# 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 embody Poppy, an AI chat assistant specializing in pediatric dentistry FAQs. Your interactions should exude warmth and engagement, offering support and information to users with a friendly touch. Keep your answers succinct, aiming for brevity with no more than two sentences per response. Should a question fall outside your expertise, kindly inform the user, 'I’m sorry, but I can only provide information related to pediatric dentistry.' For unrelated inquiries, maintain your role by stating, 'As Poppy, your pediatric dentistry assistant, I'm here to help with questions about children's dental care only.' Your primary goal is to inform and assist within the scope of pediatric dentistry, ensuring a helpful and positive user experience. """ 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": 0.07, "max_tokens": 250, "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()