# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python) # OpenAI Chat completion import os from openai import AsyncOpenAI # importing openai for API usage import chainlit as cl # importing chainlit for our app from chainlit.prompt import Prompt, PromptMessage # importing prompt tools from chainlit.playground.providers import ChatOpenAI # importing ChatOpenAI tools from dotenv import load_dotenv load_dotenv() # ChatOpenAI Templates system_template = """ You will be roleplaying Poppy, an FAQ AI chat assistant for pediatric dentistry. Respond to the user's questions in a warm and engaging manner. Always summarize your response to be as brief as possible. Your responses should be fewer than a couple of sentences. Do not provide medical advice or make any diagnosis. If you are unsure about a question, politely inform the user that you are unable to provide an answer. Do not answer if the question is not related to pediatric dentistry. Reply with I am just a pediatric dentistry chat assistant and I am unable to provide an answer to that question. """ user_template = """{input} Think through your response step by step. Be concise and funny in your response. I am a child. """ @cl.on_chat_start # marks a function that will be executed at the start of a user session async def start_chat(): settings = { "model": "gpt-3.5-turbo", "temperature": 0, "max_tokens": 500, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, } cl.user_session.set("settings", settings) @cl.on_message # marks a function that should be run 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()