class_docstr: Text classification service
class_docstr_tok: ["Text","classification","service"]
code: def compute_all_labeling_rules(
      self, dataset: ServiceTextClassificationDataset
  ):
      total, annotated, metrics = self._compute_all_lb_rules_metrics(
          dataset
      )
      coverage = metrics.covered_records / total if total else None
      coverage_annotated = (
          metrics.annotated_covered_records / annotated
          if annotated
          else None
      )
      return DatasetLabelingRulesMetricsSummary(
          coverage=coverage,
          coverage_annotated=coverage_annotated,
          total_records=total,
          annotated_records=annotated,
      )
  
imports: from typing import Iterable, List, Optional, Tuple
  from fastapi import Depends
  from argilla.server.errors.base_errors import EntityAlreadyExistsError, EntityNotFoundError, MissingDatasetRecordsError
  from argilla.server.services.datasets import DatasetsService
  from argilla.server.services.metrics import MetricsService
  from argilla.server.services.search.model import ServiceSearchResults, ServiceSortableField, ServiceSortConfig
  from argilla.server.services.search.service import SearchRecordsService
  from argilla.server.services.storage.service import RecordsStorageService
  from argilla.server.services.tasks.commons import BulkResponse
  from argilla.server.services.tasks.text_classification.metrics import TextClassificationMetrics
  from argilla.server.services.tasks.text_classification.model import DatasetLabelingRulesMetricsSummary, DatasetLabelingRulesSummary, LabelingRuleMetricsSummary, LabelingRuleSummary, ServiceLabelingRule, ServiceTextClassificationDataset, ServiceTextClassificationQuery, ServiceTextClassificationRecord
label_desc: Use image node_id 13 for calling the TextClassificationService obj's underlying member method code with example usage: obj.compute_all_labeling_rules(dataset) and returns: DatasetLabelingRulesMetricsSummary