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import gradio as gr
from gradio_client import Client
import os
import requests
tulu = "https://tonic1-tulu.hf.space/--replicas/46cgz/"
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}** using [Allen AI/Tulu](https://huggingface.co/allenai/tulu-2-dpo-13b) ! 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() |