forked from phoenix/litellm-mirror
fix linting errors on main
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parent
df4aab8be9
commit
75ca53fab5
3 changed files with 64 additions and 29 deletions
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@ -10,7 +10,7 @@ import sys, os
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sys.path.insert(
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0, os.path.abspath("../..")
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) # Adds the parent directory to the system path
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from typing import Literal
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from typing import Literal, List, Dict
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import litellm, sys
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from litellm.proxy._types import UserAPIKeyAuth
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from litellm.integrations.custom_logger import CustomLogger
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@ -18,7 +18,7 @@ from fastapi import HTTPException
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from litellm._logging import verbose_proxy_logger
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from litellm.proxy.guardrails.guardrail_helpers import should_proceed_based_on_metadata
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from litellm.types.guardrails import Role
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from litellm.types.guardrails import Role, GuardrailItem, default_roles
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from litellm._logging import verbose_proxy_logger
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from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
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@ -33,9 +33,10 @@ GUARDRAIL_NAME = "lakera_prompt_injection"
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INPUT_POSITIONING_MAP = {
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Role.SYSTEM.value: 0,
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Role.USER.value: 1,
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Role.ASSISTANT.value: 2
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Role.ASSISTANT.value: 2,
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}
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class _ENTERPRISE_lakeraAI_Moderation(CustomLogger):
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def __init__(self):
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self.async_handler = AsyncHTTPHandler(
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@ -63,41 +64,63 @@ class _ENTERPRISE_lakeraAI_Moderation(CustomLogger):
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return
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text = ""
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if "messages" in data and isinstance(data["messages"], list):
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enabled_roles = litellm.guardrail_name_config_map["prompt_injection"].enabled_roles
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lakera_input_dict = {role: None for role in INPUT_POSITIONING_MAP.keys()}
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system_message = None
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tool_call_messages = []
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enabled_roles = litellm.guardrail_name_config_map[
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"prompt_injection"
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].enabled_roles
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if enabled_roles is None:
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enabled_roles = default_roles
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lakera_input_dict: Dict = {
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role: None for role in INPUT_POSITIONING_MAP.keys()
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}
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system_message = None
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tool_call_messages: List = []
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for message in data["messages"]:
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role = message.get("role")
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if role in enabled_roles:
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if "tool_calls" in message:
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tool_call_messages = [*tool_call_messages, *message["tool_calls"]]
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if role == Role.SYSTEM.value: # we need this for later
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tool_call_messages = [
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*tool_call_messages,
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*message["tool_calls"],
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]
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if role == Role.SYSTEM.value: # we need this for later
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system_message = message
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continue
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lakera_input_dict[role] = {"role": role, "content": message.get('content')}
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lakera_input_dict[role] = {
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"role": role,
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"content": message.get("content"),
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}
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# For models where function calling is not supported, these messages by nature can't exist, as an exception would be thrown ahead of here.
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# For models where function calling is not supported, these messages by nature can't exist, as an exception would be thrown ahead of here.
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# Alternatively, a user can opt to have these messages added to the system prompt instead (ignore these, since they are in system already)
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# Finally, if the user did not elect to add them to the system message themselves, and they are there, then add them to system so they can be checked.
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# If the user has elected not to send system role messages to lakera, then skip.
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if system_message is not None:
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if not litellm.add_function_to_prompt:
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content = system_message.get("content")
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function_input = []
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function_input = []
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for tool_call in tool_call_messages:
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if "function" in tool_call:
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function_input.append(tool_call["function"]["arguments"])
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if len(function_input) > 0:
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content += " Function Input: " + ' '.join(function_input)
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lakera_input_dict[Role.SYSTEM.value] = {'role': Role.SYSTEM.value, 'content': content}
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content += " Function Input: " + " ".join(function_input)
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lakera_input_dict[Role.SYSTEM.value] = {
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"role": Role.SYSTEM.value,
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"content": content,
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}
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lakera_input = [v for k, v in sorted(lakera_input_dict.items(), key=lambda x: INPUT_POSITIONING_MAP[x[0]]) if v is not None]
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lakera_input = [
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v
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for k, v in sorted(
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lakera_input_dict.items(), key=lambda x: INPUT_POSITIONING_MAP[x[0]]
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)
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if v is not None
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]
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if len(lakera_input) == 0:
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verbose_proxy_logger.debug("Skipping lakera prompt injection, no roles with messages found")
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verbose_proxy_logger.debug(
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"Skipping lakera prompt injection, no roles with messages found"
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)
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return
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elif "input" in data and isinstance(data["input"], str):
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@ -1,14 +1,13 @@
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# This file runs a health check for the LLM, used on litellm/proxy
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import asyncio
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import logging
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import random
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from typing import Optional
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import litellm
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import logging
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from litellm._logging import print_verbose
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logger = logging.getLogger(__name__)
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@ -16,6 +15,7 @@ ILLEGAL_DISPLAY_PARAMS = ["messages", "api_key", "prompt", "input"]
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MINIMAL_DISPLAY_PARAMS = ["model"]
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def _get_random_llm_message():
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"""
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Get a random message from the LLM.
