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TextEmbeddingGenerator(
*,
model_name: typing.Literal[
"text-embedding-005", "text-embedding-004", "text-multilingual-embedding-002"
] = "text-embedding-004",
session: typing.Optional[bigframes.session.Session] = None,
connection_name: typing.Optional[str] = None
)Text embedding generator LLM model.
Parameters | |
|---|---|
| Name | Description |
model_name | str, Default to "text-embedding-004"The model for text embedding. Possible values are "text-embedding-005", "text-embedding-004" or "text-multilingual-embedding-002". text-embedding models returns model embeddings for text inputs. text-multilingual-embedding models returns model embeddings for text inputs which support over 100 languages. Default to "text-embedding-004". |
session | bigframes.Session or NoneBQ session to create the model. If None, use the global default session. |
connection_name | str or NoneConnection to connect with remote service. str of the format <PROJECT_NUMBER/PROJECT_ID>. |
Methods
__repr__
__repr__()Print the estimator's constructor with all non-default parameter values.
get_params
get_params(deep: bool = True) -> typing.Dict[str, typing.Any]Get parameters for this estimator.
| Parameter | |
|---|---|
| Name | Description |
deep | bool, default TrueDefault |
| Returns | |
|---|---|
| Type | Description |
Dictionary | A dictionary of parameter names mapped to their values. |
predict
predict(
X: typing.Union[
bigframes.dataframe.DataFrame,
bigframes.series.Series,
pandas.core.frame.DataFrame,
pandas.core.series.Series,
],
*,
max_retries: int = 0
) -> bigframes.dataframe.DataFramePredict the result from input DataFrame.
| Parameters | |
|---|---|
| Name | Description |
X | bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.SeriesInput DataFrame or Series, can contain one or more columns. If multiple columns are in the DataFrame, it must contain a "content" column for prediction. |
max_retries | int, default 0Max number of retries if the prediction for any rows failed. Each try needs to make progress (i.e. has successfully predicted rows) to continue the retry. Each retry will append newly succeeded rows. When the max retries are reached, the remaining rows (the ones without successful predictions) will be appended to the end of the result. |
| Returns | |
|---|---|
| Type | Description |
bigframes.dataframe.DataFrame | DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values. |
to_gbq
to_gbq(
model_name: str, replace: bool = False
) -> bigframes.ml.llm.TextEmbeddingGeneratorSave the model to BigQuery.
| Parameters | |
|---|---|
| Name | Description |
model_name | strThe name of the model. |
replace | bool, default FalseDetermine whether to replace if the model already exists. Default to False. |
| Returns | |
|---|---|
| Type | Description |
TextEmbeddingGenerator | Saved model. |