Update server.py

server.py

@@ -1,25 +1,40 @@
-import uvicorn
 import os
 import sys
 
-os.environ["GRADIO_MAX_FILE_SIZE"] = "50mb"
+# Umgebungsvariablen
+os.environ["GRADIO_MAX_FILE_SIZE"] = "100mb"
 os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
+os.environ["OMP_NUM_THREADS"] = "1"
+
+# Temp-Verzeichnis (optional)
+temp_dir = os.path.join(os.getcwd(), "temp_uploads")
+os.makedirs(temp_dir, exist_ok=True)
+os.environ["GRADIO_TEMP_DIR"] = temp_dir
+
+# App importieren
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from app import main_ui, load_txt2img, load_img2img  # WICHTIG: Funktionen importieren
 
 if __name__ == "__main__":
-    sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
-    
-    # Importiere die Funktion, die die UI erstellt
-    from app import main_ui
-    
-    # Rufe die Funktion auf, um das Gradio-Objekt zu erhalten
     demo = main_ui()
     
-    # Starte den Server
-    uvicorn.run(
-        demo,  # WICHTIG: Zeigt jetzt auf die LOKALE Variable 'demo'
-        host="0.0.0.0",
-        port=7860,
-        timeout_keep_alive=300,
-        limit_concurrency=100,
-        timeout_graceful_shutdown=10
+    # ---- MODELLE VORLADEN (hier hin verschoben) ----
+    print("🚀 Pre-loading models for faster first response...")
+    try:
+        txt2img_pipe = load_txt2img("runwayml/stable-diffusion-v1-5")
+        print("✅ Base model loaded.")
+        _ = load_img2img(keep_environment=True)
+        _ = load_img2img(keep_environment=False)
+        print("✅ ControlNet pipelines loaded.")
+    except Exception as e:
+        print(f"⚠️ Some models could not be pre-loaded: {e}")
+    
+    # Server starten
+    demo.queue(max_size=3).launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        max_file_size="100mb",
+        ssl_verify=False,
+        timeout=300,
+        share=False
     )