import gradio as gr
from gradio_client import Client
import os
import requests

tulu = "https://tonic1-tulu.hf.space/--replicas/t5vxm/"


def predict_beta(message, chatbot=[], system_prompt=""):
    client = Client(tulu)

    try:
        max_new_tokens = 800
        temperature = 0.4
        top_p = 0.9
        repetition_penalty = 0.9
        advanced = True

        # Making the prediction
        result = client.predict(
            message,
            system_prompt
            max_new_tokens,
            temperature,
            top_p,
            repetition_penalty,
            advanced,
            fn_index=0
        )

        if result is not None and len(result) > 0:
            bot_message = result[0] 
            return bot_message
        else:
            raise gr.Error("No response received from the model.")

    except Exception as e:
        error_msg = f"An error occurred: {str(e)}"
        raise gr.Error(error_msg)

def test_preview_chatbot(message, history):
    response = predict_beta(message, history, SYSTEM_PROMPT)
    return response


welcome_preview_message = f"""
Welcome to **{TITLE}**! Say something like: 

''{EXAMPLE_INPUT}''
"""

chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)])
textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT)

demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview)

demo.launch()