code: def convert_data_for_ranking(
      data: pd.DataFrame,
      query_column: str,
      response_column: str,
      label_column: Optional[str] = None,
  ):
      """
      Extract query and response data from a dataframe.
      If no label column exists, append one label column with all 1 labels,
      which assumes (a_i, p_i) are a positive pair and (a_i, p_j) for i!=j a negative pair.
  
      Parameters
      ----------
      data
          A dataframe with query, response, and label (optional) columns.
      query_column
          Name of the query column.
      response_column
          Name of the response column.
      label_column
          Name of the label column. If None, use `relevance` by default.
  
      Returns
      -------
      data_with_label
          A dataframe with query, response, and label columns.
      query_data
          The unique query data in the dataframe format.
      response_data
          The unique response data in the dataframe format.
      label_column
          Name of the label column.
      """
      data_with_label = data.copy()
      if label_column is None:
          data_with_label["relevance"] = [1] * len(data)
          label_column = "relevance"
  
      query_data = pd.DataFrame(
          {query_column: data[query_column].unique().tolist()}
      )
      response_data = pd.DataFrame(
          {response_column: data[response_column].unique().tolist()}
      )
  
      return data_with_label, query_data, response_data, label_column
  
imports: import copy
  import functools
  import heapq
  import logging
  from typing import Dict, List, Optional, Union
  import pandas
  import torch
  from omegaconf import DictConfig
  from torch import nn
  from torch.nn import functional
  from ..constants import FUSION, QUERY, RESPONSE
  from .data import data_to_df
  from .model import create_model
label_desc: Use image node_id 8 for calling a global function with example usage: convert_data_for_ranking(data, query_column, response_column, label_column) and returns: data_with_label,  query_data,  response_data,  label_column