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"""
Call Hook for LiteLLM Proxy which allows Langfuse prompt management.
"""
import os
from functools import lru_cache
from typing import TYPE_CHECKING, Any, List, Literal, Optional, Tuple, Union, cast
from packaging.version import Version
from typing_extensions import TypeAlias
from litellm.integrations.custom_logger import CustomLogger
from litellm.integrations.prompt_management_base import PromptManagementClient
from litellm.litellm_core_utils.asyncify import run_async_function
from litellm.types.llms.openai import AllMessageValues, ChatCompletionSystemMessage
from litellm.types.utils import StandardCallbackDynamicParams, StandardLoggingPayload
from ...litellm_core_utils.specialty_caches.dynamic_logging_cache import (
DynamicLoggingCache,
)
from ..prompt_management_base import PromptManagementBase
from .langfuse import LangFuseLogger
from .langfuse_handler import LangFuseHandler
if TYPE_CHECKING:
from langfuse import Langfuse
from langfuse.client import ChatPromptClient, TextPromptClient
LangfuseClass: TypeAlias = Langfuse
PROMPT_CLIENT = Union[TextPromptClient, ChatPromptClient]
else:
PROMPT_CLIENT = Any
LangfuseClass = Any
in_memory_dynamic_logger_cache = DynamicLoggingCache()
@lru_cache(maxsize=10)
def langfuse_client_init(
langfuse_public_key=None,
langfuse_secret=None,
langfuse_secret_key=None,
langfuse_host=None,
flush_interval=1,
) -> LangfuseClass:
"""
Initialize Langfuse client with caching to prevent multiple initializations.
Args:
langfuse_public_key (str, optional): Public key for Langfuse. Defaults to None.
langfuse_secret (str, optional): Secret key for Langfuse. Defaults to None.
langfuse_host (str, optional): Host URL for Langfuse. Defaults to None.
flush_interval (int, optional): Flush interval in seconds. Defaults to 1.
Returns:
Langfuse: Initialized Langfuse client instance
Raises:
Exception: If langfuse package is not installed
"""
try:
import langfuse
from langfuse import Langfuse
except Exception as e:
raise Exception(
f"\033[91mLangfuse not installed, try running 'pip install langfuse' to fix this error: {e}\n\033[0m"
)
# Instance variables
secret_key = (
langfuse_secret or langfuse_secret_key or os.getenv("LANGFUSE_SECRET_KEY")
)
public_key = langfuse_public_key or os.getenv("LANGFUSE_PUBLIC_KEY")
langfuse_host = langfuse_host or os.getenv(
"LANGFUSE_HOST", "https://cloud.langfuse.com"
)
if not (
langfuse_host.startswith("http://") or langfuse_host.startswith("https://")
):
# add http:// if unset, assume communicating over private network - e.g. render
langfuse_host = "http://" + langfuse_host
langfuse_release = os.getenv("LANGFUSE_RELEASE")
langfuse_debug = os.getenv("LANGFUSE_DEBUG")
parameters = {
"public_key": public_key,
"secret_key": secret_key,
"host": langfuse_host,
"release": langfuse_release,
"debug": langfuse_debug,
"flush_interval": LangFuseLogger._get_langfuse_flush_interval(
flush_interval
), # flush interval in seconds
}
if Version(langfuse.version.__version__) >= Version("2.6.0"):
parameters["sdk_integration"] = "litellm"
client = Langfuse(**parameters)
return client
class LangfusePromptManagement(LangFuseLogger, PromptManagementBase, CustomLogger):
def __init__(
self,
langfuse_public_key=None,
langfuse_secret=None,
langfuse_host=None,
flush_interval=1,
):
import langfuse
self.langfuse_sdk_version = langfuse.version.__version__
self.Langfuse = langfuse_client_init(
langfuse_public_key=langfuse_public_key,
langfuse_secret=langfuse_secret,
langfuse_host=langfuse_host,
flush_interval=flush_interval,
)
@property
def integration_name(self):
return "langfuse"
def _get_prompt_from_id(
self, langfuse_prompt_id: str, langfuse_client: LangfuseClass
) -> PROMPT_CLIENT:
return langfuse_client.get_prompt(langfuse_prompt_id)
def _compile_prompt(
self,
langfuse_prompt_client: PROMPT_CLIENT,
langfuse_prompt_variables: Optional[dict],
call_type: Union[Literal["completion"], Literal["text_completion"]],
) -> List[AllMessageValues]:
compiled_prompt: Optional[Union[str, list]] = None
if langfuse_prompt_variables is None:
langfuse_prompt_variables = {}
compiled_prompt = langfuse_prompt_client.compile(**langfuse_prompt_variables)
if isinstance(compiled_prompt, str):
compiled_prompt = [
ChatCompletionSystemMessage(role="system", content=compiled_prompt)
]
else:
compiled_prompt = cast(List[AllMessageValues], compiled_prompt)
return compiled_prompt
def _get_optional_params_from_langfuse(
self, langfuse_prompt_client: PROMPT_CLIENT
) -> dict:
config = langfuse_prompt_client.config
optional_params = {}
for k, v in config.items():
if k != "model":
optional_params[k] = v
return optional_params
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,
]:
return self.get_chat_completion_prompt(
model,
messages,
non_default_params,
prompt_id,
prompt_variables,
dynamic_callback_params,
)
def should_run_prompt_management(
self,
prompt_id: str,
dynamic_callback_params: StandardCallbackDynamicParams,
) -> bool:
langfuse_client = langfuse_client_init(
langfuse_public_key=dynamic_callback_params.get("langfuse_public_key"),
langfuse_secret=dynamic_callback_params.get("langfuse_secret"),
langfuse_secret_key=dynamic_callback_params.get("langfuse_secret_key"),
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
)
return langfuse_prompt_client is not None
def _compile_prompt_helper(
self,
prompt_id: str,
prompt_variables: Optional[dict],
dynamic_callback_params: StandardCallbackDynamicParams,
) -> PromptManagementClient:
langfuse_client = langfuse_client_init(
langfuse_public_key=dynamic_callback_params.get("langfuse_public_key"),
langfuse_secret=dynamic_callback_params.get("langfuse_secret"),
langfuse_secret_key=dynamic_callback_params.get("langfuse_secret_key"),
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
)
## SET PROMPT
compiled_prompt = self._compile_prompt(
langfuse_prompt_client=langfuse_prompt_client,
langfuse_prompt_variables=prompt_variables,
call_type="completion",
)
template_model = langfuse_prompt_client.config.get("model")
template_optional_params = self._get_optional_params_from_langfuse(
langfuse_prompt_client
)
return PromptManagementClient(
prompt_id=prompt_id,
prompt_template=compiled_prompt,
prompt_template_model=template_model,
prompt_template_optional_params=template_optional_params,
completed_messages=None,
)
def log_success_event(self, kwargs, response_obj, start_time, end_time):
return run_async_function(
self.async_log_success_event, kwargs, response_obj, start_time, end_time
)
async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
standard_callback_dynamic_params = kwargs.get(
"standard_callback_dynamic_params"
)
langfuse_logger_to_use = LangFuseHandler.get_langfuse_logger_for_request(
globalLangfuseLogger=self,
standard_callback_dynamic_params=standard_callback_dynamic_params,
in_memory_dynamic_logger_cache=in_memory_dynamic_logger_cache,
)
langfuse_logger_to_use.log_event_on_langfuse(
kwargs=kwargs,
response_obj=response_obj,
start_time=start_time,
end_time=end_time,
user_id=kwargs.get("user", None),
)
async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time):
standard_callback_dynamic_params = kwargs.get(
"standard_callback_dynamic_params"
)
langfuse_logger_to_use = LangFuseHandler.get_langfuse_logger_for_request(
globalLangfuseLogger=self,
standard_callback_dynamic_params=standard_callback_dynamic_params,
in_memory_dynamic_logger_cache=in_memory_dynamic_logger_cache,
)
standard_logging_object = cast(
Optional[StandardLoggingPayload],
kwargs.get("standard_logging_object", None),
)
if standard_logging_object is None:
return
langfuse_logger_to_use.log_event_on_langfuse(
start_time=start_time,
end_time=end_time,
response_obj=None,
user_id=kwargs.get("user", None),
status_message=standard_logging_object["error_str"],
level="ERROR",
kwargs=kwargs,
)
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