llm.py 1.9 KB

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  1. # coding=utf-8
  2. """
  3. @project: maxkb
  4. @Author:虎
  5. @file: llm.py
  6. @date:2024/4/18 15:28
  7. @desc:
  8. """
  9. from typing import List, Dict
  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 OpenAIChatModel(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. streaming = model_kwargs.get('streaming', True)
  25. if 'o1' in model_name:
  26. streaming = False
  27. chat_open_ai = OpenAIChatModel(
  28. model=model_name,
  29. openai_api_base=model_credential.get('api_base'),
  30. openai_api_key=model_credential.get('api_key'),
  31. streaming=streaming,
  32. custom_get_token_ids=custom_get_token_ids,
  33. **optional_params,
  34. )
  35. return chat_open_ai
  36. def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
  37. try:
  38. return super().get_num_tokens_from_messages(messages)
  39. except Exception as e:
  40. tokenizer = TokenizerManage.get_tokenizer()
  41. return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])
  42. def get_num_tokens(self, text: str) -> int:
  43. try:
  44. return super().get_num_tokens(text)
  45. except Exception as e:
  46. tokenizer = TokenizerManage.get_tokenizer()
  47. return len(tokenizer.encode(text))