Update app.py

app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 from transformers import pipeline
 from sentence_transformers import CrossEncoder
-import numpy as np
 
 passage_retreival_model = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2')
 qa_model = pipeline("question-answering",'a-ware/bart-squadv2')
@@ -12,8 +11,7 @@ def fetch_answers(question, clincal_note ):
     
     scores = passage_retreival_model.predict(query_paragraph_list)
     top_5_indices = scores.argsort()[-5:]
-    query_paragraph_list = np.array(query_paragraph_list)
-    top_5_query_paragraph_list = query_paragraph_list[top_5_indices]
+    top_5_query_paragraph_list = [query_paragraph_list[i] for i in top_5_indices ]
     
     top_5_query_paragraph_answer_list = []
     for query, passage in top_5_query_paragraph_list: