Update app.py

app.py

@@ -156,7 +156,6 @@ def generate_pose_transfer(
     guidance_scale=7.5,  # Increased for better pose adherence
     num_inference_steps=28,
     lora_scale=1.0,
-    controlnet_scale=1.0,  # Added control strength
     enhance_pose=False,
     progress=gr.Progress(track_tqdm=True)
 ):
@@ -243,7 +242,7 @@ def generate_pose_transfer(
         # Generate image with stronger pose control
         with torch.cuda.amp.autocast(dtype=torch.bfloat16):
             if "Kontext" in MODEL_STATUS:
-                # Use Kontext pipeline with enhanced settings
+                # Use Kontext pipeline - removed unsupported controlnet_conditioning_scale
                 result = pipe(
                     image=concatenated_input,
                     prompt=full_prompt,
@@ -253,7 +252,6 @@ def generate_pose_transfer(
                     generator=generator,
                     width=width,
                     height=height,
-                    controlnet_conditioning_scale=controlnet_scale,  # Control strength
                 ).images[0]
             else:
                 # Use standard FLUX pipeline
@@ -467,15 +465,6 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
                             interactive=False
                         )
                     
-                    controlnet_scale = gr.Slider(
-                        label="Pose Control Strength",
-                        minimum=0.5,
-                        maximum=2.0,
-                        step=0.1,
-                        value=1.0,
-                        info="How strongly to enforce the pose"
-                    )
-                    
                     enhance_pose = gr.Checkbox(
                         label="Auto-enhance pose edges",
                         value=False
@@ -562,7 +551,6 @@ with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
             guidance_scale,
             num_inference_steps,
             lora_scale,
-            controlnet_scale,
             enhance_pose
         ],
         outputs=[result_image, seed_used, concat_preview]