reflex-dev / valid_python_validator

Valid Python Guardrails AI validator - Validates that there are no Python syntactic bugs in the generated code.

Overview

Developed by	Reflex
Date of development	Feb 15, 2024
Validator type	Format
Blog	-
License	Apache 2
Input/Output	Output

Description

This validator checks if a string is valid Python syntax by trying to parse the string into an abstract syntax tree. Note that this validator doesn’t check for things such as correct argument names, etc.

Requirements

• Dependencies:
  • guardrails-ai>=0.4.0

Installation

guardrails hub install hub://reflex/valid_python

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 ValidPython
from guardrails import Guard

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

# Correct python
correct_python = """
import os

def foo():
    print(f"Current path is: {os.getcwd()}")

foo()
"""

incorrect_python = """
import os

def foo()
    print f"Current path is: {os.getcwd()}"

foo()
"""

guard.validate(correct_python)  # Validator passes
try:
    guard.validate(incorrect_python)  # Validator fails
except Exception as e:
    print(e)

Output:

Validation failed for field with errors: Syntax error: expected ':'

API Reference

__init__(self, on_fail="noop")

Initializes a new instance of the ValidPython 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.