Revert "Support passing prompt_label to langfuse (#11018)"

This reverts commit 2b50b43.

Author: ishaan-jaff

litellm/integrations/anthropic_cache_control_hook.py

@@ -28,7 +28,6 @@ def get_chat_completion_prompt(
  prompt_id: Optional[str],
  prompt_variables: Optional[dict],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
  ) -> Tuple[str, List[AllMessageValues], dict]:
  """
  Apply cache control directives based on specified injection points.
@@ -80,10 +79,10 @@ def _process_message_injection(
  # Case 1: Target by specific index
  if targetted_index is not None:
  if 0 <= targetted_index < len(messages):
- messages[
- targetted_index
- ] = AnthropicCacheControlHook._safe_insert_cache_control_in_message(
- messages[targetted_index], control
+ messages[targetted_index] = (
+ AnthropicCacheControlHook._safe_insert_cache_control_in_message(
+  messages[targetted_index], control
+ )
  )
  # Case 2: Target by role
  elif targetted_role is not None:

litellm/integrations/custom_logger.py

@@ -87,7 +87,6 @@ async def async_get_chat_completion_prompt(
  dynamic_callback_params: StandardCallbackDynamicParams,
  litellm_logging_obj: LiteLLMLoggingObj,
  tools: Optional[List[Dict]] = None,
- prompt_label: Optional[str] = None,
  ) -> Tuple[str, List[AllMessageValues], dict]:
  """
  Returns:
@@ -105,7 +104,6 @@ def get_chat_completion_prompt(
  prompt_id: Optional[str],
  prompt_variables: Optional[dict],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
  ) -> Tuple[str, List[AllMessageValues], dict]:
  """
  Returns:

litellm/integrations/custom_prompt_management.py

@@ -18,7 +18,6 @@ def get_chat_completion_prompt(
  prompt_id: Optional[str],
  prompt_variables: Optional[dict],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
  ) -> Tuple[str, List[AllMessageValues], dict]:
  """
  Returns:
@@ -44,7 +43,6 @@ def _compile_prompt_helper(
  prompt_id: str,
  prompt_variables: Optional[dict],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
  ) -> PromptManagementClient:
  raise NotImplementedError(
  "Custom prompt management does not support compile prompt helper"

litellm/integrations/humanloop.py

@@ -155,8 +155,11 @@ def get_chat_completion_prompt(
  prompt_id: Optional[str],
  prompt_variables: Optional[dict],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
- ) -> Tuple[str, List[AllMessageValues], dict,]:
+ ) -> Tuple[
+ str,
+ List[AllMessageValues],
+ dict,
+ ]:
  humanloop_api_key = dynamic_callback_params.get(
  "humanloop_api_key"
  ) or get_secret_str("HUMANLOOP_API_KEY")

litellm/integrations/langfuse/langfuse_prompt_management.py

@@ -130,12 +130,9 @@ def integration_name(self):
  return "langfuse"
 
  def _get_prompt_from_id(
- self,
- langfuse_prompt_id: str,
- langfuse_client: LangfuseClass,
- prompt_label: Optional[str] = None,
+ self, langfuse_prompt_id: str, langfuse_client: LangfuseClass
  ) -> PROMPT_CLIENT:
- return langfuse_client.get_prompt(langfuse_prompt_id, label=prompt_label)
+ return langfuse_client.get_prompt(langfuse_prompt_id)
 
  def _compile_prompt(
  self,
@@ -179,16 +176,18 @@ async def async_get_chat_completion_prompt(
  dynamic_callback_params: StandardCallbackDynamicParams,
  litellm_logging_obj: LiteLLMLoggingObj,
  tools: Optional[List[Dict]] = None,
- prompt_label: Optional[str] = None,
- ) -> Tuple[str, List[AllMessageValues], dict,]:
+ ) -> Tuple[
+ str,
+ List[AllMessageValues],
+ dict,
+ ]:
  return self.get_chat_completion_prompt(
  model,
  messages,
  non_default_params,
  prompt_id,
  prompt_variables,
  dynamic_callback_params,
- prompt_label=prompt_label,
  )
 
  def should_run_prompt_management(
@@ -212,7 +211,6 @@ def _compile_prompt_helper(
  prompt_id: str,
  prompt_variables: Optional[dict],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
  ) -> PromptManagementClient:
  langfuse_client = langfuse_client_init(
  langfuse_public_key=dynamic_callback_params.get("langfuse_public_key"),
@@ -221,9 +219,7 @@ def _compile_prompt_helper(
  langfuse_host=dynamic_callback_params.get("langfuse_host"),
  )
  langfuse_prompt_client = self._get_prompt_from_id(
- langfuse_prompt_id=prompt_id,
- langfuse_client=langfuse_client,
- prompt_label=prompt_label,
+ langfuse_prompt_id=prompt_id, langfuse_client=langfuse_client
  )
 
  ## SET PROMPT

litellm/integrations/prompt_management_base.py

@@ -33,7 +33,6 @@ def _compile_prompt_helper(
  prompt_id: str,
  prompt_variables: Optional[dict],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
  ) -> PromptManagementClient:
  pass
 
@@ -50,13 +49,11 @@ def compile_prompt(
  prompt_variables: Optional[dict],
  client_messages: List[AllMessageValues],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
  ) -> PromptManagementClient:
  compiled_prompt_client = self._compile_prompt_helper(
  prompt_id=prompt_id,
  prompt_variables=prompt_variables,
  dynamic_callback_params=dynamic_callback_params,
- prompt_label=prompt_label,
  )
 
  try:
@@ -85,7 +82,6 @@ def get_chat_completion_prompt(
  prompt_id: Optional[str],
  prompt_variables: Optional[dict],
  dynamic_callback_params: StandardCallbackDynamicParams,
- prompt_label: Optional[str] = None,
  ) -> Tuple[str, List[AllMessageValues], dict]:
  if prompt_id is None:
  raise ValueError("prompt_id is required for Prompt Management Base class")
@@ -99,7 +95,6 @@ def get_chat_completion_prompt(
  prompt_variables=prompt_variables,
  client_messages=messages,
  dynamic_callback_params=dynamic_callback_params,
- prompt_label=prompt_label,
  )
 
  completed_messages = prompt_template["completed_messages"] or messages

litellm/integrations/vector_stores/bedrock_vector_store.py

@@ -75,7 +75,6 @@ async def async_get_chat_completion_prompt(
  dynamic_callback_params: StandardCallbackDynamicParams,
  litellm_logging_obj: LiteLLMLoggingObj,
  tools: Optional[List[Dict]] = None,
- prompt_label: Optional[str] = None,
  ) -> Tuple[str, List[AllMessageValues], dict]:
  """
  Retrieves the context from the Bedrock Knowledge Base and appends it to the messages.
@@ -100,11 +99,10 @@ async def async_get_chat_completion_prompt(
  f"Bedrock Knowledge Base Response: {bedrock_kb_response}"
  )
 
- (
- context_message,
- context_string,
- ) = self.get_chat_completion_message_from_bedrock_kb_response(
- bedrock_kb_response
+ context_message, context_string = (
+ self.get_chat_completion_message_from_bedrock_kb_response(
+ bedrock_kb_response
+ )
  )
  if context_message is not None:
  messages.append(context_message)
@@ -128,9 +126,9 @@ async def async_get_chat_completion_prompt(
  )
  )
 
- litellm_logging_obj.model_call_details[
- "vector_store_request_metadata"
- ] = vector_store_request_metadata
+ litellm_logging_obj.model_call_details["vector_store_request_metadata"] = (
+ vector_store_request_metadata
+ )
 
  return model, messages, non_default_params
 
@@ -142,9 +140,9 @@ def transform_bedrock_kb_response_to_vector_store_search_response(
  """
  Transform a BedrockKBResponse to a VectorStoreSearchResponse
  """
- retrieval_results: Optional[
- List[BedrockKBRetrievalResult]
- ] = bedrock_kb_response.get("retrievalResults", None)
+ retrieval_results: Optional[List[BedrockKBRetrievalResult]] = (
+ bedrock_kb_response.get("retrievalResults", None)
+ )
  vector_store_search_response: VectorStoreSearchResponse = (
  VectorStoreSearchResponse(search_query=query, data=[])
  )

litellm/litellm_core_utils/litellm_logging.py

@@ -539,7 +539,6 @@ def get_chat_completion_prompt(
  prompt_id: Optional[str],
  prompt_variables: Optional[dict],
  prompt_management_logger: Optional[CustomLogger] = None,
- prompt_label: Optional[str] = None,
  ) -> Tuple[str, List[AllMessageValues], dict]:
  custom_logger = (
  prompt_management_logger
@@ -560,7 +559,6 @@ def get_chat_completion_prompt(
  prompt_id=prompt_id,
  prompt_variables=prompt_variables,
  dynamic_callback_params=self.standard_callback_dynamic_params,
- prompt_label=prompt_label,
  )
  self.messages = messages
  return model, messages, non_default_params
@@ -574,7 +572,6 @@ async def async_get_chat_completion_prompt(
  prompt_variables: Optional[dict],
  prompt_management_logger: Optional[CustomLogger] = None,
  tools: Optional[List[Dict]] = None,
- prompt_label: Optional[str] = None,
  ) -> Tuple[str, List[AllMessageValues], dict]:
  custom_logger = (
  prompt_management_logger
@@ -597,7 +594,6 @@ async def async_get_chat_completion_prompt(
  dynamic_callback_params=self.standard_callback_dynamic_params,
  litellm_logging_obj=self,
  tools=tools,
- prompt_label=prompt_label,
  )
  self.messages = messages
  return model, messages, non_default_params

litellm/main.py

@@ -97,7 +97,6 @@
  get_optional_params_image_gen,
  get_optional_params_transcription,
  get_secret,
- get_standard_openai_params,
  mock_completion_streaming_obj,
  read_config_args,
  supports_httpx_timeout,
@@ -429,7 +428,6 @@ async def acompletion(
  prompt_id=kwargs.get("prompt_id", None),
  prompt_variables=kwargs.get("prompt_variables", None),
  tools=tools,
- prompt_label=kwargs.get("prompt_label", None),
  )
 
  #########################################################
@@ -985,7 +983,6 @@ def completion( # type: ignore # noqa: PLR0915
  assistant_continue_message=assistant_continue_message,
  )
  ######## end of unpacking kwargs ###########
- standard_openai_params = get_standard_openai_params(params=args)
  non_default_params = get_non_default_completion_params(kwargs=kwargs)
  litellm_params = {} # used to prevent unbound var errors
  ## PROMPT MANAGEMENT HOOKS ##
@@ -1004,7 +1001,6 @@ def completion( # type: ignore # noqa: PLR0915
  non_default_params=non_default_params,
  prompt_id=prompt_id,
  prompt_variables=prompt_variables,
- prompt_label=kwargs.get("prompt_label", None),
  )
 
  try:
@@ -1238,13 +1234,10 @@ def completion( # type: ignore # noqa: PLR0915
  max_retries=max_retries,
  timeout=timeout,
  )
- cast(LiteLLMLoggingObj, logging).update_environment_variables(
+ logging.update_environment_variables(
  model=model,
  user=user,
- optional_params={
- **standard_openai_params,
- **non_default_params,
- }, # [IMPORTANT] - using standard_openai_params ensures consistent params logged to langfuse for finetuning / eval datasets.
+ optional_params=optional_params,
  litellm_params=litellm_params,
  custom_llm_provider=custom_llm_provider,
  )

litellm/proxy/_new_secret_config.yaml

@@ -1,8 +1,8 @@
 model_list:
- - model_name: "gemini-2.0-flash-gemini"
+ - model_name: "gemini-2.0-flash"
  litellm_params:
- model: gemini/gemini-2.0-flash
- - model_name: "gpt-4o-mini-openai"
+ model: gemini/gemini-2.0-flash-live-001
+ - model_name: "gpt-4.1-openai"
  litellm_params:
  model: gpt-4.1-mini-2025-04-14
  api_key: os.environ/OPENAI_API_KEY
@@ -71,16 +71,6 @@ model_list:
  model: mistral/*
  api_key: os.environ/MISTRAL_API_KEY
  access_groups: ["beta-models"]
- - model_name: my-langfuse-model
- litellm_params:
- model: langfuse/gpt-3.5-turbo
- prompt_id: "jokes"
- prompt_label: "latest"
- api_key: os.environ/OPENAI_API_KEY
 
 litellm_settings:
- callbacks: ["langfuse"]
-
-general_settings:
- store_model_in_db: true
- store_prompts_in_spend_logs: true
+ cache: true