optimize extracting keywords

app.py

@@ -2,15 +2,15 @@ from langchain.vectorstores import FAISS
 from langchain.embeddings import SentenceTransformerEmbeddings
 import gradio as gr
 import reranking
-from extract_keywords import init_keyword_extractor, extract_keywords
+#from extract_keywords import init_keyword_extractor, extract_keywords
+from extract_keywords import extract_keywords2
 
 embeddings = SentenceTransformerEmbeddings(model_name="multi-qa-MiniLM-L6-cos-v1")
 db = FAISS.load_local('faiss_qa_2023-08-20', embeddings)
-init_keyword_extractor()
 
 def main(query):
     query = query.lower()
-    query_keywords = set(extract_keywords(query))
+    query_keywords = set(extract_keywords2(query))
     result_docs = db.similarity_search_with_score(query, k=20)
 
     if len(query_keywords) > 0: