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| Developed by | Guardrails AI |
| Date of development | Feb 15, 2024 |
| Validator type | Privacy, Security |
| Blog | |
| License | Apache 2 |
| Input/Output | Input, Output |
This validator ensures that any given text does not contain PII. This validator uses Microsoft's Presidio (https://github.com/microsoft/presidio) to detect PII in the text. If PII is detected, the validator will fail with a programmatic fix that anonymizes the text. Otherwise, the validator will pass.
$ guardrails hub install hub://guardrails/detect_pii
# Import Guard and Validator
from guardrails.hub import DetectPII
from guardrails import Guard
# Setup Guard
guard = Guard().use(
DetectPII, ["EMAIL_ADDRESS", "PHONE_NUMBER"], "exception"
)
guard.validate("Good morning!") # Validator passes
try:
guard.validate(
"If interested, apply at not_a_real_email@guardrailsai.com"
) # Validator fails
except Exception as e:
print(e)
Output:
Validation failed for field with errors: The following text in your response contains PII:
If interested, apply at not_a_real_email@guardrailsai.com
In this example, we apply the validator to a string field of a JSON output generated by an LLM.
# Import Guard and Validator
from pydantic import BaseModel, Field
from guardrails.hub import DetectPII
from guardrails import Guard
# Initialize Validator
val = DetectPII(pii_entities=["EMAIL_ADDRESS", "PHONE_NUMBER"], on_fail="exception")
# Create Pydantic BaseModel
class UserHistory(BaseModel):
name: str
last_msg: str = Field(description="Last message sent by user", validators=[val])
# Create a Guard to check for valid Pydantic output
guard = Guard.from_pydantic(output_class=UserHistory)
# Run LLM output generating JSON through guard
try:
guard.parse(
"""
{
"name": "John Smith",
"last_msg": "My account isn't working. My username is not_a_real_email@guardrailsai.com"
}
"""
)
except Exception as e:
print(e)
Output:
Validation failed for field with errors: The following text in your response contains PII:
My account isn't working. My username is not_a_real_email@guardrailsai.com
__init__(self, pii_entities, on_fail="noop")
Initializes a new instance of the Validator class.
Parameters
pii_entities (Union[str, List(str)]): The types of PII entities to filter out. For a full list of entities look at https://microsoft.github.io/presidio/on_fail (str, Callable): The policy to enact when a validator fails. If str, must be one of reask, fix, filter, refrain, noop, exception or fix_reask. Otherwise, must be a function that is called when the validator fails.validate(self, value, metadata={}) -> ValidationResult
Validates the given value using the rules defined in this validator, relying on the metadata provided to customize the validation process. This method is automatically invoked by guard.parse(...), ensuring the validation logic is applied to the input data.
Note:
guard.parse(...) where this method will be called internally for each associated Validator.guard.parse(...), ensure to pass the appropriate metadata dictionary that includes keys and values required by this validator. If guard is associated with multiple validators, combine all necessary metadata into a single dictionary.Parameters
value (Any): The input value to validate.
metadata (dict): A dictionary containing metadata required for validation. Keys and values must match the expectations of this validator.
| Key | Type | Description | Default |
|---|---|---|---|
pii_entities | Union[str, list(str)] | The types of PII entities to filter out. For a full list of entities look at https://microsoft.github.io/presidio/. When pii_entities are provided in metadata, it overrides the pii_entities set during validator initialization. | N/A |
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