📘 CodeGenericScoreFilter

CodeGenericScoreFilter is a generic score-based filtering operator that filters datasets based on numerical score columns. It provides flexible comparison methods to remove samples that don't meet specified threshold criteria.

__init__ function

def __init__(self)

This operator does not require any parameters during initialization.

run function

def run(storage, input_key, output_key="generic_score_filter_label", score_threshold=8, filter_method="greater_equal")

Parameters

Name	Type	Default	Description
storage	DataFlowStorage	Required	Data flow storage instance, responsible for reading and writing data.
input_key	str	Required	The column name containing the numerical score to be used for filtering.
output_key	str	"generic_score_filter_label"	The column name for the output label. The operator will add this column with a value of 1 for rows that pass the filter.
score_threshold	int	8	The numerical threshold value used for the comparison.
filter_method	str	"greater_equal"	The comparison method to use. Options are: "greater", "greater_equal", "less", "less_equal", "equal".

Prompt Template Descriptions

Prompt Template Name	Primary Use	Applicable Scenarios	Feature Description

🧠 Example Usage

🧾 Default Output Format

The operator filters the input DataFrame, keeping only the rows that satisfy the specified condition. It also adds a new label column (specified by output_key) to the kept rows.

Field	Type	Description
<existing_columns>	any	Original columns from the input data.
<input_key>	int or float	The original score column used for filtering.
<output_key>	int	The filter label, which will be 1 for all rows in the output, indicating they passed the filter criteria.

Example Input:

{
"code_sample": "def calculate_sum(a, b): return a + b",
"code_quality_score": 9.5
}

Example Output (using input_key="code_quality_score" and default filter settings):

{
"code_sample": "def calculate_sum(a, b): return a + b",
"code_quality_score": 9.5,
"generic_score_filter_label": 1
}