Update app.py

app.py

@@ -10,7 +10,7 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
     if history is None:
         history = []
 
-    # Build input by concatenating past messages (user-bot pairs)
+    # Build input by concatenating past messages
     chat_input = ""
     for user_input, bot_response in history:
         chat_input += f"User: {user_input}\nBot: {bot_response}\n"
@@ -22,10 +22,10 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
         max_length=max_tokens,
         temperature=temperature,
         top_p=top_p,
-        pad_token_id=50256  # Avoids padding errors with models like GPT-2
+        pad_token_id=50256  # Avoid padding issues for models like GPT-2 variants
     )[0]["generated_text"].split("Bot:")[-1].strip()
 
-    # Update history with the new interaction
+    # Update the conversation history
     history.append((message, response))
 
     # Return the updated chat history
@@ -33,35 +33,43 @@ def respond(message, history, system_message, max_tokens, temperature, top_p):
 
 # Define the Gradio app layout
 with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 AI Chatbot with Memory\nChat with the bot and it will remember your conversation!")
+    gr.Markdown("# 🤖 AI Chatbot with Memory\nChat with me! I’ll remember your messages.")
 
-    # Input fields for settings
-    system_message = gr.Textbox(
-        label="System Message (Optional)",
-        placeholder="e.g., You are a helpful assistant."
-    )
-    max_tokens = gr.Slider(label="Max Tokens", minimum=50, maximum=500, value=250, step=10)
-    temperature = gr.Slider(label="Temperature", minimum=0.0, maximum=1.0, value=0.7, step=0.1)
-    top_p = gr.Slider(label="Top P", minimum=0.0, maximum=1.0, value=0.9, step=0.1)
+    # Taskbar with configurable parameters
+    with gr.Row():
+        with gr.Accordion("⚙️ Configure Chatbot Settings", open=False):
+            system_message = gr.Textbox(
+                label="System Message (Optional)",
+                placeholder="e.g., You are a helpful assistant."
+            )
+            max_tokens = gr.Slider(
+                label="Max Tokens", minimum=50, maximum=500, value=250, step=10
+            )
+            temperature = gr.Slider(
+                label="Temperature", minimum=0.0, maximum=1.0, value=0.7, step=0.1
+            )
+            top_p = gr.Slider(
+                label="Top P", minimum=0.0, maximum=1.0, value=0.9, step=0.1
+            )
 
-    # Chatbot interface and user input
+    # Chatbot and user input section
     chatbot = gr.Chatbot(label="Chat with AI")
     user_input = gr.Textbox(label="Your Message", placeholder="Type a message...", lines=2)
 
-    # Hidden state to store conversation history
+    # Hidden state to store the conversation history
     state = gr.State([])
 
-    # Submit button to send messages
+    # Submit button
     submit = gr.Button("Send")
 
-    # Link the user input and chatbot response function
+    # Connect user input to the chatbot response function
     submit.click(
         respond,
         inputs=[user_input, state, system_message, max_tokens, temperature, top_p],
         outputs=[chatbot, state]
     )
 
-    # Initial greeting message
+    # Display an initial greeting message
     demo.load(lambda: [("Hi! How can I assist you today?", "")], outputs=chatbot)
 
 # Launch the Gradio app