# YACI - Hugging Face Spaces # OpenAI chat completion import os from openai import AsyncOpenAI import chainlit as cl from chainlit.prompt import Prompt, PromptMessage # prompt tools from chainlit.playground.providers import ChatOpenAI # Chainlit's OpenAI tools from dotenv import load_dotenv load_dotenv() # Model config MODEL = "gpt-4o-mini-2024-07-18" MAX_TOKENS = 500 TEMP = 0 TOP_P = 1 # ChatOpenAI system_template = """You are a helpful assistant who always speaks in a pleasant tone!""" user_template = """{input} Think through your response step by step. """ @cl.on_chat_start # init user chat session async def start_chat(): settings = { "model": MODEL, "temperature": TEMP, "max_tokens": MAX_TOKENS, "top_p": TOP_P, "frequency_penalty": 0, "presence_penalty": 0, } cl.user_session.set("settings", settings) @cl.on_message # runs each time the chatbot receives a message from a user async def main(message: cl.Message): settings = cl.user_session.get("settings") client = AsyncOpenAI() print(message.content) prompt = Prompt( provider=ChatOpenAI.id, messages=[ PromptMessage( role="system", template=system_template, formatted=system_template, ), PromptMessage( role="user", template=user_template, formatted=user_template.format(input=message.content), ), ], inputs={"input": message.content}, settings=settings, ) print([m.to_openai() for m in prompt.messages]) msg = cl.Message(content="") # Call OpenAI async for stream_resp in await client.chat.completions.create( messages=[m.to_openai() for m in prompt.messages], stream=True, **settings ): token = stream_resp.choices[0].delta.content if not token: token = "" await msg.stream_token(token) # Update the prompt object with the completion prompt.completion = msg.content msg.prompt = prompt # Send and Close the message stream await msg.send()