Update app.py

app.py

@@ -14,6 +14,7 @@ import sys
 import tempfile
 from typing import Sequence, Mapping, Any, Union
 import asyncio
+import shutil
 
 # Copy functions from FluxSimpleUpscaler.txt
 def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
@@ -61,7 +62,7 @@ def import_custom_nodes() -> None:
     asyncio.set_event_loop(loop)
     server_instance = server.PromptServer(loop)
     execution.PromptQueue(server_instance)
-    init_extra_nodes()
+    loop.run_until_complete(init_extra_nodes())
 
 # Setup ComfyUI and custom nodes
 if not os.path.exists("ComfyUI"):
@@ -80,6 +81,7 @@ os.makedirs("ComfyUI/models/diffusion_models", exist_ok=True)
 os.makedirs("ComfyUI/models/clip", exist_ok=True)
 os.makedirs("ComfyUI/models/vae", exist_ok=True)
 os.makedirs("ComfyUI/models/upscale_models", exist_ok=True)
+os.makedirs("ComfyUI/input", exist_ok=True)
 
 # Download models if not present
 diffusion_path = "ComfyUI/models/diffusion_models/flux1-dev-fp8.safetensors"
@@ -195,7 +197,12 @@ def enhance_image(
 
     with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
         input_image.save(tmp.name)
-        image_path = tmp.name
+        temp_path = tmp.name
+
+    image_base = os.path.basename(temp_path)
+    input_dir = find_path("input")
+    input_image_path = os.path.join(input_dir, image_base)
+    shutil.copy(temp_path, input_image_path)
 
     with torch.inference_mode():
         dualcliploader = NODE_CLASS_MAPPINGS["DualCLIPLoader"]()
@@ -230,7 +237,7 @@ def enhance_image(
         )
 
         loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
-        loadimage_res = loadimage.load_image(image=os.path.basename(image_path))
+        loadimage_res = loadimage.load_image(image=image_base)
 
         fluxguidance = NODE_CLASS_MAPPINGS["FluxGuidance"]()
         fluxguidance_res = fluxguidance.append(
@@ -269,7 +276,8 @@ def enhance_image(
         output_tensor = get_value_at_index(usd_res, 0)
         image = tensor_to_pil(output_tensor)
 
-    os.unlink(image_path)
+    os.unlink(input_image_path)
+    os.unlink(temp_path)
 
     target_w, target_h = w_original * upscale_factor, h_original * upscale_factor
     if image.size != (target_w, target_h):