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- # coding=utf-8
- """
- @project: maxkb
- @Author:虎
- @file: llm.py
- @date:2024/4/18 15:28
- @desc:
- """
- from typing import List, Dict
- 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 DockerAIChatModel(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)
- streaming = model_kwargs.get('streaming', True)
- if 'o1' in model_name:
- streaming = False
- chat_open_ai = DockerAIChatModel(
- model=model_name,
- openai_api_base=model_credential.get('api_base'),
- openai_api_key=model_credential.get('api_key'),
- streaming=streaming,
- custom_get_token_ids=custom_get_token_ids,
- **optional_params,
- )
- return chat_open_ai
- 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))
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