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from endpoints.api_models import OutputGuardrailsConfig , LLMResponse | |
from model_inference.groundedness_checker import GroundednessChecker | |
import re | |
# | |
groundedness_checker = GroundednessChecker(model_path="./grounding_detector") | |
# A simple result class to hold individual check outcomes. | |
class Result: | |
def __init__(self): | |
self.details = {} | |
def add(self, rule_name: str, passed: bool): | |
self.details[rule_name] = passed | |
def grounded(self) -> bool: | |
# The response is considered "grounded" if all enabled rules pass. | |
return all(self.details.values()) | |
class ContextualGroundednessCheck: | |
name = "Contextual Groundedness" | |
def check(self,llm_response:LLMResponse) -> bool: | |
groundedness_check = groundedness_checker.check(llm_response.question, llm_response.answer, llm_response.context) | |
print(groundedness_check) | |
return groundedness_check['is_grounded'] | |
class ToxicityRule: | |
name = "Toxicity" | |
def check(self, llm_response:LLMResponse) -> bool: | |
no_toxicity = True | |
matched = re.search(r"(hate|kill|suicide|selfharm)", llm_response.answer, re.IGNORECASE) | |
if matched: | |
no_toxicity = False | |
return no_toxicity | |
# Manager class to load and execute the enabled guardrail rules. | |
class GuardrailsManager: | |
def __init__(self, config: OutputGuardrailsConfig): | |
self.config = config | |
self.rules = self.load_rules() | |
def load_rules(self): | |
rules = [] | |
if self.config.contextual_grounding: | |
rules.append(ContextualGroundednessCheck()) | |
if self.config.toxicity: | |
rules.append(ToxicityRule()) | |
# Add additional rules based on configuration here. | |
return rules | |
def check(self, llm_response: LLMResponse) -> Result: | |
result = Result() | |
for rule in self.rules: | |
rule_result = rule.check(llm_response) | |
result.add(rule.name, rule_result) | |
return result | |