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is_compliant is being deprecated. Avoid using it for new integrations. Use data_privacy_compliance for new implementations.

result = evaluator.evaluate(
    eval_templates="data_privacy_compliance",
    inputs={
        "output": "Dear Sir, I hope this email finds you well. I look forward to any insights or advice you might have whenever you have a free moment"
    },
    model_name="turing_flash"
)

print(result.eval_results[0].output)
print(result.eval_results[0].reason)
Input
Required InputTypeDescription
outputstringGenerated content by the model to be evaluated for compliance
Output
FieldDescription
ResultReturns Passed if the content is compliant with guidelines and policies, or Failed if it’s non-compliant
ReasonProvides a detailed explanation of the evaluation

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What to do If you get Undesired Results

If the content is evaluated as non-compliant (Failed) and you want to improve it:
  • Remove any potentially offensive, harmful, or discriminatory language
  • Avoid content that could be interpreted as promoting illegal activities
  • Ensure respectful and professional tone throughout
  • Remove mentions of restricted topics based on relevant guidelines
  • Avoid aggressive, threatening, or harassing language
  • Eliminate content that could be interpreted as deceptive or manipulative
  • Check for privacy violations or sharing of sensitive information
  • Consider cultural sensitivities and avoid stereotyping

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Comparing Is Compliant with Similar Evals

  • Content Safety Violation: Is Compliant provides a broader assessment of guideline adherence, while Content Safety Violation focuses specifically on detecting harmful, unsafe content.
  • Is Harmful Advice: Is Compliant evaluates overall policy adherence, whereas Is Harmful Advice specifically identifies potentially dangerous recommendations.
  • Toxicity: Is Compliant evaluates general policy compliance, while Toxicity specifically measures harmful or offensive language.