Update app.py

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 import torch
 from transformers import pipeline
 import os
+from huggingface_hub import login
 
 # --- App Configuration ---
 TITLE = "✍️ AI Story Outliner"
@@ -37,16 +38,19 @@ try:
     hf_token = os.environ.get("HF_TOKEN")
 
     if hf_token:
-        print("✅ HF_TOKEN secret found.")
+        print("✅ HF_TOKEN secret found. Logging in...")
+        # Programmatically log in to Hugging Face. This is a more robust method.
+        login(token=hf_token)
+        print("✅ Login successful.")
     else:
         # If no token is found, raise an error to prevent the app from crashing later.
         raise ValueError("Hugging Face token not found. Please set the HF_TOKEN secret in your Space settings.")
 
-    # Using 'mistralai/Mistral-7B-v0.1'. This model is gated and requires a token.
+    # Using 'mistralai/Mistral-7B-v0.1'.
+    # After login(), the token argument is no longer needed here as the session is authenticated.
     generator = pipeline(
         "text-generation",
         model="mistralai/Mistral-7B-v0.1",
-        token=hf_token,
         torch_dtype=torch.bfloat16, # More performant data type
         device_map="auto" # Will use GPU if available, otherwise CPU
     )
@@ -102,8 +106,6 @@ The outline must have three parts: a dramatic hook, a concise ballad, and a sati
         for out in outputs:
             # The model will generate the prompt plus the continuation. We extract just the new part.
             full_text = out['generated_text']
-            # Add back the part of the prompt we want to see in the output
-            story_start = "### 🎬 The Hook\n"
             # Split by the instruction closing tag to get only the model's response
             generated_part = full_text.split("[/INST]")[-1].strip()
             stories.append(generated_part)