Profanity Metric

pydantic model ibm_watsonx_gov.metrics.profanity.profanity_metric.ProfanityMetric

Bases: GenAIMetric

Defines the Profanity metric class.

The Profanity metric measures the risk of use of language considered offensive or socially unacceptable in a given context. This primarily refers to curse words, swear words, and crude expressions, excluding slurs or derogatory terms targeting specific groups. It is computed using the granite guardian model.

Examples

  1. Create Profanity metric with default parameters and compute using metrics evaluator.
    metric = ProfanityMetric()
    result = MetricsEvaluator().evaluate(data={"input_text": "...", metrics=[metric])
    
  2. Create Profanity metric with a custom threshold.
    threshold  = MetricThreshold(type="lower_limit", value=0.5)
    metric = ProfanityMetric(threshold=threshold)
    

Show JSON schema
{
   "title": "ProfanityMetric",
   "description": "Defines the Profanity metric class.\n\nThe Profanity metric measures the risk of use of language considered offensive or socially unacceptable in a given context. This primarily refers to curse words, swear words, and crude expressions, excluding slurs or derogatory terms targeting specific groups.\nIt is computed using the granite guardian model.\n\nExamples:\n    1. Create Profanity metric with default parameters and compute using metrics evaluator.\n        .. code-block:: python\n\n            metric = ProfanityMetric()\n            result = MetricsEvaluator().evaluate(data={\"input_text\": \"...\", metrics=[metric])\n\n    2. Create Profanity metric with a custom threshold.\n        .. code-block:: python\n\n            threshold  = MetricThreshold(type=\"lower_limit\", value=0.5)\n            metric = ProfanityMetric(threshold=threshold)",
   "type": "object",
   "properties": {
      "name": {
         "const": "profanity",
         "default": "profanity",
         "description": "The profanity metric name.",
         "title": "Name",
         "type": "string"
      },
      "thresholds": {
         "default": [
            {
               "type": "lower_limit",
               "value": 0.7
            }
         ],
         "description": "The metric thresholds.",
         "items": {
            "$ref": "#/$defs/MetricThreshold"
         },
         "title": "Thresholds",
         "type": "array"
      },
      "tasks": {
         "default": [
            "question_answering",
            "classification",
            "summarization",
            "generation",
            "extraction",
            "retrieval_augmented_generation"
         ],
         "description": "The list of supported tasks.",
         "items": {
            "$ref": "#/$defs/TaskType"
         },
         "title": "Tasks",
         "type": "array"
      },
      "group": {
         "$ref": "#/$defs/MetricGroup",
         "default": "content_safety",
         "description": "The metric group.",
         "title": "Group"
      },
      "is_reference_free": {
         "default": true,
         "description": "Decides whether this metric needs a reference for computation",
         "title": "Is Reference Free",
         "type": "boolean"
      },
      "method": {
         "const": "granite_guardian",
         "default": "granite_guardian",
         "description": "The method used to compute harm metric.",
         "title": "Method",
         "type": "string"
      },
      "metric_dependencies": {
         "default": [],
         "description": "Metrics that needs to be evaluated first",
         "items": {
            "$ref": "#/$defs/GenAIMetric"
         },
         "title": "Metric Dependencies",
         "type": "array"
      }
   },
   "$defs": {
      "GenAIMetric": {
         "description": "Defines the Generative AI metric interface",
         "properties": {
            "name": {
               "description": "The name of the metric",
               "title": "Metric Name",
               "type": "string"
            },
            "thresholds": {
               "default": [],
               "description": "The list of thresholds",
               "items": {
                  "$ref": "#/$defs/MetricThreshold"
               },
               "title": "Thresholds",
               "type": "array"
            },
            "tasks": {
               "description": "The task types this metric is associated with.",
               "items": {
                  "$ref": "#/$defs/TaskType"
               },
               "title": "Tasks",
               "type": "array"
            },
            "group": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/MetricGroup"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The metric group this metric belongs to."
            },
            "is_reference_free": {
               "default": true,
               "description": "Decides whether this metric needs a reference for computation",
               "title": "Is Reference Free",
               "type": "boolean"
            },
            "method": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The method used to compute the metric.",
               "title": "Method"
            },
            "metric_dependencies": {
               "default": [],
               "description": "Metrics that needs to be evaluated first",
               "items": {
                  "$ref": "#/$defs/GenAIMetric"
               },
               "title": "Metric Dependencies",
               "type": "array"
            }
         },
         "required": [
            "name",
            "tasks"
         ],
         "title": "GenAIMetric",
         "type": "object"
      },
      "MetricGroup": {
         "enum": [
            "retrieval_quality",
            "answer_quality",
            "content_safety",
            "performance",
            "usage",
            "tool_call_quality",
            "readability"
         ],
         "title": "MetricGroup",
         "type": "string"
      },
      "MetricThreshold": {
         "description": "The class that defines the threshold for a metric.",
         "properties": {
            "type": {
               "description": "Threshold type. One of 'lower_limit', 'upper_limit'",
               "enum": [
                  "lower_limit",
                  "upper_limit"
               ],
               "title": "Type",
               "type": "string"
            },
            "value": {
               "default": 0,
               "description": "The value of metric threshold",
               "title": "Threshold value",
               "type": "number"
            }
         },
         "required": [
            "type"
         ],
         "title": "MetricThreshold",
         "type": "object"
      },
      "TaskType": {
         "description": "Supported task types for generative AI models",
         "enum": [
            "question_answering",
            "classification",
            "summarization",
            "generation",
            "extraction",
            "retrieval_augmented_generation"
         ],
         "title": "TaskType",
         "type": "string"
      }
   }
}

