Upload app.py

app.py

@@ -16,11 +16,12 @@ print("Loading restaurant data...")
 data = pd.read_csv("data/toy_data_aggregated_embeddings.csv")
 print(f"Loaded {len(data)} restaurants")
 
-# Compute Bayesian popularity scores
-print("Computing popularity scores...")
-data = compute_bayesian_popularity_score(data)
-print("Popularity scores computed")
+# # Compute Bayesian popularity scores
+# print("Computing popularity scores...")
+# data = compute_bayesian_popularity_score(data)
+# print("Popularity scores computed")
 
+# Load embeddings
 print("Loading pre-computed embeddings...")
 all_desc_embeddings = np.vstack(data["embedding"].values)
 print(f"Loaded embeddings with shape {all_desc_embeddings.shape}")
@@ -203,7 +204,10 @@ def search_restaurants(query_input, data_source, num_results):
     return get_recommendations(query_clean, n_candidates, num_results)
 
 # Create Gradio interface
-with gr.Blocks(title="Restaurant Finder", theme=gr.themes.Soft()) as app:
+with gr.Blocks(
+    title="Restaurant Finder", 
+    # theme=gr.themes.Soft()
+    ) as app:
     gr.Markdown("""
     # Advanced Restaurant Recommendation System
     ### Search Through 5,000+ Restaurants with AI-Powered Semantic Search