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chore: change error to warning for gemini models #1715

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merged 2 commits into from
May 9, 2025
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chore: change error to warning for gemini models #1715

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2c3c761
chore: change error to warning for gemini models
shuoweil May 8, 2025
74ddf5a
remove model
shuoweil May 9, 2025
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21 changes: 17 additions & 4 deletions bigframes/ml/llm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -53,6 +53,7 @@
_GEMINI_2_FLASH_EXP_ENDPOINT = "gemini-2.0-flash-exp"
_GEMINI_2_FLASH_001_ENDPOINT = "gemini-2.0-flash-001"
_GEMINI_2_FLASH_LITE_001_ENDPOINT = "gemini-2.0-flash-lite-001"
_GEMINI_2P5_PRO_PREVIEW_ENDPOINT = "gemini-2.5-pro-preview-05-06"
_GEMINI_ENDPOINTS = (
_GEMINI_1P5_PRO_PREVIEW_ENDPOINT,
_GEMINI_1P5_PRO_FLASH_PREVIEW_ENDPOINT,
Expand Down Expand Up @@ -104,6 +105,12 @@

_REMOVE_DEFAULT_MODEL_WARNING = "Since upgrading the default model can cause unintended breakages, the default model will be removed in BigFrames 3.0. Please supply an explicit model to avoid this message."

_GEMINI_MULTIMODAL_MODEL_NOT_SUPPORTED_WARNING = (
"The model '{model_name}' may not be fully supported by GeminiTextGenerator for Multimodal prompts. "
"GeminiTextGenerator is known to support the following models for Multimodal prompts: {known_models}. "
"If you proceed with '{model_name}', it might not work as expected or could lead to errors with multimodal inputs."
)


@log_adapter.class_logger
class TextEmbeddingGenerator(base.RetriableRemotePredictor):
Expand Down Expand Up @@ -540,9 +547,10 @@ def fit(
GeminiTextGenerator: Fitted estimator.
"""
if self.model_name not in _GEMINI_FINE_TUNE_SCORE_ENDPOINTS:
raise NotImplementedError(
msg = exceptions.format_message(
"fit() only supports gemini-1.5-pro-002, or gemini-1.5-flash-002 model."
)
warnings.warn(msg)

X, y = utils.batch_convert_to_dataframe(X, y)

Expand Down Expand Up @@ -651,9 +659,13 @@ def predict(

if prompt:
if self.model_name not in _GEMINI_MULTIMODAL_ENDPOINTS:
raise NotImplementedError(
f"GeminiTextGenerator only supports model_name {', '.join(_GEMINI_MULTIMODAL_ENDPOINTS)} for Multimodal prompt."
msg = exceptions.format_message(
_GEMINI_MULTIMODAL_MODEL_NOT_SUPPORTED_WARNING.format(
model_name=self.model_name,
known_models=", ".join(_GEMINI_MULTIMODAL_ENDPOINTS),
)
)
warnings.warn(msg)

df_prompt = X[[X.columns[0]]].rename(
columns={X.columns[0]: "bigframes_placeholder_col"}
Expand Down Expand Up @@ -750,9 +762,10 @@ def score(
raise RuntimeError("A model must be fitted before score")

if self.model_name not in _GEMINI_FINE_TUNE_SCORE_ENDPOINTS:
raise NotImplementedError(
msg = exceptions.format_message(
"score() only supports gemini-1.5-pro-002, gemini-1.5-flash-2, gemini-2.0-flash-001, and gemini-2.0-flash-lite-001 model."
)
warnings.warn(msg)

X, y = utils.batch_convert_to_dataframe(X, y, session=self._bqml_model.session)

Expand Down
1 change: 1 addition & 0 deletions bigframes/ml/loader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -66,6 +66,7 @@
llm._GEMINI_2_FLASH_EXP_ENDPOINT: llm.GeminiTextGenerator,
llm._GEMINI_2_FLASH_001_ENDPOINT: llm.GeminiTextGenerator,
llm._GEMINI_2_FLASH_LITE_001_ENDPOINT: llm.GeminiTextGenerator,
llm._GEMINI_2P5_PRO_PREVIEW_ENDPOINT: llm.GeminiTextGenerator,
llm._CLAUDE_3_HAIKU_ENDPOINT: llm.Claude3TextGenerator,
llm._CLAUDE_3_SONNET_ENDPOINT: llm.Claude3TextGenerator,
llm._CLAUDE_3_5_SONNET_ENDPOINT: llm.Claude3TextGenerator,
Expand Down