Update app.py

app.py

@@ -317,24 +317,32 @@ try:
     import os
     # Get HuggingFace token from environment/secrets
     hf_token = os.getenv('HF_TOKEN')
-    if hf_token:
-        os.environ['HF_TOKEN'] = hf_token
-    
-    chatbot_model = Gemma3nForConditionalGeneration.from_pretrained(
-        "google/gemma-3n-e4b-it",
-        device_map="auto",
-        torch_dtype=torch.bfloat16,
-        use_auth_token=hf_token
-    ).eval()
+    print(f"HF_TOKEN found: {'Yes' if hf_token else 'No'}")
     
-    chatbot_processor = AutoProcessor.from_pretrained(
-        "google/gemma-3n-e4b-it",
-        use_auth_token=hf_token
-    )
-    
-    print("Chatbot model loaded successfully")
+    if hf_token:
+        print("Loading chatbot model with token...")
+        chatbot_model = Gemma3nForConditionalGeneration.from_pretrained(
+            "google/gemma-3n-e4b-it",
+            device_map="auto",
+            torch_dtype=torch.bfloat16,
+            token=hf_token  # Use 'token' instead of 'use_auth_token'
+        ).eval()
+        
+        chatbot_processor = AutoProcessor.from_pretrained(
+            "google/gemma-3n-e4b-it",
+            token=hf_token  # Use 'token' instead of 'use_auth_token'
+        )
+        
+        print("✅ Chatbot model loaded successfully")
+    else:
+        print("❌ No HF_TOKEN found in environment")
+        chatbot_model = None
+        chatbot_processor = None
+        
 except Exception as e:
-    print(f"Error loading chatbot model: {e}")
+    print(f"❌ Error loading chatbot model: {e}")
+    import traceback
+    traceback.print_exc()
     chatbot_model = None
     chatbot_processor = None
 
@@ -342,7 +350,7 @@ except Exception as e:
 # Global state for managing tabs
 processed_markdown = ""
 show_results_tab = False
-chatbot_model = None
+# chatbot_model is initialized above
 
 
 def process_uploaded_pdf(pdf_file, progress=gr.Progress()):
@@ -437,10 +445,12 @@ with gr.Blocks(
     with gr.Tabs() as main_tabs:
         # Home Tab
         with gr.TabItem("🏠 Home", id="home"):
+            chatbot_status = "✅ Chatbot ready" if chatbot_model else "❌ Chatbot not loaded"
             gr.Markdown(
                 "# Scholar Express\n"
                 "### Upload a research paper to get a web-friendly version, an AI chatbot, and a podcast summary. Because of our reliance on Generative AI, some errors are inevitable.\n"
-                f"**Status:** {model_status}"
+                f"**PDF Processing:** {model_status}\n"
+                f"**Chatbot:** {chatbot_status}"
             )
             
             with gr.Column(elem_classes="upload-container"):