# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python) # OpenAI Chat completion import openai # importing openai for API usage import chainlit as cl # importing chainlit for our app from chainlit.input_widget import ( Select, Switch, Slider, ) # importing chainlit settings selection tools from chainlit.prompt import Prompt, PromptMessage # importing prompt tools from chainlit.playground.providers import ChatOpenAI # importing ChatOpenAI tools # You only need the api key inserted here if it's not in your .env file # openai.api_key = "YOUR_API_KEY" # ChatOpenAI Templates 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 # 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): settings = cl.user_session.get("settings") 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 openai.ChatCompletion.acreate( messages=[m.to_openai() for m in prompt.messages], stream=True, **settings ): token = stream_resp.choices[0]["delta"].get("content", "") 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()