Update app.py

app.py

@@ -37,10 +37,8 @@ def question_answering(question):
     query_embedding = st.session_state.model_embedding.encode(query_sentence)
     k = 100
     D, I = index_loaded.search(query_embedding.astype('float32'), k)  # D is distances, I is indices
-    # answer = [question_answerer(question=query_sentence[0], context=articles[I[0][i]], max_answer_len = 512) for i in range(k)]
-    # best_answer = max(answer, key=lambda x: x['score'])
-    context = [articles[I[0][i]] for i in range(k)]
-    best_answer = question_answerer(question=query_sentence[0], context= context, max_answer_len = 512)
+    answer = [question_answerer(question=query_sentence[0], context=articles[I[0][i]], max_answer_len = 512) for i in range(k)]
+    best_answer = max(answer, key=lambda x: x['score'])
     print(best_answer)
     if best_answer['score'] > 0.5:
         return best_answer['answer']