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| Developed by | Guardrails AI |
|---|---|
| Date of development | Feb 15, 2024 |
| Validator type | Format |
| Blog | - |
| License | Apache 2 |
| Input/Output | Output |
This validator ensures that a generated string ends with an expected text. This validator works on strings or lists.
$ guardrails hub install hub://guardrails/ends_with
In this example, we apply the validator to a string generated by an LLM.
# Import Guard and Validator
from guardrails import Guard
from guardrails.hub import EndsWith
# Setup Guard
guard = Guard().use(EndsWith, end="a", on_fail="exception")
response = guard.validate("Llama") # Validator passes
try:
response = guard.validate("Mistral") # Validator fails
except Exception as e:
print(e)
Output:
Validation failed for field with errors: Mistral must end with a
In this example, we apply the validator to a list field of a generated JSON output by an LLM.
# Import Guard and Validator
from pydantic import BaseModel, Field
from guardrails.hub import EndsWith
from guardrails import Guard
# Initialize Validator
val = EndsWith(end="all", on_fail="exception")
class Article(BaseModel):
"""Info about article."""
title: str = Field(description="Title of the article")
tags: list[str] = Field(
description="Tags that describe the article", validators=[val]
)
# Create a Guard to check for valid Pydantic output
guard = Guard.from_pydantic(output_class=Article)
# Run LLM output generating JSON through guard
guard.parse(
"""
{
"title": "The LLM Infra Stack",
"tags": ["infra", "ai", "quick read", "all"]
}
"""
)
try:
# Run LLM output generating JSON through guard
guard.parse(
"""
{
"title": "The LLM Infra Stack",
"tags": ["infra", "ai", "quick read"]
}
"""
)
except Exception as e:
print(e)
Output:
Validation failed for field with errors: ['infra', 'ai', 'quick read'] must end with all
__init__(self, on_fail="noop")
Initializes a new instance of the Validator class.
Parameters:
end (str): The expected end to the string or list. For strings, the input must end with this character. For lists, the last element must be equal to this string value.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:
guard.parse(...) where this method will be called internally for each associated Validator.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.The validator playground is available to authenticated users. Please log in to use it.