mirror of
https://github.com/BerriAI/litellm.git
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310 lines
12 KiB
Python
310 lines
12 KiB
Python
from typing import Any, Dict, List, Optional
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import litellm
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from litellm import get_secret
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from litellm._logging import verbose_proxy_logger
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from litellm.proxy._types import CommonProxyErrors, LiteLLMPromptInjectionParams
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from litellm.proxy.types_utils.utils import get_instance_fn
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blue_color_code = "\033[94m"
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reset_color_code = "\033[0m"
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def initialize_callbacks_on_proxy( # noqa: PLR0915
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value: Any,
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premium_user: bool,
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config_file_path: str,
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litellm_settings: dict,
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callback_specific_params: dict = {},
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):
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from litellm.proxy.proxy_server import prisma_client
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verbose_proxy_logger.debug(
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f"{blue_color_code}initializing callbacks={value} on proxy{reset_color_code}"
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)
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if isinstance(value, list):
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imported_list: List[Any] = []
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for callback in value: # ["presidio", <my-custom-callback>]
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if (
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isinstance(callback, str)
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and callback in litellm._known_custom_logger_compatible_callbacks
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):
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imported_list.append(callback)
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elif isinstance(callback, str) and callback == "presidio":
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from litellm.proxy.guardrails.guardrail_hooks.presidio import (
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_OPTIONAL_PresidioPIIMasking,
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)
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presidio_logging_only: Optional[bool] = litellm_settings.get(
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"presidio_logging_only", None
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)
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if presidio_logging_only is not None:
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presidio_logging_only = bool(
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presidio_logging_only
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) # validate boolean given
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_presidio_params = {}
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if "presidio" in callback_specific_params and isinstance(
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callback_specific_params["presidio"], dict
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):
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_presidio_params = callback_specific_params["presidio"]
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params: Dict[str, Any] = {
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"logging_only": presidio_logging_only,
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**_presidio_params,
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}
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pii_masking_object = _OPTIONAL_PresidioPIIMasking(**params)
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imported_list.append(pii_masking_object)
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elif isinstance(callback, str) and callback == "llamaguard_moderations":
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from enterprise.enterprise_hooks.llama_guard import (
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_ENTERPRISE_LlamaGuard,
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)
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if premium_user is not True:
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raise Exception(
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"Trying to use Llama Guard"
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+ CommonProxyErrors.not_premium_user.value
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)
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llama_guard_object = _ENTERPRISE_LlamaGuard()
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imported_list.append(llama_guard_object)
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elif isinstance(callback, str) and callback == "hide_secrets":
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from enterprise.enterprise_hooks.secret_detection import (
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_ENTERPRISE_SecretDetection,
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)
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if premium_user is not True:
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raise Exception(
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"Trying to use secret hiding"
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+ CommonProxyErrors.not_premium_user.value
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)
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_secret_detection_object = _ENTERPRISE_SecretDetection()
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imported_list.append(_secret_detection_object)
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elif isinstance(callback, str) and callback == "openai_moderations":
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from enterprise.enterprise_hooks.openai_moderation import (
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_ENTERPRISE_OpenAI_Moderation,
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)
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if premium_user is not True:
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raise Exception(
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"Trying to use OpenAI Moderations Check"
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+ CommonProxyErrors.not_premium_user.value
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)
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openai_moderations_object = _ENTERPRISE_OpenAI_Moderation()
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imported_list.append(openai_moderations_object)
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elif isinstance(callback, str) and callback == "lakera_prompt_injection":
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from litellm.proxy.guardrails.guardrail_hooks.lakera_ai import (
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lakeraAI_Moderation,
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)
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init_params = {}
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if "lakera_prompt_injection" in callback_specific_params:
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init_params = callback_specific_params["lakera_prompt_injection"]
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lakera_moderations_object = lakeraAI_Moderation(**init_params)
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imported_list.append(lakera_moderations_object)
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elif isinstance(callback, str) and callback == "aporia_prompt_injection":
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from litellm.proxy.guardrails.guardrail_hooks.aporia_ai import (
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AporiaGuardrail,
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)
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aporia_guardrail_object = AporiaGuardrail()
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imported_list.append(aporia_guardrail_object)
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elif isinstance(callback, str) and callback == "google_text_moderation":
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from enterprise.enterprise_hooks.google_text_moderation import (
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_ENTERPRISE_GoogleTextModeration,
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)
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if premium_user is not True:
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raise Exception(
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"Trying to use Google Text Moderation"
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+ CommonProxyErrors.not_premium_user.value
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)
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google_text_moderation_obj = _ENTERPRISE_GoogleTextModeration()
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imported_list.append(google_text_moderation_obj)
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elif isinstance(callback, str) and callback == "llmguard_moderations":
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from enterprise.enterprise_hooks.llm_guard import _ENTERPRISE_LLMGuard
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if premium_user is not True:
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raise Exception(
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"Trying to use Llm Guard"
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+ CommonProxyErrors.not_premium_user.value
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)
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llm_guard_moderation_obj = _ENTERPRISE_LLMGuard()
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imported_list.append(llm_guard_moderation_obj)
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elif isinstance(callback, str) and callback == "blocked_user_check":
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from enterprise.enterprise_hooks.blocked_user_list import (
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_ENTERPRISE_BlockedUserList,
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)
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if premium_user is not True:
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raise Exception(
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"Trying to use ENTERPRISE BlockedUser"
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+ CommonProxyErrors.not_premium_user.value
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)
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blocked_user_list = _ENTERPRISE_BlockedUserList(
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prisma_client=prisma_client
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)
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imported_list.append(blocked_user_list)
