From d250e14789b84842ff1acd1ce2ce79124fbf4f1b Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Tue, 9 Sep 2025 04:34:10 +0000
Subject: [PATCH 01/11] feat: Add ai_generate_bool to the bigframes.bigquery
 package

---
 bigframes/bigquery/__init__.py                |   3 +
 bigframes/bigquery/_operations/ai.py          | 177 ++++++++++++++++++
 .../ibis_compiler/scalar_op_registry.py       |  28 +++
 bigframes/operations/__init__.py              |   3 +
 bigframes/operations/ai_ops.py                |  47 +++++
 tests/system/large/bigquery/__init__.py       |  13 ++
 tests/system/large/bigquery/test_ai.py        |  35 ++++
 tests/system/small/bigquery/test_ai.py        |  37 ++++
 .../sql/compilers/bigquery/__init__.py        |  15 ++
 .../ibis/expr/operations/ai_ops.py            |  30 +++
 10 files changed, 388 insertions(+)
 create mode 100644 bigframes/bigquery/_operations/ai.py
 create mode 100644 bigframes/operations/ai_ops.py
 create mode 100644 tests/system/large/bigquery/__init__.py
 create mode 100644 tests/system/large/bigquery/test_ai.py
 create mode 100644 tests/system/small/bigquery/test_ai.py
 create mode 100644 third_party/bigframes_vendored/ibis/expr/operations/ai_ops.py

diff --git a/bigframes/bigquery/__init__.py b/bigframes/bigquery/__init__.py
index 32412648d6..c82306c764 100644
--- a/bigframes/bigquery/__init__.py
+++ b/bigframes/bigquery/__init__.py
@@ -18,6 +18,7 @@
 
 import sys
 
+from bigframes.bigquery._operations.ai import ai_generate_bool
 from bigframes.bigquery._operations.approx_agg import approx_top_count
 from bigframes.bigquery._operations.array import (
     array_agg,
@@ -57,6 +58,8 @@
 from bigframes.core import log_adapter
 
