Update app.py

app.py

@@ -1,27 +1,30 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import os
 
-# --- 1. Load your Model from its Hugging Face Repository ---
-# This is the correct, professional way to do it.
+# --- 1. Get the Hugging Face Token from Space Secrets ---
+# The os.getenv() function securely reads the secret you just created.
+auth_token = os.getenv("HF_TOKEN")
+
+# --- 2. Load your Model from its Hub Repository using the Token ---
 MODEL_ID = "Bur3hani/karani_ofline"
 
 try:
     print(f"Loading tokenizer and model from Hub: {MODEL_ID}...")
-    tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
-    model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_ID)
-    print("✅ Model and Tokenizer loaded successfully.")
+    # We pass the token to the 'from_pretrained' method.
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, token=auth_token)
+    model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_ID, token=auth_token)
+    print("✅ Model and Tokenizer loaded successfully using the provided token.")
+    MODEL_LOADED = True
 except Exception as e:
     print(f"❌ Error loading from Hub: {e}")
-    # Set to None so the app can show an error state if loading fails.
-    tokenizer = None
-    model = None
+    MODEL_LOADED = False
 
-# --- 2. Define the Prediction Function ---
+# --- 3. Define the Prediction Function ---
 def get_chat_response(message, history):
-    if not model or not tokenizer:
-        return "ERROR: The AI model failed to load. Please check the Space logs for details."
+    if not MODEL_LOADED:
+        return "ERROR: The AI model failed to load. This could be due to a missing token or an issue with the model repository."
 
-    # Format the conversation history for the model
     input_text = ""
     for user_turn, bot_turn in history:
         input_text += f"user: {user_turn} bot: {bot_turn} "
@@ -32,8 +35,7 @@ def get_chat_response(message, history):
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response
 
-# --- 3. Build and Launch the Gradio Interface ---
-# This version is simplified to avoid any deprecated arguments.
+# --- 4. Build and Launch the Gradio Interface ---
 demo = gr.ChatInterface(
     fn=get_chat_response,
     title="Karani v1 - AI Secretary",