Update app.py

app.py

@@ -106,10 +106,10 @@ def preprocess_plain_text(text, window_size=3):
     return passages
 
 
-def bi_encode(passages):
+def bi_encode(bi_enc,passages):
     global bi_encoder
     # We use the Bi-Encoder to encode all passages, so that we can use it with sematic search
-    bi_encoder = SentenceTransformer("multi-qa-mpnet-base-dot-v1")
+    bi_encoder = SentenceTransformer(bi_enc)
 
 
     # Compute the embeddings 
@@ -139,6 +139,7 @@ def display_as_table(model, score='score'):
 
 st.title("Search Your Query Here")
 window_size = 3
+bi_enc_options = "multi-qa-mpnet-base-dot-v1"
 
 # This will search articles for passages to answer the query
 def search_func(query):
@@ -217,11 +218,11 @@ with col2:
     clear = st.button("Clear Text Input", on_click=clear_text, key='clear',help='Click to clear the URL and query')
 
 if search:
-    if bi_encoder_type:
+    if bi_encoder_type=="multi-qa-mpnet-base-dot-v1":
         with st.spinner(
                 text=f"Loading..........................."
         ):
-            bi_encoder, corpus_embeddings = bi_encode(passages)
+            bi_encoder, corpus_embeddings = bi_encode(bi_encoder_type,passages)
             cross_encoder = cross_encode()
 
         with st.spinner(