 _functions = [
+    # ai ops
+    ai_generate_bool,
     # approximate aggregate ops
     approx_top_count,
     # array ops
diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
new file mode 100644
index 0000000000..6ba7423680
--- /dev/null
+++ b/bigframes/bigquery/_operations/ai.py
@@ -0,0 +1,177 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import functools
+import json
+from typing import Any, List, Literal, Mapping, Sequence, Tuple
+
+from bigframes import clients, dtypes, series
+from bigframes.operations import ai_ops
+
+
+def ai_generate_bool(
+    prompt: series.Series | List[str | series.Series] | Tuple[str | series.Series],
+    *,
+    connection_id: str | None = None,
+    endpoint: str | None = None,
+    request_type: Literal["dedicated", "shared", "unspecified"] = "unspecified",
+    model_params: Mapping[Any, Any] | None = None,
+) -> series.Series:
+    """Returns the AI analysis based on the prompt, which can be any combination of text and unstructured data.
+
+    **Examples:**
+
+        >>> import bigframes.pandas as bpd
+        >>> import bigframes.bigquery as bbq
+        >>> bpd.options.display.progress_bar = None
+        >>> df = bpd.DataFrame({
+        ...     "col_1": ["apple", "bear", "pear"],
+        ...     "col_2": ["fruit", "animal", "animal"]
+        ... })
+        >>> bbq.ai_generate_bool((df["col_1"], " is a ", df["col_2"]))
+        0    {'result': True, 'full_response': '{"candidate...
+        1    {'result': True, 'full_response': '{"candidate...
+        2    {'result': False, 'full_response': '{"candidat...
+        dtype: struct<result: bool, full_response: string, status: string>[pyarrow]
+
+        >>> bbq.ai_generate_bool((df["col_1"], " is a ", df["col_2"])).struct.field("result")
+        0     True
+        1     True
+        2    False
+        Name: result, dtype: boolean
+
+        >>> model_params = {
+        ...     "generation_config": {
+        ...         "thinking_config": {
+        ...             "thinking_budget": 0
+        ...         }
+        ...     }
+        ... }
+        >>> bbq.ai_generate_bool(
+        ...     (df["col_1"], " is a ", df["col_2"]),
+        ...     endpoint="gemini-2.5-pro",
+        ...     model_params=model_params,
+        ... ).struct.field("result")
+        0     True
+        1     True
+        2    False
+        Name: result, dtype: boolean
+
+    Args:
+        prompt (series.Series | List[str|series.Series] | Tuple[str|series.Series]):
+            A mixture of Series and string literals that specifies the prompt to send to the model.
+        connection_id (str, optional):
+            Specifies the connection to use to communicate with the model. For example, `myproject.us.myconnection`.
+            If not provided, the connection from the current session will be used.
+        endpoint (str, optional):
+            Specifies the Vertex AI endpoint to use for the model. You can specify any generally available
+            or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
+            uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML selects
+            a recent stable version of Gemini to use.
+        request_type (Literal["dedicated", "shared", "unspecified"]):
+            Specifies the type of inference request to send to the Gemini model. The request type determines what
+            quota the request uses.
+            * "dedicated": function only uses Provisioned Throughput quota. The AI.GENERATE function returns the error Provisioned throughput is not purchased or is not active if Provisioned Throughput quota isn't available.
+            * "shared": the function only uses dynamic shared quota (DSQ), even if you have purchased Provisioned Throughput quota.
+            * "unspecified":
+                * If you haven't purchased Provisioned Throughput quota, the function uses DSQ quota.
+                * If you have purchased Provisioned Throughput quota, the function uses the Provisioned Throughput quota first. If requests exceed the Provisioned Throughput quota, the overflow traffic uses DSQ quota.
+        model_params (Mapping[Any, Any]):
+            Provides additional parameters to the model. The MODEL_PARAMS value must conform to the generateContent request body format.
+
+    Returns:
+        bigframes.series.Series: A new struct Series with the result data. The struct contains these fields:
+        * "result": a BOOL value containing the model's response to the prompt. The result is None if the request fails or is filtered by responsible AI.
+        * "full_resposne": a STRING value containing the JSON response from the projects.locations.endpoints.generateContent call to the model. The generated text is in the text element.
+        * "status": a STRING value that contains the API response status for the corresponding row. This value is empty if the operation was successful.
+    """
+
+    if request_type not in ("dedicated", "shared", "unspecified"):
+        raise ValueError(f"Unsupported request type: {request_type}")
+
+    prompt_context, series_list = _separate_context_and_series(prompt)
+
+    if not series_list:
+        raise ValueError("Please provide at least one Series in the prompt")
+
+    operator = ai_ops.AIGenerateBool(
+        prompt_context=tuple(prompt_context),
+        connection_id=_resolve_connection_id(series_list[0], connection_id),
+        endpoint=endpoint,
+        request_type=request_type,
+        model_params=json.dumps(model_params) if model_params else None,
+    )
+
+    return series_list[0]._apply_nary_op(operator, series_list[1:])
+
+
+@functools.singledispatch
+def _separate_context_and_series(
+    prompt: Any,
+) -> Tuple[List[str | None], List[series.Series]]:
+    """
+    Returns the two values. The first value is the prompt with all series replaced by None. The second value is all the series
+    in the prompt. The original item order is kept.
+    For example:
+    Input: ("str1", series1, "str2", "str3", series2)
+    Output: ["str1", None, "str2", "str3", None], [series1, series2]
+    """
+    raise ValueError(f"Unsupported prompt type: {type(prompt)}")
+
+
+@_separate_context_and_series.register
+def _(
+    prompt: series.Series,
+) -> Tuple[List[str | None], List[series.Series]]:
+    if prompt.dtype == dtypes.OBJ_REF_DTYPE:
+        # Multi-model support
+        return [None], [prompt.blob.read_url()]
+    return [None], [prompt]
+
+
+@_separate_context_and_series.register(list)
+@_separate_context_and_series.register(tuple)
+def _(
+    prompt: Sequence[str | series.Series],
+) -> Tuple[List[str | None], List[series.Series]]:
+
+    prompt_context: List[str | None] = []
+    series_list: List[series.Series] = []
+
+    for item in prompt:
+        if isinstance(item, str):
+            prompt_context.append(item)
+
+        elif isinstance(item, series.Series):
+            prompt_context.append(None)
+
+            if item.dtype == dtypes.OBJ_REF_DTYPE:
+                # Multi-model support
+                item = item.blob.read_url()
+            series_list.append(item)
+
+        else:
+            raise ValueError(f"Unsupported type in prompt: {type(item)}")
+
+    return prompt_context, series_list
+
+
+def _resolve_connection_id(series: series.Series, connection_id: str | None):
+    return clients.get_canonical_bq_connection_id(
+        connection_id or series._session._bq_connection,
+        series._session._project,
+        series._session._location,
+    )
diff --git a/bigframes/core/compile/ibis_compiler/scalar_op_registry.py b/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
index 044fc90306..8cfbb9936d 100644
--- a/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
+++ b/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
@@ -17,8 +17,10 @@
 import functools
 import typing
 
