code: def st_extractor() -> SentenceTransformersExtractor:
      model = SentenceTransformer("TaylorAI/bge-micro-v2")
      model.get_sentence_embedding_dimension = MagicMock(return_value=1)
      model.encode = MagicMock(return_value=np.array([1]))
      return SentenceTransformersExtractor(model=model)
  
file_path: argilla/tests/unit/client/feedback/integrations/test_sentencetransformers.py
imports: from typing import List
  from unittest.mock import MagicMock
  import numpy
  import pytest
  from argilla.client.feedback.dataset.local.dataset import FeedbackDataset
  from argilla.client.feedback.integrations.sentencetransformers import SentenceTransformersExtractor
  from argilla.client.feedback.schemas.fields import TextField
  from argilla.client.feedback.schemas.questions import TextQuestion
  from argilla.client.feedback.schemas.records import FeedbackRecord
  from argilla.client.feedback.schemas.vector_settings import VectorSettings
  from sentence_transformers import SentenceTransformer
label_desc: Use image node_id 3 for calling a global function with example usage: st_extractor() and returns: SentenceTransformersExtractor