mirror of
https://github.com/BerriAI/litellm.git
synced 2026-11-13 08:52:02 +00:00
fix(guardrails): restore main's guardrails types and re-add tealtiger enum member
This commit is contained in:
AlphaRex-pixel
parent
195226e42e
commit
e0e2e009ed
1 changed files with 200 additions and 47 deletions
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@ -2,12 +2,14 @@ from collections.abc import Mapping
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from datetime import datetime
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from enum import Enum
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from types import MappingProxyType
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from typing import Final, Literal
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from typing import Final, Literal, cast
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from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
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from pydantic import ConfigDict, Field, field_validator, model_validator
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from typing_extensions import ReadOnly, Required, TypedDict
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from litellm._logging import verbose_logger
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from litellm.constants import BEDROCK_APPLY_GUARDRAIL_CHUNK_BUDGET_CHARS
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from litellm.types.llms.base import LiteLLMBaseModel
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from litellm.types.proxy.guardrails.guardrail_hooks.agent_365 import (
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Agent365GuardrailConfigModel,
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)
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@ -23,6 +25,9 @@ from litellm.types.proxy.guardrails.guardrail_hooks.cisco_ai_defense import (
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from litellm.types.proxy.guardrails.guardrail_hooks.compresr import (
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CompresrGuardrailConfigModel,
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)
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from litellm.types.proxy.guardrails.guardrail_hooks.decision_model import (
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DecisionModelCheck,
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)
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from litellm.types.proxy.guardrails.guardrail_hooks.enkryptai import (
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EnkryptAIGuardrailConfigs,
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)
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@ -145,9 +150,10 @@ class SupportedGuardrailIntegrations(Enum):
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STRAIKER = "straiker"
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ALICE = "alice"
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AGENT_365 = "agent_365"
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LLM_SHIELD_PROXY = "llm_shield_proxy"
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CONDUCT = "conduct"
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TEALTIGER = "tealtiger"
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DECISION_MODEL = "decision_model"
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TEALTIGER = 'tealtiger'
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class Role(Enum):
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@ -167,7 +173,7 @@ class GuardrailItemSpec(TypedDict, total=False):
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callback_args: dict[str, dict]
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class GuardrailItem(BaseModel):
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class GuardrailItem(LiteLLMBaseModel):
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callbacks: list[str]
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default_on: bool
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logging_only: bool | None
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@ -437,7 +443,7 @@ class GuardrailParamUITypes(str, Enum):
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PERCENTAGE = "percentage"
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class PresidioPresidioConfigModelUserInterface(BaseModel):
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class PresidioPresidioConfigModelUserInterface(LiteLLMBaseModel):
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"""Configuration parameters for the Presidio PII masking guardrail on LiteLLM UI"""
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presidio_analyzer_api_base: str | None = Field(
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@ -546,31 +552,31 @@ BedrockChecksSensitiveInformationEntity = Literal[
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]
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class BedrockChecksContentFilterCategoryItem(BaseModel):
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class BedrockChecksContentFilterCategoryItem(LiteLLMBaseModel):
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category: BedrockChecksContentFilterCategory
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class BedrockChecksContentFilterModel(BaseModel):
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class BedrockChecksContentFilterModel(LiteLLMBaseModel):
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categories: list[BedrockChecksContentFilterCategoryItem]
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class BedrockChecksPromptAttackCategoryItem(BaseModel):
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class BedrockChecksPromptAttackCategoryItem(LiteLLMBaseModel):
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category: BedrockChecksPromptAttackCategory
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class BedrockChecksPromptAttackModel(BaseModel):
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class BedrockChecksPromptAttackModel(LiteLLMBaseModel):
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categories: list[BedrockChecksPromptAttackCategoryItem]
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class BedrockChecksSensitiveInformationEntityItem(BaseModel):
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class BedrockChecksSensitiveInformationEntityItem(LiteLLMBaseModel):
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type: BedrockChecksSensitiveInformationEntity
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class BedrockChecksSensitiveInformationModel(BaseModel):
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class BedrockChecksSensitiveInformationModel(LiteLLMBaseModel):
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entities: list[BedrockChecksSensitiveInformationEntityItem]
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class BedrockChecksConfigModel(BaseModel):
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class BedrockChecksConfigModel(LiteLLMBaseModel):
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"""Inline `checks` config for the resource-less Bedrock InvokeGuardrailChecks API.
