bigframes.bigquery.ml.generate_embedding#
- bigframes.bigquery.ml.generate_embedding(model: BaseEstimator | str | Series, input_: DataFrame | DataFrame | str, *, flatten_json_output: bool | None = None, task_type: str | None = None, output_dimensionality: int | None = None) DataFrame[source]#
Generates text embedding using a BigQuery ML model.
See the BigQuery ML GENERATE_EMBEDDING function syntax for additional reference.
- Parameters:
model (bigframes.ml.base.BaseEstimator or str) – The model to use for text embedding.
input (Union[bigframes.pandas.DataFrame, str]) – The DataFrame or query to use for text embedding.
flatten_json_output (bool, optional) – A BOOL value that determines the content of the generated JSON column.
task_type (str, optional) – A STRING value that specifies the intended downstream application task. Supported values are: - RETRIEVAL_QUERY - RETRIEVAL_DOCUMENT - SEMANTIC_SIMILARITY - CLASSIFICATION - CLUSTERING - QUESTION_ANSWERING - FACT_VERIFICATION - CODE_RETRIEVAL_QUERY
output_dimensionality (int, optional) – An INT64 value that specifies the size of the output embedding.
- Returns:
The generated text embedding.
- Return type: