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")
on_fail
(str, Callable): The policy to enact when a validator fails. Ifstr
, must be one ofreask
,fix
,filter
,refrain
,noop
,exception
orfix_reask
. Otherwise, must be a function that is called when the validator fails.
Initializes a new instance of the Validator class.
Parameters:
__call__(self, value, metadata={}) → ValidationResult
- 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 appropriatemetadata
dictionary that includes keys and values required by this validator. Ifguard
is associated with multiple validators, combine all necessary metadata into a single dictionary. 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.
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:
Parameters: