Update app.py

app.py

@@ -7,6 +7,8 @@ import time
 import os
 import tempfile
 import random
+import threading
+import queue
 
 # === OPTIMIERTE EINSTELLUNGEN ===
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -20,14 +22,17 @@ current_txt2img_task_id = None
 current_img2img_task_id = None
 cancel_txt2img = False
 cancel_img2img = False
+interrupt_queue = queue.Queue()
 
-def interrupt_callback(pipe, step, timestep, callback_kwargs):
-    """Callback für Diffusers: Prüft Flag und löst Exception für Interrupt aus"""
+def interrupt_monitor(task_id, is_txt2img):
+    """Überwacht Cancel-Flags in einem separaten Thread und löst Interrupt aus"""
     global cancel_txt2img, cancel_img2img
-    if (pipe == pipe_txt2img and cancel_txt2img) or (pipe == pipe_img2img and cancel_img2img):
-        print(f"🛑 Interrupt ausgelöst für Pipeline (Step: {step})")
-        raise RuntimeError("Task interrupted by user")
-    return callback_kwargs
+    while True:
+        if (is_txt2img and cancel_txt2img) or (not is_txt2img and cancel_img2img):
+            print(f"🛑 Interrupt ausgelöst für Task ID: {task_id}")
+            interrupt_queue.put(("interrupt", task_id))
+            break
+        time.sleep(0.1)  # Polling-Intervall
 
 # === GESICHTSMASKEN-FUNKTIONEN ===
 def create_face_mask(image, bbox_coords):
@@ -130,13 +135,18 @@ def text_to_image(prompt, steps, guidance_scale):
         if current_txt2img_task_id is not None:
             print(f"🛑 Cancel vorheriger Text-to-Image Task (ID: {current_txt2img_task_id})")
             cancel_txt2img = True
-            time.sleep(1.0)  # Längere Pause für CPU
+            time.sleep(1.0)  # Wartezeit für CPU
 
         current_txt2img_task_id = task_id
         cancel_txt2img = False
         print(f"Starting generation for: {prompt} (Task ID: {task_id})")
         start_time = time.time()
         
+        # Starte Interrupt-Monitor in einem separaten Thread
+        monitor_thread = threading.Thread(target=interrupt_monitor, args=(task_id, True))
+        monitor_thread.daemon = True
+        monitor_thread.start()
+        
         pipe = load_txt2img()
         
         # ZUFÄLLIGER SEED für Variation
@@ -144,14 +154,21 @@ def text_to_image(prompt, steps, guidance_scale):
         generator = torch.Generator(device=device).manual_seed(seed)
         print(f"🎲 Using seed: {seed}")
         
+        # Prüfe Interrupt-Queue während der Generierung
+        for step in range(steps):
+            if not interrupt_queue.empty():
+                action, interrupted_task_id = interrupt_queue.get()
+                if action == "interrupt" and interrupted_task_id == task_id:
+                    raise RuntimeError("Task interrupted by user")
+            time.sleep(0.01)  # Kurze Pause für Queue-Prüfung
+        
         image = pipe(
             prompt=prompt,
             height=IMG_SIZE,
             width=IMG_SIZE,
             num_inference_steps=steps,
             guidance_scale=guidance_scale,
-            generator=generator,
-            callback_on_step_end=interrupt_callback
+            generator=generator
         ).images[0]
         
         end_time = time.time()
@@ -188,7 +205,7 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale, fac
         if current_img2img_task_id is not None:
             print(f"🛑 Cancel vorheriger Image-to-Image Task (ID: {current_img2img_task_id})")
             cancel_img2img = True
-            time.sleep(1.0)  # Längere Pause für CPU
+            time.sleep(1.0)  # Wartezeit für CPU
 
         current_img2img_task_id = task_id
         cancel_img2img = False
@@ -197,6 +214,11 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale, fac
         print(f"Gesicht beibehalten: {face_preserve}")
         start_time = time.time()
 
+        # Starte Interrupt-Monitor in einem separaten Thread
+        monitor_thread = threading.Thread(target=interrupt_monitor, args=(task_id, False))
+        monitor_thread.daemon = True
+        monitor_thread.start()
+
         pipe = load_img2img()
         img_resized = image.convert("RGB").resize((IMG_SIZE, IMG_SIZE))
 
@@ -238,6 +260,14 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale, fac
             mask = None
 
         # --- PIPELINE-AUFRUF ---
+        # Prüfe Interrupt-Queue während der Generierung
+        for step in range(int(steps)):
+            if not interrupt_queue.empty():
+                action, interrupted_task_id = interrupt_queue.get()
+                if action == "interrupt" and interrupted_task_id == task_id:
+                    raise RuntimeError("Task interrupted by user")
+            time.sleep(0.01)  # Kurze Pause für Queue-Prüfung
+
         result = pipe(
             prompt=prompt,
             negative_prompt=neg_prompt,
@@ -246,8 +276,7 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale, fac
             strength=adj_strength,
             num_inference_steps=int(steps),
             guidance_scale=adj_guidance,
-            generator=generator,
-            callback_on_step_end=interrupt_callback
+            generator=generator
         )
         
         end_time = time.time()