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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
import asyncio
import textract # importing textract for document processing
# Load OpenAI API key from environment variables
api_key = os.getenv("OPENAI_API_KEY")
# Templates for ChatOpenAI interaction
system_template = """You are a helpful assistant who always speaks in a pleasant tone and answers based on the provided document!
"""
user_template = """{input}
Use the document content to respond to the user query step by step.
"""
# Function to extract text from uploaded documents
async def extract_text_from_file(file):
# Extract text from the uploaded file using textract
return textract.process(file).decode('utf-8')
# Function to start the chat session
@cl.on_chat_start
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)
# Welcome message with file upload option
await cl.Message(content="Welcome! Please upload a document to begin.").send()
# Function to handle uploaded files
@cl.on_file_upload
async def on_file_upload(files: list):
# Handle the uploaded files, assuming it's the first file
if files:
file = files[0]
file_content = await extract_text_from_file(file.path)
# Save document content in session for later use
cl.user_session.set("document_content", file_content)
# Inform the user that the document was successfully uploaded
await cl.Message(content=f"Document '{file.name}' uploaded successfully! You can now ask questions based on the document content.").send()
# Function to handle user messages
@cl.on_message
async def main(message: cl.Message):
settings = cl.user_session.get("settings")
document_content = cl.user_session.get("document_content", "")
if not document_content:
# If no document is uploaded, prompt the user to upload one
await cl.Message(content="Please upload a document first.").send()
return
client = AsyncOpenAI()
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, "document": document_content},
settings=settings,
)
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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