from typing import Dict, List, Literal, Optional, Union
from litellm._logging import verbose_logger
from litellm.integrations.custom_logger import CustomLogger
from litellm.types.guardrails import DynamicGuardrailParams, GuardrailEventHooks
from litellm.types.utils import StandardLoggingGuardrailInformation
class CustomGuardrail(CustomLogger):
def __init__(
self,
guardrail_name: Optional[str] = None,
supported_event_hooks: Optional[List[GuardrailEventHooks]] = None,
event_hook: Optional[
Union[GuardrailEventHooks, List[GuardrailEventHooks]]
] = None,
default_on: bool = False,
**kwargs,
):
"""
Initialize the CustomGuardrail class
Args:
guardrail_name: The name of the guardrail. This is the name used in your requests.
supported_event_hooks: The event hooks that the guardrail supports
event_hook: The event hook to run the guardrail on
default_on: If True, the guardrail will be run by default on all requests
"""
self.guardrail_name = guardrail_name
self.supported_event_hooks = supported_event_hooks
self.event_hook: Optional[
Union[GuardrailEventHooks, List[GuardrailEventHooks]]
] = event_hook
self.default_on: bool = default_on
if supported_event_hooks:
## validate event_hook is in supported_event_hooks
self._validate_event_hook(event_hook, supported_event_hooks)
super().__init__(**kwargs)
def _validate_event_hook(
self,
event_hook: Optional[Union[GuardrailEventHooks, List[GuardrailEventHooks]]],
supported_event_hooks: List[GuardrailEventHooks],
) -> None:
if event_hook is None:
return
if isinstance(event_hook, list):
for hook in event_hook:
if hook not in supported_event_hooks:
raise ValueError(
f"Event hook {hook} is not in the supported event hooks {supported_event_hooks}"
)
elif isinstance(event_hook, GuardrailEventHooks):
if event_hook not in supported_event_hooks:
raise ValueError(
f"Event hook {event_hook} is not in the supported event hooks {supported_event_hooks}"
)
def get_guardrail_from_metadata(
self, data: dict
) -> Union[List[str], List[Dict[str, DynamicGuardrailParams]]]:
"""
Returns the guardrail(s) to be run from the metadata
"""
metadata = data.get("metadata") or {}
requested_guardrails = metadata.get("guardrails") or []
return requested_guardrails
def _guardrail_is_in_requested_guardrails(
self,
requested_guardrails: Union[List[str], List[Dict[str, DynamicGuardrailParams]]],
) -> bool:
for _guardrail in requested_guardrails:
if isinstance(_guardrail, dict):
if self.guardrail_name in _guardrail:
return True
elif isinstance(_guardrail, str):
if self.guardrail_name == _guardrail:
return True
return False
def should_run_guardrail(self, data, event_type: GuardrailEventHooks) -> bool:
"""
Returns True if the guardrail should be run on the event_type
"""
requested_guardrails = self.get_guardrail_from_metadata(data)
verbose_logger.debug(
"inside should_run_guardrail for guardrail=%s event_type= %s guardrail_supported_event_hooks= %s requested_guardrails= %s self.default_on= %s",
self.guardrail_name,
event_type,
self.event_hook,
requested_guardrails,
self.default_on,
)
if self.default_on is True:
if self._event_hook_is_event_type(event_type):
return True
return False
if (
self.event_hook
and not self._guardrail_is_in_requested_guardrails(requested_guardrails)
and event_type.value != "logging_only"
):
return False
if not self._event_hook_is_event_type(event_type):
return False
return True
def _event_hook_is_event_type(self, event_type: GuardrailEventHooks) -> bool:
"""
Returns True if the event_hook is the same as the event_type
eg. if `self.event_hook == "pre_call" and event_type == "pre_call"` -> then True
eg. if `self.event_hook == "pre_call" and event_type == "post_call"` -> then False
"""
if self.event_hook is None:
return True
if isinstance(self.event_hook, list):
return event_type.value in self.event_hook
return self.event_hook == event_type.value
def get_guardrail_dynamic_request_body_params(self, request_data: dict) -> dict:
"""
Returns `extra_body` to be added to the request body for the Guardrail API call
Use this to pass dynamic params to the guardrail API call - eg. success_threshold, failure_threshold, etc.
```
[{"lakera_guard": {"extra_body": {"foo": "bar"}}}]
```
Will return: for guardrail=`lakera-guard`:
{
"foo": "bar"
}
Args:
request_data: The original `request_data` passed to LiteLLM Proxy
"""
requested_guardrails = self.get_guardrail_from_metadata(request_data)
# Look for the guardrail configuration matching self.guardrail_name
for guardrail in requested_guardrails:
if isinstance(guardrail, dict) and self.guardrail_name in guardrail:
# Get the configuration for this guardrail
guardrail_config: DynamicGuardrailParams = DynamicGuardrailParams(
**guardrail[self.guardrail_name]
)
if self._validate_premium_user() is not True:
return {}
# Return the extra_body if it exists, otherwise empty dict
return guardrail_config.get("extra_body", {})
return {}
def _validate_premium_user(self) -> bool:
"""
Returns True if the user is a premium user
"""
from litellm.proxy.proxy_server import CommonProxyErrors, premium_user
if premium_user is not True:
verbose_logger.warning(
f"Trying to use premium guardrail without premium user {CommonProxyErrors.not_premium_user.value}"
)
return False
return True
def add_standard_logging_guardrail_information_to_request_data(
self,
guardrail_json_response: Union[Exception, str, dict],
request_data: dict,
guardrail_status: Literal["success", "failure"],
) -> None:
"""
Builds `StandardLoggingGuardrailInformation` and adds it to the request metadata so it can be used for logging to DataDog, Langfuse, etc.
"""
from litellm.proxy.proxy_server import premium_user
if premium_user is not True:
verbose_logger.warning(
f"Guardrail Tracing is only available for premium users. Skipping guardrail logging for guardrail={self.guardrail_name} event_hook={self.event_hook}"
)
return
if isinstance(guardrail_json_response, Exception):
guardrail_json_response = str(guardrail_json_response)
slg = StandardLoggingGuardrailInformation(
guardrail_name=self.guardrail_name,
guardrail_mode=self.event_hook,
guardrail_response=guardrail_json_response,
guardrail_status=guardrail_status,
)
if "metadata" in request_data:
request_data["metadata"]["standard_logging_guardrail_information"] = slg
elif "litellm_metadata" in request_data:
request_data["litellm_metadata"][
"standard_logging_guardrail_information"
] = slg
else:
verbose_logger.warning(
"unable to log guardrail information. No metadata found in request_data"
)
def log_guardrail_information(func):
"""
Decorator to add standard logging guardrail information to any function
Add this decorator to ensure your guardrail response is logged to DataDog, OTEL, s3, GCS etc.
Logs for:
- pre_call
- during_call
- TODO: log post_call. This is more involved since the logs are sent to DD, s3 before the guardrail is even run
"""
import asyncio
import functools
def process_response(self, response, request_data):
self.add_standard_logging_guardrail_information_to_request_data(
guardrail_json_response=response,
request_data=request_data,
guardrail_status="success",
)
return response
def process_error(self, e, request_data):
self.add_standard_logging_guardrail_information_to_request_data(
guardrail_json_response=e,
request_data=request_data,
guardrail_status="failure",
)
raise e
@functools.wraps(func)
async def async_wrapper(*args, **kwargs):
self: CustomGuardrail = args[0]
request_data: Optional[dict] = (
kwargs.get("data") or kwargs.get("request_data") or {}
)
try:
response = await func(*args, **kwargs)
return process_response(self, response, request_data)
except Exception as e:
return process_error(self, e, request_data)
@functools.wraps(func)
def sync_wrapper(*args, **kwargs):
self: CustomGuardrail = args[0]
request_data: Optional[dict] = (
kwargs.get("data") or kwargs.get("request_data") or {}
)
try:
response = func(*args, **kwargs)
return process_response(self, response, request_data)
except Exception as e:
return process_error(self, e, request_data)
@functools.wraps(func)
def wrapper(*args, **kwargs):
if asyncio.iscoroutinefunction(func):
return async_wrapper(*args, **kwargs)
return sync_wrapper(*args, **kwargs)
return wrapper
