Update app.py

app.py

@@ -314,8 +314,8 @@ def match_entities(query_entities, sentence_entities):
 def extract_relevant_portions(document_texts, query, max_portions=3, portion_size=1, min_query_words=1):
     relevant_portions = {}
     # Extract entities from the query
-    ner_biobert = models['ner_pipeline']
-    query_entities = extract_entities(query, ner_biobert)
+    #ner_biobert = models['ner_pipeline']
+    query_entities = extract_entities(query)
     print(f"Extracted Query Entities: {query_entities}")
     for doc_id, doc_text in enumerate(document_texts):
         sentences = nltk.sent_tokenize(doc_text)  # Split document into sentences