import json
import os
import sys
import openai
from llama_index import GPTVectorStoreIndex, download_loader
# from llama_index.chat_engine import SimpleChatEngine
from datetime import datetime
from django.db import connection, models
from django.db.models import Q
import re

from adm.constants import CTS as cts
from adm.storage import MediaStorage
from adm.services import ParameterService

class Chatbot():
    def __init__(self) -> None:
        objParameter = ParameterService()
        openai.api_key = objParameter.getParameterByKey("OPENAI_API_KEY").value
        media_storage = MediaStorage()
        self.bucket = media_storage.storage.bucket.name
        self.storage = media_storage.storage
        self.credentials = json.dumps(media_storage.credentials)
        # self.docs_path = objParameter.getParameterByKey("CHATBOT_DOCS_PATH").value
        self.docs_path = '/chatbot/docs'
        self.endpoint = 'https://' + cts.GCP_ST_ACCESS_KEY_ID
        pass

    def train (self):
        OpendalGcsReader = download_loader("OpendalGcsReader")
        
        loader = OpendalGcsReader(
            bucket=self.bucket,
            path=self.docs_path,
            endpoint=self.endpoint,
            credentials=self.credentials,
        )
        documents = loader.load_data()

        # construct the index with the txt document
        index = GPTVectorStoreIndex.from_documents(documents)

        chat_engine = index.as_chat_engine(
            chat_mode='condense_question', 
            verbose=True
        )

        chat_engine.chat_repl()