feat: publish bigframes blob(Multimodal) to preview

bigframes/_config/display_options.py

@@ -35,6 +35,10 @@ class DisplayOptions:
     max_info_rows: Optional[int] = 200000
     memory_usage: bool = True
 
+    blob_display: bool = True
+    blob_display_width: Optional[int] = None
+    blob_display_height: Optional[int] = None
+
 
 @contextlib.contextmanager
 def pandas_repr(display_options: DisplayOptions):

bigframes/_config/experiment_options.py

@@ -15,6 +15,7 @@
 from typing import Optional
 import warnings
 
+import bigframes
 import bigframes.exceptions as bfe
 
 
@@ -26,10 +27,6 @@ class ExperimentOptions:
     def __init__(self):
         self._semantic_operators: bool = False
         self._ai_operators: bool = False
-        self._blob: bool = False
-        self._blob_display: bool = True
-        self._blob_display_width: Optional[int] = None
-        self._blob_display_height: Optional[int] = None
 
     @property
     def semantic_operators(self) -> bool:
@@ -60,41 +57,72 @@ def ai_operators(self, value: bool):
 
     @property
     def blob(self) -> bool:
-        return self._blob
+        msg = bfe.format_message(
+            "BigFrames Blob is in preview now. This flag is no longer needed."
+        )
+        warnings.warn(msg, category=bfe.ApiDeprecationWarning)
+        return True
 
     @blob.setter
     def blob(self, value: bool):
-        if value is True:
-            msg = bfe.format_message(
-                "BigFrames Blob is still under experiments. It may not work and "
-                "subject to change in the future."
-            )
-            warnings.warn(msg, category=bfe.PreviewWarning)
-        self._blob = value
+        msg = bfe.format_message(
+            "BigFrames Blob is in preview now. This flag is no longer needed."
+        )
+        warnings.warn(msg, category=bfe.ApiDeprecationWarning)
 
     @property
     def blob_display(self) -> bool:
         """Whether to display the blob content in notebook DataFrame preview. Default True."""
-        return self._blob_display
+        msg = bfe.format_message(
+            "BigFrames Blob is in preview now. The option has been moved to bigframes.options.display.blob_display."
+        )
+        warnings.warn(msg, category=bfe.ApiDeprecationWarning)
+
+        return bigframes.options.display.blob_display
 
     @blob_display.setter
     def blob_display(self, value: bool):
-        self._blob_display = value
+        msg = bfe.format_message(
+            "BigFrames Blob is in preview now. The option has been moved to bigframes.options.display.blob_display."
+        )
+        warnings.warn(msg, category=bfe.ApiDeprecationWarning)
+
+        bigframes.options.display.blob_display = value
 
     @property
     def blob_display_width(self) -> Optional[int]:
         """Width in pixels that the blob constrained to."""
-        return self._blob_display_width
+        msg = bfe.format_message(
+            "BigFrames Blob is in preview now. The option has been moved to bigframes.options.display.blob_display_width."
+        )
+        warnings.warn(msg, category=bfe.ApiDeprecationWarning)
+
+        return bigframes.options.display.blob_display_width
 
     @blob_display_width.setter
     def blob_display_width(self, value: Optional[int]):
-        self._blob_display_width = value
+        msg = bfe.format_message(
+            "BigFrames Blob is in preview now. The option has been moved to bigframes.options.display.blob_display_width."
+        )
+        warnings.warn(msg, category=bfe.ApiDeprecationWarning)
+
+        bigframes.options.display.blob_display_width = value
 
     @property
     def blob_display_height(self) -> Optional[int]:
         """Height in pixels that the blob constrained to."""
-        return self._blob_display_height
+        msg = bfe.format_message(
+            "BigFrames Blob is in preview now. The option has been moved to bigframes.options.display.blob_display_height."
+        )
+        warnings.warn(msg, category=bfe.ApiDeprecationWarning)
+
+        return bigframes.options.display.blob_display_height
 
