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Revert "feat: support gemini-3.x models in loader and update default … (#17602)
This reverts PR: #17409 Fixes #<issue_number_goes_here> 🦕
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Lines changed: 3726 additions & 3768 deletions

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‎packages/bigframes/bigframes/bigquery/_operations/ai.py‎

Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -87,7 +87,7 @@ def generate(
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Specifies the connection to use to communicate with the model. For example, ``myproject.us.myconnection``.
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If not provided, the query uses your end-user credential.
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endpoint (str, optional):
90-
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-3.5-flash"``. You can specify any
90+
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-2.5-flash"``. You can specify any
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generally available or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
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uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML selects a recent stable
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version of Gemini to use.
@@ -178,7 +178,7 @@ def generate_bool(
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Specifies the connection to use to communicate with the model. For example, ``myproject.us.myconnection``.
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If not provided, the query uses your end-user credential.
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endpoint (str, optional):
181-
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-3.5-flash"``. You can specify any
181+
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-2.5-flash"``. You can specify any
182182
generally available or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
183183
uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML selects a recent stable
184184
version of Gemini to use.
@@ -252,7 +252,7 @@ def generate_int(
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Specifies the connection to use to communicate with the model. For example, ``myproject.us.myconnection``.
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If not provided, the query uses your end-user credential.
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endpoint (str, optional):
255-
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-3.5-flash"``. You can specify any
255+
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-2.5-flash"``. You can specify any
256256
generally available or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
257257
uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML selects a recent stable
258258
version of Gemini to use.
@@ -326,7 +326,7 @@ def generate_double(
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Specifies the connection to use to communicate with the model. For example, ``myproject.us.myconnection``.
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If not provided, the query uses your end-user credential.
328328
endpoint (str, optional):
329-
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-3.5-flash"``. You can specify any
329+
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-2.5-flash"``. You can specify any
330330
generally available or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
331331
uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML selects a recent stable
332332
version of Gemini to use.
@@ -809,7 +809,7 @@ def if_(
809809
Specifies the connection to use to communicate with the model. For example, ``myproject.us.myconnection``.
810810
If not provided, the query uses your end-user credential.
811811
endpoint (str, optional):
812-
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-3.5-flash"``. You can specify any
812+
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-2.5-flash"``. You can specify any
813813
generally available or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
814814
uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML dynamically chooses a model based on your query to have the
815815
best cost to quality tradeoff for the task.
@@ -960,7 +960,7 @@ def score(
960960
Specifies the connection to use to communicate with the model. For example, ``myproject.us.myconnection``.
961961
If not provided, the query uses your end-user credential.
962962
endpoint (str, optional):
963-
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-3.5-flash"``. You can specify any
963+
Specifies the Vertex AI endpoint to use for the model. For example ``"gemini-2.5-flash"``. You can specify any
964964
generally available or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
965965
uses the full endpoint of the model. If you don't specify an endpoint value, BigQuery ML dynamically chooses a model
966966
based on your query to have the best cost to quality tradeoff for the task.

‎packages/bigframes/bigframes/ml/llm.py‎

Lines changed: 9 additions & 24 deletions
Original file line numberDiff line numberDiff line change
@@ -59,8 +59,6 @@
5959
_GEMINI_2P5_PRO_ENDPOINT = "gemini-2.5-pro"
6060
_GEMINI_2P5_FLASH_ENDPOINT = "gemini-2.5-flash"
6161
_GEMINI_2P5_FLASH_LITE_ENDPOINT = "gemini-2.5-flash-lite"
62-
_GEMINI_3P1_FLASH_LITE_ENDPOINT = "gemini-3.1-flash-lite"
63-
_GEMINI_3P5_FLASH_ENDPOINT = "gemini-3.5-flash"
6462

6563
_GEMINI_ENDPOINTS = (
6664
_GEMINI_1P5_PRO_PREVIEW_ENDPOINT,
@@ -75,8 +73,6 @@
7573
_GEMINI_2P5_PRO_ENDPOINT,
7674
_GEMINI_2P5_FLASH_ENDPOINT,
7775
_GEMINI_2P5_FLASH_LITE_ENDPOINT,
78-
_GEMINI_3P1_FLASH_LITE_ENDPOINT,
79-
_GEMINI_3P5_FLASH_ENDPOINT,
8076
)
8177
_GEMINI_PREVIEW_ENDPOINTS = (
8278
_GEMINI_1P5_PRO_PREVIEW_ENDPOINT,
@@ -100,8 +96,6 @@
10096
_GEMINI_2P5_PRO_ENDPOINT,
10197
_GEMINI_2P5_FLASH_ENDPOINT,
10298
_GEMINI_2P5_FLASH_LITE_ENDPOINT,
103-
_GEMINI_3P1_FLASH_LITE_ENDPOINT,
104-
_GEMINI_3P5_FLASH_ENDPOINT,
10599
)
106100

