Update app.py

app.py

@@ -141,7 +141,7 @@ def cross_encode():
 bi_enc_options = ["multi-qa-mpnet-base-dot-v1", "all-mpnet-base-v2", "multi-qa-MiniLM-L6-cos-v1"]
 
 
-def display_as_table(model, top_k, score='score'):
+def display_as_table(model, top_k=2, score='score'):
     # Display the df with text and scores as a table
     df = pd.DataFrame([(hit[score], passages[hit['corpus_id']]) for hit in model[0:top_k]], columns=['Score', 'Text'])
     df['Score'] = round(df['Score'], 2)
@@ -155,7 +155,7 @@ st.title("Search with Retrieve & Rerank")
 
 
 # This function will search all wikipedia articles for passages that answer the query
-def search_func(query, top_k=top_k):
+def search_func(query, top_k=2):
     global bi_encoder, cross_encoder
 
     st.subheader(f"Search Query: {query}")
@@ -251,7 +251,7 @@ if search:
 
         with st.spinner(
                 text="Embedding completed, searching for relevant text for given query and hits..."):
-            search_func(search_query, top_k)
+            search_func(search_query, top_k=2)
 
 st.markdown("""
             """)