# start with the following comando: panel serve chat-panel.py

import os
import platform


# Environment Variablen importieren
from dotenv import load_dotenv
load_dotenv()

from crewai import Crew, Process, Agent, Task
from langchain_openai import ChatOpenAI

from langchain_core.callbacks import BaseCallbackHandler
from typing import TYPE_CHECKING, Any, Dict, Optional

from langchain.agents import load_tools
#human = load_tools(["human"])

# pip install panel
import panel as pn 
pn.extension(design="material")



import threading

from crewai.agents import CrewAgentExecutor
import time 

def custom_ask_human_input(self, final_answer: dict) -> str:
      
      global user_input

      prompt = self._i18n.slice("getting_input").format(final_answer=final_answer)

      chat_interface.send(prompt, user="Lehrkraft", respond=False)

      while user_input == None:
          time.sleep(1)  

      human_comments = user_input
      user_input = None

      return human_comments


CrewAgentExecutor._ask_human_input = custom_ask_human_input

user_input = None
initiate_chat_task_created = False

def initiate_chat(message):

    global initiate_chat_task_created
    # Indicate that the task has been created
    initiate_chat_task_created = True

    StartCrew(message)

def callback(contents: str, user: str, instance: pn.chat.ChatInterface):
    
    global initiate_chat_task_created
    global user_input

    if not initiate_chat_task_created:
        thread = threading.Thread(target=initiate_chat, args=(contents,))
        thread.start()

    else:
        user_input = contents

avators = {"Writer":"https://cdn-icons-png.flaticon.com/512/320/320336.png",
            "Reviewer":"https://cdn-icons-png.freepik.com/512/9408/9408201.png"}

class MyCustomHandler(BaseCallbackHandler):

    
    def __init__(self, agent_name: str) -> None:
        self.agent_name = agent_name

    def on_chain_start(
        self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any
    ) -> None:
        """Print out that we are entering a chain."""

        chat_interface.send(inputs['input'], user=BaseCallbackHandler, respond=False)

    def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
        """Print out that we finished a chain."""
    
        chat_interface.send(outputs['output'], user=self.agent_name, avatar=avators[self.agent_name], respond=False)

llm = ChatOpenAI(model="gpt-3.5-turbo-0125")
#llm = ChatOpenAI(model="gpt-4")

writer = Agent(

    role='Theologische Inhalte entwickeln',
    backstory='''Langjähriger Theologieprofessor mit Spezialisierung auf historisch-kritische Bibelinterpretation''',
    goal="Verständnis für biblische Texte und christliche Lehren fördern.",
    llm=llm,
    callbacks=[MyCustomHandler("Thelogical Content Developer")],
)
reviewer = Agent(
    role='Interreligiösen Dialog fördern',
    backstory='''Religionswissenschaftler mit internationaler Erfahrung im Dialog zwischen Weltreligionen.''',
    goal="Förderung von ethischer Argumentation und philosophischem Denken",
    llm=llm,
    callbacks=[MyCustomHandler("Religious Dialogue Promoter")],
    allow_delegation=True
)

def StartCrew(prompt):

    task1 = Task(
      description=f"""Entwickeln Sie einen Unterrichtsplan zum Thema {prompt}. """,
      agent=writer,
      expected_output="Unterrichtsplan mit relevante theologischen Perspektiven und zeitgemäßen Methoden."
    )

    task2 = Task(
      description=("Entwickeln Sie zusammen mit Ihren Kollegen an einen Unterrichtsplan unter Berücksichtigung der religionswissenschaftlicher und interreligiöser Aspekte"),
      agent=reviewer,
      expected_output="Kollaborativ entwickelter Unterrichtsplan",
      human_input=True,
      allow_delegation=True
    
    )
    # Establishing the crew with a hierarchical process
    project_crew = Crew(
        tasks=[task1, task2],  # Tasks to be delegated and executed under the manager's supervision
        agents=[writer, reviewer],
        manager_llm=llm,
        language="de",
        process=Process.hierarchical  # Specifies the hierarchical management approach
    )

    result = project_crew.kickoff()

    chat_interface.send("## Final Result\n"+result, user="assistant", respond=False)


chat_interface = pn.chat.ChatInterface(callback=callback)
chat_interface.send("Beschreibe dein Unterrichttsvorhaben!", user="System", respond=False)
chat_interface.servable()