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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() | |