import gradio as gr
from gradio_client import Client

# Initialize the client by pointing to the Gradio Space
client = Client("yuntian-deng/ChatGPT4")


def chat_with_model(message, history):
    """
    Interact with the chatbot while maintaining conversation context.

    Args:
        message (str): User's most recent message.
        history (list of dict): Conversation history with 'role' and 'content' keys.

    Returns:
        str: The chatbot's response to the latest user message.
    """
    # Transform history from OpenAI-style dicts to a list of tuples for compatibility
    formatted_history = [(entry["role"], entry["content"]) for entry in history]
    
    if message.strip():  # Avoid empty input
        # Call the Gradio backend Space
        result = client.predict(
            message,             # User message
            1.0,                 # Top-p value for creativity
            0.7,                 # Temperature for randomness
            len(formatted_history),   # Chat counter
            formatted_history,        # Conversation history context
            api_name="/predict"       # API endpoint exposed from Gradio Space
        )

        # Extract updated conversation response (simplify for gr.ChatInterface)
        updated_response = result[0][-1][1]  # Get the chatbot's latest message
        return updated_response
    else:
        return "Please enter a valid message."


# Use gr.ChatInterface for a modern chatbot UI
app = gr.ChatInterface(
    fn=chat_with_model,
    type="messages",  # Ensure compatibility with message history
    title="🤖 ChatGPT-4o",
    description="Interact with GPT-4o without any limitations for free. Type your message below!"
)

# Launch the app
app.launch()