Update handler.py

handler.py

@@ -326,7 +326,6 @@ class UptakeModel:
 class FocusingQuestionModel:
     def __init__(self, device, tokenizer, input_builder, max_length=128, path=FOCUSING_QUESTION_MODEL):
         print("Loading models...")
-        print("TEST IN FOCUSING QUESTION MODEL")
         self.device = device
         self.tokenizer = tokenizer
         self.input_builder = input_builder
@@ -373,7 +372,6 @@ def load_math_terms():
     return math_terms, math_terms_dict
 
 def run_math_density(transcript, uptake_speaker=None):
-    print("IN MATH DENSITY")
     math_terms, math_terms_dict = load_math_terms()
     sorted_terms = sorted(math_terms, key=len, reverse=True)
     math_word_cloud = {}
@@ -384,7 +382,6 @@ def run_math_density(transcript, uptake_speaker=None):
         match_list = []
         for term in sorted_terms:
             matches = list(re.finditer(term, text, re.IGNORECASE))
-            print("math term matches: ", matches)
             # Filter out matches that share positions with longer terms
             matches = [match for match in matches if not any(match.start() in range(existing[0], existing[1]) for existing in matched_positions)]
             if len(matches) > 0:
@@ -395,8 +392,6 @@ def run_math_density(transcript, uptake_speaker=None):
             # Update matched positions
             matched_positions.update((match.start(), match.end()) for match in matches)
             num_matches += len(matches)
-        print("num matches: ", num_matches)
-        print("math terms: ", match_list)
         utt.num_math_terms = num_matches
         utt.math_terms = match_list
     dict_list = []
@@ -425,13 +420,8 @@ class EndpointHandler():
         """
         # get inputs
         utterances = data.pop("inputs", data)
-        print("utterances: ", utterances)
         params = data.pop("parameters", None)
 
-        print("EXAMPLES")
-        for utt in utterances[:3]:
-            print("speaker %s: %s" % (utt["speaker"], utt["text"]))
-
         transcript = Transcript(filename=params.pop("filename", None))
         for utt in utterances:
             transcript.add_utterance(Utterance(**utt))