+from bigframes_vendored import ibis
 import bigframes_vendored.ibis.expr.api as ibis_api
 import bigframes_vendored.ibis.expr.datatypes as ibis_dtypes
+import bigframes_vendored.ibis.expr.operations.ai_ops as ai_ops
 import bigframes_vendored.ibis.expr.operations.generic as ibis_generic
 import bigframes_vendored.ibis.expr.operations.udf as ibis_udf
 import bigframes_vendored.ibis.expr.types as ibis_types
@@ -1963,6 +1965,32 @@ def struct_op_impl(
     return ibis_types.struct(data)
 
 
+@scalar_op_compiler.register_nary_op(ops.AIGenerateBool, pass_op=True)
+def ai_generate_bool(
+    *values: ibis_types.Value, op: ops.AIGenerateBool
+) -> ibis_dtypes.StructValue:
+
+    prompt = {}
+    column_ref_idx = 0
+
+    for idx, elem in enumerate(op.prompt_context):
+        if elem is None:
+            value = values[column_ref_idx]
+            column_ref_idx += 1
+        else:
+            value = elem
+
+        prompt[f"_field_{idx + 1}"] = value
+
+    return ai_ops.AIGenerateBool(
+        ibis.struct(prompt),
+        op.connection_id,
+        op.endpoint,
+        op.request_type.upper(),
+        op.model_params,
+    ).to_expr()
+
+
 @scalar_op_compiler.register_nary_op(ops.RowKey, pass_op=True)
 def rowkey_op_impl(*values: ibis_types.Value, op: ops.RowKey) -> ibis_types.Value:
     return bigframes.core.compile.default_ordering.gen_row_key(values)
diff --git a/bigframes/operations/__init__.py b/bigframes/operations/__init__.py
index e5888ace00..bb9ec4d294 100644
--- a/bigframes/operations/__init__.py
+++ b/bigframes/operations/__init__.py
@@ -14,6 +14,7 @@
 
