Topic Relevance Metric

pydantic model ibm_watsonx_gov.metrics.topic_relevance.topic_relevance_metric.TopicRelevanceMetric

Bases: GenAIMetric

Defines the TopicRelevance metric class.

The TopicRelevance metric evaluates how closely the input content aligns with the topic specified by the system_prompt.

Note : system_prompt is mandatory

Examples

1. Create TopicRelevance metric with default parameters and compute using metrics evaluator.

   metric = TopicRelevanceMetric(system_prompt="...")
   result = MetricsEvaluator().evaluate(data={"input_text": "...", metrics=[metric])
   

2. Create TopicRelevance metric with a custom threshold.

   threshold  = MetricThreshold(type="lower_limit", value=0.5)
   metric = TopicRelevanceMetric(threshold=threshold, system_prompt="...")
   

Show JSON schema

{
   "title": "TopicRelevanceMetric",
   "description": "Defines the TopicRelevance metric class.\n\nThe TopicRelevance metric evaluates how closely the input content aligns with the topic specified by the system_prompt.\n\nNote : system_prompt is mandatory\n\nExamples:\n    1. Create TopicRelevance metric with default parameters and compute using metrics evaluator.\n        .. code-block:: python\n\n            metric = TopicRelevanceMetric(system_prompt=\"...\")\n            result = MetricsEvaluator().evaluate(data={\"input_text\": \"...\", metrics=[metric])\n\n    2. Create TopicRelevance metric with a custom threshold.\n        .. code-block:: python\n\n            threshold  = MetricThreshold(type=\"lower_limit\", value=0.5)\n            metric = TopicRelevanceMetric(threshold=threshold, system_prompt=\"...\")",
   "type": "object",
   "properties": {
      "name": {
         "const": "topic_relevance",
         "default": "topic_relevance",
         "description": "The topic relevance metric name.",
         "title": "Name",
         "type": "string"
      },
      "display_name": {
         "const": "Topic Relevance",
         "default": "Topic Relevance",
         "description": "The topic relevance metric display name.",
         "title": "Display Name",
         "type": "string"
      },
      "type_": {
         "default": "ootb",
         "description": "The type of the metric. Indicates whether the metric is ootb or custom.",
         "examples": [
            "ootb",
            "custom"
         ],
         "title": "Metric type",
         "type": "string"
      },
      "value_type": {
         "default": "numeric",
         "description": "The type of the metric value. Indicates whether the metric value is numeric or categorical.",
         "examples": [
            "numeric",
            "categorical"
         ],
         "title": "Metric value type",
         "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": {
         "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"
      },
      "applies_to": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": "message",
         "description": "The tag to indicate for which the metric is applied to. Used for agentic application metric computation.",
         "examples": [
            "message",
            "conversation",
            "sub_agent"
         ],
         "title": "Applies to"
      },
      "mapping": {
         "anyOf": [
            {
               "$ref": "#/$defs/Mapping"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "The data mapping details for the metric which are used to read the values needed to compute the metric.",
         "examples": {
            "items": [
               {
                  "attribute_name": "traceloop.entity.input",
                  "column_name": null,
                  "json_path": "$.inputs.input_text",
                  "lookup_child_spans": false,
                  "name": "input_text",
                  "span_name": "LangGraph.workflow",
                  "type": "input"
               },
               {
                  "attribute_name": "traceloop.entity.output",
                  "column_name": null,
                  "json_path": "$.outputs.generated_text",
                  "lookup_child_spans": false,
                  "name": "generated_text",
                  "span_name": "LangGraph.workflow",
                  "type": "output"
               }
            ],
            "source": "trace"
         },
         "title": "Mapping"
      },
      "system_prompt": {
         "description": "The AI model system prompt which contains instructions to define its overall behavior.",
         "title": "System Prompt",
         "type": "string"
      }
   },
   "$defs": {
      "GenAIMetric": {
         "description": "Defines the Generative AI metric interface",
         "properties": {
            "name": {
               "description": "The name of the metric.",
               "examples": [
                  "answer_relevance",
                  "context_relevance"
               ],
               "title": "Metric Name",
               "type": "string"
            },
            "display_name": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The display name of the metric.",
               "examples": [
                  "Answer Relevance",
                  "Context Relevance"
               ],
               "title": "Metric display name"
            },
            "type_": {
               "default": "ootb",
               "description": "The type of the metric. Indicates whether the metric is ootb or custom.",
               "examples": [
                  "ootb",
                  "custom"
               ],
               "title": "Metric type",
               "type": "string"
            },
            "value_type": {
               "default": "numeric",
               "description": "The type of the metric value. Indicates whether the metric value is numeric or categorical.",
               "examples": [
                  "numeric",
                  "categorical"
               ],
               "title": "Metric value type",
               "type": "string"
            },
            "thresholds": {
               "default": [],
               "description": "The list of thresholds",
               "items": {
                  "$ref": "#/$defs/MetricThreshold"
               },
               "title": "Thresholds",
               "type": "array"
            },
            "tasks": {
               "default": [],
               "description": "The task types this metric is associated with.",
               "items": {
                  "$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": "#/$defs/GenAIMetric"
               },
               "title": "Metric Dependencies",
               "type": "array"
            },
            "applies_to": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": "message",
               "description": "The tag to indicate for which the metric is applied to. Used for agentic application metric computation.",
               "examples": [
                  "message",
                  "conversation",
                  "sub_agent"
               ],
               "title": "Applies to"
            },
            "mapping": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/Mapping"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The data mapping details for the metric which are used to read the values needed to compute the metric.",
               "examples": {
                  "items": [
                     {
                        "attribute_name": "traceloop.entity.input",
                        "column_name": null,
                        "json_path": "$.inputs.input_text",
                        "lookup_child_spans": false,
                        "name": "input_text",
                        "span_name": "LangGraph.workflow",
                        "type": "input"
                     },
                     {
                        "attribute_name": "traceloop.entity.output",
                        "column_name": null,
                        "json_path": "$.outputs.generated_text",
                        "lookup_child_spans": false,
                        "name": "generated_text",
                        "span_name": "LangGraph.workflow",
                        "type": "output"
                     }
                  ],
                  "source": "trace"
               },
               "title": "Mapping"
            }
         },
         "required": [
            "name"
         ],
         "title": "GenAIMetric",
         "type": "object"
      },
      "Mapping": {
         "description": "Defines the field mapping details to be used for computing a metric.",
         "properties": {
            "source": {
               "default": "trace",
               "description": "The source type of the data. Use trace if the data should be read from span in trace. Use tabular if the data is passed as a dataframe.",
               "enum": [
                  "trace",
                  "tabular"
               ],
               "examples": [
                  "trace",
                  "tabular"
               ],
               "title": "Source",
               "type": "string"
            },
            "items": {
               "description": "The list of mapping items for the field. They are used to read the data from trace or tabular data for computing the metric.",
               "items": {
                  "$ref": "#/$defs/MappingItem"
               },
               "title": "Mapping Items",
               "type": "array"
            }
         },
         "required": [
            "items"
         ],
         "title": "Mapping",
         "type": "object"
      },
      "MappingItem": {
         "description": "The mapping details to be used for reading the values from the data.",
         "properties": {
            "name": {
               "description": "The name of the item.",
               "examples": [
                  "input_text",
                  "generated_text",
                  "context",
                  "ground_truth"
               ],
               "title": "Name",
               "type": "string"
            },
            "type": {
               "description": "The type of the item.",
               "enum": [
                  "input",
                  "output",
                  "reference",
                  "context",
                  "tool_call"
               ],
               "examples": [
                  "input"
               ],
               "title": "Type",
               "type": "string"
            },
            "column_name": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The column name in the tabular data to be used for reading the field value. Applicable for tabular source.",
               "title": "Column Name"
            },
            "span_name": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The span name in the trace data to be used for reading the field value. Applicable for trace source.",
               "title": "Span Name"
            },
            "attribute_name": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The attribute name in the trace to be used for reading the field value. Applicable for trace source.",
               "title": "Attribute Name"
            },
            "json_path": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The json path to be used for reading the field value from the attribute value. Applicable for trace source. If not provided, the span attribute value is read as the field value.",
               "title": "Json Path"
            },
            "lookup_child_spans": {
               "anyOf": [
                  {
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": false,
               "description": "The flag to indicate if all the child spans should be searched for the attribute value. Applicable for trace source.",
               "title": "Look up child spans"
            }
         },
         "required": [
            "name",
            "type"
         ],
         "title": "MappingItem",
         "type": "object"
      },
      "MetricGroup": {
         "enum": [
            "retrieval_quality",
            "answer_quality",
            "content_safety",
            "performance",
            "usage",
            "message_completion",
            "tool_call_quality",
            "readability",
            "custom"
         ],
         "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"
      }
   },
   "required": [
      "system_prompt"
   ]
}

