python-bigquery-dataframes/tests/system/small/bigquery/test_ai.py at 6f092876b233a2ec8bb829413002e7b5ce23e354 · googleapis/python-bigquery-dataframes · GitHub

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# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import sys

import pandas as pd
import pyarrow as pa
import pytest

from bigframes import series
import bigframes.bigquery as bbq
import bigframes.pandas as bpd


def test_ai_generate_bool(session):
    s1 = bpd.Series(["apple", "bear"], session=session)
    s2 = bpd.Series(["fruit", "tree"], session=session)
    prompt = (s1, " is a ", s2)

    result = bbq.ai.generate_bool(prompt, endpoint="gemini-2.5-flash")

    assert _contains_no_nulls(result)
    assert result.dtype == pd.ArrowDtype(
        pa.struct(
            (
                pa.field("result", pa.bool_()),
                pa.field("full_response", pa.string()),
                pa.field("status", pa.string()),
            )
        )
    )


def test_ai_generate_bool_with_pandas(session):
    s1 = pd.Series(["apple", "bear"])
    s2 = bpd.Series(["fruit", "tree"], session=session)
    prompt = (s1, " is a ", s2)

    result = bbq.ai.generate_bool(prompt, endpoint="gemini-2.5-flash")

    assert _contains_no_nulls(result)
    assert result.dtype == pd.ArrowDtype(
        pa.struct(
            (
                pa.field("result", pa.bool_()),
                pa.field("full_response", pa.string()),
                pa.field("status", pa.string()),
            )
        )
    )


def test_ai_generate_bool_with_model_params(session):
    if sys.version_info < (3, 12):
        pytest.skip(
            "Skip test because SQLGLot cannot compile model params to JSON at this env."
        )

    s1 = bpd.Series(["apple", "bear"], session=session)
    s2 = bpd.Series(["fruit", "tree"], session=session)
    prompt = (s1, " is a ", s2)
    model_params = {"generation_config": {"thinking_config": {"thinking_budget": 0}}}

    result = bbq.ai.generate_bool(
        prompt, endpoint="gemini-2.5-flash", model_params=model_params
    )

    assert _contains_no_nulls(result)
    assert result.dtype == pd.ArrowDtype(
        pa.struct(
            (
                pa.field("result", pa.bool_()),
                pa.field("full_response", pa.string()),
                pa.field("status", pa.string()),
            )
        )
    )


def test_ai_generate_bool_multi_model(session):
    df = session.from_glob_path(
        "gs://bigframes-dev-testing/a_multimodel/images/*", name="image"
    )

    result = bbq.ai.generate_bool((df["image"], " contains an animal"))

    assert _contains_no_nulls(result)
    assert result.dtype == pd.ArrowDtype(
        pa.struct(
            (
                pa.field("result", pa.bool_()),
                pa.field("full_response", pa.string()),
                pa.field("status", pa.string()),
            )
        )
    )


def _contains_no_nulls(s: series.Series) -> bool:
    return len(s) == s.count()