class_docstr: Record for a token classification task
  
  Args:
      text:
          The input of the record
      tokens:
          The tokenized input of the record. We use this to guide the annotation process
          and to cross-check the spans of your `prediction`/`annotation`.
      prediction:
          A list of tuples containing the predictions for the record. The first entry of the tuple is the name of
          predicted entity, the second and third entry correspond to the start and stop character index of the entity.
          The fourth entry is optional and corresponds to the score of the entity (a float number between 0 and 1).
      prediction_agent:
          Name of the prediction agent. By default, this is set to the hostname of your machine.
      annotation:
          A list of tuples containing annotations (gold labels) for the record. The first entry of the tuple is the
          name of the entity, the second and third entry correspond to the start and stop char index of the entity.
      annotation_agent:
          Name of the prediction agent. By default, this is set to the hostname of your machine.
      vectors:
          Vector data mappings of the natural language text containing class attributes'
      id:
          The id of the record. By default (None), we will generate a unique ID for you.
      metadata:
          Metadata for the record. Defaults to `{}`.
      status:
          The status of the record. Options: 'Default', 'Edited', 'Discarded', 'Validated'.
          If an annotation is provided, this defaults to 'Validated', otherwise 'Default'.
      event_timestamp:
          The timestamp for the creation of the record. Defaults to `datetime.datetime.now()`.
      metrics:
          READ ONLY! Metrics at record level provided by the server when using `rg.load`.
          This attribute will be ignored when using `rg.log`.
      search_keywords:
          READ ONLY! Relevant record keywords/terms for provided query when using `rg.load`.
          This attribute will be ignored when using `rg.log`.
  Examples:
      >>> import argilla as rg
      >>> record = rg.TokenClassificationRecord(
      ...     text = "Michael is a professor at Harvard",
      ...     tokens = ["Michael", "is", "a", "professor", "at", "Harvard"],
      ...     prediction = [('NAME', 0, 7), ('LOC', 26, 33)],
      ...     vectors = {
      ...            "bert_base_uncased": [3.2, 4.5, 5.6, 8.9]
      ...          }
      ... )
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code: def _check_if_empty_after_strip(cls, text: str):
      assert (
          text.strip()
      ), "The provided `text` contains only whitespaces."
      return text
  
imports: import datetime
  import logging
  import uuid
  import warnings
  from enum import Enum
  from typing import Any, Dict, List, Optional, Tuple, Union
  import pandas
  from deprecated import deprecated
  from argilla import _messages
  from argilla._constants import DEFAULT_MAX_KEYWORD_LENGTH
  from argilla.pydantic_v1 import BaseModel, Field, PrivateAttr, root_validator, validator
  from argilla.utils.span_utils import SpanUtils
label_desc: Use image node_id 6 for calling the TokenClassificationRecord obj's underlying member method code with example usage: obj._check_if_empty_after_strip(cls, text) and returns: text