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elif isinstance(callback, str) and callback == "banned_keywords":
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from enterprise.enterprise_hooks.banned_keywords import (
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_ENTERPRISE_BannedKeywords,
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)
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if premium_user is not True:
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raise Exception(
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"Trying to use ENTERPRISE BannedKeyword"
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+ CommonProxyErrors.not_premium_user.value
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)
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banned_keywords_obj = _ENTERPRISE_BannedKeywords()
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imported_list.append(banned_keywords_obj)
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elif isinstance(callback, str) and callback == "detect_prompt_injection":
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from litellm.proxy.hooks.prompt_injection_detection import (
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_OPTIONAL_PromptInjectionDetection,
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)
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prompt_injection_params = None
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if "prompt_injection_params" in litellm_settings:
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prompt_injection_params_in_config = litellm_settings[
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"prompt_injection_params"
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]
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prompt_injection_params = LiteLLMPromptInjectionParams(
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**prompt_injection_params_in_config
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)
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prompt_injection_detection_obj = _OPTIONAL_PromptInjectionDetection(
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prompt_injection_params=prompt_injection_params,
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)
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imported_list.append(prompt_injection_detection_obj)
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elif isinstance(callback, str) and callback == "batch_redis_requests":
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from litellm.proxy.hooks.batch_redis_get import (
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_PROXY_BatchRedisRequests,
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)
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batch_redis_obj = _PROXY_BatchRedisRequests()
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imported_list.append(batch_redis_obj)
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elif isinstance(callback, str) and callback == "azure_content_safety":
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from litellm.proxy.hooks.azure_content_safety import (
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_PROXY_AzureContentSafety,
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)
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azure_content_safety_params = litellm_settings[
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"azure_content_safety_params"
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]
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for k, v in azure_content_safety_params.items():
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if (
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v is not None
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and isinstance(v, str)
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and v.startswith("os.environ/")
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):
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azure_content_safety_params[k] = get_secret(v)
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azure_content_safety_obj = _PROXY_AzureContentSafety(
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**azure_content_safety_params,
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)
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imported_list.append(azure_content_safety_obj)
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else:
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verbose_proxy_logger.debug(
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f"{blue_color_code} attempting to import custom calback={callback} {reset_color_code}"
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)
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imported_list.append(
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get_instance_fn(
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value=callback,
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config_file_path=config_file_path,
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)
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)
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if isinstance(litellm.callbacks, list):
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litellm.callbacks.extend(imported_list)
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else:
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litellm.callbacks = imported_list # type: ignore
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if "prometheus" in value:
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from litellm.integrations.prometheus import PrometheusLogger
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PrometheusLogger._mount_metrics_endpoint(premium_user)
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else:
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litellm.callbacks = [
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get_instance_fn(
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value=value,
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config_file_path=config_file_path,
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)
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]
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verbose_proxy_logger.debug(
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f"{blue_color_code} Initialized Callbacks - {litellm.callbacks} {reset_color_code}"
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)
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def get_model_group_from_litellm_kwargs(kwargs: dict) -> Optional[str]:
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_litellm_params = kwargs.get("litellm_params", None) or {}
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_metadata = _litellm_params.get("metadata", None) or {}
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_model_group = _metadata.get("model_group", None)
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if _model_group is not None:
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return _model_group
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return None
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def get_model_group_from_request_data(data: dict) -> Optional[str]:
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_metadata = data.get("metadata", None) or {}
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_model_group = _metadata.get("model_group", None)
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if _model_group is not None:
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return _model_group
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return None
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def get_remaining_tokens_and_requests_from_request_data(data: Dict) -> Dict[str, str]:
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"""
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Helper function to return x-litellm-key-remaining-tokens-{model_group} and x-litellm-key-remaining-requests-{model_group}
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Returns {} when api_key + model rpm/tpm limit is not set
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"""
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headers = {}
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_metadata = data.get("metadata", None) or {}
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model_group = get_model_group_from_request_data(data)
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# Remaining Requests
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remaining_requests_variable_name = f"litellm-key-remaining-requests-{model_group}"
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remaining_requests = _metadata.get(remaining_requests_variable_name, None)
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if remaining_requests:
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headers[f"x-litellm-key-remaining-requests-{model_group}"] = remaining_requests
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# Remaining Tokens
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remaining_tokens_variable_name = f"litellm-key-remaining-tokens-{model_group}"
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remaining_tokens = _metadata.get(remaining_tokens_variable_name, None)
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if remaining_tokens:
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headers[f"x-litellm-key-remaining-tokens-{model_group}"] = remaining_tokens
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return headers
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def get_logging_caching_headers(request_data: Dict) -> Optional[Dict]:
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_metadata = request_data.get("metadata", None) or {}
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headers = {}
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if "applied_guardrails" in _metadata:
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headers["x-litellm-applied-guardrails"] = ",".join(
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_metadata["applied_guardrails"]
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)
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if "semantic-similarity" in _metadata:
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headers["x-litellm-semantic-similarity"] = str(_metadata["semantic-similarity"])
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return headers
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def add_guardrail_to_applied_guardrails_header(
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request_data: Dict, guardrail_name: Optional[str]
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):
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if guardrail_name is None:
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return
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_metadata = request_data.get("metadata", None) or {}
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if "applied_guardrails" in _metadata:
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_metadata["applied_guardrails"].append(guardrail_name)
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else:
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_metadata["applied_guardrails"] = [guardrail_name]
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