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| Developed by | Tryolabs |
| Date of development | Feb 15, 2024 |
| Validator type | Format |
| Blog | |
| License | Apache 2 |
| Input/Output | Output |
This validator checks if a text is related with a topic.
Dependencies:
Foundation model access keys:
$ guardrails hub install hub://tryolabs/restricttotopic
In this example, we apply the validator to a string output generated by an LLM.
# Import Guard and Validator
from guardrails.hub import RestrictToTopic
from guardrails import Guard
# Setup Guard
guard = Guard().use(
RestrictToTopic(
valid_topics=["sports"],
invalid_topics=["music"],
disable_classifier=True,
disable_llm=False,
on_fail="exception"
)
)
guard.validate("""
In Super Bowl LVII in 2023, the Chiefs clashed with the Philadelphia Eagles in a fiercely contested battle, ultimately emerging victorious with a score of 38-35.
""") # Validator passes
guard.validate("""
The Beatles were a charismatic English pop-rock band of the 1960s.
""") # Validator fails
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 RestrictToTopic
from guardrails import Guard
# Initialize Validator
val = RestrictToTopic(
valid_topics=["sports"],
disable_classifier=True,
disable_llm=False,
on_fail="exception"
)
# Create Pydantic BaseModel
class TopicSummary(BaseModel):
topic: str
summary: str = Field(validators=[val])
# Create a Guard to check for valid Pydantic output
guard = Guard.from_pydantic(output_class=TopicSummary)
# Run LLM output generating JSON through guard
guard.parse("""
{
"topic": "Super Bowl LVII",
"summary": "In Super Bowl LVII in 2023, the Chiefs clashed with the Philadelphia Eagles in a fiercely contested battle, ultimately emerging victorious with a score of 38-35."
}
""")
__init__(self, on_fail="noop")
Initializes a new instance of the RestrictToTopic class.
Parameters
valid_topics (List[str]): topics that the text should be about (one or many).invalid_topics (List[str]): topics that the text cannot be about. Defaults to [].device (int): Device ordinal for CPU/GPU supports for Zero-Shot classifier. Setting this to -1 will leverage CPU, a positive will run the Zero-Shot model on the associated CUDA device id. Defaults to -1.model (str): The Zero-Shot model that will be used to classify the topic. See a list of all models here: https://huggingface.co/models?pipeline_tag=zero-shot-classification. Defaults to facebook/bart-large-mnli.llm_callable (Union[str, Callable, None]): Either the name of the OpenAI model, or a callable that takes a prompt and returns a response. Defaults to gpt-3.5-turbo.disable_classifier (bool): Controls whether to use the Zero-Shot model. At least one of disable_classifier and disable_llm must be False. Defaults to False.disable_llm (bool): Controls whether to use the LLM fallback. At least one of disable_classifier and disable_llm must be False. Defaults to False.model_threshold (float): The threshold used to determine whether to accept a topic from the Zero-Shot model. Must be a number between 0 and 1. Defaults to 0.5.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:
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.