     @blob_display_height.setter
     def blob_display_height(self, value: Optional[int]):
-        self._blob_display_height = value
+        msg = bfe.format_message(
+            "BigFrames Blob is in preview now. The option has been moved to bigframes.options.display.blob_display_height."
+        )
+        warnings.warn(msg, category=bfe.ApiDeprecationWarning)
+
+        bigframes.options.display.blob_display_height = value

bigframes/dataframe.py

@@ -768,14 +768,11 @@ def _repr_html_(self) -> str:
             return formatter.repr_query_job(self._compute_dry_run())
 
         df = self.copy()
-        if (
-            bigframes.options.experiments.blob
-            and bigframes.options.experiments.blob_display
-        ):
+        if bigframes.options.display.blob_display:
             blob_cols = [
-                col
-                for col in df.columns
-                if df[col].dtype == bigframes.dtypes.OBJ_REF_DTYPE
+                series_name
+                for series_name, series in df.items()
+                if series.dtype == bigframes.dtypes.OBJ_REF_DTYPE
             ]
             for col in blob_cols:
                 # TODO(garrettwu): Not necessary to get access urls for all the rows. Update when having a to get URLs from local data.
@@ -794,10 +791,7 @@ def _repr_html_(self) -> str:
 
         with display_options.pandas_repr(opts):
             # Allows to preview images in the DataFrame. The implementation changes the string repr as well, that it doesn't truncate strings or escape html charaters such as "<" and ">". We may need to implement a full-fledged repr module to better support types not in pandas.
-            if (
-                bigframes.options.experiments.blob
-                and bigframes.options.experiments.blob_display
-            ):
+            if bigframes.options.display.blob_display and blob_cols:
 
                 def obj_ref_rt_to_html(obj_ref_rt) -> str:
                     obj_ref_rt_json = json.loads(obj_ref_rt)
@@ -809,12 +803,12 @@ def obj_ref_rt_to_html(obj_ref_rt) -> str:
                         )
                         if content_type.startswith("image"):
                             size_str = ""
-                            if bigframes.options.experiments.blob_display_width:
-                                size_str = f' width="{bigframes.options.experiments.blob_display_width}"'
-                            if bigframes.options.experiments.blob_display_height:
+                            if bigframes.options.display.blob_display_width:
+                                size_str = f' width="{bigframes.options.display.blob_display_width}"'
+                            if bigframes.options.display.blob_display_height:
                                 size_str = (
                                     size_str
-                                    + f' height="{bigframes.options.experiments.blob_display_height}"'
+                                    + f' height="{bigframes.options.display.blob_display_height}"'
                                 )
                             url = obj_ref_rt_json["access_urls"]["read_url"]
                             return f'<img src="{url}"{size_str}>'

bigframes/ml/llm.py

@@ -250,7 +250,10 @@ class MultimodalEmbeddingGenerator(base.RetriableRemotePredictor):
     """Multimodal embedding generator LLM model.
 
     .. note::
-        BigFrames Blob is still under experiments. It may not work and subject to change in the future.
+        BigFrames Blob is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
+        Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available "as is"
+        and might have limited support. For more information, see the launch stage descriptions
+        (https://cloud.google.com/products#product-launch-stages).
 
     Args:
         model_name (str, Default to "multimodalembedding@001"):
@@ -271,8 +274,6 @@ def __init__(
         session: Optional[bigframes.Session] = None,
         connection_name: Optional[str] = None,
     ):
-        if not bigframes.options.experiments.blob:
-            raise NotImplementedError()
         if model_name is None:
             model_name = "multimodalembedding@001"
             msg = exceptions.format_message(_REMOVE_DEFAULT_MODEL_WARNING)
@@ -610,7 +611,10 @@ def predict(
 
             prompt (Iterable of str or bigframes.series.Series, or None, default None):
                 .. note::
-                    BigFrames Blob is still under experiments. It may not work and subject to change in the future.
+                    BigFrames Blob is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
+                    Service Specific Terms(https://cloud.google.com/terms/service-terms#1). Pre-GA products and features are available "as is"
+                    and might have limited support. For more information, see the launch stage descriptions
+                    (https://cloud.google.com/products#product-launch-stages).
 
                 Construct a prompt struct column for prediction based on the input. The input must be an Iterable that can take string literals,
                 such as "summarize", string column(s) of X, such as X["str_col"], or blob column(s) of X, such as X["blob_col"].
@@ -646,9 +650,6 @@ def predict(
         (X,) = utils.batch_convert_to_dataframe(X, session=session)
 
         if prompt:
-            if not bigframes.options.experiments.blob:
-                raise NotImplementedError()
-
             if self.model_name not in _GEMINI_MULTIMODAL_ENDPOINTS:
                 raise NotImplementedError(
                     f"GeminiTextGenerator only supports model_name {', '.join(_GEMINI_MULTIMODAL_ENDPOINTS)} for Multimodal prompt."