Evaluator families group together evaluators that perform the same function. Evaluators in the same family share evaluator profiles and accept the same set of inputs. Importantly, the performance and cost of evaluators in the family may differ.

Custom Evaluator Family

Custom evaluators perform evaluations based on pass criteria defined in natural language, such as "The MODEL OUTPUT should be free from brackets". Custom evaluators also support active learning, which means that you can improve their performance by annotating historical evaluations with thumbs up or thumbs down. To learn more about Custom Evaluators, visit their documentation page.

Required Input Fields

• evaluated_model_input
• evaluated_model_output

Optional Input Fields

• evaluated_model_gold_answer

Aliases

Evaluators

PHI (Protected Health Information) Evaluator Family

Checks for protected health information (PHI), defined broadly as any information about an individual's health status or provision of healthcare.

Required Input Fields

• evaluated_model_output

Optional Input Fields

None

Aliases

Evaluators

Metrics Evaluator Family

Computes common NLP metrics on the output and label fields to measure semantic overlap and similarity. Currently supports the bleu and rouge frameworks.

Required Input Fields

• evaluated_model_output
• evaluated_model_gold_answer

Optional Input Fields

None

Aliases

Evaluators

Exact Match Evaluator Family

Check that your model output is the same as the provided gold answer. Useful for checking boolean or multiple choice model outputs.

Required Input Fields

• evaluated_model_output
• evaluated_model_gold_answer

Optional Input Fields

None

Aliases

Evaluators

PII (Personally Identifiable Information) Evaluator Family

Checks for personally identifiable information (PII). PII is information that, in conjunction with other data, can identify an individual.

Required Input Fields

• evaluated_model_output

Optional Input Fields

None

Aliases

Evaluators

Retrieval Answer Relevance Evaluator Family

Checks whether the model output is on-topic to the input question. Does not measure correctness.

Required Input Fields

• evaluated_model_input
• evaluated_model_output

Optional Input Fields

None

Aliases

Evaluators

Retrieval Context Sufficiency Evaluator Family

Checks whether the retrieved context is sufficient to generate an output similar in meaning to the label. The label should be the correct evaluation result.

Required Input Fields

• evaluated_model_input
• evaluated_model_output
• evaluated_model_gold_answer
• evaluated_model_retrieved_context

Optional Input Fields

None

Aliases

Evaluators

Retrieval Hallucination Evaluator Family

Checks whether the LLM response is hallucinatory, i.e. the output is not grounded in the provided context.

Required Input Fields

• evaluated_model_input
• evaluated_model_output
• evaluated_model_retrieved_context

Optional Input Fields

None

Aliases

Evaluators

Lynx Retrieval Hallucination Evaluator Family

Checks whether the LLM response is hallucinatory, i.e. the output is not grounded in the provided context. Uses Patronus Lynx to power the evaluation. See the research paper here .

Required Input Fields

• evaluated_model_input
• evaluated_model_output
• evaluated_model_retrieved_context

Optional Input Fields

None

Aliases

Evaluators

Retrieval Context Relevance Family

Checks whether the retrieved context is on-topic or relevant to the input question.

Required Input Fields

• evaluated_model_input
• evaluated_model_retrieved_context

Optional Input Fields

None

Aliases

Evaluators

Toxicity Evaluator Family

Checks output for abusive and hateful messages.

Required Input Fields

• evaluated_model_output

Optional Input Fields

None

Aliases

Evaluators