Overview

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

Description

Intended Use

This validator ensures that a generated output is parseable as valid JSON.

Requirements

• Dependencies:
  • guardrails-ai>=0.4.0

Installation

$ guardrails hub install hub://guardrails/valid_json

Usage Examples

Validating string output via Python

In this example, we’ll test that a generated value is valid json.

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

# Setup Guard
guard = Guard().use(ValidJson, on_fail="exception")

guard.validate('{ "value": "a test value" }')  # Validator passes

try:
    guard.validate(
        '{ "value": "a test value", }'
    )  # Validator fails; note the trailing comma
except Exception as e:
    print(e)

Output:

Validation failed for field with errors: Value is not parseable as valid JSON! Reason: Expecting property name enclosed in double quotes: line 1 column 28 (char 27)

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.

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:

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.