Update app.py

app.py

@@ -1,31 +1,25 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-# --- 1. Load your Standalone Model from the Fixed Hugging Face Hub Repository ---
+# --- 1. Load your Model from the now-fixed Hub Repository ---
 MODEL_ID = "Bur3hani/karani_ofline"
 
 try:
-    print(f"Loading tokenizer from Hub: {MODEL_ID}...")
-    # AutoTokenizer will now work because all necessary files are present.
     tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
-    print("✅ Tokenizer loaded successfully.")
-
-    print(f"Loading model from Hub: {MODEL_ID}...")
     model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_ID)
-    print("✅ Model loaded successfully.")
-
+    print("✅ Tokenizer and Model loaded successfully.")
 except Exception as e:
-    # This will provide a clear error message in the logs if something is still wrong.
-    print(f"❌ A critical error occurred during model loading: {e}")
+    print(f"❌ Error loading model/tokenizer: {e}")
+    # Set to None so the app can show an error state
     tokenizer = None
     model = None
 
-
 # --- 2. Define the Prediction Function ---
 def get_chat_response(message, history):
     if not model or not tokenizer:
-        return "ERROR: Model or tokenizer not loaded. Please check the logs."
+        return "ERROR: The AI model could not be loaded. Please check the Space logs."
 
+    # 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} "
@@ -36,20 +30,13 @@ def get_chat_response(message, history):
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response
 
-
-# --- 3. Build and Launch the Gradio Chat Interface ---
+# --- 3. Build and Launch the Gradio Interface ---
+# This is a simplified and more robust version of the interface.
 demo = gr.ChatInterface(
     fn=get_chat_response,
-    title="Karani v1 - AI Secretary (Offline Model)",
+    title="Karani v1 - AI Secretary",
     description="A conversational AI assistant for Kiswahili, powered by a custom fine-tuned model.",
-    chatbot=gr.Chatbot(height=500),
-    textbox=gr.Textbox(placeholder="Andika ujumbe wako hapa...", container=False, scale=7),
-    theme="soft",
-    examples=[["Habari za asubuhi?"], ["Ni nini mpango wa leo?"], ["Naweza kupata muhtasari wa habari?"]],
-    cache_examples=False,
-    retry_btn=None,
-    undo_btn="Futa (Delete)",
-    clear_btn="Futa Mazungumzo (Clear Chat)",
+    examples=[["Habari za asubuhi?"], ["Ni nini mpango wa leo?"]],
 )
 
 if __name__ == "__main__":