class_docstr: Search Query teacher.
  
  Given an input context, predict the title of the document from which the "gold"
  knowledge is derived.
class_docstr_tok: ["Search","Query","teacher",".","Given","an","input","context",",","predict","the","title","of","the","document","from","which","the","``","gold","''","knowledge","is","derived","."]
code: def add_cmdline_args(cls, parser, partial_opt=None):
      KnowledgeTeacher.add_cmdline_args(parser, partial_opt=partial_opt)
      agent = parser.add_argument_group("Selected Doc Titles Arguments")
      agent.add_argument(
          "--remove-possible-title",
          type=bool,
          default=True,
          help="Remove the length of characters from the beginning of the text that exactly match the title.",
      )
      agent.add_argument(
          "--random-trim-min-length",
          type=int,
          default=-1,
          help=(
              "If text is longer than this length (in chars), randomly trim from the beginning "
              "such that the text is at least this long (default -1, no trimming)."
          ),
      )
      return parser
  
imports: from abc import ABC, abstractmethod
  import os
  from typing import Tuple, List, Optional, Any, Dict
  import random
  from parlai.core.message import Message
  from parlai.core.metrics import F1Metric, BleuMetric, RougeMetric, AverageMetric, ExactMatchMetric, normalize_answer
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.teachers import ChunkTeacher, ChunkOutput
  import parlai.tasks.wizard_of_internet.constants
  from parlai.utils.conversations import Conversations
  from parlai.utils.data import DatatypeHelper
  import parlai.utils.logging
  from parlai.tasks.wizard_of_wikipedia.agents import TOKEN_KNOWLEDGE, TOKEN_END_KNOWLEDGE
  from projects.seeker.utils import extract_entities, remove_possible_title_from_text
label_desc: Use image node_id 1 for calling the SearchQueryTeacher obj's underlying member method code with example usage: obj.add_cmdline_args(cls, parser, partial_opt) and returns: parser