Update app.py

app.py

@@ -104,18 +104,19 @@ def load_img2img():
 
     return pipe_img2img
 
-# === CALLBACK-FUNKTIONEN FÜR FORTSCHRITT ===
+# === NEUE CALLBACK-FUNKTIONEN FÜR FORTSCHRITT (kompatibel mit neuer API) ===
 class TextToImageProgressCallback:
     def __init__(self, progress, total_steps):
         self.progress = progress
         self.total_steps = total_steps
         self.current_step = 0
     
-    def __call__(self, step, timestep, latents):
+    def __call__(self, pipe, step, timestep, callback_kwargs):
+        """Neue Callback-Signatur für diffusers >= 1.0.0"""
         self.current_step = step + 1
         progress_percent = (step / self.total_steps) * 100
         self.progress(progress_percent / 100, desc="Generierung läuft - CPU benötigt bis zu 6 Minuten!")
-        return False
+        return callback_kwargs
 
 class ImageToImageProgressCallback:
     def __init__(self, progress, total_steps, strength):
@@ -125,7 +126,8 @@ class ImageToImageProgressCallback:
         self.strength = strength
         self.actual_total_steps = None
 
-    def __call__(self, step, timestep, latents):
+    def __call__(self, pipe, step, timestep, callback_kwargs):
+        """Neue Callback-Signatur für diffusers >= 1.0.0"""
         self.current_step = step + 1
     
         # Korrekte Berechnung der tatsächlichen Steps
@@ -140,8 +142,7 @@ class ImageToImageProgressCallback:
         
         progress_percent = (step / self.actual_total_steps) * 100
         self.progress(progress_percent / 100, desc="Generierung läuft - CPU benötigt bis zu 8 Minuten!")
-        #self.progress(progress_percent / 100, desc=f"Schritt {self.current_step}/{self.actual_total_steps} - {progress_percent:.1f}%")
-        return False
+        return callback_kwargs
 
 # === FUNKTIONEN ===
 def text_to_image(prompt, steps, guidance_scale, progress=gr.Progress()):
@@ -162,7 +163,7 @@ def text_to_image(prompt, steps, guidance_scale, progress=gr.Progress()):
         generator = torch.Generator(device=device).manual_seed(seed)
         print(f"Using seed: {seed}")
         
-        # Progress Callback hinzufügen
+        # NEUE Callback-Implementierung
         callback = TextToImageProgressCallback(progress, steps)
         
         image = pipe(
@@ -172,8 +173,8 @@ def text_to_image(prompt, steps, guidance_scale, progress=gr.Progress()):
             num_inference_steps=steps,
             guidance_scale=guidance_scale,
             generator=generator,
-            callback=callback,
-            callback_steps=1
+            callback_on_step_end=callback,  # NEUE Parameter-Name
+            callback_on_step_end_tensor_inputs=[],  # Keine zusätzlichen Tensor-Inputs
         ).images[0]
         
         end_time = time.time()
@@ -253,10 +254,10 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale, fac
         actual_steps_from_strength = int(steps * adj_strength)
         print(f"🎯 KORREKTE INTERNE STEP-AUSGABE: {int(steps)} Steps × Strength {adj_strength:.3f} = {actual_steps_from_strength} tatsächliche Schritte")
 
-        # Progress Callback hinzufügen
+        # NEUE Callback-Implementierung
         callback = ImageToImageProgressCallback(progress, int(steps), adj_strength)
 
-        # --- PIPELINE-AUFRUF ---
+        # --- PIPELINE-AUFRUF MIT NEUER API ---
         result = pipe(
             prompt=prompt,
             negative_prompt=neg_prompt,
@@ -266,8 +267,8 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale, fac
             num_inference_steps=int(steps),
             guidance_scale=adj_guidance,
             generator=generator,
-            callback=callback,
-            callback_steps=1
+            callback_on_step_end=callback,  # NEUE Parameter-Name
+            callback_on_step_end_tensor_inputs=[],  # Keine zusätzlichen Tensor-Inputs
         )
 
         # ZUSÄTZLICHE AUSGABE: Tatsächliche Steps vom Scheduler - Inpaint berechnet steps intern. Max_step ist aus UI-Übergabe.