Fields:

• display_name (Annotated[Literal['Topic Relevance'], FieldInfo(annotation=NoneType, required=False, default='Topic Relevance', title='Display Name', description='The topic relevance metric display name.', frozen=True)])

• name (Annotated[Literal['topic_relevance'], FieldInfo(annotation=NoneType, required=False, default='topic_relevance', title='Name', description='The topic relevance metric name.', frozen=True)])

• system_prompt (Annotated[str, FieldInfo(annotation=NoneType, required=True, title='System Prompt', description='The AI model system prompt which contains instructions to define its overall behavior.')])

• tasks (Annotated[list[ibm_watsonx_gov.entities.enums.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)])

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

Validators:

field display_name: Annotated[Literal['Topic Relevance'], FieldInfo(annotation=NoneType, required=False, default='Topic Relevance', title='Display Name', description='The topic relevance metric display name.', frozen=True)] = 'Topic Relevance'

The topic relevance metric display name.

Validated by:

• validate

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

The topic relevance metric name.

Validated by:

• validate

field system_prompt: Annotated[str, FieldInfo(annotation=NoneType, required=True, title='System Prompt', description='The AI model system prompt which contains instructions to define its overall behavior.')] [Required]

The AI model system prompt which contains instructions to define its overall behavior.

Validated by:

• validate

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.

Validated by:

• validate

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.

Validated by:

• validate

evaluate(data: DataFrame | dict, configuration: GenAIConfiguration, **kwargs)

async evaluate_async(data: DataFrame | dict, 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.