Overview
Install
pip install guardrails-ai-profanity-freefrom guardrails import Guard
from guardrails_ai.profanity_free import ProfanityFree
guard = Guard().use(ProfanityFree)
guard.validate("some text")This validator ensures that there’s no profanity in any generated text. This validator uses the alt-profanity-check package to check if a string contains profane language.
This validator catches profanity in the English language only.
- Dependencies:
- guardrails-ai>=0.4.0
- alt-profanity-check
pip install guardrails-ai-profanity-free
This validator ships local models. After installing, run the post-install step to download them:
python -m guardrails_ai.profanity_free.post_install
In this example, we apply the validator to a string output generated by an LLM.
# Import Guard and Validator
from guardrails_ai.profanity_free import ProfanityFree
from guardrails import Guard
# Use the Guard with the validator
guard = Guard().use(
ProfanityFree, on_fail="exception"
)
guard.validate(
"""
Director Denis Villeneuve's Dune is a visually stunning and epic adaptation of the classic science fiction novel.
It is reminiscent of the original Star Wars trilogy, with its grand scale and epic storytelling.
"""
) # Test passing response
try:
guard.validate(
"""
He is such a dickhead and a fucking idiot.
"""
) # Test failing response
except Exception as e:
print(e)
Output:
Validation failed for field with errors:
He is such a dickhead and a fucking idiot.
contains profanity. Please return profanity-free output.
__init__(self, on_fail="noop")
Initializes a new instance of the Validator class.
Parameters
on_fail(str, Callable): The policy to enact when a validator fails. Ifstr, must be one ofreask,fix,filter,refrain,noop,exceptionorfix_reask. Otherwise, must be a function that is called when the validator fails.
__call__(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:
- This method should not be called directly by the user. Instead, invoke
guard.parse(...)where this method will be called internally for each associated Validator. - When invoking
guard.parse(...), ensure to pass the appropriatemetadatadictionary that includes keys and values required by this validator. Ifguardis 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. No additional metadata keys are needed for this validator.
MIT — © Guardrails AI.