class_docstr: (Experimental) Text Analysis agent, a subclass of ConversableAgent designed to analyze text as instructed.
docstr: Analyzes the given text as instructed, and returns the analysis as a message.
  Assumes exactly two messages containing the text to analyze and the analysis instructions.
  See Teachability.analyze for an example of how to use this method.
code: def _analyze_in_reply(
      self,
      messages: Optional[List[Dict]] = None,
      sender: Optional[Agent] = None,
      config: Optional[Any] = None,
  ) -> Tuple[bool, Union[str, Dict, None]]:
      """Analyzes the given text as instructed, and returns the analysis as a message.
      Assumes exactly two messages containing the text to analyze and the analysis instructions.
      See Teachability.analyze for an example of how to use this method.
      """
      if self.llm_config is False:
          raise ValueError(
              "TextAnalyzerAgent requires self.llm_config to be set in its base class."
          )
      if messages is None:
          messages = self._oai_messages[
              sender
          ]  # In case of a direct call.
      assert len(messages) == 2
  
      # Delegate to the analysis method.
      return True, self.analyze_text(
          messages[0]["content"], messages[1]["content"]
      )
  
file_path: autogen/autogen/agentchat/contrib/text_analyzer_agent.py
imports: from autogen import oai
  from autogen.agentchat.agent import Agent
  from autogen.agentchat.assistant_agent import ConversableAgent
  from typing import Callable, Dict, Optional, Union, List, Tuple, Any
label_desc: Use image node_id 2 for calling the TextAnalyzerAgent obj's underlying member method code with example usage: obj._analyze_in_reply(messages, sender, config) and returns: True,  self