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| Developed by | Guardrails AI |
|---|---|
| Date of development | Feb 15, 2024 |
| Validator type | Format |
| Blog | - |
| License | Apache 2 |
| Input/Output | Output |
This validator ensures that a generated output is in lowercase.
guardrails hub install hub://guardrails/lowercase
In this example, we’ll test that a generated sentence is lowercase.
# Import Guard and Validator
from guardrails import Guard
from guardrails.hub import LowerCase
# Setup Guard
guard = Guard().use(LowerCase, on_fail="exception")
response = guard.validate("may december") # Validator passes
try:
response = guard.validate("PAST LIVES") # Validator fails
except Exception as e:
print(e)
Output:
Validation failed for field with errors: Value PAST LIVES is not lowercase.
__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.__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:
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.