bigframes.bigquery.ai.score(prompt: str | Series | Series | List[str | Series | Series] | Tuple[str | Series | Series, ...], *, connection_id: str | None = None) → Series[source]#

Computes a score based on rubrics described in natural language. It will return a double value. There is no fixed range for the score returned. To get high quality results, provide a scoring rubric with examples in the prompt.

Examples:

>>> import bigframes.pandas as bpd
>>> import bigframes.bigquery as bbq
>>> animal = bpd.Series(["Tiger", "Rabbit", "Blue Whale"])
>>> bbq.ai.score(("Rank the relative weights of ", animal, " on the scale from 1 to 3"))
0    2.0
1    1.0
2    3.0
dtype: Float64
Parameters:

  • prompt (str | Series | List[str|Series] | Tuple[str|Series, ...]) – A mixture of Series and string literals that specifies the prompt to send to the model. The Series can be BigFrames Series or pandas Series.

  • connection_id (str, optional) – Specifies the connection to use to communicate with the model. For example, myproject.us.myconnection. If not provided, the query uses your end-user credential.

Returns:

A new series of double (float) values.

Return type:

bigframes.series.Series