Overview

Description

Intended Use

This validator ensures that a generated output is in uppercase.

Requirements

Dependencies:
- guardrails-ai>=0.4.0

Installation

$ guardrails hub install hub://guardrails/uppercase

Usage Examples

Validating string output via Python

In this example, we’ll test that a generated sentence is uppercase.

# Import Guard and Validator
from guardrails import Guard
from guardrails.hub import UpperCase

# Setup Guard
guard = Guard().use(UpperCase, 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 uppercase.

API Reference

__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:

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 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.