llm.py 1.8 KB

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  1. # coding=utf-8
  2. """
  3. @project: maxkb
  4. @Author:虎
  5. @file: llm.py
  6. @date:2024/4/28 11:42
  7. @desc:
  8. """
  9. from typing import Dict, List
  10. from langchain_core.messages import BaseMessage, get_buffer_string
  11. from common.config.tokenizer_manage_config import TokenizerManage
  12. from models_provider.base_model_provider import MaxKBBaseModel
  13. from models_provider.impl.base_chat_open_ai import BaseChatOpenAI
  14. def custom_get_token_ids(text: str):
  15. tokenizer = TokenizerManage.get_tokenizer()
  16. return tokenizer.encode(text)
  17. class ZhipuChatModel(MaxKBBaseModel, BaseChatOpenAI):
  18. @staticmethod
  19. def is_cache_model():
  20. return False
  21. @staticmethod
  22. def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
  23. optional_params = MaxKBBaseModel.filter_optional_params(model_kwargs)
  24. zhipuai_chat = ZhipuChatModel(
  25. api_key=model_credential.get('api_key'),
  26. model=model_name,
  27. base_url=model_credential.get('api_base') or 'https://open.bigmodel.cn/api/paas/v4',
  28. streaming=model_kwargs.get('streaming', False),
  29. custom_get_token_ids=custom_get_token_ids,
  30. **optional_params,
  31. )
  32. return zhipuai_chat
  33. def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
  34. try:
  35. return super().get_num_tokens_from_messages(messages)
  36. except Exception as e:
  37. tokenizer = TokenizerManage.get_tokenizer()
  38. return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])
  39. def get_num_tokens(self, text: str) -> int:
  40. try:
  41. return super().get_num_tokens(text)
  42. except Exception as e:
  43. tokenizer = TokenizerManage.get_tokenizer()
  44. return len(tokenizer.encode(text))