Update app.py

app.py

@@ -19,25 +19,32 @@ The app uses **DistilGPT-2** to generate creative outlines formatted in Markdown
 examples = [
     ["The old lighthouse keeper stared into the storm. He'd seen many tempests, but this one was different. This one had eyes..."],
     ["In a city powered by dreams, a young inventor creates a machine that can record them. His first recording reveals a nightmare that doesn't belong to him."],
-    ["The knight adjusted his helmet, the dragon's roar echoing in the valley. He was ready for the fight, but not for what the dragon said when it finally spoke."],
+    ["The knight adjusted his helmet, the dragon's roar echoing in the valley. He was ready for the fight, but for what the dragon said when it finally spoke."],
     ["She found the old leather-bound journal in her grandfather's attic. The first entry read: 'To relieve stress, I walk in the woods. But today, the woods walked with me.'"],
     ["The meditation app promised to help her 'delete unhelpful thoughts.' She tapped the button, and to her horror, the memory of her own name began to fade..."]
 ]
 
 # --- Model Initialization ---
-# This section loads a smaller, CPU-friendly model that does not require a token.
+# This section loads a smaller, CPU-friendly model.
+# It will automatically use the HF_TOKEN secret when deployed on Hugging Face Spaces.
 generator = None
 model_error = None
 
 try:
     print("Initializing model... This may take a moment.")
     
-    # Using a smaller, fully open model that does not require authentication.
+    # Explicitly load the token from environment variables (for HF Spaces secrets)
+    # This makes the authentication more robust.
+    hf_token = os.environ.get("HF_TOKEN", None)
+    
+    # Using a smaller, fully open model. Passing the token explicitly handles
+    # environments that might otherwise send invalid credentials.
     generator = pipeline(
         "text-generation",
         model="distilgpt2",
         torch_dtype=torch.float32, # Use float32 for wider CPU compatibility
-        device_map="auto" # Will use GPU if available, otherwise CPU
+        device_map="auto", # Will use GPU if available, otherwise CPU
+        token=hf_token
     )
     print("✅ DistilGPT-2 model loaded successfully!")