app.py

# from openai import AsyncOpenAI
# import chainlit as cl
# from chainlit.playground.providers import ChatOpenAI

# client = AsyncOpenAI()

# template = "Hello, {name}!"
# inputs = {"name": "John"}

# settings = {
#     "model": "gpt-3.5-turbo",
#     "temperature": 0,
#     # ... more settings
# }


# @cl.step(name="gpt-3.5", type="llm")
# async def call_openai():
#     generation = cl.ChatGeneration(
#         provider=ChatOpenAI.id,
#         inputs=inputs,
#         settings=settings,
#         messages=[
#             cl.GenerationMessage(
#                 template=template, formatted=template.format(**inputs), role="assistant"
#             )
#         ],
#     )

#     # Make the call to OpenAI
#     response = await client.chat.completions.create(
#         messages=[m.to_openai() for m in generation.messages], **settings
#     )

#     generation.completion = response.choices[0].message.content

#     cl.context.current_step.generation = generation

#     return generation.completion


# @cl.on_chat_start
# async def start():
#     await call_openai()


# 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!
"""

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()

    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()