Update app.py

app.py

@@ -3,10 +3,9 @@ import spaces
 import torch
 from model import ModelHandler
 from generator import Generator
-from config import Config
 
-# 1. Initialize Models Globally
-# Models are loaded into RAM here. The @spaces.GPU decorator moves them to VRAM on demand.
+# 1. Initialize Models Globally (in RAM)
+# ZeroGPU will move them to VRAM inside the @spaces.GPU function
 print("Initializing Application...")
 handler = ModelHandler()
 handler.load_models()
@@ -21,6 +20,7 @@ def process_img(image, prompt):
     try:
         print("--- Starting Generation ---")
         result = gen.predict(image, prompt)
+        print("--- Generation Complete ---")
         return result
         
     except Exception as e:
@@ -44,7 +44,7 @@ with gr.Blocks(title="Face To Pixel Art", theme=gr.themes.Soft()) as demo:
                 placeholder="Leave empty for auto-captioning...",
                 info="The trigger words 'p1x3l4rt, pixel art' are added automatically."
             )
-            run_btn = gr.Button("Generat Pixel Art", variant="primary")
+            run_btn = gr.Button("Generate Pixel Art", variant="primary")
         
         with gr.Column():
             output_img = gr.Image(label="Pixel Art Result")
@@ -56,10 +56,16 @@ with gr.Blocks(title="Face To Pixel Art", theme=gr.themes.Soft()) as demo:
         outputs=[output_img]
     )
 
-    # Examples (Optional: Add valid paths if you have example images)
-    # gr.Examples(examples=["./examples/face.jpg"], inputs=[input_img])
+    gr.Examples(
+        examples=[
+            ["./examples/monalisa.jpg", "mona lisa portrait"],
+            ["./examples/man.jpg", "photo of a man"],
+            ["./examples/landscape.jpg", "a beautiful landscape"]
+        ],
+        inputs=[input_img, prompt]
+    )
 
-# 4. Launch
+# 4. Launch the App
 if __name__ == "__main__":
     demo.queue(max_size=20, api_open=True)
     demo.launch(