 from __future__ import annotations
 
+from bigframes.operations.ai_ops import AIGenerateBool
 from bigframes.operations.array_ops import (
     ArrayIndexOp,
     ArrayReduceOp,
@@ -408,6 +409,8 @@
     "geo_x_op",
     "geo_y_op",
     "GeoStDistanceOp",
+    # AI ops
+    "AIGenerateBool",
     # Numpy ops mapping
     "NUMPY_TO_BINOP",
     "NUMPY_TO_OP",
diff --git a/bigframes/operations/ai_ops.py b/bigframes/operations/ai_ops.py
new file mode 100644
index 0000000000..e9ba2ceeee
--- /dev/null
+++ b/bigframes/operations/ai_ops.py
@@ -0,0 +1,47 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import dataclasses
+from typing import ClassVar, Literal, Tuple
+
+import pandas as pd
+import pyarrow as pa
+
+from bigframes import dtypes
+from bigframes.operations import base_ops
+
+
+@dataclasses.dataclass(frozen=True)
+class AIGenerateBool(base_ops.NaryOp):
+    name: ClassVar[str] = "ai_generate_bool"
+
+    # None are the placeholders for column references.
+    prompt_context: Tuple[str | None]
+    connection_id: str
+    endpoint: str | None
+    request_type: Literal["dedicated", "shared", "unspecified"]
+    model_params: str | None
+
+    def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
+        return pd.ArrowDtype(
+            pa.struct(
+                (
+                    pa.field("result", pa.bool_()),
+                    pa.field("full_response", pa.string()),
+                    pa.field("status", pa.string()),
+                )
+            )
+        )
diff --git a/tests/system/large/bigquery/__init__.py b/tests/system/large/bigquery/__init__.py
new file mode 100644
index 0000000000..0a2669d7a2
--- /dev/null
+++ b/tests/system/large/bigquery/__init__.py
@@ -0,0 +1,13 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/tests/system/large/bigquery/test_ai.py b/tests/system/large/bigquery/test_ai.py
new file mode 100644
index 0000000000..447105148e
--- /dev/null
+++ b/tests/system/large/bigquery/test_ai.py
@@ -0,0 +1,35 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import pandas as pd
+import pandas.testing
+
+import bigframes.bigquery as bbq
+
+
+def test_ai_generate_bool_multi_model(session):
+    df = session.from_glob_path(
+        "gs://bigframes-dev-testing/a_multimodel/images/*", name="image"
+    )
+
+    result = bbq.ai_generate_bool((df["image"], " contains an animal")).struct.field(
+        "result"
+    )
+
+    pandas.testing.assert_series_equal(
+        result.to_pandas(),
+        pd.Series([True, True, False, False, False], name="result"),
+        check_dtype=False,
+        check_index=False,
+    )
diff --git a/tests/system/small/bigquery/test_ai.py b/tests/system/small/bigquery/test_ai.py
new file mode 100644
index 0000000000..42cbaee7ed
--- /dev/null
+++ b/tests/system/small/bigquery/test_ai.py
@@ -0,0 +1,37 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import pandas as pd
+import pandas.testing
+
+import bigframes.bigquery as bbq
+import bigframes.pandas as bpd
+
+
+def test_ai_generate_bool(session):
+    s1 = bpd.Series(["apple", "bear"], session=session)
+    s2 = bpd.Series(["fruit", "tree"], session=session)
+    prompt = (s1, " is a ", s2)
+    model_params = {"generation_config": {"thinking_config": {"thinking_budget": 0}}}
+
+    result = bbq.ai_generate_bool(
+        prompt, endpoint="gemini-2.5-flash", model_params=model_params
+    ).struct.field("result")
+
+    pandas.testing.assert_series_equal(
+        result.to_pandas(),
+        pd.Series([True, False], name="result"),
+        check_dtype=False,
+        check_index=False,
+    )
diff --git a/third_party/bigframes_vendored/ibis/backends/sql/compilers/bigquery/__init__.py b/third_party/bigframes_vendored/ibis/backends/sql/compilers/bigquery/__init__.py
index 9af2a4afe4..6ea11d5215 100644
--- a/third_party/bigframes_vendored/ibis/backends/sql/compilers/bigquery/__init__.py
+++ b/third_party/bigframes_vendored/ibis/backends/sql/compilers/bigquery/__init__.py
@@ -1104,6 +1104,21 @@ def visit_StringAgg(self, op, *, arg, sep, order_by, where):
             expr = arg
         return self.agg.string_agg(expr, sep, where=where)
 
+    def visit_AIGenerateBool(self, op, **kwargs):
+        func_name = "AI.GENERATE_BOOL"
+
+        args = []
+        for key, val in kwargs.items():
+            if val is None:
+                continue
+
+            if key == "model_params":
+                val = sge.JSON(this=val)
+
+            args.append(sge.Kwarg(this=sge.Identifier(this=key), expression=val))
+
+        return sge.func(func_name, *args)
+
     def visit_FirstNonNullValue(self, op, *, arg):
         return sge.IgnoreNulls(this=sge.FirstValue(this=arg))
 
