📘 Overview [TextbookSampleEvaluator]

TextbookSampleEvaluator assesses the educational value of text using a FastText classifier (kenhktsui/llm-data-textbook-quality-fasttext-classifer-v2). It categorizes text into Low, Mid, and High levels, which are then mapped to scores of 1.0, 3.0, and 5.0 respectively. This operator is suitable for filtering high-quality text content to be used as teaching materials.

init function

def __init__(self, model_cache_dir='./dataflow_cache')

init parameters

Parameter	Type	Default	Description
model_cache_dir	str	'./dataflow_cache'	The directory to cache the downloaded model files from Hugging Face Hub.

run function

def run(self, storage: DataFlowStorage, input_key: str, output_key: str='TextbookScore')

Parameters

Name	Type	Default	Description
storage	DataFlowStorage	Required	The data flow storage instance, responsible for reading and writing the dataframe.
input_key	str	Required	The name of the input column containing the text to be evaluated.
output_key	str	'TextbookScore'	The name of the output column where the calculated score will be stored.

🧠 Example Usage

🧾 Default Output Format (Output Format)

The operator adds the output_key column to the existing dataframe.

Field	Type	Description
...	...	Original columns from the input dataframe are preserved.
TextbookScore	float	The educational value score assigned by the classifier. The value is a float derived from a weighted sum of 'Low' (1.0), 'Mid' (3.0), and 'High' (5.0) probabilities.