Update app.py

app.py

@@ -8,15 +8,37 @@ import uuid
 from diffusers import StableDiffusionPipeline
 import torch
 
+# --- OUTPUT DIRECTORY ---
 OUTPUT_DIR = "outputs"
 os.makedirs(OUTPUT_DIR, exist_ok=True)
 
+# --- DEVICE SETUP ---
 device = "cuda" if torch.cuda.is_available() else "cpu"
-pipe = StableDiffusionPipeline.from_pretrained(
-    "Lykon/anything-cartoon", torch_dtype=torch.float16 if device=="cuda" else torch.float32
-)
+
+# --- LOAD STABLE DIFFUSION PIPELINE ---
+MODEL_NAME = "Lykon/anything-cartoon"  # original model
+PUBLIC_MODEL = "runwayml/stable-diffusion-v1-5"  # fallback
+
+# Use HF token if required
+HF_TOKEN = os.getenv("HF_TOKEN", None)  # set environment variable HF_TOKEN if private repo
+
+try:
+    pipe = StableDiffusionPipeline.from_pretrained(
+        MODEL_NAME,
+        torch_dtype=torch.float16 if device == "cuda" else torch.float32,
+        use_auth_token=HF_TOKEN
+    )
+except Exception as e:
+    print(f"Failed to load '{MODEL_NAME}': {e}")
+    print(f"Falling back to public model '{PUBLIC_MODEL}'")
+    pipe = StableDiffusionPipeline.from_pretrained(
+        PUBLIC_MODEL,
+        torch_dtype=torch.float16 if device == "cuda" else torch.float32
+    )
+
 pipe.to(device)
 
+# --- HELPER FUNCTIONS ---
 def load_image(file):
     ext = os.path.splitext(file.name)[1].lower()
     if ext in [".heic", ".heif"]:
@@ -100,6 +122,7 @@ def apply_filters(file, mode):
 
     return processed, output_path
 
+# --- GRADIO INTERFACE ---
 demo = gr.Interface(
     fn=apply_filters,
     inputs=[