class_docstr: Cache class for caching queries. It is used to cache queries
  to save time and money.
  
  Args:
      filename (str): filename to store the cache.
docstr: Return the cache key for the current conversation.
  
  Returns:
      str: The cache key for the current conversation
docstr_tok: ["Return","the","cache","key","for","the","current","conversation",".","Returns",":","str",":","The","cache","key","for","the","current","conversation"]
code: def get_cache_key(self, context: Any) -> str:
      """
      Return the cache key for the current conversation.
  
      Returns:
          str: The cache key for the current conversation
      """
      cache_key = context.memory.get_conversation()
  
      # make the cache key unique for each combination of dfs
      for df in context.dfs:
          hash = df.column_hash()
          cache_key += str(hash)
  
      return cache_key
  
file_path: pandas-ai/pandasai/helpers/cache.py
imports: import os
  import glob
  from typing import Any
  import duckdb
  from .path import find_project_root
  from ..constants import DEFAULT_FILE_PERMISSIONS, CACHE_TOKEN
label_desc: Use image node_id 9 for calling the Cache obj's underlying member method code with example usage: obj.get_cache_key(context) and returns: cache_key