Update app.py

app.py

@@ -22,19 +22,21 @@ st.write("Enter a potential typosquatted domain and select the number of top res
 domain = st.text_input("Potential Typosquatted Domain")
 top_k = st.number_input("Top K Results", min_value=1, max_value=len(corpus_domains), value=5, step=1)
 
-# Perform Semantic Search
-if domain:
-    query_emb = model.encode(domain)
-    print('QUERY',query_emb[:5])
-    print('CORPUS',corpus_embeddings[:1,:5])
-    semantic_res = util.semantic_search(query_emb, corpus_embeddings, top_k=top_k)[0]
-    ids = [r['corpus_id'] for r in semantic_res]
-    scores = [r['score'] for r in semantic_res]
-    
-    # Create a DataFrame for the results
-    res_df = domains_df.iloc[ids].copy()
-    res_df['score'] = scores
-    
-    # Display the result DataFrame
-    st.write("Mined Domains:")
-    st.dataframe(res_df)
+# Button to trigger search
+if st.button("Search for Legitimate Domains"):
+    if domain:
+        # Perform Semantic Search
+        query_emb = model.encode(domain)
+        semantic_res = util.semantic_search(query_emb, corpus_embeddings, top_k=top_k)[0]
+        ids = [r['corpus_id'] for r in semantic_res]
+        scores = [r['score'] for r in semantic_res]
+        
+        # Create a DataFrame for the results
+        res_df = domains_df.iloc[ids].copy()
+        res_df['score'] = scores
+        
+        # Display the result DataFrame
+        st.write("Mined Domains:")
+        st.dataframe(res_df)
+    else:
+        st.warning("Please enter a domain to perform the search.")