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# YACI - Hugging Face Spaces
# OpenAI chat completion
import os
from openai import AsyncOpenAI
import chainlit as cl
from chainlit.prompt import Prompt, PromptMessage # prompt tools
from chainlit.playground.providers import ChatOpenAI # Chainlit's OpenAI tools
from dotenv import load_dotenv
load_dotenv()
# Model config
MODEL = "gpt-4o-mini-2024-07-18"
MAX_TOKENS = 500
TEMP = 0
TOP_P = 1
# ChatOpenAI
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 # init user chat session
async def start_chat():
settings = {
"model": MODEL,
"temperature": TEMP,
"max_tokens": MAX_TOKENS,
"top_p": TOP_P,
"frequency_penalty": 0,
"presence_penalty": 0,
}
cl.user_session.set("settings", settings)
@cl.on_message # runs 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()
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