code: def feedback_dataset_huggingface() -> Dataset:
      return Dataset.from_dict(
          {
              "text": ["This is a positive example"],
              "label": ["positive"],
              "question-1": [
                  {
                      "user_id": [None],
                      "value": ["This is a response to question 1"],
                      "status": ["submitted"],
                  }
              ],
              "question-2": [
                  {
                      "user_id": [None],
                      "value": [1],
                      "status": ["submitted"],
                  }
              ],
              "question-3": [
                  {
                      "user_id": [None],
                      "value": ["a"],
                      "status": ["submitted"],
                  }
              ],
              "question-4": [
                  {
                      "user_id": [None],
                      "value": [["a", "b"]],
                      "status": ["submitted"],
                  }
              ],
              "question-5": [
                  {
                      "user_id": [None],
                      "value": [
                          [
                              {"rank": 1, "value": "a"},
                              {"rank": 2, "value": "b"},
                          ]
                      ],
                      "status": ["submitted"],
                  }
              ],
              "question-1-suggestion": [
                  "This is a suggestion to question 1"
              ],
              "question-1-suggestion-metadata": [
                  {"type": None, "score": None, "agent": None}
              ],
              "question-2-suggestion": [1],
              "question-2-suggestion-metadata": [
                  {"type": None, "score": None, "agent": None}
              ],
              "question-3-suggestion": ["a"],
              "question-3-suggestion-metadata": [
                  {"type": None, "score": None, "agent": None}
              ],
              "question-4-suggestion": [["a", "b"]],
              "question-4-suggestion-metadata": [
                  {"type": None, "score": None, "agent": None}
              ],
              "question-5-suggestion": [
                  [{"rank": 1, "value": "a"}, {"rank": 2, "value": "b"}]
              ],
              "question-5-suggestion-metadata": [
                  {"type": None, "score": None, "agent": None}
              ],
              "external_id": ["1"],
          }
      )
  
imports: import datetime
  import random
  from typing import TYPE_CHECKING, Generator, List
  import pytest
  from argilla.client.api import log
  from argilla.client.datasets import read_datasets
  from argilla.client.feedback.dataset.local.dataset import FeedbackDataset
  from argilla.client.feedback.schemas import FeedbackRecord, LabelQuestion, MultiLabelQuestion, RankingQuestion, RatingQuestion, TextField, TextQuestion
  from argilla.client.feedback.schemas.metadata import FloatMetadataProperty, IntegerMetadataProperty, TermsMetadataProperty
  from argilla.client.feedback.schemas.vector_settings import VectorSettings
  from argilla.client.models import Text2TextRecord, TextClassificationRecord, TokenAttributions, TokenClassificationRecord
  from argilla.client.sdk.datasets.models import TaskType
  from argilla.client.sdk.text2text.models import CreationText2TextRecord, Text2TextBulkData
  from argilla.client.sdk.text_classification.models import CreationTextClassificationRecord, TextClassificationBulkData
  from argilla.client.sdk.token_classification.models import CreationTokenClassificationRecord, TokenClassificationBulkData
  from argilla.client.singleton import init
  from argilla.server.models import User
  from datasets import Dataset
  from tests.integration.utils import delete_ignoring_errors
label_desc: Use image node_id 19 for calling a global function with example usage: feedback_dataset_huggingface() and returns: Dataset