Update app.py

app.py

@@ -13,19 +13,17 @@ OUTPUT_DIR = "outputs"
 os.makedirs(OUTPUT_DIR, exist_ok=True)
 
 # --- DEVICE SETUP ---
-device = "cuda" if torch.cuda.is_available() else "cpu"
+device = "cpu"  # Force CPU for safety
 
 # --- 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
+HF_TOKEN = os.getenv("HF_TOKEN", None)  # optional token for private repo
 
 try:
     pipe = StableDiffusionPipeline.from_pretrained(
         MODEL_NAME,
-        torch_dtype=torch.float16 if device == "cuda" else torch.float32,
+        torch_dtype=torch.float32,
         use_auth_token=HF_TOKEN
     )
 except Exception as e:
@@ -33,7 +31,7 @@ except Exception as 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
+        torch_dtype=torch.float32
     )
 
 pipe.to(device)
@@ -96,8 +94,8 @@ def apply_filters(file, mode):
     elif mode == "AI Cartoon":
         pil_img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
         prompt = "cartoon, anime style, vibrant colors, detailed, smooth"
-        with torch.autocast(device):
-            cartoon_img = pipe(prompt=prompt, image=pil_img, num_inference_steps=30).images[0]
+        # CPU only, no GPU/autocast
+        cartoon_img = pipe(prompt=prompt, image=pil_img, num_inference_steps=30).images[0]
         processed = np.array(cartoon_img)
     elif mode == "Sepia":
         sepia_filter = np.array([[0.272, 0.534, 0.131],