Coverage for .venv/lib/python3.13/site-packages/litellm/proxy/custom_prompt_management.py: 0%

1from typing import Final 

2 

3from litellm._logging import verbose_logger 

4from litellm.integrations.custom_prompt_management import CustomPromptManagement 

5from litellm.types.llms.openai import AllMessageValues 

6from litellm.types.prompts.init_prompts import PromptSpec 

7from litellm.types.utils import StandardCallbackDynamicParams 

8 

9 

10class X42PromptManagement(CustomPromptManagement): 

11 def get_chat_completion_prompt( 

12 self, 

13 model: str, 

14 messages: list[AllMessageValues], 

15 non_default_params: dict, 

16 prompt_id: str | None, 

17 prompt_variables: dict | None, 

18 dynamic_callback_params: StandardCallbackDynamicParams, 

19 prompt_spec: PromptSpec | None = None, 

20 prompt_label: str | None = None, 

21 prompt_version: int | None = None, 

22 ignore_prompt_manager_model: bool | None = False, 

23 ignore_prompt_manager_optional_params: bool | None = False, 

24 ) -> tuple[str, list[AllMessageValues], dict]: 

25 """ 

26 Returns: 

27 - model: str - the model to use (can be pulled from prompt management tool) 

28 - messages: List[AllMessageValues] - the messages to use (can be pulled from prompt management tool) 

29 - non_default_params: dict - update with any optional params (e.g. temperature, max_tokens, etc.) to use (can be pulled from prompt management tool) 

30 """ 

31 verbose_logger.debug( 

32 "in async get chat completion prompt. Prompt ID: %s, Prompt Variables: %s, Dynamic Callback Params: %s", 

33 prompt_id, 

34 prompt_variables, 

35 dynamic_callback_params, 

36 ) 

37 

38 return model, messages, non_default_params 

39 

40 @property 

41 def integration_name(self) -> str: 

42 return "x42-prompt-management" 

43 

44 

45x42_prompt_management: Final = X42PromptManagement()