code: def test_annotator_metric_from_feedback_dataset(
      feedback_dataset_guidelines: str,
      feedback_dataset_fields: List["AllowedFieldTypes"],
      feedback_dataset_questions: List["AllowedQuestionTypes"],
      feedback_dataset_records_with_paired_suggestions: List[
          FeedbackRecord
      ],
      question: str,
      metric_names: Union[str, List[str]],
      responses_vs_suggestions: bool,
  ):
      dataset = FeedbackDataset(
          guidelines=feedback_dataset_guidelines,
          fields=feedback_dataset_fields,
          questions=feedback_dataset_questions,
      )
      dataset.add_records(
          records=feedback_dataset_records_with_paired_suggestions
      )
      if responses_vs_suggestions:
          metrics_report = dataset.compute_model_metrics(
              question_name=question, metric_names=metric_names
          )
  
      assert len(metrics_report) == 3  # Number of annotators
      assert isinstance(metrics_report, dict)
      user_id = str(uuid.UUID(int=1))
      metric_results = metrics_report[user_id]
      assert isinstance(metric_results, list)
      metric_result = metric_results[0]
      assert isinstance(metric_result, ModelMetricResult)
      if isinstance(metric_names, str):
          metric_names = [metric_names]
  
      assert all(
          [
              result.metric_name == name
              for result, name in zip(metric_results, metric_names)
          ]
      )
  
file_path: argilla/tests/integration/client/feedback/metrics/test_annotator_metrics.py
imports: import uuid
  from typing import TYPE_CHECKING, List, Union
  import pytest
  from argilla import User, init
  from argilla.client.feedback.dataset import FeedbackDataset
  from argilla.client.feedback.metrics.annotator_metrics import AnnotatorMetric, UnifiedAnnotatorMetric
  from argilla.client.feedback.metrics.base import ModelMetricResult
  from argilla.client.feedback.schemas import FeedbackRecord
  from tests.factories import UserFactory, WorkspaceFactory
label_desc: Use image node_id 3 for calling a global function with example usage: test_annotator_metric_from_feedback_dataset(feedback_dataset_guidelines, feedback_dataset_fields, feedback_dataset_questions, feedback_dataset_records_with_paired_suggestions, question, metric_names, responses_vs_suggestions) without return types