xpark.dataset.TextExtract#

class xpark.dataset.TextExtract(labels: list[str], /, *, ensure_ascii: bool = False, base_url: str, model: str, api_key: str = 'NOT_SET', max_qps: int | None = None, max_retries: int = 0, fallback_response: str | None = '{}', **kwargs: dict[str, Any])[source]#
TextExtract processor extracts structured information from text based on user-defined

labels using an LLM model, and returns the results as a JSON string.

Parameters:
  • labels – The labels to extract from the text.

  • ensure_ascii – If True, the output JSON will escape all non-ASCII characters. If False (default), non-ASCII characters will be preserved in the output. This is useful when working with multilingual text to maintain readability.

  • base_url – The base URL of the LLM server.

  • model – The request model name.

  • api_key – The request API key.

  • max_qps – The maximum number of requests per second.

  • max_retries – The maximum number of retries per request in the event of failures. We retry with exponential backoff upto this specific maximum retries.

  • fallback_response – The response value to return when the LLM request fails. If set to None, the exception will be raised instead.

  • **kwargs – Keyword arguments to pass to the openai.AsyncClient.chat.completions.create API.

Examples

from xpark.dataset.expressions import col
from xpark.dataset import TextExtract, from_items

ds = from_items(["John Doe lives in New York and works for Acme Corp"])
ds = ds.with_column(
    "extracted",
    TextExtract(
        ["person", "location", "organization"],
        model="deepseek-v3-0324",
        base_url=os.getenv("LLM_ENDPOINT"),
        api_key=os.getenv("LLM_API_KEY"),
    )
    .options(num_workers={"IO": 1}, batch_size=1)
    .with_column(col("item")),
)

print(ds.take_all())

Methods

__call__(texts)

Call self as a function.

options(**kwargs)

with_column(texts)

__call__(texts: pa.ChunkedArray) pa.Array#

Call self as a function.

options(**kwargs: Unpack[ExprUDFOptions]) Self#
with_column(texts: pa.ChunkedArray) pa.Array#