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Guardrails AI
Valid URL
1
See on Github
Validates that text is a syntactically-valid URL
en
string
Formatting
CodeGen
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Overview

updated 2 years
Developed by:
Guardrails AI
Date of development:
Feb 15, 2024
Validator type:
Format
Blog:
License:
Apache 2
Input/Output:
Output

Playground

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Description
Intended Use

This validator checks that any URL generated by an LLM is valid

Requirements
  • Dependencies:
    • guardrails-ai>=0.4.0
Installation
$ guardrails hub install hub://guardrails/valid_url
Usage Examples
Validating string output via Python

In this example, we use the guardrails/valid_url validator on any LLM generated URL.

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

# Setup Guard
guard = Guard().use(ValidURL, on_fail="exception")
response = guard.validate("http://www.google.com")  # Validator passes

try:
    response = guard.validate("notalink.xyzq")  # Validator fails
except Exception as e:
    print(e)

Output:

Validation failed for field with errors: URL notalink.xyzq is not valid.
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:

  1. 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.
  2. 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.

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.