diff --git a/third_party/bigframes_vendored/ibis/expr/operations/ai_ops.py b/third_party/bigframes_vendored/ibis/expr/operations/ai_ops.py
new file mode 100644
index 0000000000..5a81738c6b
--- /dev/null
+++ b/third_party/bigframes_vendored/ibis/expr/operations/ai_ops.py
@@ -0,0 +1,30 @@
+# Contains code from https://github.com/ibis-project/ibis/blob/9.2.0/ibis/expr/operations/maps.py
+
+"""Operations for working with maps."""
+
+from __future__ import annotations
+
+from bigframes_vendored.ibis.common.annotations import attribute
+import bigframes_vendored.ibis.expr.datatypes as dt
+from bigframes_vendored.ibis.expr.operations.core import Value
+import bigframes_vendored.ibis.expr.rules as rlz
+from public import public
+
+
+@public
+class AIGenerateBool(Value):
+    """Generate Bool based on the prompt"""
+
+    prompt: Value
+    connection_id: Value[dt.String]
+    endpoint: Value[dt.String] | None
+    request_type: Value[dt.String]
+    model_params: Value[dt.String] | None
+
+    shape = rlz.shape_like("prompt")
+
+    @attribute
+    def dtype(self) -> dt.Struct:
+        return dt.Struct.from_tuples(
+            (("result", dt.bool), ("full_resposne", dt.string), ("status", dt.string))
+        )

From 442654d0369fe0d0198117abfaf5379a6fab49c2 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Tue, 9 Sep 2025 04:59:17 +0000
Subject: [PATCH 02/11] fix stuffs

---
 bigframes/bigquery/_operations/ai.py          | 10 +++++-----
 .../ibis_compiler/scalar_op_registry.py       | 20 +++++++++----------
 bigframes/operations/ai_ops.py                |  2 +-
 .../ibis/expr/operations/ai_ops.py            |  6 ++++--
 4 files changed, 19 insertions(+), 19 deletions(-)

diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
index 6ba7423680..aa701a4d66 100644
--- a/bigframes/bigquery/_operations/ai.py
+++ b/bigframes/bigquery/_operations/ai.py
@@ -23,7 +23,7 @@
 
 
 def ai_generate_bool(
-    prompt: series.Series | List[str | series.Series] | Tuple[str | series.Series],
+    prompt: series.Series | List[str | series.Series] | Tuple[str | series.Series, ...],
     *,
     connection_id: str | None = None,
     endpoint: str | None = None,
@@ -71,7 +71,7 @@ def ai_generate_bool(
         Name: result, dtype: boolean
 
     Args:
-        prompt (series.Series | List[str|series.Series] | Tuple[str|series.Series]):
+        prompt (series.Series | List[str|series.Series] | Tuple[str|series.Series, ...]):
             A mixture of Series and string literals that specifies the prompt to send to the model.
         connection_id (str, optional):
             Specifies the connection to use to communicate with the model. For example, `myproject.us.myconnection`.
@@ -87,15 +87,15 @@ def ai_generate_bool(
             * "dedicated": function only uses Provisioned Throughput quota. The AI.GENERATE function returns the error Provisioned throughput is not purchased or is not active if Provisioned Throughput quota isn't available.
             * "shared": the function only uses dynamic shared quota (DSQ), even if you have purchased Provisioned Throughput quota.
             * "unspecified":
-                * If you haven't purchased Provisioned Throughput quota, the function uses DSQ quota.
-                * If you have purchased Provisioned Throughput quota, the function uses the Provisioned Throughput quota first. If requests exceed the Provisioned Throughput quota, the overflow traffic uses DSQ quota.
+                If you haven't purchased Provisioned Throughput quota, the function uses DSQ quota.
+                If you have purchased Provisioned Throughput quota, the function uses the Provisioned Throughput quota first. If requests exceed the Provisioned Throughput quota, the overflow traffic uses DSQ quota.
         model_params (Mapping[Any, Any]):
             Provides additional parameters to the model. The MODEL_PARAMS value must conform to the generateContent request body format.
 
