Update app.py

app.py

@@ -152,7 +152,6 @@ with gr.Blocks(js=js_func, css="""
 """) as demo:
     gr.HTML(elem_classes="title", value="🌍")
     gr.HTML("<img src='https://see.fontimg.com/api/rf5/JpZqa/MWMyNzc2ODk3OTFlNDk2OWJkY2VjYTIzNzFlY2E4MWIudHRm/bm9tYWQgZGVzdGluYXRpb25z/super-feel.png?r=fs&h=130&w=2000&fg=e2e2e2&bg=FFFFFF&tb=1&s=65' alt='Graffiti fonts'></a>")
-
     gr.Markdown("Discover the best places for digital nomads around the globe")
     
     with gr.Row():
@@ -338,77 +337,5 @@ with gr.Blocks(js=js_func, css="""
                        "- Consider internet speed if you need to attend video meetings  \n"
                        "- Balance cost of living with quality of life for the best experience  \n"
                        "- Some newer nomad destinations may have incomplete data")
-    
-  
-    gr.Markdown("### 🎯 Find Your Ideal Destination")
-    with gr.Row():
-        with gr.Column():
-            priority = gr.CheckboxGroup(
-                ["Best Quality of Life", "Fastest Internet", "Most Affordable", "Balance of All Factors"],
-                label="What are Your Priorities?",
-                value=["Balance of All Factors"]
-            )
-            
-            find_btn = gr.Button("Find My Ideal Destination", variant="primary")
-            
-            recommendation = gr.Textbox(label="Recommended Location", lines=3)
-            
-            def recommend_location(priorities, max_budget):
-                if not priorities:
-                    return "Please select at least one priority to get a recommendation."
-                
-                budget_filtered_df = df[df["Monthly Cost Living (USD)"] <= max_budget]
-                
-                budget_warning = ""
-                if len(budget_filtered_df) == 0:
-                    budget_filtered_df = df
-                    budget_warning = "⚠️ No cities match your budget. Showing best options regardless of cost.\n\n"
-                
-                recommendations = []
-                
-                if "Best Quality of Life" in priorities:
-                    top_city = budget_filtered_df.sort_values("Quality of Life", ascending=False).iloc[0]
-                    terrain_emoji = terrain_emoji_map.get(top_city['Terrain'], top_city['Terrain']).split()[0]
-                    message = f"{terrain_emoji} {top_city['City']}, {top_city['Country']} - Quality of Life: {top_city['Quality of Life']}\n"
-                    message += f"Monthly Cost: ${top_city['Monthly Cost Living (USD)']}\n"
-                    message += f"Key Feature: {top_city['Key Feature']}"
-                    recommendations.append(message)
-                    
-                if "Fastest Internet" in priorities:
-                    top_city = budget_filtered_df.sort_values("Internet Speed (Mbps)", ascending=False).iloc[0]
-                    terrain_emoji = terrain_emoji_map.get(top_city['Terrain'], top_city['Terrain']).split()[0]
-                    message = f"{terrain_emoji} {top_city['City']}, {top_city['Country']} - Internet Speed: {top_city['Internet Speed (Mbps)']} Mbps\n"
-                    message += f"Monthly Cost: ${top_city['Monthly Cost Living (USD)']}\n"
-                    message += f"Key Feature: {top_city['Key Feature']}"
-                    recommendations.append(message)
-                    
-                if "Most Affordable" in priorities:
-                    top_city = budget_filtered_df.sort_values("Monthly Cost Living (USD)", ascending=True).iloc[0]
-                    terrain_emoji = terrain_emoji_map.get(top_city['Terrain'], top_city['Terrain']).split()[0]
-                    message = f"{terrain_emoji} {top_city['City']}, {top_city['Country']} - Monthly Cost: ${top_city['Monthly Cost Living (USD)']}\n"
-                    message += f"Quality of Life: {top_city['Quality of Life']}, Internet: {top_city['Internet Speed (Mbps)']} Mbps\n"
-                    message += f"Key Feature: {top_city['Key Feature']}"
-                    recommendations.append(message)
-                    
-                if "Balance of All Factors" in priorities:
-                    df_temp = budget_filtered_df.copy()
-                    df_temp['quality_norm'] = df_temp['Quality of Life'] / 10
-                    df_temp['internet_norm'] = df_temp['Internet Speed (Mbps)'] / 400
-                    df_temp['cost_norm'] = 1 - (df_temp['Monthly Cost Living (USD)'] / 4000)
-                    
-                    df_temp['composite_score'] = (df_temp['quality_norm'] + df_temp['internet_norm'] + df_temp['cost_norm']) / 3
-                    top_city = df_temp.sort_values("composite_score", ascending=False).iloc[0]
-                    
-                    terrain_emoji = terrain_emoji_map.get(top_city['Terrain'], top_city['Terrain']).split()[0]
-                    message = f"{terrain_emoji} {top_city['City']}, {top_city['Country']} - Balanced Choice\n"
-                    message += f"Quality: {top_city['Quality of Life']}, Internet: {top_city['Internet Speed (Mbps)']} Mbps, Cost: ${top_city['Monthly Cost Living (USD)']}\n"
-                    message += f"Key Feature: {top_city['Key Feature']}"
-                    recommendations.append(message)
-                
-                return budget_warning + "\n\n".join(recommendations)
-            
-            find_btn.click(recommend_location, inputs=[priority, cost_slider], outputs=recommendation)
-            
-            cost_slider.change(recommend_location, inputs=[priority, cost_slider], outputs=recommendation)
             
 demo.launch()