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| """Base classes for evaluation metrics.""" |
|
|
| import abc |
| from typing import Any, Callable, Dict, Literal, Union |
|
|
| from vertexai.evaluation import constants |
| from vertexai.evaluation.metrics import ( |
| metric_prompt_template as metric_prompt_template_base, |
| ) |
|
|
|
|
| class _Metric(abc.ABC): |
| """The abstract class for evaluation metric.""" |
|
|
| def __init__(self, metric: str): |
| self._metric = metric |
|
|
| def __str__(self): |
| return self.metric_name |
|
|
| @property |
| def metric_name(self) -> str: |
| return self._metric |
|
|
|
|
| class _ModelBasedMetric(_Metric): |
| """A Model-based Metric. |
| |
| An evaluation metric that evaluates generative AI model responses with |
| another ML model (eg. Gemini) as a rater. It can be for a single model, |
| or two models. |
| |
| For more details on when to use model-based metrics, see |
| [Evaluation methods and metrics](https://cloud.google.com/vertex-ai/generative-ai/docs/models/determine-eval). |
| """ |
|
|
| def __init__( |
| self, |
| *, |
| metric: str, |
| metric_prompt_template: Union[ |
| metric_prompt_template_base.PointwiseMetricPromptTemplate, |
| metric_prompt_template_base.PairwiseMetricPromptTemplate, |
| str, |
| ], |
| ): |
| """Initializes the model-based evaluation metric. |
| |
| Args: |
| metric: Generic model based metric name. |
| metric_prompt_template: A metric prompt template for performing |
| the model-based evaluation. A freeform string is also accepted. |
| """ |
| super().__init__(metric=metric) |
| self.metric_prompt_template = str(metric_prompt_template) |
|
|
|
|
| class CustomMetric(_Metric): |
| """The custom evaluation metric. |
| |
| A fully-customized CustomMetric that can be used to evaluate a single model |
| by defining a metric function for a computation-based metric. The |
| CustomMetric is computed on the client-side using the user-defined metric |
| function in SDK only, not by the Vertex Gen AI Evaluation Service. |
| |
| Attributes: |
| name: The name of the metric. |
| metric_function: The user-defined evaluation function to compute a metric |
| score. Must use the dataset row dictionary as the metric function |
| input and return per-instance metric result as a dictionary output. |
| The metric score must mapped to the name of the CustomMetric as key. |
| """ |
|
|
| def __init__( |
| self, |
| name: str, |
| metric_function: Callable[ |
| [Dict[str, Any]], |
| Dict[str, Any], |
| ], |
| ): |
| """Initializes the evaluation metric.""" |
| super().__init__(name) |
| self.name = name |
| self.metric_function = metric_function |
|
|
|
|
| class _AutomaticMetric(_Metric): |
| """An automatic metric that computes deterministic score based on reference. |
| |
| An lexicon-based evaluation metric that evaluate a generative model's |
| response on the given evaluation task with reference ground truth answers. |
| It is a type of pointwise evaluation metric. |
| |
| For more details on when to use automatic metrics, see |
| [Evaluation methods and |
| metrics](https://cloud.google.com/vertex-ai/generative-ai/docs/models/determine-eval). |
| """ |
|
|
| def __init__( |
| self, |
| metric: Literal[constants.Metric.ROUGE], |
| ): |
| """Initializes the automatic evaluation metric. |
| |
| Args: |
| metric: The automatic evaluation metric name. |
| """ |
| super().__init__(metric=metric) |
|
|
|
|
| class _TranslationMetric(_Metric): |
| """A Translation Metric. |
| |
| Evaluates a score for the given instance using an underlying machine |
| learning model. |
| For now, only COMET and MetricX are supported. |
| |
| For more details on how to evaluate translation, see |
| [Evaluation a translation |
| model](https://cloud.google.com/vertex-ai/generative-ai/docs/models/run-evaluation#translation). |
| """ |
|
|
| def __init__( |
| self, |
| name: str, |
| version: str, |
| source_language: str, |
| target_language: str, |
| ): |
| """Initializes the Translation metric. |
| |
| Args: |
| name: The name of the metric. |
| version: The version to use for evaluation. |
| source_language: The source language of the translation. |
| target_language: The target language of the translation. |
| """ |
| self._version = version |
| self._source_language = source_language |
| self._target_language = target_language |
|
|
| super().__init__(metric=name) |
|
|
| @property |
| def version(self) -> str: |
| return self._version |
|
|
| @property |
| def source_language(self) -> str: |
| return self._source_language |
|
|
| @property |
| def target_language(self) -> str: |
| return self._target_language |
|
|
