fixed callback

check_app.py

@@ -15,17 +15,17 @@ def generate_image_with_progress(pipe, prompt, num_steps, guidance_scale=None, s
         generator = torch.Generator("cpu").manual_seed(seed)
     print("Start generating")
     # Wrapper to track progress
-    def callback(step, timestep, latents):
-        cur_prg = step / num_steps
-        print(f"Progressing {cur_prg} ")
-        progress(cur_prg, desc=f"Step {step}/{num_steps}")
+    def callback(pipe, step_index, timestep, callback_kwargs): # pipe, step_index, timestep, callback_kwargs
+        cur_prg = step_index / num_steps
+        print(f"Progressing {cur_prg} Step {step_index}/{num_steps}")
+        progress(cur_prg, desc=f"Step {step_index}/{num_steps}")
 
     if isinstance(pipe, StableDiffusion3Pipeline):
         image = pipe(
             prompt,
             num_inference_steps=num_steps,
             guidance_scale=guidance_scale,
-            callback=callback,
+            callback_on_step_end=callback,
         ).images[0]
     elif isinstance(pipe, FluxPipeline):
         image = pipe(
@@ -33,7 +33,7 @@ def generate_image_with_progress(pipe, prompt, num_steps, guidance_scale=None, s
             num_inference_steps=num_steps,
             generator=generator,
             output_type="pil",
-            callback=callback,
+            callback_on_step_end=callback,
         ).images[0]
     return image