app.py

# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python)

# OpenAI Chat completion
import os
import sys
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()
sys.path.append(".")
sys.path.append("aimakerspace/openai_utils")

import raqa
from raqa import retrieval_augmented_qa_pipeline

# 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: cl.Message):
    settings = cl.user_session.get("settings")

    client = AsyncOpenAI()

    # Do some raqa stuff
    #msg = cl.Message(content=message.content)
    response=retrieval_augmented_qa_pipeline.run_pipeline(message.content)
    msg = cl.Message(content=response)
    
    # Send and close the message stream
    await msg.send()