# coding=utf-8
"""
    @project: maxkb
    @Author：虎
    @file： llm.py
    @date：2024/4/28 11:42
    @desc:
"""

from typing import Dict, List

from langchain_core.messages import BaseMessage, get_buffer_string

from common.config.tokenizer_manage_config import TokenizerManage
from models_provider.base_model_provider import MaxKBBaseModel
from models_provider.impl.base_chat_open_ai import BaseChatOpenAI


def custom_get_token_ids(text: str):
    tokenizer = TokenizerManage.get_tokenizer()
    return tokenizer.encode(text)


class ZhipuChatModel(MaxKBBaseModel, BaseChatOpenAI):

    @staticmethod
    def is_cache_model():
        return False

    @staticmethod
    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
        optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs)
        zhipuai_chat = ZhipuChatModel(
            api_key=model_credential.get('api_key'),
            model=model_name,
            base_url=model_credential.get('api_base') or 'https://open.bigmodel.cn/api/paas/v4',
            streaming=model_kwargs.get('streaming', False),
            custom_get_token_ids=custom_get_token_ids,
            **optional_params,
        )
        return zhipuai_chat

    def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
        try:
            return super().get_num_tokens_from_messages(messages)
        except Exception as e:
            tokenizer = TokenizerManage.get_tokenizer()
            return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])

    def get_num_tokens(self, text: str) -> int:
        try:
            return super().get_num_tokens(text)
        except Exception as e:
            tokenizer = TokenizerManage.get_tokenizer()
            return len(tokenizer.encode(text))