     Returns:
         bigframes.series.Series: A new struct Series with the result data. The struct contains these fields:
         * "result": a BOOL value containing the model's response to the prompt. The result is None if the request fails or is filtered by responsible AI.
-        * "full_resposne": a STRING value containing the JSON response from the projects.locations.endpoints.generateContent call to the model. The generated text is in the text element.
+        * "full_response": a STRING value containing the JSON response from the projects.locations.endpoints.generateContent call to the model. The generated text is in the text element.
         * "status": a STRING value that contains the API response status for the corresponding row. This value is empty if the operation was successful.
     """
 
diff --git a/bigframes/core/compile/ibis_compiler/scalar_op_registry.py b/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
index 8cfbb9936d..2f7d943829 100644
--- a/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
+++ b/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
@@ -1968,26 +1968,24 @@ def struct_op_impl(
 @scalar_op_compiler.register_nary_op(ops.AIGenerateBool, pass_op=True)
 def ai_generate_bool(
     *values: ibis_types.Value, op: ops.AIGenerateBool
-) -> ibis_dtypes.StructValue:
+) -> ibis_types.StructValue:
 
-    prompt = {}
+    prompt: dict[str, ibis_types.Value | str] = {}
     column_ref_idx = 0
 
     for idx, elem in enumerate(op.prompt_context):
         if elem is None:
-            value = values[column_ref_idx]
+            prompt[f"_field_{idx + 1}"] = values[column_ref_idx]
             column_ref_idx += 1
         else:
-            value = elem
-
-        prompt[f"_field_{idx + 1}"] = value
+            prompt[f"_field_{idx + 1}"] = elem
 
     return ai_ops.AIGenerateBool(
-        ibis.struct(prompt),
-        op.connection_id,
-        op.endpoint,
-        op.request_type.upper(),
-        op.model_params,
+        ibis.struct(prompt),  # type: ignore  
+        op.connection_id,# type: ignore
+        op.endpoint,# type: ignore
+        op.request_type.upper(),# type: ignore
+        op.model_params,# type: ignore
     ).to_expr()
 
 
diff --git a/bigframes/operations/ai_ops.py b/bigframes/operations/ai_ops.py
index e9ba2ceeee..fe5eb1406f 100644
--- a/bigframes/operations/ai_ops.py
+++ b/bigframes/operations/ai_ops.py
@@ -29,7 +29,7 @@ class AIGenerateBool(base_ops.NaryOp):
     name: ClassVar[str] = "ai_generate_bool"
 
     # None are the placeholders for column references.
-    prompt_context: Tuple[str | None]
+    prompt_context: Tuple[str | None, ...]
     connection_id: str
     endpoint: str | None
     request_type: Literal["dedicated", "shared", "unspecified"]
diff --git a/third_party/bigframes_vendored/ibis/expr/operations/ai_ops.py b/third_party/bigframes_vendored/ibis/expr/operations/ai_ops.py
index 5a81738c6b..1f8306bad6 100644
--- a/third_party/bigframes_vendored/ibis/expr/operations/ai_ops.py
+++ b/third_party/bigframes_vendored/ibis/expr/operations/ai_ops.py
@@ -4,6 +4,8 @@
 
 from __future__ import annotations
 
+from typing import Optional
+
 from bigframes_vendored.ibis.common.annotations import attribute
 import bigframes_vendored.ibis.expr.datatypes as dt
 from bigframes_vendored.ibis.expr.operations.core import Value
@@ -17,9 +19,9 @@ class AIGenerateBool(Value):
 
     prompt: Value
     connection_id: Value[dt.String]
-    endpoint: Value[dt.String] | None
+    endpoint: Optional[Value[dt.String]]
     request_type: Value[dt.String]
-    model_params: Value[dt.String] | None
+    model_params: Optional[Value[dt.String]]
 
     shape = rlz.shape_like("prompt")
 

From cf255ec7f1ad243f155a9182acf046b6e4debd88 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Tue, 9 Sep 2025 05:05:16 +0000
Subject: [PATCH 03/11] Fix format

---
 bigframes/bigquery/_operations/ai.py                | 13 +++++++------
 .../compile/ibis_compiler/scalar_op_registry.py     | 10 +++++-----
 2 files changed, 12 insertions(+), 11 deletions(-)

diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
index aa701a4d66..d0625888f2 100644
--- a/bigframes/bigquery/_operations/ai.py
+++ b/bigframes/bigquery/_operations/ai.py
@@ -30,7 +30,8 @@ def ai_generate_bool(
     request_type: Literal["dedicated", "shared", "unspecified"] = "unspecified",
     model_params: Mapping[Any, Any] | None = None,
 ) -> series.Series:
-    """Returns the AI analysis based on the prompt, which can be any combination of text and unstructured data.
+    """
+    Returns the AI analysis based on the prompt, which can be any combination of text and unstructured data.
 
