class_docstr: Result Validation Stage
docstr: This method will return output according to
  Implementation.
  
  :param input: Your input data.
  :param kwargs: A dictionary of keyword arguments.
      - 'logger' (any): The logger for logging.
      - 'config' (Config): Global configurations for the test
      - 'context' (any): The execution context.
  
  :return: The result of the execution.
docstr_tok: ["This","method","will","return","output","according","to","Implementation",".",":","param","input",":","Your","input","data",".",":","param","kwargs",":","A","dictionary","of","keyword","arguments",".","-","'logger","'","(","any",")",":","The","logger","for","logging",".","-","'config","'","(","Config",")",":","Global","configurations","for","the","test","-","'context","'","(","any",")",":","The","execution","context",".",":","return",":","The","result","of","the","execution","."]
code: def execute(self, input: Any, **kwargs) -> Any:
      """
      This method will return output according to
      Implementation.
  
      :param input: Your input data.
      :param kwargs: A dictionary of keyword arguments.
          - 'logger' (any): The logger for logging.
          - 'config' (Config): Global configurations for the test
          - 'context' (any): The execution context.
  
      :return: The result of the execution.
      """
      pipeline_context: PipelineContext = kwargs.get("context")
      logger: Logger = kwargs.get("logger")
  
      result = input
      if result is not None:
          if isinstance(result, dict):
              (
                  validation_ok,
                  validation_logs,
              ) = pipeline_context.get_intermediate_value(
                  "output_type_helper"
              ).validate(
                  result
              )
              if not validation_ok:
                  logger.log(
                      "\n".join(validation_logs), level=logging.WARNING
                  )
                  pipeline_context.query_exec_tracker.add_step(
                      {
                          "type": "Validating Output",
                          "success": False,
                          "message": "Output Validation Failed",
                      }
                  )
              else:
                  pipeline_context.query_exec_tracker.add_step(
                      {
                          "type": "Validating Output",
                          "success": True,
                          "message": "Output Validation Successful",
                      }
                  )
  
          pipeline_context.add_intermediate_value("last_result", result)
          logger.log(f"Answer: {result}")
  
      logger.log(
          f"Executed in: {pipeline_context.query_exec_tracker.get_execution_time()}s"
      )
  
      return result
  
file_path: pandas-ai/pandasai/pipelines/smart_datalake_chat/result_validation.py
imports: import logging
  from typing import Any
  from pandasai.helpers.logger import Logger
  from ..base_logic_unit import BaseLogicUnit
  from ..pipeline_context import PipelineContext
label_desc: Use image node_id 1 for calling the ResultValidation obj's underlying member method code with example usage: obj.execute(input) and returns: result