def run_inference(self, transcript, min_num_words=8, uptake_speaker=None):
         self.model.eval()
         with torch.no_grad():
             for i, utt in enumerate(transcript.utterances):
-                if utt.get_num_words() >= min_num_words:
+                if utt.get_num_words() >= min_num_words and utt.speaker != uptake_speaker:
                     instance = self.input_builder.build_inputs([], utt.text,
                                                                max_length=self.max_length,
                                                                input_str=True)
@@ -430,7 +430,7 @@ class EndpointHandler():
         # Reasoning
         reasoning_model = ReasoningModel(
             self.device, self.tokenizer, self.input_builder)
-        reasoning_model.run_inference(transcript)
+        reasoning_model.run_inference(transcript, uptake_speaker=uptake_speaker)
 
         # Question
         question_model = QuestionModel(