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| Developed by | GroundedAI |
|---|---|
| Date of development | October 9, 2024 |
| Validator type | Hallucination |
| Blog | |
| License | Apache 2 |
| Input/Output | Output |
This validator uses a fine-tuned language model to detect hallucinations in AI-generated responses. It evaluates whether a given response is grounded in the provided context or if it contains factually incorrect or nonsensical information.
Dependencies:
Foundation model access:
$ guardrails hub install hub://groundedai/grounded_ai_hallucination
In this example, we apply the validator to check if an AI-generated response is a hallucination.
from guardrails.hub import GroundedAIHallucination
from guardrails import Guard
guard = Guard().use(GroundedAIHallucination(quant=True))
guard.validate("The capital of France is London.", metadata={
"query": "What is the capital of France?",
"reference": "The capital of France is Paris."
})
>>> # Validator fails
guard.validate("The capital of France is Paris.", metadata={
"query": "What is the capital of France?",
"reference": "The capital of France is Paris."
})
>>> # Validator passes
# with llm
messages = [{"role":"user", "content":"What is the capital of France?"}]
guard(
messages=messages,
model="gpt-4o-mini",
metadata={
"query": messages[0]["content"],
"reference": "The capital of France is Paris."
})
>>> # Validator passes
__init__(self, quant: bool, base_prompt: Optional[str] = HALLUCINATION_EVAL_BASE)
Initializes a new instance of the GroundedAIHallucination class.
Parameters
quant (bool): Whether to use quantization for the model.base_prompt (Optional[str]): The base prompt template for hallucination evaluation. Defaults to HALLUCINATION_EVAL_BASE, but you may customize this to your need.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: str, metadata: Dict = {}) -> ValidationResult
Validates whether the given response is a hallucination based on the provided query and reference.
Parameters
value (str): A string The AI-generated response to validate.metadata (dict): Additional metadata (not used in this validator).
query (str): The original question or prompt.reference (str): Optional reference information for fact-checking.Returns
ValidationResult: Indicates whether the validation passed or failed.