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 is a template for creating other validators, but for demonstrative purposes it ensures that a generated output is the literal pass.

Requirements

• Dependencies:

  • guardrails-ai>=0.4.0

• Foundation model access keys:

  • OPENAI_API_KEY

Installation

$ guardrails hub install hub://guardrails/validator_template

Usage Examples

Validating string output via Python

In this example, we apply the validator to a string output generated by an LLM.

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

# Setup Guard
guard = Guard().use(
    ValidatorTemplate
)

guard.validate("pass")  # Validator passes
guard.validate("fail")  # Validator fails

Validating JSON output via Python

In this example, we apply the validator to a string field of a JSON output generated by an LLM.

# Import Guard and Validator
from pydantic import BaseModel, Field
from guardrails.hub import ValidatorTemplate
from guardrails import Guard

# Initialize Validator
val = ValidatorTemplate()

# Create Pydantic BaseModel
class Process(BaseModel):
		process_name: str
		status: str = Field(validators=[val])

# Create a Guard to check for valid Pydantic output
guard = Guard.from_pydantic(output_class=Process)

# Run LLM output generating JSON through guard
guard.parse("""
{
	"process_name": "templating",
	"status": "pass"
}
""")

API Reference

__init__(self, on_fail="noop")

Initializes a new instance of the ValidatorTemplate class.

Parameters

• arg_1 (str): A placeholder argument to demonstrate how to use init arguments.
• arg_2 (str): Another placeholder argument to demonstrate how to use init arguments.
• 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. Keys and values must match the expectations of this validator.

  Key	Type	Description	Default
  key1	String	Description of key1's role.	N/A