107101
_CLAUDE_3_SONNET_ENDPOINT = "claude-3-sonnet"
@@ -437,22 +431,21 @@ class GeminiTextGenerator(base.RetriableRemotePredictor):
437431
"""Gemini text generator LLM model.
438432
439433
.. note::
440-
gemini-1.5-X are going to be deprecated. Use gemini-3.5-flash (https://cloud.google.com/python/docs/reference/bigframes/latest/bigframes.ml.llm.GeminiTextGenerator) instead.
434+
gemini-1.5-X are going to be deprecated. Use gemini-2.5-X (https://cloud.google.com/python/docs/reference/bigframes/latest/bigframes.ml.llm.GeminiTextGenerator) instead.
441435
442436
Args:
443-
model_name (str, Default to "gemini-3.5-flash"):
437+
model_name (str, Default to "gemini-2.0-flash-001"):
444438
The model for natural language tasks. Accepted values are
445439
"gemini-1.5-pro-preview-0514", "gemini-1.5-flash-preview-0514",
446440
"gemini-1.5-pro-001", "gemini-1.5-pro-002", "gemini-1.5-flash-001",
447441
"gemini-1.5-flash-002", "gemini-2.0-flash-exp",
448442
"gemini-2.0-flash-lite-001", "gemini-2.0-flash-001",
449-
"gemini-2.5-pro", "gemini-2.5-flash", "gemini-2.5-flash-lite",
450-
"gemini-3.1-flash-lite" and "gemini-3.5-flash".
451-
If no setting is provided, "gemini-3.5-flash" will be used by
443+
"gemini-2.5-pro", "gemini-2.5-flash" and "gemini-2.5-flash-lite".
444+
If no setting is provided, "gemini-2.0-flash-001" will be used by
452445
default and a warning will be issued.
453446
454447
.. note::
455-
"gemini-1.5-X" is going to be deprecated. Please use gemini-3.5-flash instead.
448+
"gemini-1.5-X" is going to be deprecated. Please use gemini-2.5-X instead. For example, "gemini-2.5-flash".
456449
"gemini-2.0-flash-exp", "gemini-1.5-pro-preview-0514" and "gemini-1.5-flash-preview-0514" is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
457450
Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available "as is"
458451
and might have limited support. For more information, see the launch stage descriptions
@@ -485,8 +478,6 @@ def __init__(
485478
"gemini-2.5-pro",
486479
"gemini-2.5-flash",
487480
"gemini-2.5-flash-lite",
488-
"gemini-3.1-flash-lite",
489-
"gemini-3.5-flash",
490481
]
491482
] = None,
492483
session: Optional[bigframes.Session] = None,
@@ -505,7 +496,7 @@ def __init__(
505496
warnings.warn(msg, category=exceptions.PreviewWarning)
506497

507498
if model_name is None:
508-
model_name = "gemini-3.5-flash"
499+
model_name = "gemini-2.0-flash-001"
509500
msg = exceptions.format_message(_REMOVE_DEFAULT_MODEL_WARNING)
510501
warnings.warn(msg, category=FutureWarning, stacklevel=2)
511502

@@ -531,21 +522,15 @@ def _create_bqml_model(self):
531522
)
532523
)
533524
warnings.warn(msg)
534-
if self.model_name.startswith(
535-
("gemini-2.0", "gemini-1.5")
536-
) or self.model_name in (
537-
"gemini-2.5-flash",
538-
"gemini-2.5-flash-lite",
539-
"gemini-2.5-pro-preview-05-06",
540-
):
525+
if self.model_name.startswith("gemini-1.5"):
541526
msg = exceptions.format_message(
542527
_MODEL_DEPRECATE_WARNING.format(
543528
model_name=self.model_name,
544-
new_model_name="gemini-3.5-flash",
529+
new_model_name="gemini-2.5-X",
545530
link="https://cloud.google.com/python/docs/reference/bigframes/latest/bigframes.ml.llm.GeminiTextGenerator",
546531
)
547532
)
548-
warnings.warn(msg, category=exceptions.ApiDeprecationWarning)
533+
warnings.warn(msg)
549534

