Update app.py

app.py

@@ -26,7 +26,7 @@ DEFAULT_HEIGHT = 1024
 DEFAULT_INFERENCE_STEPS = 1 # FLUX Schnell is designed for few steps
 MIN_INFERENCE_STEPS = 1
 MAX_INFERENCE_STEPS = 8 # Allow slightly more steps for potential quality boost
-ENHANCE_STEPS = 4 # Fixed steps for the enhance button
+ENHANCE_STEPS = 2 # Fixed steps for the enhance button
 
 # --- Device and Model Setup ---
 dtype = torch.float16
@@ -87,7 +87,7 @@ 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 = DEFAULT_INFERENCE_STEPS, 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 = 4, is_enhance: bool = False):
     """Generates an image using the FLUX pipeline with error handling."""
     
     if pipe is None:
@@ -214,7 +214,7 @@ with gr.Blocks() as demo:
                     with gr.Row():
                         width = gr.Slider(label="Width", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=DEFAULT_WIDTH)
                         height = gr.Slider(label="Height", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=DEFAULT_HEIGHT)
-                        num_inference_steps = gr.Slider(label="Inference Steps", minimum=1, maximum=4, step=1, value=DEFAULT_INFERENCE_STEPS)
+                        num_inference_steps = gr.Slider(label="Inference Steps", minimum=MIN_INFERENCE_STEPS, maximum=MAX_INFERENCE_STEPS, step=1, value=DEFAULT_INFERENCE_STEPS)
 
         with gr.Row():
             gr.Markdown("### 🌟 Inspiration Gallery")