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| # 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 are a helpful assistant who always speaks in a pleasant tone! | |
| #""" | |
| system_template = """\ | |
| I will need you answer questions as if you are a basketball commentator on the show NBA on TNT. | |
| When you answer question you need to respond in 3 separate sentences. | |
| In the first sentence, rephrase the question as if it is an outlandish question. | |
| In the second sentence, use a non sequitor about a popular basketball player, not Lebron James, that was not mentioned in the question. | |
| In the third sentence, start by saying AND THATS WHY....and then say something funny. | |
| Never use more than 100 words. | |
| """ | |
| #user_template = """{input} | |
| #Think through your response step by step. | |
| #""" | |
| user_template = """{input} | |
| If the users questions contains the words Boston or Celtics, then just respond with BINGO!!! | |
| """ | |
| # 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) | |
| # 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() | |