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Include only the checks you want to run; at least one must be set.
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@ -589,7 +595,7 @@ class BedrockChecksConfigModel(BaseModel):
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return self
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class BedrockGuardrailConfigModel(BaseModel):
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class BedrockGuardrailConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the AWS Bedrock guardrail"""
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guardrailIdentifier: str | None = Field(default=None, description="The ID of your guardrail on Bedrock")
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@ -664,7 +670,7 @@ class BedrockGuardrailConfigModel(BaseModel):
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)
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class BedrockGuardrailStreamingParams(BaseModel):
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class BedrockGuardrailStreamingParams(LiteLLMBaseModel):
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streaming_buffer_until_moderated: bool = Field(
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default=True,
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description="If True (default), withhold every streamed chunk until the end-of-stream "
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@ -704,7 +710,7 @@ class BedrockGuardrailStreamingParams(BaseModel):
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)
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class LakeraV2GuardrailConfigModel(BaseModel):
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class LakeraV2GuardrailConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the Lakera AI v2 guardrail"""
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api_key: str | None = Field(default=None, description="API key for the Lakera AI service")
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@ -729,7 +735,7 @@ class LakeraV2GuardrailConfigModel(BaseModel):
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)
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class LassoGuardrailConfigModel(BaseModel):
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class LassoGuardrailConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the Lasso guardrail"""
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lasso_user_id: str | None = Field(default=None, description="User ID for the Lasso guardrail")
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@ -737,7 +743,7 @@ class LassoGuardrailConfigModel(BaseModel):
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mask: bool | None = Field(default=False, description="Enable content masking using Lasso classifix API")
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class DeepKeepGuardrailConfigModel(BaseModel):
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class DeepKeepGuardrailConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the DeepKeep AI Firewall guardrail"""
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deepkeep_firewall_id: str | None = Field(
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@ -749,7 +755,7 @@ class DeepKeepGuardrailConfigModel(BaseModel):
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)
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class PillarGuardrailConfigModel(BaseModel):
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class PillarGuardrailConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the Pillar Security guardrail"""
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on_flagged_action: str | None = Field(
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@ -774,7 +780,7 @@ class PillarGuardrailConfigModel(BaseModel):
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)
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class NomaGuardrailConfigModel(BaseModel):
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class NomaGuardrailConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the Noma Security guardrail"""
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use_v2: bool | None = Field(
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@ -803,7 +809,7 @@ class NomaGuardrailConfigModel(BaseModel):
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)
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class ZscalerAIGuardConfigModel(BaseModel):
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class ZscalerAIGuardConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the Zscaler AI Guard guardrail"""
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policy_id: int | None = Field(
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@ -821,7 +827,7 @@ class ZscalerAIGuardConfigModel(BaseModel):
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)
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class JavelinGuardrailConfigModel(BaseModel):
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class JavelinGuardrailConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the Javelin guardrail"""
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guard_name: str | None = Field(default=None, description="Name of the Javelin guard to use")
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@ -838,7 +844,7 @@ class ContentFilterAction(str, Enum):
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MASK = "MASK"
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class BlockedWord(BaseModel):
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class BlockedWord(LiteLLMBaseModel):
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"""Represents a blocked word with its action and optional description"""
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keyword: str = Field(description="The keyword to block or mask")
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@ -849,7 +855,7 @@ class BlockedWord(BaseModel):
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)
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class ContentFilterPattern(BaseModel):
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class ContentFilterPattern(LiteLLMBaseModel):
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"""Represents a content filter pattern (prebuilt or custom regex)"""
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pattern_type: Literal["prebuilt", "regex"] = Field(
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@ -870,7 +876,7 @@ class ContentFilterPattern(BaseModel):
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action: ContentFilterAction = Field(description="Action to take when pattern matches (BLOCK or MASK)")
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class ContentFilterConfigModel(BaseModel):
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class ContentFilterConfigModel(LiteLLMBaseModel):
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"""Configuration parameters for the content filter guardrail"""
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patterns: list[ContentFilterPattern] | None = Field(
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@ -901,6 +907,95 @@ class ContentFilterConfigModel(BaseModel):
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MCP_SECURITY_ON_VIOLATION: Final = frozenset({"block", "alert"})
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GuardrailStreamScope = Literal["streaming", "non_streaming", "both"]
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DEFAULT_GUARDRAIL_STREAM_SCOPE: Final[GuardrailStreamScope] = "both"
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class GuardrailEventHooks(str, Enum):
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pre_call = "pre_call"
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post_call = "post_call"
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during_call = "during_call"
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logging_only = "logging_only"
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pre_mcp_call = "pre_mcp_call"
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during_mcp_call = "during_mcp_call"
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post_mcp_call = "post_mcp_call"
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realtime_input_transcription = "realtime_input_transcription"
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GUARDRAIL_EVENT_HOOK_VALUES: Final = frozenset(member.value for member in GuardrailEventHooks)
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_GUARDRAIL_STREAM_SCOPES: Final[Mapping[str, GuardrailStreamScope]] = MappingProxyType(
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{
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"streaming": "streaming",
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"non_streaming": "non_streaming",
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"both": "both",
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}
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)
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def _as_guardrail_stream_scope(value: object) -> GuardrailStreamScope:
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if not isinstance(value, str):
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raise ValueError(f"stream_scope values must be strings, got {type(value).__name__}")
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scope: Final = _GUARDRAIL_STREAM_SCOPES.get(value.lower())
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if scope is None:
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raise ValueError(f"stream_scope must be one of both, streaming, non_streaming, got {value!r}")
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return scope
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def _validated_stream_scope_hook(key: object) -> str:
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if not isinstance(key, str):
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raise ValueError(f"stream_scope keys must be strings, got {type(key).__name__}")
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hook: Final = key.lower()
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if hook not in GUARDRAIL_EVENT_HOOK_VALUES:
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raise ValueError(
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f"stream_scope keys must be guardrail modes ({sorted(GUARDRAIL_EVENT_HOOK_VALUES)}), got {key!r}"
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)
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return hook
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def coerce_stream_scope(value: object) -> GuardrailStreamScope | dict[str, GuardrailStreamScope] | None:
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if value is None:
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return None
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if isinstance(value, str):
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return _as_guardrail_stream_scope(value)
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if isinstance(value, Mapping):
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scope_map: Final[Mapping[str, object]] = cast(Mapping[str, object], value) # cast-ok: keys validated below
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return {
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_validated_stream_scope_hook(key): _as_guardrail_stream_scope(scope) for key, scope in scope_map.items()
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}
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raise ValueError(f"stream_scope must be a string or mapping, got {type(value).__name__}")
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def stored_stream_scope(value: object) -> GuardrailStreamScope | dict[str, GuardrailStreamScope] | None:
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try:
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return coerce_stream_scope(value)
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except ValueError:
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verbose_logger.warning("Ignoring invalid stored stream_scope value of type %s", type(value).__name__)
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return None
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def with_tolerated_stream_scope(params: Mapping[str, object]) -> dict[str, object]:
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if "stream_scope" not in params:
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return dict(params)
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return {
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**params,
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"stream_scope": stored_stream_scope(params["stream_scope"]),
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}
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def runtime_stream_scope(
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stream_scope: object,
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) -> tuple[GuardrailStreamScope, MappingProxyType[str, GuardrailStreamScope]]:
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coerced: Final = coerce_stream_scope(stream_scope)
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if coerced is None:
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return DEFAULT_GUARDRAIL_STREAM_SCOPE, MappingProxyType({})
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if isinstance(coerced, str):
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return coerced, MappingProxyType({})
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return DEFAULT_GUARDRAIL_STREAM_SCOPE, MappingProxyType(coerced)
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LoggingOnlyScope = Literal["input", "output"]
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class BaseLitellmParams(ContentFilterConfigModel): # works for new and patch update guardrails
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api_key: str | None = Field(default=None, description="API key for the guardrail service")
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@ -1043,9 +1138,11 @@ class BaseLitellmParams(ContentFilterConfigModel): # works for new and patch up
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skip_unscannable_attachments: bool | None = Field(
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default=False,
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description=(
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"Implemented by guardrail='model_armor'. When True, attachment references that carry no "
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"inline bytes (file_id, gs://, or http(s) URLs) pass through unscanned instead of blocking, "
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"while fail_on_error still governs real Model Armor API errors. Default False blocks them."
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"Implemented by guardrail='model_armor' and guardrail='bedrock'. When True, attachments the "
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"guardrail cannot scan pass through unscanned instead of blocking. For Model Armor these are "
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"references with no inline bytes (file_id, gs://, or http(s) URLs), and fail_on_error still "
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"governs real Model Armor API errors. For Bedrock these are documents, files, audio, video, "
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"and images that are not inline PNG or JPEG up to 4 MB. Default False blocks them."
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),
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)
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sanitize_error_detail: bool | None = Field(
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@ -1066,10 +1163,23 @@ class BaseLitellmParams(ContentFilterConfigModel): # works for new and patch up
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description=(
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"Behavior when a guardrail endpoint is unreachable due to network errors. "
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"Implemented by guardrail='generic_guardrail_api', 'agent_365', 'akto', 'vigil_guard', 'repelloai', 'headroom', 'compresr', and 'typesafe'. "
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"'fail_closed' raises an error (default). 'fail_open' logs a critical error and allows the request to proceed."
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"'fail_closed' raises an error (default). 'fail_open' logs a critical error and allows the request to proceed. "
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"Also implemented by guardrail='decision_model'."
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),
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)
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max_input_chars: int | None = Field(
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default=None,
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gt=0,
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description="Character budget for each text sent to the guardrail's model. Implemented by guardrail='decision_model'.",
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)
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max_concurrent_decision_calls: int | None = Field(
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default=None,
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gt=0,
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description="Maximum decisions calls in flight at once on the guardrail in each proxy worker. Implemented by guardrail='decision_model'.",
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)
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extra_headers: list[str] | None = Field(
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default=None,
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description=(
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@ -1142,6 +1252,39 @@ class BaseLitellmParams(ContentFilterConfigModel): # works for new and patch up
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),
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)
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stream_scope: GuardrailStreamScope | dict[str, GuardrailStreamScope] | None = Field(
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default=None,
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description=(
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"Whether this guardrail runs on streaming requests, non-streaming requests, or both. "
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"A string applies to every configured mode. A map overrides named modes "
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"(pre_call, during_call, post_call, ...); omitted keys default to both. "
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"Unset means both, matching historical behavior."
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),
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)
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@field_validator("stream_scope", mode="before")
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@classmethod
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def normalize_stream_scope(cls, v: object) -> GuardrailStreamScope | dict[str, GuardrailStreamScope] | None:
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return coerce_stream_scope(v)
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logging_only_scope: LoggingOnlyScope | None = Field(
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default=None,
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description=(
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"which direction a logging_only scan observes: 'input' (request) or 'output' (response); "
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"unset scans both directions. Only applies to mode logging_only; pre_call/post_call on the "
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"same guardrail keep blocking."
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),
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)
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logging_only_continue_on_input_failure: bool | None = Field(
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default=None,
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description=(
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"when True, a flagged or raising logging_only request scan is logged and the response is "
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"still scanned, so both verdicts land. Only applies to mode logging_only and is ignored "
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"when logging_only_scope is 'input' or 'output'."
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),
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)
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@field_validator(
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"mode",
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"default_action",
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@ -1169,7 +1312,7 @@ class BaseLitellmParams(ContentFilterConfigModel): # works for new and patch up
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model_config = ConfigDict(extra="allow", protected_namespaces=())
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class Mode(BaseModel):
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class Mode(LiteLLMBaseModel):
