code: def get_chained_prompt_text_list(self, idx: int) -> List[str]:
      text_dict = self.conversation_chain_handler[idx]
      chat_history = "".join(
          [
              prompt + TEXT_SEPARATOR + answer + TEXT_SEPARATOR
              for prompt, answer in zip(
                  text_dict["prompts"][:-1], text_dict["answers"][:-1]
              )
          ]
      )
      prompt_text = (
          text_dict["systems"][0]
          + chat_history
          + text_dict["prompts"][-1]
      )
      return prompt_text.split(TEXT_SEPARATOR)
  
file_path: h2o-llmstudio/llm_studio/src/datasets/text_rlhf_modeling_ds.py
imports: import logging
  from typing import Any, Dict, List
  import numpy
  import pandas
  import torch
  from llm_studio.src.datasets.text_causal_language_modeling_ds import CustomDataset
  from llm_studio.src.datasets.text_utils import TEXT_SEPARATOR
label_desc: Use image node_id 7 for calling the CustomDataset obj's underlying member method code with example usage: obj.get_chained_prompt_text_list(idx) and returns: prompt_text