550535
options = {"endpoint": self.model_name}
551536

‎packages/bigframes/bigframes/ml/loader.py‎

Lines changed: 0 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -70,8 +70,6 @@
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llm._GEMINI_2P5_FLASH_ENDPOINT: llm.GeminiTextGenerator,
7171
llm._GEMINI_2P5_FLASH_LITE_ENDPOINT: llm.GeminiTextGenerator,
7272
llm._GEMINI_2P5_PRO_ENDPOINT: llm.GeminiTextGenerator,
73-
llm._GEMINI_3P1_FLASH_LITE_ENDPOINT: llm.GeminiTextGenerator,
74-
llm._GEMINI_3P5_FLASH_ENDPOINT: llm.GeminiTextGenerator,
7573
llm._CLAUDE_3_HAIKU_ENDPOINT: llm.Claude3TextGenerator,
7674
llm._CLAUDE_3_SONNET_ENDPOINT: llm.Claude3TextGenerator,
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llm._CLAUDE_3_5_SONNET_ENDPOINT: llm.Claude3TextGenerator,

‎packages/bigframes/bigframes/operations/semantics.py‎

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -57,7 +57,7 @@ def agg(
5757
>>> bpd.options.compute.semantic_ops_confirmation_threshold = 25
5858
5959
>>> import bigframes.ml.llm as llm
60-
>>> model = llm.GeminiTextGenerator(model_name="gemini-3.5-flash") # doctest: +SKIP
60+
>>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001") # doctest: +SKIP
6161
6262
>>> df = bpd.DataFrame(
6363
... {
@@ -330,7 +330,7 @@ def filter(self, instruction: str, model, ground_with_google_search: bool = Fals
330330
>>> bpd.options.compute.semantic_ops_confirmation_threshold = 25
331331
332332
>>> import bigframes.ml.llm as llm
333-
>>> model = llm.GeminiTextGenerator(model_name="gemini-3.5-flash") # doctest: +SKIP
333+
>>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001") # doctest: +SKIP
334334
335335
>>> df = bpd.DataFrame({"country": ["USA", "Germany"], "city": ["Seattle", "Berlin"]})
336336
>>> df.semantics.filter("{city} is the capital of {country}", model) # doctest: +SKIP
@@ -443,7 +443,7 @@ def map(
443443
>>> bpd.options.compute.semantic_ops_confirmation_threshold = 25
444444
445445
>>> import bigframes.ml.llm as llm
446-
>>> model = llm.GeminiTextGenerator(model_name="gemini-3.5-flash") # doctest: +SKIP
446+
>>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001") # doctest: +SKIP
447447
448448
>>> df = bpd.DataFrame({"ingredient_1": ["Burger Bun", "Soy Bean"], "ingredient_2": ["Beef Patty", "Bittern"]})
449449
>>> df.semantics.map("What is the food made from {ingredient_1} and {ingredient_2}? One word only.", output_column="food", model=model) # doctest: +SKIP
@@ -565,7 +565,7 @@ def join(
565565
>>> bpd.options.compute.semantic_ops_confirmation_threshold = 25
566566
567567
>>> import bigframes.ml.llm as llm
568-
>>> model = llm.GeminiTextGenerator(model_name="gemini-3.5-flash") # doctest: +SKIP
568+
>>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001") # doctest: +SKIP
569569
570570
>>> cities = bpd.DataFrame({'city': ['Seattle', 'Ottawa', 'Berlin', 'Shanghai', 'New Delhi']})
571571
>>> continents = bpd.DataFrame({'continent': ['North America', 'Africa', 'Asia']})
@@ -805,7 +805,7 @@ def top_k(
805805
>>> bpd.options.compute.semantic_ops_confirmation_threshold = 25
806806
807807
>>> import bigframes.ml.llm as llm
808-
>>> model = llm.GeminiTextGenerator(model_name="gemini-3.5-flash") # doctest: +SKIP
808+
>>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001") # doctest: +SKIP
809809
810810
>>> df = bpd.DataFrame(
811811
... {

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