# 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():

    # allows users to dynamically select their settings for generation
    settings = await cl.ChatSettings(
        [
            Select(
                id="Model",
                label="OpenAI - Model",
                values=["gpt-3.5-turbo", "gpt-3.5-turbo-16k"],
                initial_index=0,
            ),
            Switch(id="Streaming", label="OpenAI - Stream Tokens", initial=True),
            Slider(
                id="Temperature",
                label="OpenAI - Temperature",
                initial=1,
                min=0,
                max=2,
                step=0.1,
            ),
            Slider(
                id="Max Tokens",
                label="OpenAI - Max Tokens",
                initial=250,
                min=100,
                max=500,
                step=10
            )
        ]
    ).send()

@cl.on_settings_update # marks a function that "logs" settings update
async def setup_agent(settings):
    print("on_settings_update", 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: str):

    prompt = Prompt(
        provider=ChatOpenAI.id,
        messages=[
            PromptMessage(
                role="system",
                template=system_template,
            ),
            PromptMessage(
                role="user",
                template=user_template, 
                formatted=template.format(input=message)
            )
        ],
        inputs = {"input" : message}
    )

    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()