app.py

SYSTEM_PROMPT = "Your bot's primary function is to have meaningful conversations about scooped bagels. Your prompts should be engaging, and should help users explore their thoughts and feelings about this delicious breakfast food."
TITLE = "[Tulu](https://huggingface.co/allenai/tulu-2-dpo-13b) Bagel Buddy"
EXAMPLE_INPUT = "How do you like your scooped bagels topped?"
import gradio as gr
from gradio_client import Client
import os
import requests

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


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
        )
        print("Raw API Response:", result)  # Debugging print
        if result is not None:
            print("Processed bot_message:", result)  # Debugging print
            return result
        else:
            print("No response or empty response from the model.")  # Debugging print
            return None
            
    except Exception as e:
        error_msg = f"An error occurred: {str(e)}"
        print(error_msg)  # Debugging print
        return None

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()