code: def create_most_conservative_formatter_configs(
      agent_type_to_check: AgentType,
  ) -> FormatterConfigs:
      return FormatterConfigs(
          guidelines=Guidelines(
              categories=[
                  Category(
                      name="cat V", description="cat V description"
                  ),
                  Category(
                      name="cat W", description="cat W description"
                  ),
                  Category(
                      name="cat X", description="cat X description"
                  ),
                  Category(
                      name="cat Y", description="cat Y description"
                  ),
                  Category(
                      name="cat Z", description="cat Z description"
                  ),
              ],
              category_code_prefix="O",
          ),
          llama_guard_prompt_configs=LlamaGuardPromptConfigs(
              instructions_format_string=f"""[INST] Task: Check if there is unsafe content in '{agent_type_to_check}' messages in conversations according our safety policy with the below categories.
  <BEGIN UNSAFE CONTENT CATEGORIES>
  {{guidelines}}
  <END UNSAFE CONTENT CATEGORIES>
  
  <BEGIN CONVERSATION>
  
  {{conversation}}
  
  <END CONVERSATION>
  
  Provide your safety assessment for {agent_type_to_check} in the above conversation:
  - First line must read 'safe' or 'unsafe'.
  - If unsafe, a second line must include a comma-separated list of violated categories. [/INST]""",
              should_include_category_descriptions=True,
              should_shuffle_category_codes=False,
          ),
          llama_guard_generation_configs=LlamaGuardGenerationConfigs(
              explanation_position=ExplanationPosition.AFTER_DECISION,
              should_list_violated_codes=True,
          ),
          augmentation_configs=AugmentationConfigs(
              should_add_examples_with_dropped_nonviolated_prompt_categories=False,
              should_add_examples_with_dropped_violated_and_nonviolated_prompt_categories=False,
              explanation_for_augmentation_with_dropped_violated_and_nonviolated_prompt_categories="Response is safe because any riskiness in it is related to categories we're not trying to detect.",
          ),
          random_seed=42,
      )
  
file_path: llama-recipes/tests/test_finetuning_data_formatter.py
imports: from enum import Enum
  import unittest
  from typing import Optional, List
  from llama_recipes.data.llama_guard.finetuning_data_formatter import AugmentationConfigs, Category, create_formatted_finetuning_examples, ExplanationPosition, FormatterConfigs, Guidelines, LlamaGuardGenerationConfigs, LlamaGuardPromptConfigs, TrainingExample
label_desc: Use image node_id 2 for calling the FinetuningDataFormatterTests obj's underlying member method code with example usage: obj.create_most_conservative_formatter_configs(agent_type_to_check) and returns: FormatterConfigs