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| Developed by | Cartesia AI |
| Date of development | Feb 15, 2024 |
| Validator type | Format |
| Blog | |
| License | Apache 2 |
| Input/Output | Output |
This validator checks if an LLM-generated text contains names of any drugs. It uses a pre-specified list of drug names to check for matches in the input text. If a match is found, the validator fails.
$ guardrails hub install hub://cartesia/mentions_drugs
In this example, we use the mentions_drugs validator on any LLM generated text.
# Import Guard and Validator
from guardrails import Guard
from guardrails.hub import MentionsDrugs
# Setup the Guard with the validator
guard = Guard().use(MentionsDrugs, on_fail="exception")
# Test passing response
guard.validate("You should take this medicine every day after breakfast.")
# Test failing response
try:
response = guard.validate(
"Take one dose of aspirin each night before going to sleep."
)
except Exception as e:
print(e)
Output:
Validation failed for field with errors: The generated text contains a drug name.
__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. 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. No additional metadata keys are needed for this validator.The validator playground is available to authenticated users. Please log in to use it.