Updated code to address “UserWarning: You have not specified a value for the `type` parameter”

chatbot.py

@@ -180,57 +180,53 @@ def create_chatbot_tab(model: str):
     
     This function sets up all UI components for the conversational chatbot,
     including:
-    - Chatbot component for displaying conversation history
+    - Chatbot component for displaying conversation history (using messages format)
     - Text input box for user messages
     - Send button and Enter key submission support
-    - Internal state management for conversation history
     
-    It also wires up event handlers for both button clicks and Enter key presses,
-    and manages the conversion between Gradio's chat format and the internal
-    conversation history format.
+    It also wires up event handlers for both button clicks and Enter key presses.
+    The conversation history uses Gradio's messages format (list of dicts with
+    "role" and "content" keys), which matches the internal chatbot API format.
     
     Args:
         model: Hugging Face model ID to use for the chatbot.
     """
     gr.Markdown("Have a conversation with an AI chatbot.")
-    chatbot_history = gr.State(value=None)  # Store the conversation history.
-    chatbot_output = gr.Chatbot(label="Conversation")
+    chatbot_output = gr.Chatbot(label="Conversation", type="messages")
     chatbot_input = gr.Textbox(label="Your message")
     chatbot_send_button = gr.Button("Send")
     
-    def chat_interface(message: str, history: list | None, conversation_state: list[dict] | None):
-        """Handle chatbot interaction with Gradio chat format.
+    def chat_interface(message: str, history: list[dict] | None):
+        """Handle chatbot interaction with Gradio messages format.
         
-        This function serves as the bridge between Gradio's chat interface format
-        and the internal chatbot API. It converts formats, handles empty messages,
-        and manages state updates.
+        This function handles chatbot interactions using Gradio's messages format,
+        where each message is a dictionary with "role" and "content" keys.
         
         Args:
             message: The user's message string from the input box.
-            history: Gradio's chat history format (list of [user_msg, bot_msg] pairs).
-            conversation_state: Internal conversation history format (list of dicts).
+            history: Gradio's chat history in messages format (list of dicts with
+                "role" and "content" keys). If None, starts a new conversation.
         
         Returns:
             Tuple containing:
-                - Updated Gradio chat history
-                - Updated internal conversation state
+                - Updated chat history in messages format
                 - Empty string (to clear the input field)
         """
         if not message.strip():
-            return history, conversation_state, ""
-        response, updated_conversation = chat(model, message, conversation_state)  # Get response from chatbot.
-        if history is None:  # Update Gradio chat history format: list of [user_message, bot_message] pairs.
-            history = []
-        history.append([message, response])
-        return history, updated_conversation, ""  # Clear input field for the next message from the user.
+            return history, ""
+        print(history)
+        
+        # Use history directly as conversation_state since they're the same format
+        response, updated_conversation = chat(model, message, history)
+        return updated_conversation, ""  # Return updated conversation history and clear input field
     
     chatbot_send_button.click(
         fn=chat_interface,
-        inputs=[chatbot_input, chatbot_output, chatbot_history],
-        outputs=[chatbot_output, chatbot_history, chatbot_input]
+        inputs=[chatbot_input, chatbot_output],
+        outputs=[chatbot_output, chatbot_input]
     )
     chatbot_input.submit(
         fn=chat_interface,
-        inputs=[chatbot_input, chatbot_output, chatbot_history],
-        outputs=[chatbot_output, chatbot_history, chatbot_input]
+        inputs=[chatbot_input, chatbot_output],
+        outputs=[chatbot_output, chatbot_input]
     )