📘 Overview

The CondorRefiner is an operator designed to improve the quality of instruction-response pairs through a two-stage process. In the first stage, it generates a critique of the initial response. In the second stage, it uses this critique to refine the original response, thereby enhancing the overall quality of the question-answering pair through iterative optimization.

__init__

def __init__(self, llm_serving: LLMServingABC = None)

Parameter	Type	Default	Description
llm_serving	LLMServingABC	None	An instance of a Large Language Model service, used for generating critiques and refined answers.

Prompt Template Descriptions

Prompt Template Name	Primary Use	Applicable Scenarios	Feature Description

run

def run(self, storage: DataFlowStorage, input_instruction_key: str='instruction', input_output_key: str='output')

Parameter	Type	Default	Description
storage	DataFlowStorage	Required	An instance of DataFlowStorage, responsible for reading and writing data.
input_instruction_key	str	"instruction"	The column name in the input data that contains the instructions or questions.
input_output_key	str	"output"	The column name in the input data that contains the responses to be refined. This column will be overwritten with the refined answers.

🧠 Example Usage

🧾 Input Format

🧾 Output Format