import datetime
import json
import os

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer


class AiBase:
    model_id_or_path: str = None
    model = None
    tokenizer = None

    def __init__(self, model_id_or_path: str = None):
        self.model_id_or_path = model_id_or_path

    def ensure_loaded(self):
        if self.model is not None:
            return

        print('Loading ' + self.model_id_or_path)
        self.model = AutoModelForCausalLM.from_pretrained(self.model_id_or_path, torch_dtype='auto', device_map='auto')
        self.tokenizer = AutoTokenizer.from_pretrained(self.model_id_or_path)
        # print(self.tokenizer.default_chat_template)
        # print(type(self.model))
        # print(type(self.tokenizer))
        print('Loaded')

    def ensure_unload(self):
        if self.model is None:
            del self

    def generate(self, messages):
        return []

    def record_conversation(self, messages, response):
        messages = messages + [response]

        this_dir = os.path.dirname(os.path.abspath(__file__))
        conversations_folder = this_dir + '/../../../conversations'
        folder = conversations_folder + '/' + self.model_id_or_path.replace('/', '_')
        self._mkdir(conversations_folder)
        self._mkdir(folder)
        timestamp = datetime.datetime.utcnow().strftime('%Y%m%d%H%M%S')
        pickle_filename = folder + '/' + timestamp + '.json'
        with open(pickle_filename, 'w') as file:
            json.dump(messages, file)

    def _mkdir(self, path):
        if not os.path.isdir(path):
            os.mkdir(path)

    def __del__(self):
        try:
            raise Exception()
        except Exception as e:
            print(e)
        del self.model
        del self.tokenizer

        import gc
        gc.collect()
        torch.cuda.empty_cache()