Litellm dev 01 06 2025 p1 (#7594)

* fix(custom_logger.py): expose new 'async_get_chat_completion_prompt' event hook

* fix(custom_logger.py): langfuse_prompt_management.py

remove 'headers' from custom logger 'async_get_chat_completion_prompt' and 'get_chat_completion_prompt' event hooks

* feat(router.py): expose new function for prompt management based routing

* feat(router.py): partial working router prompt factory logic

allows load balanced model to be used for model name w/ langfuse prompt management call

* feat(router.py): fix prompt management with load balanced model group

* feat(langfuse_prompt_management.py): support reading in openai params from langfuse

enables user to define optional params on langfuse vs. client code

* test(test_Router.py): add unit test for router based langfuse prompt management

* fix: fix linting errors

litellm/integrations/custom_logger.py

@@ -63,12 +63,28 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
 
     #### PROMPT MANAGEMENT HOOKS ####
 
+    async def async_get_chat_completion_prompt(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        non_default_params: dict,
+        prompt_id: str,
+        prompt_variables: Optional[dict],
+        dynamic_callback_params: StandardCallbackDynamicParams,
+    ) -> Tuple[str, List[AllMessageValues], dict]:
+        """
+        Returns:
+        - model: str - the model to use (can be pulled from prompt management tool)
+        - messages: List[AllMessageValues] - the messages to use (can be pulled from prompt management tool)
+        - non_default_params: dict - update with any optional params (e.g. temperature, max_tokens, etc.) to use (can be pulled from prompt management tool)
+        """
+        return model, messages, non_default_params
+
     def get_chat_completion_prompt(
         self,
         model: str,
         messages: List[AllMessageValues],
         non_default_params: dict,
-        headers: dict,
         prompt_id: str,
         prompt_variables: Optional[dict],
         dynamic_callback_params: StandardCallbackDynamicParams,