revert to "115ed91ec0cf30ab2a18690605ace834f2cd63bc"

app.py

@@ -157,11 +157,9 @@ def predict_test(model, tokenizer, embedding_model, df, question, index):  # sen
 
 
     segments = sent_tokenize(mostSimContext, engine="crfcut")
-    print('segments',segments)
     segments_index = set_index(get_embeddings(embedding_model,segments))
     _distances,_indices = faiss_search(segments_index, question_vector)
     mostSimSegment = segments[_indices[0][0]]
-    print('mostSimSegment',mostSimSegment)
 
     Answer = model_pipeline(model, tokenizer,question,mostSimSegment)