1

app.py

@@ -49,20 +49,18 @@ def get_answers_timestamp(question, final_transcript, transcript):
   idxmax = lst_scores.index(max(lst_scores))
   lst_scores.remove(max(lst_scores))
   idxmax2 = lst_scores.index(max(lst_scores))
-
-  idxcont = lst[idxmax2]['start']
-  answer = final_transcript[len(contx[0])-135 + idxcont:]
-  sentence_keyword = answer[:50]
-
+  
+  sentence_for_timestamp = lst[idxmax]['answer']
+  
   dftranscript = pd.DataFrame(transcript)
 
   modelST = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
   embedding_1= modelST.encode(dftranscript.text, convert_to_tensor=True)
-  embedding_2 = modelST.encode(sentence_keyword, convert_to_tensor=True)
+  embedding_2 = modelST.encode(sentence_for_timestamp, convert_to_tensor=True)
 
   similarity_tensor = util.pytorch_cos_sim(embedding_1, embedding_2)
   idx = torch.argmax(similarity_tensor)
-  start_timestamp = dftranscript.iloc[[int(idx)+1]].start.values[0]
+  start_timestamp = dftranscript.iloc[[int(idx)-1]].start.values[0]
   start_timestamp = round(start_timestamp)
 
   return start_timestamp