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tags: dict[str, str | list[str]] = Field(description="Tags for the guardrail mode")
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default: str | list[str] | None = Field(default=None, description="Default mode when no tags match")
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@ -1207,6 +1350,17 @@ class LitellmParams( # pyright: ignore[reportIncompatibleVariableOverride] # o
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Agent365GuardrailConfigModel,
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):
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guardrail: str = Field(description="The type of guardrail integration to use")
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decision_model: str | None = Field(
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default=None,
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description="For guardrail='decision_model': the Decisions-API model that scores each check",
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)
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checks: BedrockChecksConfigModel | tuple[DecisionModelCheck, ...] | None = Field( # pyright: ignore[reportIncompatibleVariableOverride] # widened to also accept decision-model checks
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default=None,
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description=(
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"Inline Bedrock InvokeGuardrailChecks config for guardrail='bedrock', or the predicate "
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"checks a decision_model guardrail scores for guardrail='decision_model'"
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),
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)
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mode: str | list[str] | Mode = Field(
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description="When to apply the guardrail (pre_call, post_call, during_call, logging_only)"
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)
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@ -1232,6 +1386,14 @@ class LitellmParams( # pyright: ignore[reportIncompatibleVariableOverride] # o
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raise ValueError(f"on_violation={self.on_violation!r} is only supported by guardrail='mcp_security'")
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return self
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@model_validator(mode="after")
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def validate_checks_list_for_guardrail(self) -> "LitellmParams":
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if isinstance(self.checks, tuple) and self.guardrail != SupportedGuardrailIntegrations.DECISION_MODEL.value:
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raise ValueError(
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f"checks as a list is only supported by guardrail='decision_model', got guardrail={self.guardrail!r}"
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)
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||||
return self
|
||||
|
||||
def __init__(self, **kwargs) -> None:
|
||||
default_on: Final = kwargs.pop("default_on", None)
|
||||
if default_on is not None:
|
||||
|
|
@ -1268,17 +1430,6 @@ class guardrailConfig(TypedDict):
|
|||
guardrails: list[Guardrail]
|
||||
|
||||
|
||||
class GuardrailEventHooks(str, Enum):
|
||||
pre_call = "pre_call"
|
||||
post_call = "post_call"
|
||||
during_call = "during_call"
|
||||
logging_only = "logging_only"
|
||||
pre_mcp_call = "pre_mcp_call"
|
||||
during_mcp_call = "during_mcp_call"
|
||||
post_mcp_call = "post_mcp_call"
|
||||
realtime_input_transcription = "realtime_input_transcription"
|
||||
|
||||
|
||||
class DynamicGuardrailParams(TypedDict):
|
||||
extra_body: ReadOnly[dict[str, object]]
|
||||
|
||||
|
|
@ -1288,7 +1439,7 @@ class GUARDRAIL_DEFINITION_LOCATION(str, Enum):
|
|||
CONFIG = "config"
|
||||
|
||||
|
||||
class GuardrailInfoResponse(BaseModel):
|
||||
class GuardrailInfoResponse(LiteLLMBaseModel):
|
||||
guardrail_id: str | None = None
|
||||
guardrail_name: str
|
||||
litellm_params: BaseLitellmParams | None = None
|
||||
|
|
@ -1301,20 +1452,22 @@ class GuardrailInfoResponse(BaseModel):
|
|||
super().__init__(**kwargs)
|
||||
|
||||
|
||||
class ListGuardrailsResponse(BaseModel):
|
||||
class ListGuardrailsResponse(LiteLLMBaseModel):
|
||||
guardrails: list[GuardrailInfoResponse]
|
||||
|
||||
|
||||
class GuardrailUIAddGuardrailSettings(BaseModel):
|
||||
class GuardrailUIAddGuardrailSettings(LiteLLMBaseModel):
|
||||
supported_entities: list[str]
|
||||
supported_actions: list[str]
|
||||
supported_modes: list[str]
|
||||
supported_modes_by_provider: dict[str, list[str]]
|
||||
providers_without_directional_logging_only_scope: tuple[str, ...]
|
||||
pii_entity_categories: list[PiiEntityCategoryMap]
|
||||
content_filter_settings: dict[str, object] | None = None
|
||||
decision_model_providers: tuple[str, ...] = Field(default_factory=tuple)
|
||||
|
||||
|
||||
class PresidioPerRequestConfig(BaseModel):
|
||||
class PresidioPerRequestConfig(LiteLLMBaseModel):
|
||||
"""
|
||||
presdio params that can be controlled per request, api key
|
||||
"""
|
||||
|
|
@ -1323,7 +1476,7 @@ class PresidioPerRequestConfig(BaseModel):
|
|||
entities: list[PiiEntityType] | None = None
|
||||
|
||||
|
||||
class ApplyGuardrailRequest(BaseModel):
|
||||
class ApplyGuardrailRequest(LiteLLMBaseModel):
|
||||
guardrail_name: str
|
||||
text: str
|
||||
language: str | None = None
|
||||
|
|
@ -1333,11 +1486,11 @@ class ApplyGuardrailRequest(BaseModel):
|
|||
metadata: dict[str, object] | None = None
|
||||
|
||||
|
||||
class ApplyGuardrailResponse(BaseModel):
|
||||
class ApplyGuardrailResponse(LiteLLMBaseModel):
|
||||
response_text: str
|
||||
|
||||
|
||||
class PatchGuardrailRequest(BaseModel):
|
||||
class PatchGuardrailRequest(LiteLLMBaseModel):
|
||||
guardrail_name: str | None = None
|
||||
litellm_params: BaseLitellmParams | None = None
|
||||
guardrail_info: dict[str, object] | None = None
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue