pyflink.dataframe.ai.llm.LLMAccessor.ai_classify#
- LLMAccessor.ai_classify(input_col: Union[str, Expression], labels: List[str], *, provider: str = None, model: str = None, config: Dict[str, str] = None) DataFrame[source]#
Classify text into one of the provided labels.
- Parameters
input_col – Column name (str) or Expression for the input text.
labels – List of label strings.
provider – Provider name.
model – Model name.
config – Optional runtime config.
- Returns
category(STRING): the predicted label.confidence(DOUBLE): confidence score.
- Return type
A new DataFrame with columns appended
- Example::
>>> df.llm.ai_classify("text", ["positive", "negative"], ... model="qwen-plus")