class_docstr: LM Chunk Teacher, base.
  
  Provides functionality for subclassed teachers for extracting data from world log
  files, generated via `generate_lm_data.py`
class_docstr_tok: ["LM","Chunk","Teacher",",","base",".","Provides","functionality","for","subclassed","teachers","for","extracting","data","from","world","log","files",",","generated","via","`","generate_lm_data.py","`"]
docstr: Given the tuple output of the queue, return an act.
  
  May depend on entry index if queue output is a multi-turn episode.
docstr_tok: ["Given","the","tuple","output","of","the","queue",",","return","an","act",".","May","depend","on","entry","index","if","queue","output","is","a","multi-turn","episode","."]
code: def create_message(
      self, queue_output: ChunkOutput, entry_idx=0
  ) -> Message:
      """
      Given the tuple output of the queue, return an act.
  
      May depend on entry index if queue output is a multi-turn episode.
      """
      return queue_output
  
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 9 for calling the AbstractLMChunkTeacher obj's underlying member method code with example usage: obj.create_message(queue_output, entry_idx) and returns: queue_output