code: def get_conversation_chains(
      df, cfg, limit_chained_samples=True
  ) -> List[Dict[str, List[str]]]:
      with PatchedAttribute(
          cfg.dataset, "limit_chained_samples", limit_chained_samples
      ):
          conversation_chain_handler = ConversationChainHandler(df, cfg)
      conversations = [
          conversation
          for conversation in conversation_chain_handler  # type: ignore[attr-defined]
      ]
      return conversations
  
file_path: h2o-llmstudio/llm_studio/src/datasets/conversation_chain_handler.py
imports: import logging
  from typing import Dict, List
  import numpy
  from llm_studio.src.datasets.text_utils import get_texts
  from llm_studio.src.utils.utils import PatchedAttribute
label_desc: Use image node_id 1 for calling a global function with example usage: get_conversation_chains(df, cfg, limit_chained_samples) and returns: conversations