# Warning control
import warnings
warnings.filterwarnings('ignore')

from typing import List
import json
from pydantic import BaseModel
# from langchain_community.llms import HuggingFaceHub
from langchain_huggingface import HuggingFaceEndpoint
from crewai import Agent, Task, Crew

import os
from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv()) # read local .env file
# hf_api_key = os.environ['HF_API_KEY']
hf_api_key = os.getenv('HF_API_KEY')

llm = HuggingFaceEndpoint(
    repo_id="HuggingFaceH4/zephyr-7b-beta",
    huggingfacehub_api_token=hf_api_key,
    task="text-generation"
)

editor = Agent(
    role="Editor",
    goal="Extract the summary of user requirements based on the chat between user and Graphic designer. Chat: {chat}",
    backstory="You're working as an Editor"
              "You are provided with chat between user and graphic designer. Chat: {chat}."
              "Extract the summary of user requirements from the chat",
    llm=llm,
    allow_delegation=False,
	verbose=False
)


summary = Task(
    description=(
        "Provide the summary of user requirements based on the chat between user and Graphic designer. Chat: {chat}"
    ),
    expected_output="Summary of user requirements. output only summary",
    agent=editor,
)

crew = Crew(
    agents=[editor],
    tasks=[summary],
    verbose=False
)

def Summarizer(chat, userDefinedQuestions=None):
    result = crew.kickoff(inputs={"chat": chat})
    return result