import logging
import re
import os
import pytz

from typing import List
from datetime import datetime
from datetime import timedelta
from fastapi.responses import JSONResponse
from script.vector_db import IndexManager
from llama_index.core.llms import MessageRole

from core.chat.engine import Engine
from core.chat.chatstore import ChatStore
from core.parser import (
    filter_metadata_by_pages,
    extract_sorted_page_numbers

)

from service.dto import ChatMessage
from pymongo.mongo_client import MongoClient


class ChatCompletionService:
    def __init__(
        self,
        session_id: str,
        user_request: str,
        titles: List = None,
        type_bot: str = "general",
    ):
        self.session_id = session_id
        self.user_request = user_request
        self.titles = titles
        self.type_bot = type_bot
        self.client = MongoClient(os.getenv("MONGO_URI"))
        self.engine = Engine()
        self.index_manager = IndexManager()
        self.chatstore = ChatStore()

    def generate_completion(self):
        if not self._ping_mongo():
            return JSONResponse(
                status_code=500, content="Database Error: Unable to connect to MongoDB"
            )

        try:
            # Load and retrieve chat engine with appropriate index
            index = self.index_manager.load_existing_indexes()
            chat_engine = self._get_chat_engine(index)

            # Generate chat response
            response = chat_engine.chat(self.user_request)

            sources = response.source_nodes

            contents, metadata_collection, scores = self._process_sources_images(sources)
            
            # Update response and renumber sources
            response = str(response)

            # Add contents to metadata
            metadata_collection = self._attach_contents_to_metadata(
                contents, metadata_collection
            )
            
            page_sources = extract_sorted_page_numbers(response)
            metadata_collection = filter_metadata_by_pages(metadata_collection, page_sources)

            # Save the message to chat store
            self._store_message_in_chatstore(response, metadata_collection)

        except Exception as e:
            logging.error(f"An error occurred in generate text: {e}")
            return JSONResponse(
                status_code=500, content=f"An internal server error occurred: {e}"
            )

        try:
            if self.type_bot == "specific":
                self._save_chat_history_to_db(response, metadata_collection)

            return str(response), metadata_collection, scores

        except Exception as e:
            logging.error(f"An error occurred while saving chat history: {e}")
            return JSONResponse(
                status_code=500,
                content=f"An internal server error occurred while saving chat history: {e}",
            )

    def _ping_mongo(self):
        try:
            self.client.admin.command("ping")
            print("Pinged your deployment. Successfully connected to MongoDB!")
            return True
        except Exception as e:
            logging.error(f"MongoDB connection failed: {e}")
            return False

    def _get_chat_engine(self, index):
        if self.type_bot == "general":
            return self.engine.get_chat_engine(self.session_id, index)
        return self.engine.get_chat_engine(
            self.session_id, index, self.titles, self.type_bot
        )

    def _extract_sorted_references(self, response):
        number_reference = list(set(re.findall(r"\[(\d+)\]", str(response))))
        return sorted(number_reference)

    
    def _process_sources_images(self, sources):
        contents, metadata_collection, scores = [], [], []

        for number in range (len(sources)):
            if sources and len(sources) > 0:
                content = sources[number - 1].node.get_text()
                contents.append(content)
                metadata = dict(sources[number - 1].node.metadata)
                metadata_collection.append(metadata)
                score = sources[number - 1].score
                scores.append(score)
            else:
                print("No sources available")

        return contents, metadata_collection, scores

    def _attach_contents_to_metadata(self, contents, metadata_collection):
        for i in range(min(len(contents), len(metadata_collection))):
            metadata_collection[i]["content"] = contents[i]
        return metadata_collection

    def _store_message_in_chatstore(self, response, metadata_collection):
        message = ChatMessage(
            role=MessageRole.ASSISTANT, 
            content=response, 
            metadata=metadata_collection,
        )
        self.chatstore.delete_last_message(self.session_id)
        self.chatstore.add_message(self.session_id, message)
        self.chatstore.clean_message(self.session_id)

    def _save_chat_history_to_db(self, response, metadata_collection):
        jakarta_tz = pytz.timezone("Asia/Jakarta")
        time_now = datetime.now(jakarta_tz)
        user_timestamp = time_now - timedelta(seconds=0.2)
        chat_history_db = [
            ChatMessage(
                role=MessageRole.USER,
                content=self.user_request,
                timestamp=user_timestamp,
                payment="free" if self.type_bot == "general" else None,
            ),
            ChatMessage(
                role=MessageRole.ASSISTANT,
                content=response,
                metadata=metadata_collection,
                timestamp=time_now,
                payment="free" if self.type_bot == "general" else None,
            ),
        ]

        chat_history_json = [message.model_dump() for message in chat_history_db]

        db = self.client["bot_database"]  # Replace with your database name
        collection = db[self.session_id]  # Replace with your collection name
        collection.insert_many(chat_history_json)