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chore(bigframes): move some ai accessor tests outside the SQLGlot compiler dir #17318

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20efd93
chore(bigframes): move some ai accessor tests outside the SQLGlot com…
sycai May 29, 2026
1f092be
Update packages/bigframes/tests/unit/extensions/core/test_dataframe_a…
sycai May 29, 2026
4284888
Update packages/bigframes/tests/unit/extensions/core/test_dataframe_a…
sycai May 29, 2026
311b452
polish tests
sycai May 29, 2026
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292 changes: 0 additions & 292 deletions packages/bigframes/tests/unit/core/compile/sqlglot/test_dataframe_accessor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,295 +58,3 @@ def test_bigframes_sql_scalar(scalar_types_df: bpd.DataFrame, snapshot):
# Bigframes implementation returns a bigframes.series.Series
sql, _, _ = result.to_frame()._to_sql_query(include_index=True)
snapshot.assert_match(sql, "out.sql")


def test_ai_forecast(snapshot, monkeypatch):
import bigframes.bigquery.ai
import bigframes.session

session = mock.create_autospec(bigframes.session.Session)
bf_df = mock.create_autospec(bpd.DataFrame)
session.read_pandas.return_value = bf_df

def mock_ai_forecast(df, **kwargs):
assert df is bf_df
result_df = mock.create_autospec(bpd.DataFrame)
result_df.to_pandas.return_value = kwargs
return result_df

import bigframes.bigquery.ai

monkeypatch.setattr(bigframes.bigquery.ai, "forecast", mock_ai_forecast)

df = pd.DataFrame({"date": ["2020-01-01"], "value": [1.0]})
result = df.bigquery.ai.forecast(
timestamp_col="date",
data_col="value",
horizon=5,
session=session,
)

session.read_pandas.assert_called_once()
assert result == {
"timestamp_col": "date",
"data_col": "value",
"model": "TimesFM 2.0",
"id_cols": None,
"horizon": 5,
"confidence_level": 0.95,
"context_window": None,
"output_historical_time_series": False,
}


def test_bigframes_ai_forecast(snapshot, monkeypatch):
import bigframes.bigquery.ai
import bigframes.session

session = mock.create_autospec(bigframes.session.Session)
bf_df = mock.create_autospec(bpd.DataFrame)

def mock_ai_forecast(df, **kwargs):
assert df is bf_df
result_df = mock.create_autospec(bpd.DataFrame)
return result_df

monkeypatch.setattr(bigframes.bigquery.ai, "forecast", mock_ai_forecast)

result = bf_df.bigquery.ai.forecast(
timestamp_col="date",
data_col="value",
horizon=5,
session=session,
)

session.read_pandas.assert_not_called()
# BigFrames accessor returns the bf_df directly without calling to_pandas
assert result is not None


def test_ai_generate(monkeypatch):
import bigframes.bigquery.ai

def mock_generate(prompt, **kwargs):
result_series = mock.create_autospec(bpd.Series)
result_series.to_pandas.return_value = (prompt, kwargs)
return result_series

monkeypatch.setattr(bigframes.bigquery.ai, "generate", mock_generate)

df = pd.DataFrame({"text_input": ["Is this a positive review?"]})
result = df.bigquery.ai.generate(
df["text_input"],
connection_id="conn",
endpoint="endpoint",
request_type="dedicated",
model_params={"temp": 0.5},
output_schema={"res": "STRING"},
)

assert result == (
df["text_input"],
{
"connection_id": "conn",
"endpoint": "endpoint",
"request_type": "dedicated",
"model_params": {"temp": 0.5},
"output_schema": {"res": "STRING"},
},
)


def test_bigframes_ai_generate(scalar_types_df: bpd.DataFrame, monkeypatch):
import bigframes.bigquery.ai
import bigframes.session

session = mock.create_autospec(bigframes.session.Session)
bf_series = mock.create_autospec(bpd.Series)

def mock_generate(prompt, **kwargs):
assert prompt is bf_series
result_series = mock.create_autospec(bpd.Series)
return result_series

monkeypatch.setattr(bigframes.bigquery.ai, "generate", mock_generate)

result = scalar_types_df.bigquery.ai.generate(
bf_series,
connection_id="conn",
endpoint="endpoint",
request_type="dedicated",
model_params={"temp": 0.5},
output_schema={"res": "STRING"},
)

session.read_pandas.assert_not_called()
assert result is not None


def test_ai_generate_bool(monkeypatch):
import bigframes.bigquery.ai

def mock_generate_bool(prompt, **kwargs):
result_series = mock.create_autospec(bpd.Series)
result_series.to_pandas.return_value = (prompt, kwargs)
return result_series

monkeypatch.setattr(bigframes.bigquery.ai, "generate_bool", mock_generate_bool)

df = pd.DataFrame({"text_input": ["Is this a positive review?"]})
result = df.bigquery.ai.generate_bool(
df["text_input"],
connection_id="conn",
endpoint="endpoint",
request_type="dedicated",
model_params={"temp": 0.5},
)

assert result == (
df["text_input"],
{
"connection_id": "conn",
"endpoint": "endpoint",
"request_type": "dedicated",
"model_params": {"temp": 0.5},
},
)


def test_bigframes_ai_generate_bool(scalar_types_df: bpd.DataFrame, monkeypatch):
import bigframes.bigquery.ai
import bigframes.session

session = mock.create_autospec(bigframes.session.Session)
bf_series = mock.create_autospec(bpd.Series)

def mock_generate_bool(prompt, **kwargs):
assert prompt is bf_series
result_series = mock.create_autospec(bpd.Series)
return result_series

monkeypatch.setattr(bigframes.bigquery.ai, "generate_bool", mock_generate_bool)

result = scalar_types_df.bigquery.ai.generate_bool(
bf_series,
connection_id="conn",
endpoint="endpoint",
request_type="dedicated",
model_params={"temp": 0.5},
)

session.read_pandas.assert_not_called()
assert result is not None


def test_ai_generate_int(monkeypatch):
import bigframes.bigquery.ai

def mock_generate_int(prompt, **kwargs):
result_series = mock.create_autospec(bpd.Series)
result_series.to_pandas.return_value = (prompt, kwargs)
return result_series

monkeypatch.setattr(bigframes.bigquery.ai, "generate_int", mock_generate_int)

df = pd.DataFrame({"text_input": ["How many legs?"]})
result = df.bigquery.ai.generate_int(
df["text_input"],
connection_id="conn",
endpoint="endpoint",
request_type="dedicated",
model_params={"temp": 0.5},
)

assert result == (
df["text_input"],
{
"connection_id": "conn",
"endpoint": "endpoint",
"request_type": "dedicated",
"model_params": {"temp": 0.5},
},
)


def test_bigframes_ai_generate_int(scalar_types_df: bpd.DataFrame, monkeypatch):
import bigframes.bigquery.ai
import bigframes.session

session = mock.create_autospec(bigframes.session.Session)
bf_series = mock.create_autospec(bpd.Series)

def mock_generate_int(prompt, **kwargs):
assert prompt is bf_series
result_series = mock.create_autospec(bpd.Series)
return result_series

monkeypatch.setattr(bigframes.bigquery.ai, "generate_int", mock_generate_int)

result = scalar_types_df.bigquery.ai.generate_int(
bf_series,
connection_id="conn",
endpoint="endpoint",
request_type="dedicated",
model_params={"temp": 0.5},
)

session.read_pandas.assert_not_called()
assert result is not None


def test_ai_generate_double(monkeypatch):
import bigframes.bigquery.ai

def mock_generate_double(prompt, **kwargs):
result_series = mock.create_autospec(bpd.Series)
result_series.to_pandas.return_value = (prompt, kwargs)
return result_series

monkeypatch.setattr(bigframes.bigquery.ai, "generate_double", mock_generate_double)

df = pd.DataFrame({"text_input": ["How tall?"]})
result = df.bigquery.ai.generate_double(
df["text_input"],
connection_id="conn",
endpoint="endpoint",
request_type="dedicated",
model_params={"temp": 0.5},
)

assert result == (
df["text_input"],
{
"connection_id": "conn",
"endpoint": "endpoint",
"request_type": "dedicated",
"model_params": {"temp": 0.5},
},
)


def test_bigframes_ai_generate_double(scalar_types_df: bpd.DataFrame, monkeypatch):
import bigframes.bigquery.ai
import bigframes.session

session = mock.create_autospec(bigframes.session.Session)
bf_series = mock.create_autospec(bpd.Series)

def mock_generate_double(prompt, **kwargs):
assert prompt is bf_series
result_series = mock.create_autospec(bpd.Series)
return result_series

monkeypatch.setattr(bigframes.bigquery.ai, "generate_double", mock_generate_double)

result = scalar_types_df.bigquery.ai.generate_double(
bf_series,
connection_id="conn",
endpoint="endpoint",
request_type="dedicated",
model_params={"temp": 0.5},
)

session.read_pandas.assert_not_called()
assert result is not None
13 changes: 13 additions & 0 deletions packages/bigframes/tests/unit/extensions/core/__init__.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,13 @@
# Copyright 2026 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.
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