Update app.py

app.py

@@ -57,21 +57,12 @@ try:
     logging.info("LoRA fused and unloaded.")
 
     # --- Compilation (Major Speed Optimization) ---
-    # Note: Compilation takes time on the first run.
-    # logging.info("Compiling UNet (this may take a moment)...")
-    # pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True) # Use reduce-overhead for dynamic shapes
     # logging.info("Compiling VAE Decoder...")
     # pipe.vae.decoder = torch.compile(pipe.vae.decoder, mode="reduce-overhead", fullgraph=True)
     # logging.info("Compiling VAE Encoder...")
     # pipe.vae.encoder = torch.compile(pipe.vae.encoder, mode="reduce-overhead", fullgraph=True)
     # logging.info("Model compilation finished.")
 
-    # --- Optional: Warm-up Run ---
-    # logging.info("Performing warm-up run...")
-    # with torch.inference_mode():
-    #     _ = pipe(prompt="warmup", num_inference_steps=1, generator=torch.Generator(device=device).manual_seed(0), output_type="pil", return_dict=False)[0]
-    # logging.info("Warm-up complete.")
-
     # Clear cache after setup
     if torch.cuda.is_available():
         torch.cuda.empty_cache()
@@ -87,7 +78,7 @@ except Exception as e:
 
 # --- Inference Function ---
 @spaces.GPU(duration=30) # Slightly increased duration buffer
-def generate_image(prompt: str, seed: int = 42, width: int = DEFAULT_WIDTH, height: int = DEFAULT_HEIGHT, randomize_seed: bool = False, num_inference_steps: int = 4, is_enhance: bool = False):
+def generate_image(prompt: str, seed: int = 42, width: int = DEFAULT_WIDTH, height: int = DEFAULT_HEIGHT, randomize_seed: bool = False, num_inference_steps: int = DEFAULT_INFERENCE_STEPS, is_enhance: bool = False):
     """Generates an image using the FLUX pipeline with error handling."""
     
     if pipe is None:
@@ -224,7 +215,7 @@ with gr.Blocks() as demo:
                 fn=generate_image,
                 inputs=[prompt],
                 outputs=[result, seed, latency],
-                cache_examples="lazy" 
+                cache_examples=True
             )
 
     enhanceBtn.click(