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@ -25,7 +25,7 @@ def _get_random_llm_message():
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return [{"role": "user", "content": random.choice(messages)}]
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def _clean_endpoint_data(endpoint_data: dict, details: bool):
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def _clean_endpoint_data(endpoint_data: dict, details: Optional[bool] = True):
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"""
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Clean the endpoint data for display to users.
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"""
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@ -36,7 +36,7 @@ def _clean_endpoint_data(endpoint_data: dict, details: bool):
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)
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async def _perform_health_check(model_list: list, details: bool):
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async def _perform_health_check(model_list: list, details: Optional[bool] = True):
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"""
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Perform a health check for each model in the list.
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"""
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@ -64,9 +64,13 @@ async def _perform_health_check(model_list: list, details: bool):
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litellm_params = model["litellm_params"]
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if isinstance(is_healthy, dict) and "error" not in is_healthy:
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healthy_endpoints.append(_clean_endpoint_data({**litellm_params, **is_healthy}, details))
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healthy_endpoints.append(
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_clean_endpoint_data({**litellm_params, **is_healthy}, details)
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)
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elif isinstance(is_healthy, dict):
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unhealthy_endpoints.append(_clean_endpoint_data({**litellm_params, **is_healthy}, details))
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unhealthy_endpoints.append(
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_clean_endpoint_data({**litellm_params, **is_healthy}, details)
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)
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else:
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unhealthy_endpoints.append(_clean_endpoint_data(litellm_params, details))
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@ -74,7 +78,10 @@ async def _perform_health_check(model_list: list, details: bool):
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async def perform_health_check(
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model_list: list, model: Optional[str] = None, cli_model: Optional[str] = None, details: Optional[bool] = True
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model_list: list,
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model: Optional[str] = None,
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cli_model: Optional[str] = None,
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details: Optional[bool] = True,
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):
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"""
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Perform a health check on the system.
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@ -98,6 +105,8 @@ async def perform_health_check(
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_new_model_list = [x for x in model_list if x["model_name"] == model]
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model_list = _new_model_list
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healthy_endpoints, unhealthy_endpoints = await _perform_health_check(model_list, details)
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healthy_endpoints, unhealthy_endpoints = await _perform_health_check(
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model_list, details
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)
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return healthy_endpoints, unhealthy_endpoints
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@ -18,12 +18,15 @@ litellm_settings:
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default_on: true
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"""
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class Role(Enum):
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SYSTEM = "system"
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ASSISTANT = "assistant"
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USER = "user"
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default_roles = [Role.SYSTEM, Role.ASSISTANT, Role.USER];
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default_roles = [Role.SYSTEM, Role.ASSISTANT, Role.USER]
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class GuardrailItemSpec(TypedDict, total=False):
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callbacks: Required[List[str]]
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@ -37,7 +40,7 @@ class GuardrailItem(BaseModel):
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default_on: bool
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logging_only: Optional[bool]
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guardrail_name: str
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enabled_roles: List[Role]
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enabled_roles: Optional[List[Role]]
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model_config = ConfigDict(use_enum_values=True)
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def __init__(
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@ -46,7 +49,7 @@ class GuardrailItem(BaseModel):
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guardrail_name: str,
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default_on: bool = False,
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logging_only: Optional[bool] = None,
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enabled_roles: List[Role] = default_roles,
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enabled_roles: Optional[List[Role]] = default_roles,
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):
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super().__init__(
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callbacks=callbacks,
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