Fields:
field group: ', frozen=True)] = MetricGroup.CONTENT_SAFETY

The metric group.

field method: Annotated[Literal['granite_guardian'], FieldInfo(annotation=NoneType, required=False, default='granite_guardian', title='Method', description='The method used to compute harm metric.')] = 'granite_guardian'

The method used to compute harm metric.

field name: Annotated[Literal['profanity'], FieldInfo(annotation=NoneType, required=False, default='profanity', title='Name', description='The profanity metric name.', frozen=True)] = 'profanity'

The profanity metric name.

field tasks: Annotated[list[TaskType], FieldInfo(annotation=NoneType, required=False, default=['question_answering', 'classification', 'summarization', 'generation', 'extraction', 'retrieval_augmented_generation'], title='Tasks', description='The list of supported tasks.', frozen=True)] = ['question_answering', 'classification', 'summarization', 'generation', 'extraction', 'retrieval_augmented_generation']

The list of supported tasks.

field thresholds: Annotated[list[MetricThreshold], FieldInfo(annotation=NoneType, required=False, default=[MetricThreshold(type='lower_limit', value=0.7)], title='Thresholds', description='The metric thresholds.')] = [MetricThreshold(type='lower_limit', value=0.7)]

The metric thresholds.

evaluate(data: DataFrame | dict, configuration: GenAIConfiguration, **kwargs)
async evaluate_async(data: DataFrame, configuration: GenAIConfiguration, **kwargs) list[AggregateMetricResult]
model_post_init(context: Any, /) None

We need to both initialize private attributes and call the user-defined model_post_init method.

pydantic model ibm_watsonx_gov.metrics.profanity.profanity_metric.ProfanityResult

Bases: RecordMetricResult

Show JSON schema
{
   "title": "ProfanityResult",
   "type": "object",
   "properties": {
      "name": {
         "default": "profanity",
         "title": "Name",
         "type": "string"
      },
      "method": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The method used to compute this metric result.",
         "examples": [
            "token_recall"
         ],
         "title": "Method"
      },
      "provider": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The provider used to compute this metric result.",
         "title": "Provider"
      },
      "value": {
         "anyOf": [
            {
               "type": "number"
            },
            {
               "type": "string"
            },
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "description": "The metric value.",
         "title": "Value"
      },
      "errors": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/Error"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The list of error messages",
         "title": "Errors"
      },
      "additional_info": {
         "anyOf": [
            {
               "type": "object"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The additional information about the metric result.",
         "title": "Additional Info"
      },
      "group": {
         "$ref": "#/$defs/MetricGroup",
         "default": "content_safety"
      },
      "thresholds": {
         "default": [],
         "description": "The metric thresholds",
         "items": {
            "$ref": "#/$defs/MetricThreshold"
         },
         "title": "Thresholds",
         "type": "array"
      },
      "record_id": {
         "description": "The record identifier.",
         "examples": [
            "record1"
         ],
         "title": "Record Id",
         "type": "string"
      },
      "record_timestamp": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The record timestamp.",
         "examples": [
            "2025-01-01T00:00:00.000000Z"
         ],
         "title": "Record Timestamp"
      }
   },
   "$defs": {
      "Error": {
         "properties": {
            "code": {
               "description": "The error code",
               "title": "Code",
               "type": "string"
            },
            "message_en": {
               "description": "The error message in English.",
               "title": "Message En",
               "type": "string"
            },
            "parameters": {
               "default": [],
               "description": "The list of parameters to construct the message in a different locale.",
               "items": {},
               "title": "Parameters",
               "type": "array"
            }
         },
         "required": [
            "code",
            "message_en"
         ],
         "title": "Error",
         "type": "object"
      },
      "MetricGroup": {
         "enum": [
            "retrieval_quality",
            "answer_quality",
            "content_safety",
            "performance",
            "usage",
            "tool_call_quality",
            "readability"
         ],
         "title": "MetricGroup",
         "type": "string"
      },
      "MetricThreshold": {
         "description": "The class that defines the threshold for a metric.",
         "properties": {
            "type": {
               "description": "Threshold type. One of 'lower_limit', 'upper_limit'",
               "enum": [
                  "lower_limit",
                  "upper_limit"
               ],
               "title": "Type",
               "type": "string"
            },
            "value": {
               "default": 0,
               "description": "The value of metric threshold",
               "title": "Threshold value",
               "type": "number"
            }
         },
         "required": [
            "type"
         ],
         "title": "MetricThreshold",
         "type": "object"
      }
   },
   "required": [
      "value",
      "record_id"
   ]
}

Config:
  • arbitrary_types_allowed: bool = True

  • use_enum_values: bool = True

Fields:
field group: MetricGroup = MetricGroup.CONTENT_SAFETY
field name: str = 'profanity'