added a placeholder message

app.py

@@ -273,7 +273,6 @@ def create_interface():
     generator_tokenizer, generator, sentiment_analyzer, content_checker = load_models()
     print("Models loaded successfully!")
     
-    # Sample data function remains the same
     def fill_sample_data():
         return [
             "EcoBottle",
@@ -285,18 +284,73 @@ def create_interface():
             "professional"
         ]
     
-    # Process input function remains the same
-    def process_input(
+    import time
+    
+    def process_input_with_loading(
         product_name,
         product_description,
         target_audience,
         key_features,
         unique_benefits,
         platform,
-        tone
+        tone,
+        progress=gr.Progress()
     ):
-        # Your existing process_input function code here
-        pass
+        # Initial loading message
+        features_list = """⚡ While I generate your content, here's what I can do:
+        
+📝 Generate multiple unique marketing messages
+🎯 Adapt content for different platforms
+🔍 Ensure ethical content generation
+📊 Analyze sentiment and safety
+✨ Create platform-specific formatting
+        
+Processing your request..."""
+        
+        yield features_list + "\n\n⏳ Starting generation..."
+        time.sleep(1)
+        
+        # Update message with steps
+        steps = [
+            "Loading language models...",
+            "Analyzing product information...",
+            "Generating content variations...",
+            "Checking content safety...",
+            "Finalizing output..."
+        ]
+        
+        for i, step in enumerate(steps, 1):
+            progress(i/len(steps))
+            yield features_list + f"\n\n⏳ {step}"
+            time.sleep(1)
+        
+        # Generate actual content
+        try:
+            results = generate_content(
+                product_name,
+                product_description,
+                target_audience,
+                key_features,
+                unique_benefits,
+                platform,
+                tone,
+                generator_tokenizer,
+                generator,
+                sentiment_analyzer,
+                content_checker
+            )
+            
+            output = "🎯 Generated Marketing Content:\n\n"
+            for i, content in enumerate(results, 1):
+                output += f"Version {i}:\n"
+                output += f"📝 Content: {content['text']}\n"
+                output += f"😊 Sentiment: {content['sentiment']}\n"
+                output += f"✅ Safety Score: {content['safety_score']}\n"
+                output += "-" * 50 + "\n"
+            
+            yield output
+        except Exception as e:
+            yield f"An error occurred: {str(e)}"
 
     # Create the interface with blocks for custom layout
     with gr.Blocks(theme=gr.themes.Default()) as demo:
@@ -309,7 +363,7 @@ def create_interface():
                 "Fill the form with sample data",
                 variant="primary",
                 size="sm",
-                scale=0.2  # Makes button smaller
+                scale=0.2
             )
 
         # Main content area with two columns
@@ -331,7 +385,11 @@ def create_interface():
 
             # Right column - Output
             with gr.Column(scale=1):
-                output = gr.Textbox(label="Generated Content", lines=12)
+                output = gr.Textbox(
+                    label="Generated Content", 
+                    lines=12,
+                    value="✨ Enter your product details and click 'Generate Content' to start!"
+                )
 
         # Connect the buttons to functions
         fill_button.click(
@@ -348,7 +406,7 @@ def create_interface():
         )
         
         submit_button.click(
-            fn=process_input,
+            fn=process_input_with_loading,
             inputs=[
                 product_name,
                 product_description,