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This repository was archived by the owner on May 7, 2026. It is now read-only.

Commit 44e0ffd

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tswastgoogle-labs-jules[bot]
tswast
and
google-labs-jules[bot]
authored
docs: Rename Blob column references to ObjectRef column (#2535)
Updates documentation and internal comments to use the term "ObjectRef column" instead of "Blob column", as per the official BigQuery documentation. Links to the documentation are included in user-facing docstrings. --- *PR created automatically by Jules for task [15739234298342142432](https://jules.google.com/task/15739234298342142432) started by @tswast* Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com> Co-authored-by: tswast <247555+tswast@users.noreply.github.com>
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+14-14Lines changed: 14 additions & 14 deletions

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‎bigframes/dataframe.py‎

Copy file name to clipboardExpand all lines: bigframes/dataframe.py
+1-1Lines changed: 1 addition & 1 deletion
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@@ -817,7 +817,7 @@ def __repr__(self) -> str:
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)
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def _get_display_df_and_blob_cols(self) -> tuple[DataFrame, list[str]]:
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"""Process blob columns for display."""
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"""Process ObjectRef columns for display."""
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df = self
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blob_cols = []
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if bigframes.options.display.blob_display:
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‎bigframes/ml/llm.py‎

Copy file name to clipboardExpand all lines: bigframes/ml/llm.py
+4-4Lines changed: 4 additions & 4 deletions
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@@ -286,7 +286,7 @@ class MultimodalEmbeddingGenerator(base.RetriableRemotePredictor):
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"""Multimodal embedding generator LLM model.
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.. note::
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BigFrames Blob is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
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BigFrames ObjectRef is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
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Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available "as is"
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and might have limited support. For more information, see the launch stage descriptions
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(https://cloud.google.com/products#product-launch-stages).
@@ -374,7 +374,7 @@ def predict(
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Args:
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X (bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.Series):
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Input DataFrame or Series, can contain one or more columns. If multiple columns are in the DataFrame, it must contain a "content" column for prediction.
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The content column must be of string type or BigFrames Blob of image or video.
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The content column must be of string type or BigFrames `ObjectRef <https://docs.cloud.google.com/bigquery/docs/objectref-columns>`_ of image or video.
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max_retries (int, default 0):
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Max 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.
@@ -668,13 +668,13 @@ def predict(
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prompt (Iterable of str or bigframes.series.Series, or None, default None):
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.. note::
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BigFrames Blob is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
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BigFrames ObjectRef is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
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Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available "as is"
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and might have limited support. For more information, see the launch stage descriptions
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(https://cloud.google.com/products#product-launch-stages).
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Construct a prompt struct column for prediction based on the input. The input must be an Iterable that can take string literals,
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such as "summarize", string column(s) of X, such as X["str_col"], or blob column(s) of X, such as X["blob_col"].
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such as "summarize", string column(s) of X, such as X["str_col"], or `ObjectRef column(s) <https://docs.cloud.google.com/bigquery/docs/objectref-columns>`_ of X, such as X["objectref_col"].
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It creates a struct column of the items of the iterable, and use the concatenated result as the input prompt. No-op if set to None.
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output_schema (Mapping[str, str] or None, default None):
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The schema used to generate structured output as a bigframes DataFrame. The schema is a string key-value pair of <column_name>:<type>.
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‎bigframes/operations/ai.py‎

Copy file name to clipboardExpand all lines: bigframes/operations/ai.py
+1-1Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -203,7 +203,7 @@ def map(
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has_blob_column = False
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for column in columns:
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if df[column].dtype == dtypes.OBJ_REF_DTYPE:
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# Don't cast blob columns to string
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# Don't cast ObjectRef columns to string
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has_blob_column = True
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continue
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‎bigframes/operations/semantics.py‎

Copy file name to clipboardExpand all lines: bigframes/operations/semantics.py
+2-2Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -382,7 +382,7 @@ def filter(self, instruction: str, model, ground_with_google_search: bool = Fals
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has_blob_column = False
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for column in columns:
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if df[column].dtype == dtypes.OBJ_REF_DTYPE:
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# Don't cast blob columns to string
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# Don't cast ObjectRef columns to string
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has_blob_column = True
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continue
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@@ -501,7 +501,7 @@ def map(
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has_blob_column = False
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for column in columns:
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if df[column].dtype == dtypes.OBJ_REF_DTYPE:
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# Don't cast blob columns to string
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# Don't cast ObjectRef columns to string
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has_blob_column = True
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continue
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‎bigframes/session/__init__.py‎

Copy file name to clipboardExpand all lines: bigframes/session/__init__.py
+6-6Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -2234,12 +2234,12 @@ def _create_temp_table(
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def from_glob_path(
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self, path: str, *, connection: Optional[str] = None, name: Optional[str] = None
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) -> dataframe.DataFrame:
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r"""Create a BigFrames DataFrame that contains a BigFrames Blob column from a global wildcard path.
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r"""Create a BigFrames DataFrame that contains a BigFrames `ObjectRef column <https://docs.cloud.google.com/bigquery/docs/objectref-columns>`_ from a global wildcard path.
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This operation creates a temporary BQ Object Table under the hood and requires bigquery.connections.delegate permission or BigQuery Connection Admin role.
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If you have an existing BQ Object Table, use read_gbq_object_table().
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.. note::
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BigFrames Blob is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
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BigFrames ObjectRef is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
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Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available "as is"
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and might have limited support. For more information, see the launch stage descriptions
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(https://cloud.google.com/products#product-launch-stages).
@@ -2252,7 +2252,7 @@ def from_glob_path(
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If None, use default connection in session context. BigQuery DataFrame will try to create the connection and attach
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permission if the connection isn't fully set up.
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name (str):
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The column name of the Blob column.
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The column name of the ObjectRef column.
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Returns:
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bigframes.pandas.DataFrame:
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Result BigFrames DataFrame.
@@ -2295,18 +2295,18 @@ def _create_bq_connection(
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def read_gbq_object_table(
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self, object_table: str, *, name: Optional[str] = None
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) -> dataframe.DataFrame:
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"""Read an existing object table to create a BigFrames Blob DataFrame. Use the connection of the object table for the connection of the blob.
2298+
"""Read an existing object table to create a BigFrames `ObjectRef <https://docs.cloud.google.com/bigquery/docs/objectref-columns>`_ DataFrame. Use the connection of the object table for the connection of the ObjectRef.
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This function dosen't retrieve the object table data. If you want to read the data, use read_gbq() instead.
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.. note::
2302-
BigFrames Blob is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
2302+
BigFrames ObjectRef is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
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Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available "as is"
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and might have limited support. For more information, see the launch stage descriptions
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(https://cloud.google.com/products#product-launch-stages).
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Args:
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object_table (str): name of the object table of form <PROJECT_ID>.<DATASET_ID>.<TABLE_ID>.
2309-
name (str or None): the returned blob column name.
2309+
name (str or None): the returned ObjectRef column name.
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Returns:
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bigframes.pandas.DataFrame:

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