code: def test_incomplete_chained_samples(cfg, df_short):
      cfg.dataset.limit_chained_samples = False
  
      handler = ConversationChainHandler(df_short, cfg)
      assert handler.conversation_chain_ids == [
          [0],
          [0, 1],
          [0, 1, 2],
          [0, 1, 2, 3],
      ]
      assert len(handler) == 4
      for i in range(4):
          assert handler[i] == {
              "prompts": [f"prompt{j + 1}" for j in range(i + 1)],
              "answers": [f"answer{j + 1}" for j in range(i + 1)],
              "systems": [f"system{j + 1}" for j in range(i + 1)],
          }
  
file_path: h2o-llmstudio/tests/src/datasets/test_conversation_chain_handler.py
imports: import time
  from unittest import mock
  from unittest.mock import MagicMock
  import pandas
  import pytest
  from llm_studio.app_utils.default_datasets import prepare_default_dataset_causal_language_modeling
  from llm_studio.src.datasets.conversation_chain_handler import ConversationChainHandler
label_desc: Use image node_id 6 for calling a global function with example usage: test_incomplete_chained_samples(cfg, df_short) without return types