📘 Overview

ReasoningAnswerExtractionQwenMathEvalGenerator This operator is used to extract normalized answer expressions from mathematical problem responses, performing string cleaning, unit processing, and format standardization.

__init__ function

@OPERATOR_REGISTRY.register()
class ReasoningAnswerExtractionQwenMathEvalGenerator(OperatorABC):
    """
    A class to handle the process of extracting answers from a dataset.
    """

    def __init__(self, dataset_name:str = None):

init Parameter Description

Parameter Name	Type	Default	Description
dataset_name	str	None	Dataset name, used for specific dataset answer extraction logic.

run function

def run(self, storage: DataFlowStorage, response_key:str = "pseudo_correct_solution_example", extraction_key:str = "extraction")

Executes the main logic of the operator, reads a DataFrame containing answers to be extracted from storage, extracts normalized answers, and writes the results back to storage.

Name	Type	Default	Description
storage	DataFlowStorage	Required	DataFlow storage instance for reading and writing data.
response_key	str	"pseudo_correct_solution_example"	Input column name, corresponding to the original text field containing answers to be extracted.
extraction_key	str	"extraction"	Output column name, corresponding to the extracted and normalized answer field.

🧠 Example Usage

from dataflow.operators.reasoning import ReasoningAnswerExtractionQwenMathEvalGenerator
from dataflow.utils.storage import FileStorage
from dataflow.core import LLMServingABC

class ReasoningAnswerExtractionQwenMathEvalGeneratorTest():
    def __init__(self, llm_serving: LLMServingABC = None):
        
        self.storage = FileStorage(
            first_entry_file_name="example.json",
            cache_path="./cache_local",
            file_name_prefix="dataflow_cache_step",
            cache_type="jsonl",
        )
        
        self.operator = ReasoningAnswerExtractionQwenMathEvalGenerator()
        
    def forward(self):
        self.operator.run(
            storage = self.storage.step(),
            response_key = "pseudo_correct_solution_example",
            extraction_key = "extraction"
        )

if __name__ == "__main__":
    pl = ReasoningAnswerExtractionQwenMathEvalGeneratorTest()
    pl.forward()

🧾 Default Output Format

Field	Type	Description
(Original fields)	-	All original fields from the input data will be preserved.
extraction	str	Extracted and normalized mathematical answer expression.

Example input:

{
"pseudo_correct_solution_example": "The circumference of the circle is 2 * pi * 5, which is approximately 31.4. Therefore, the answer is \\boxed{31.4}."
}

Example output:

{
"pseudo_correct_solution_example": "The circumference of the circle is 2 * pi * 5, which is approximately 31.4. Therefore, the answer is \\boxed{31.4}.",
"extraction": "31.4"
}