code: def common_prompt_suffix_validator(df: pd.DataFrame) -> Remediation:
      """
      This validator will suggest to add a common suffix to the prompt if one doesn't already exist in case of classification or conditional generation.
      """
      error_msg = None
      immediate_msg = None
      optional_msg = None
      optional_fn = None  # type: ignore
  
      # Find a suffix which is not contained within the prompt otherwise
      suggested_suffix = "\n\n### =>\n\n"
      suffix_options = [
          " ->",
          "\n\n###\n\n",
          "\n\n===\n\n",
          "\n\n---\n\n",
          "\n\n===>\n\n",
          "\n\n--->\n\n",
      ]
      for suffix_option in suffix_options:
          if suffix_option == " ->":
              if df.prompt.str.contains("\n").any():
                  continue
          if df.prompt.str.contains(suffix_option, regex=False).any():
              continue
          suggested_suffix = suffix_option
          break
      display_suggested_suffix = suggested_suffix.replace("\n", "\\n")
  
      ft_type = infer_task_type(df)
      if ft_type == "open-ended generation":
          return Remediation(name="common_suffix")
  
      def add_suffix(x: Any, suffix: Any) -> Any:
          x["prompt"] += suffix
          return x
  
      common_suffix = get_common_xfix(df.prompt, xfix="suffix")
      if (df.prompt == common_suffix).all():
          error_msg = f"All prompts are identical: `{common_suffix}`\nConsider leaving the prompts blank if you want to do open-ended generation, otherwise ensure prompts are different"
          return Remediation(name="common_suffix", error_msg=error_msg)
  
      if common_suffix != "":
          common_suffix_new_line_handled = common_suffix.replace(
              "\n", "\\n"
          )
          immediate_msg = f"\n- All prompts end with suffix `{common_suffix_new_line_handled}`"
          if len(common_suffix) > 10:
              immediate_msg += f". This suffix seems very long. Consider replacing with a shorter suffix, such as `{display_suggested_suffix}`"
          if (
              df.prompt.str[: -len(common_suffix)]
              .str.contains(common_suffix, regex=False)
              .any()
          ):
              immediate_msg += f"\n  WARNING: Some of your prompts contain the suffix `{common_suffix}` more than once. We strongly suggest that you review your prompts and add a unique suffix"
  
      else:
          immediate_msg = "\n- Your data does not contain a common separator at the end of your prompts. Having a separator string appended to the end of the prompt makes it clearer to the fine-tuned model where the completion should begin. See https://platform.openai.com/docs/guides/fine-tuning/preparing-your-dataset for more detail and examples. If you intend to do open-ended generation, then you should leave the prompts empty"
  
      if common_suffix == "":
          optional_msg = f"Add a suffix separator `{display_suggested_suffix}` to all prompts"
  
          def optional_fn(x: Any) -> Any:
              return add_suffix(x, suggested_suffix)
  
      return Remediation(
          name="common_completion_suffix",
          immediate_msg=immediate_msg,
          optional_msg=optional_msg,
          optional_fn=optional_fn,
          error_msg=error_msg,
      )
  
imports: from __future__ import annotations
  import os
  import sys
  from typing import Any, TypeVar, Callable, Optional, NamedTuple
  from typing_extensions import TypeAlias
  from .._extras import pandas
label_desc: Use image node_id 7 for calling a global function with example usage: common_prompt_suffix_validator(df) and returns: Remediation, Remediation, x, Remediation, add_suffix