forked from phoenix-oss/llama-stack-mirror
Split safety into (llama-guard, prompt-guard, code-scanner) (#400)
Splits the meta-reference safety implementation into three distinct providers: - inline::llama-guard - inline::prompt-guard - inline::code-scanner Note that this PR is a backward incompatible change to the llama stack server. I have added deprecation_error field to ProviderSpec -- the server reads it and immediately barfs. This is used to direct the user with a specific message on what action to perform. An automagical "config upgrade" is a bit too much work to implement right now :/ (Note that we will be gradually prefixing all inline providers with inline:: -- I am only doing this for this set of new providers because otherwise existing configuration files will break even more badly.)
This commit is contained in:
Ashwin Bharambe
GitHub
parent
6d38b1690b
commit
c1f7ba3aed
47 changed files with 464 additions and 500 deletions
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@ -25,7 +25,7 @@ class MetaReferenceCodeScannerSafetyImpl(Safety):
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pass
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async def register_shield(self, shield: Shield) -> None:
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if shield.shield_type != ShieldType.code_scanner.value:
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if shield.shield_type != ShieldType.code_scanner:
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raise ValueError(f"Unsupported safety shield type: {shield.shield_type}")
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async def run_shield(
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@ -7,5 +7,5 @@
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from pydantic import BaseModel
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class CodeShieldConfig(BaseModel):
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class CodeScannerConfig(BaseModel):
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pass
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19
llama_stack/providers/inline/safety/llama_guard/__init__.py
Normal file
19
llama_stack/providers/inline/safety/llama_guard/__init__.py
Normal file
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@ -0,0 +1,19 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from .config import LlamaGuardConfig
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async def get_provider_impl(config: LlamaGuardConfig, deps):
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from .llama_guard import LlamaGuardSafetyImpl
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assert isinstance(
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config, LlamaGuardConfig
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), f"Unexpected config type: {type(config)}"
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impl = LlamaGuardSafetyImpl(config, deps)
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await impl.initialize()
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return impl
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@ -4,20 +4,14 @@
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from enum import Enum
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from typing import List, Optional
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from typing import List
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from llama_models.sku_list import CoreModelId, safety_models
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from pydantic import BaseModel, field_validator
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class PromptGuardType(Enum):
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injection = "injection"
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jailbreak = "jailbreak"
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class LlamaGuardShieldConfig(BaseModel):
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class LlamaGuardConfig(BaseModel):
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model: str = "Llama-Guard-3-1B"
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excluded_categories: List[str] = []
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@ -41,8 +35,3 @@ class LlamaGuardShieldConfig(BaseModel):
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f"Invalid model: {model}. Must be one of {permitted_models}"
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)
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return model
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class SafetyConfig(BaseModel):
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llama_guard_shield: Optional[LlamaGuardShieldConfig] = None
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enable_prompt_guard: Optional[bool] = False
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@ -7,16 +7,21 @@
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import re
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from string import Template
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from typing import List, Optional
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from typing import Any, Dict, List, Optional
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from llama_models.llama3.api.datatypes import * # noqa: F403
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from llama_stack.apis.inference import * # noqa: F403
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from llama_stack.apis.safety import * # noqa: F403
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from llama_stack.distribution.datatypes import Api
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from .base import CANNED_RESPONSE_TEXT, OnViolationAction, ShieldBase, ShieldResponse
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from llama_stack.providers.datatypes import ShieldsProtocolPrivate
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from .config import LlamaGuardConfig
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CANNED_RESPONSE_TEXT = "I can't answer that. Can I help with something else?"
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SAFE_RESPONSE = "safe"
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_INSTANCE = None
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CAT_VIOLENT_CRIMES = "Violent Crimes"
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CAT_NON_VIOLENT_CRIMES = "Non-Violent Crimes"
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@ -107,16 +112,52 @@ PROMPT_TEMPLATE = Template(
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)
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class LlamaGuardShield(ShieldBase):
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class LlamaGuardSafetyImpl(Safety, ShieldsProtocolPrivate):
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def __init__(self, config: LlamaGuardConfig, deps) -> None:
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self.config = config
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self.inference_api = deps[Api.inference]
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async def initialize(self) -> None:
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self.shield = LlamaGuardShield(
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model=self.config.model,
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inference_api=self.inference_api,
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excluded_categories=self.config.excluded_categories,
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)
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async def shutdown(self) -> None:
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pass
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async def register_shield(self, shield: Shield) -> None:
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print(f"Registering shield {shield}")
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if shield.shield_type != ShieldType.llama_guard:
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raise ValueError(f"Unsupported shield type: {shield.shield_type}")
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async def run_shield(
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self,
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shield_id: str,
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messages: List[Message],
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params: Dict[str, Any] = None,
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) -> RunShieldResponse:
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shield = await self.shield_store.get_shield(shield_id)
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if not shield:
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raise ValueError(f"Unknown shield {shield_id}")
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messages = messages.copy()
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# some shields like llama-guard require the first message to be a user message
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# since this might be a tool call, first role might not be user
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if len(messages) > 0 and messages[0].role != Role.user.value:
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messages[0] = UserMessage(content=messages[0].content)
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return await self.shield.run(messages)
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class LlamaGuardShield:
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def __init__(
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self,
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model: str,
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inference_api: Inference,
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excluded_categories: List[str] = None,
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on_violation_action: OnViolationAction = OnViolationAction.RAISE,
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excluded_categories: Optional[List[str]] = None,
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):
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super().__init__(on_violation_action)
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if excluded_categories is None:
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excluded_categories = []
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@ -174,7 +215,7 @@ class LlamaGuardShield(ShieldBase):
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)
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return messages
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async def run(self, messages: List[Message]) -> ShieldResponse:
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async def run(self, messages: List[Message]) -> RunShieldResponse:
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messages = self.validate_messages(messages)
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if self.model == CoreModelId.llama_guard_3_11b_vision.value:
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@ -195,8 +236,7 @@ class LlamaGuardShield(ShieldBase):
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content += event.delta
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content = content.strip()
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shield_response = self.get_shield_response(content)
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return shield_response
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return self.get_shield_response(content)
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def build_text_shield_input(self, messages: List[Message]) -> UserMessage:
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return UserMessage(content=self.build_prompt(messages))
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@ -250,19 +290,23 @@ class LlamaGuardShield(ShieldBase):
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conversations=conversations_str,
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)
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def get_shield_response(self, response: str) -> ShieldResponse:
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def get_shield_response(self, response: str) -> RunShieldResponse:
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response = response.strip()
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if response == SAFE_RESPONSE:
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return ShieldResponse(is_violation=False)
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return RunShieldResponse(violation=None)
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unsafe_code = self.check_unsafe_response(response)
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if unsafe_code:
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unsafe_code_list = unsafe_code.split(",")
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if set(unsafe_code_list).issubset(set(self.excluded_categories)):
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return ShieldResponse(is_violation=False)
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return ShieldResponse(
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is_violation=True,
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violation_type=unsafe_code,
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violation_return_message=CANNED_RESPONSE_TEXT,
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return RunShieldResponse(violation=None)
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return RunShieldResponse(
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violation=SafetyViolation(
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violation_level=ViolationLevel.ERROR,
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user_message=CANNED_RESPONSE_TEXT,
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metadata={"violation_type": unsafe_code},
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),
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)
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raise ValueError(f"Unexpected response: {response}")
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@ -1,17 +0,0 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from .config import LlamaGuardShieldConfig, SafetyConfig # noqa: F401
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async def get_provider_impl(config: SafetyConfig, deps):
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from .safety import MetaReferenceSafetyImpl
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assert isinstance(config, SafetyConfig), f"Unexpected config type: {type(config)}"
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impl = MetaReferenceSafetyImpl(config, deps)
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await impl.initialize()
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return impl
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@ -1,57 +0,0 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from abc import ABC, abstractmethod
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from typing import List
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from llama_models.llama3.api.datatypes import interleaved_text_media_as_str, Message
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from pydantic import BaseModel
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from llama_stack.apis.safety import * # noqa: F403
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CANNED_RESPONSE_TEXT = "I can't answer that. Can I help with something else?"
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# TODO: clean this up; just remove this type completely
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class ShieldResponse(BaseModel):
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is_violation: bool
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violation_type: Optional[str] = None
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violation_return_message: Optional[str] = None
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# TODO: this is a caller / agent concern
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class OnViolationAction(Enum):
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IGNORE = 0
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WARN = 1
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RAISE = 2
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class ShieldBase(ABC):
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def __init__(
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self,
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on_violation_action: OnViolationAction = OnViolationAction.RAISE,
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):
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self.on_violation_action = on_violation_action
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@abstractmethod
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async def run(self, messages: List[Message]) -> ShieldResponse:
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raise NotImplementedError()
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def message_content_as_str(message: Message) -> str:
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return interleaved_text_media_as_str(message.content)
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class TextShield(ShieldBase):
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def convert_messages_to_text(self, messages: List[Message]) -> str:
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return "\n".join([message_content_as_str(m) for m in messages])
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async def run(self, messages: List[Message]) -> ShieldResponse:
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text = self.convert_messages_to_text(messages)
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return await self.run_impl(text)
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@abstractmethod
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async def run_impl(self, text: str) -> ShieldResponse:
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raise NotImplementedError()
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@ -1,145 +0,0 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from enum import auto, Enum
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from typing import List
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import torch
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from llama_models.llama3.api.datatypes import Message
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from termcolor import cprint
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from .base import message_content_as_str, OnViolationAction, ShieldResponse, TextShield
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class PromptGuardShield(TextShield):
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class Mode(Enum):
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INJECTION = auto()
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JAILBREAK = auto()
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_instances = {}
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_model_cache = None
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@staticmethod
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def instance(
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model_dir: str,
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threshold: float = 0.9,
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temperature: float = 1.0,
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mode: "PromptGuardShield.Mode" = Mode.JAILBREAK,
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on_violation_action=OnViolationAction.RAISE,
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) -> "PromptGuardShield":
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action_value = on_violation_action.value
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key = (model_dir, threshold, temperature, mode, action_value)
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if key not in PromptGuardShield._instances:
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PromptGuardShield._instances[key] = PromptGuardShield(
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model_dir=model_dir,
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threshold=threshold,
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temperature=temperature,
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mode=mode,
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on_violation_action=on_violation_action,
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)
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return PromptGuardShield._instances[key]
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def __init__(
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self,
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model_dir: str,
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threshold: float = 0.9,
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temperature: float = 1.0,
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mode: "PromptGuardShield.Mode" = Mode.JAILBREAK,
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on_violation_action: OnViolationAction = OnViolationAction.RAISE,
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):
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super().__init__(on_violation_action)
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assert (
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model_dir is not None
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), "Must provide a model directory for prompt injection shield"
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if temperature <= 0:
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raise ValueError("Temperature must be greater than 0")
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self.device = "cuda"
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if PromptGuardShield._model_cache is None:
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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# load model and tokenizer
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tokenizer = AutoTokenizer.from_pretrained(model_dir)
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model = AutoModelForSequenceClassification.from_pretrained(
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model_dir, device_map=self.device
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)
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PromptGuardShield._model_cache = (tokenizer, model)
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self.tokenizer, self.model = PromptGuardShield._model_cache
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self.temperature = temperature
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self.threshold = threshold
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self.mode = mode
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def convert_messages_to_text(self, messages: List[Message]) -> str:
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return message_content_as_str(messages[-1])
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async def run_impl(self, text: str) -> ShieldResponse:
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# run model on messages and return response
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inputs = self.tokenizer(text, return_tensors="pt")
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inputs = {name: tensor.to(self.model.device) for name, tensor in inputs.items()}
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with torch.no_grad():
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outputs = self.model(**inputs)
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logits = outputs[0]
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probabilities = torch.softmax(logits / self.temperature, dim=-1)
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score_embedded = probabilities[0, 1].item()
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score_malicious = probabilities[0, 2].item()
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cprint(
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f"Ran PromptGuardShield and got Scores: Embedded: {score_embedded}, Malicious: {score_malicious}",
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color="magenta",
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)
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if self.mode == self.Mode.INJECTION and (
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score_embedded + score_malicious > self.threshold
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):
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return ShieldResponse(
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is_violation=True,
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violation_type=f"prompt_injection:embedded={score_embedded},malicious={score_malicious}",
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violation_return_message="Sorry, I cannot do this.",
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)
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elif self.mode == self.Mode.JAILBREAK and score_malicious > self.threshold:
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return ShieldResponse(
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is_violation=True,
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violation_type=f"prompt_injection:malicious={score_malicious}",
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violation_return_message="Sorry, I cannot do this.",
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)
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return ShieldResponse(
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is_violation=False,
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)
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class JailbreakShield(PromptGuardShield):
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def __init__(
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self,
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model_dir: str,
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threshold: float = 0.9,
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temperature: float = 1.0,
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on_violation_action: OnViolationAction = OnViolationAction.RAISE,
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):
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super().__init__(
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model_dir=model_dir,
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threshold=threshold,
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temperature=temperature,
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mode=PromptGuardShield.Mode.JAILBREAK,
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on_violation_action=on_violation_action,
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)
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class InjectionShield(PromptGuardShield):
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def __init__(
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self,
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model_dir: str,
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threshold: float = 0.9,
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temperature: float = 1.0,
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on_violation_action: OnViolationAction = OnViolationAction.RAISE,
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):
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super().__init__(
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model_dir=model_dir,
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threshold=threshold,
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temperature=temperature,
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mode=PromptGuardShield.Mode.INJECTION,
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on_violation_action=on_violation_action,
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)
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|
|
@ -1,107 +0,0 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
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# This source code is licensed under the terms described in the LICENSE file in
|
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# the root directory of this source tree.
|
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|
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from typing import Any, Dict, List
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from llama_stack.distribution.utils.model_utils import model_local_dir
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from llama_stack.apis.inference import * # noqa: F403
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from llama_stack.apis.safety import * # noqa: F403
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from llama_models.llama3.api.datatypes import * # noqa: F403
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from llama_stack.distribution.datatypes import Api
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from llama_stack.providers.datatypes import ShieldsProtocolPrivate
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from .base import OnViolationAction, ShieldBase
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from .config import SafetyConfig
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from .llama_guard import LlamaGuardShield
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from .prompt_guard import InjectionShield, JailbreakShield, PromptGuardShield
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PROMPT_GUARD_MODEL = "Prompt-Guard-86M"
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SUPPORTED_SHIELDS = [ShieldType.llama_guard, ShieldType.prompt_guard]
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class MetaReferenceSafetyImpl(Safety, ShieldsProtocolPrivate):
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def __init__(self, config: SafetyConfig, deps) -> None:
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self.config = config
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self.inference_api = deps[Api.inference]
|
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|
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self.available_shields = []
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if config.llama_guard_shield:
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self.available_shields.append(ShieldType.llama_guard)
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if config.enable_prompt_guard:
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self.available_shields.append(ShieldType.prompt_guard)
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async def initialize(self) -> None:
|
||||
if self.config.enable_prompt_guard:
|
||||
model_dir = model_local_dir(PROMPT_GUARD_MODEL)
|
||||
_ = PromptGuardShield.instance(model_dir)
|
||||
|
||||
async def shutdown(self) -> None:
|
||||
pass
|
||||
|
||||
async def register_shield(self, shield: Shield) -> None:
|
||||
if shield.shield_type not in self.available_shields:
|
||||
raise ValueError(f"Shield type {shield.shield_type} not supported")
|
||||
|
||||
async def run_shield(
|
||||
self,
|
||||
shield_id: str,
|
||||
messages: List[Message],
|
||||
params: Dict[str, Any] = None,
|
||||
) -> RunShieldResponse:
|
||||
shield = await self.shield_store.get_shield(shield_id)
|
||||
if not shield:
|
||||
raise ValueError(f"Shield {shield_id} not found")
|
||||
|
||||
shield_impl = self.get_shield_impl(shield)
|
||||
|
||||
messages = messages.copy()
|
||||
# some shields like llama-guard require the first message to be a user message
|
||||
# since this might be a tool call, first role might not be user
|
||||
if len(messages) > 0 and messages[0].role != Role.user.value:
|
||||
messages[0] = UserMessage(content=messages[0].content)
|
||||
|
||||
# TODO: we can refactor ShieldBase, etc. to be inline with the API types
|
||||
res = await shield_impl.run(messages)
|
||||
violation = None
|
||||
if (
|
||||
res.is_violation
|
||||
and shield_impl.on_violation_action != OnViolationAction.IGNORE
|
||||
):
|
||||
violation = SafetyViolation(
|
||||
violation_level=(
|
||||
ViolationLevel.ERROR
|
||||
if shield_impl.on_violation_action == OnViolationAction.RAISE
|
||||
else ViolationLevel.WARN
|
||||
),
|
||||
user_message=res.violation_return_message,
|
||||
metadata={
|
||||
"violation_type": res.violation_type,
|
||||
},
|
||||
)
|
||||
|
||||
return RunShieldResponse(violation=violation)
|
||||
|
||||
def get_shield_impl(self, shield: Shield) -> ShieldBase:
|
||||
if shield.shield_type == ShieldType.llama_guard:
|
||||
cfg = self.config.llama_guard_shield
|
||||
return LlamaGuardShield(
|
||||
model=cfg.model,
|
||||
inference_api=self.inference_api,
|
||||
excluded_categories=cfg.excluded_categories,
|
||||
)
|
||||
elif shield.shield_type == ShieldType.prompt_guard:
|
||||
model_dir = model_local_dir(PROMPT_GUARD_MODEL)
|
||||
subtype = shield.params.get("prompt_guard_type", "injection")
|
||||
if subtype == "injection":
|
||||
return InjectionShield.instance(model_dir)
|
||||
elif subtype == "jailbreak":
|
||||
return JailbreakShield.instance(model_dir)
|
||||
else:
|
||||
raise ValueError(f"Unknown prompt guard type: {subtype}")
|
||||
else:
|
||||
raise ValueError(f"Unknown shield type: {shield.shield_type}")
|
||||
15
llama_stack/providers/inline/safety/prompt_guard/__init__.py
Normal file
15
llama_stack/providers/inline/safety/prompt_guard/__init__.py
Normal file
|
|
@ -0,0 +1,15 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
from .config import PromptGuardConfig # noqa: F401
|
||||
|
||||
|
||||
async def get_provider_impl(config: PromptGuardConfig, deps):
|
||||
from .prompt_guard import PromptGuardSafetyImpl
|
||||
|
||||
impl = PromptGuardSafetyImpl(config, deps)
|
||||
await impl.initialize()
|
||||
return impl
|
||||
25
llama_stack/providers/inline/safety/prompt_guard/config.py
Normal file
25
llama_stack/providers/inline/safety/prompt_guard/config.py
Normal file
|
|
@ -0,0 +1,25 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
from enum import Enum
|
||||
|
||||
from pydantic import BaseModel, field_validator
|
||||
|
||||
|
||||
class PromptGuardType(Enum):
|
||||
injection = "injection"
|
||||
jailbreak = "jailbreak"
|
||||
|
||||
|
||||
class PromptGuardConfig(BaseModel):
|
||||
guard_type: str = PromptGuardType.injection.value
|
||||
|
||||
@classmethod
|
||||
@field_validator("guard_type")
|
||||
def validate_guard_type(cls, v):
|
||||
if v not in [t.value for t in PromptGuardType]:
|
||||
raise ValueError(f"Unknown prompt guard type: {v}")
|
||||
return v
|
||||
120
llama_stack/providers/inline/safety/prompt_guard/prompt_guard.py
Normal file
120
llama_stack/providers/inline/safety/prompt_guard/prompt_guard.py
Normal file
|
|
@ -0,0 +1,120 @@
|
|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
||||
# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
from typing import Any, Dict, List
|
||||
|
||||
import torch
|
||||
from termcolor import cprint
|
||||
|
||||
from transformers import AutoModelForSequenceClassification, AutoTokenizer
|
||||
|
||||
from llama_stack.distribution.utils.model_utils import model_local_dir
|
||||
from llama_stack.apis.inference import * # noqa: F403
|
||||
from llama_stack.apis.safety import * # noqa: F403
|
||||
from llama_models.llama3.api.datatypes import * # noqa: F403
|
||||
|
||||
from llama_stack.providers.datatypes import ShieldsProtocolPrivate
|
||||
|
||||
from .config import PromptGuardConfig, PromptGuardType
|
||||
|
||||
|
||||
PROMPT_GUARD_MODEL = "Prompt-Guard-86M"
|
||||
|
||||
|
||||
class PromptGuardSafetyImpl(Safety, ShieldsProtocolPrivate):
|
||||
def __init__(self, config: PromptGuardConfig, _deps) -> None:
|
||||
self.config = config
|
||||
|
||||
async def initialize(self) -> None:
|
||||
model_dir = model_local_dir(PROMPT_GUARD_MODEL)
|
||||
self.shield = PromptGuardShield(model_dir, self.config)
|
||||
|
||||
async def shutdown(self) -> None:
|
||||
pass
|
||||
|
||||
async def register_shield(self, shield: Shield) -> None:
|
||||
if shield.shield_type != ShieldType.prompt_guard:
|
||||
raise ValueError(f"Unsupported shield type: {shield.shield_type}")
|
||||
|
||||
async def run_shield(
|
||||
self,
|
||||
shield_id: str,
|
||||
messages: List[Message],
|
||||
params: Dict[str, Any] = None,
|
||||
) -> RunShieldResponse:
|
||||
shield = await self.shield_store.get_shield(shield_id)
|
||||
if not shield:
|
||||
raise ValueError(f"Unknown shield {shield_id}")
|
||||
|
||||
return await self.shield.run(messages)
|
||||
|
||||
|
||||
class PromptGuardShield:
|
||||
def __init__(
|
||||
self,
|
||||
model_dir: str,
|
||||
config: PromptGuardConfig,
|
||||
threshold: float = 0.9,
|
||||
temperature: float = 1.0,
|
||||
):
|
||||
assert (
|
||||
model_dir is not None
|
||||
), "Must provide a model directory for prompt injection shield"
|
||||
if temperature <= 0:
|
||||
raise ValueError("Temperature must be greater than 0")
|
||||
|
||||
self.config = config
|
||||
self.temperature = temperature
|
||||
self.threshold = threshold
|
||||
|
||||
self.device = "cuda"
|
||||
|
||||
# load model and tokenizer
|
||||
self.tokenizer = AutoTokenizer.from_pretrained(model_dir)
|
||||
self.model = AutoModelForSequenceClassification.from_pretrained(
|
||||
model_dir, device_map=self.device
|
||||
)
|
||||
|
||||
async def run(self, messages: List[Message]) -> RunShieldResponse:
|
||||
message = messages[-1]
|
||||
text = interleaved_text_media_as_str(message.content)
|
||||
|
||||
# run model on messages and return response
|
||||
inputs = self.tokenizer(text, return_tensors="pt")
|
||||
inputs = {name: tensor.to(self.model.device) for name, tensor in inputs.items()}
|
||||
with torch.no_grad():
|
||||
outputs = self.model(**inputs)
|
||||
logits = outputs[0]
|
||||
probabilities = torch.softmax(logits / self.temperature, dim=-1)
|
||||
score_embedded = probabilities[0, 1].item()
|
||||
score_malicious = probabilities[0, 2].item()
|
||||
cprint(
|
||||
f"Ran PromptGuardShield and got Scores: Embedded: {score_embedded}, Malicious: {score_malicious}",
|
||||
color="magenta",
|
||||
)
|
||||
|
||||
violation = None
|
||||
if self.config.guard_type == PromptGuardType.injection.value and (
|
||||
score_embedded + score_malicious > self.threshold
|
||||
):
|
||||
violation = SafetyViolation(
|
||||
violation_level=ViolationLevel.ERROR,
|
||||
user_message="Sorry, I cannot do this.",
|
||||
metadata={
|
||||
"violation_type": f"prompt_injection:embedded={score_embedded},malicious={score_malicious}",
|
||||
},
|
||||
)
|
||||
elif (
|
||||
self.config.guard_type == PromptGuardType.jailbreak.value
|
||||
and score_malicious > self.threshold
|
||||
):
|
||||
violation = SafetyViolation(
|
||||
violation_level=ViolationLevel.ERROR,
|
||||
violation_type=f"prompt_injection:malicious={score_malicious}",
|
||||
violation_return_message="Sorry, I cannot do this.",
|
||||
)
|
||||
|
||||
return RunShieldResponse(violation=violation)
|
||||
Loading…
Add table
Add a link
Reference in a new issue