Update app.py

app.py

@@ -126,6 +126,9 @@ model = FastText.load(
 
 restaurant_embeddings = extract_restaurant_embeddings(model, df)
 
+clusters_jsons = None
+
+
 def run_clustering(num_clusters, clusters_to_display):
     kmeans = KMeans(n_clusters=num_clusters, random_state=42)
     restaurant_clusters = cluster_embeddings(restaurant_embeddings, kmeans)
@@ -157,6 +160,20 @@ def run_clustering(num_clusters, clusters_to_display):
     
     return analysis, m
 
+def update_display(clusters_to_display):
+    
+    if clusters_jsons is None:
+        return "Please run clustering first", None
+    
+    # Ensure we don't try to show more clusters than exist
+    if clusters_to_display > len(clusters_jsons):
+        clusters_to_display = len(clusters_jsons)
+    
+    # Create map visualization with selected number of clusters
+    m = visualise_on_map(clusters_jsons[:clusters_to_display])
+    
+    return m
+
 # Create Gradio interface
 with gr.Blocks(title="Restaurant Clustering Tool") as app:
     gr.Markdown("# Restaurant K-Means Clustering Analysis")
@@ -194,6 +211,8 @@ with gr.Blocks(title="Restaurant Clustering Tool") as app:
         inputs=[num_clusters_input, display_clusters_input],
         outputs=[output_text, output_plot]
     )
+
+    display_clusters_input.change(update_display, inputs=[display_clusters_input], outputs=[output_plot])
     
     gr.Markdown("""
     ## About this app