Update app.py

app.py

@@ -26,13 +26,23 @@ def retrieve_records(query, min_date, top_n):
     query_embedding = model.encode([query], convert_to_tensor=False)
 
     # Compute cosine similarity
-    scores = cosine_similarity([query_embedding], text_embeddings)[0]
+    # scores = cosine_similarity([query_embedding], text_embeddings)[0]
+    # filtered_df = filtered_df.copy()
+    # filtered_df["similarity"] = scores
+
+    # # Return top-N results
+    # top_results = filtered_df.sort_values(by="similarity", ascending=False).head(top_n)
+    # return top_results[["Title", "Description", "Date", "Link"]]
+
+    scores = cosine_similarity(query_embedding, text_embeddings).flatten()
     filtered_df = filtered_df.copy()
     filtered_df["similarity"] = scores
 
     # Return top-N results
-    top_results = filtered_df.sort_values(by="similarity", ascending=False).head(top_n)
-    return top_results[["Title", "Description", "Date", "Link"]]
+    top_results = filtered_df.sort_values(by=['similarity', 'Date'], ascending=[False, False]).head(top_n)
+    return top_results[["Title", "Description", "Date", "Link", 'similarity']]
+
+    
 
 # Gradio interface
 demo = gr.Interface(