     **Examples:**
 
@@ -77,14 +78,14 @@ def ai_generate_bool(
             Specifies the connection to use to communicate with the model. For example, `myproject.us.myconnection`.
             If not provided, the connection from the current session will be used.
         endpoint (str, optional):
-            Specifies the Vertex AI endpoint to use for the model. You can specify any generally available
-            or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
-            uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML selects
-            a recent stable version of Gemini to use.
+            Specifies the Vertex AI endpoint to use for the model. For example `"gemini-2.5-flash"`. You can specify any
+            generally available or preview Gemini model. If you specify the model name, BigQuery ML automatically identifies and
+            uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML selects a recent stable
+            version of Gemini to use.
         request_type (Literal["dedicated", "shared", "unspecified"]):
             Specifies the type of inference request to send to the Gemini model. The request type determines what
             quota the request uses.
-            * "dedicated": function only uses Provisioned Throughput quota. The AI.GENERATE function returns the error Provisioned throughput is not purchased or is not active if Provisioned Throughput quota isn't available.
+            * "dedicated": function only uses Provisioned Throughput quota. The function returns the error Provisioned throughput is not purchased or is not active if Provisioned Throughput quota isn't available.
             * "shared": the function only uses dynamic shared quota (DSQ), even if you have purchased Provisioned Throughput quota.
             * "unspecified":
                 If you haven't purchased Provisioned Throughput quota, the function uses DSQ quota.
diff --git a/bigframes/core/compile/ibis_compiler/scalar_op_registry.py b/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
index 2f7d943829..3cc9cc32d5 100644
--- a/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
+++ b/bigframes/core/compile/ibis_compiler/scalar_op_registry.py
@@ -1981,11 +1981,11 @@ def ai_generate_bool(
             prompt[f"_field_{idx + 1}"] = elem
 
     return ai_ops.AIGenerateBool(
-        ibis.struct(prompt),  # type: ignore  
-        op.connection_id,# type: ignore
-        op.endpoint,# type: ignore
-        op.request_type.upper(),# type: ignore
-        op.model_params,# type: ignore
+        ibis.struct(prompt),  # type: ignore
+        op.connection_id,  # type: ignore
+        op.endpoint,  # type: ignore
+        op.request_type.upper(),  # type: ignore
+        op.model_params,  # type: ignore
     ).to_expr()
 
 

From 85d5f934757cad9f5a372b0b6c96a96f712feb03 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Tue, 9 Sep 2025 05:10:51 +0000
Subject: [PATCH 04/11] fix doc format

---
 bigframes/bigquery/_operations/ai.py | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
index d0625888f2..db581a89cf 100644
--- a/bigframes/bigquery/_operations/ai.py
+++ b/bigframes/bigquery/_operations/ai.py
@@ -83,20 +83,21 @@ def ai_generate_bool(
             uses the full endpoint of the model. If you don't specify an ENDPOINT value, BigQuery ML selects a recent stable
             version of Gemini to use.
         request_type (Literal["dedicated", "shared", "unspecified"]):
-            Specifies the type of inference request to send to the Gemini model. The request type determines what
-            quota the request uses.
-            * "dedicated": function only uses Provisioned Throughput quota. The function returns the error Provisioned throughput is not purchased or is not active if Provisioned Throughput quota isn't available.
+            Specifies the type of inference request to send to the Gemini model. The request type determines what quota the request uses.
+            * "dedicated": function only uses Provisioned Throughput quota. The function returns the error Provisioned throughput is not 
+            purchased or is not active if Provisioned Throughput quota isn't available.
             * "shared": the function only uses dynamic shared quota (DSQ), even if you have purchased Provisioned Throughput quota.
-            * "unspecified":
-                If you haven't purchased Provisioned Throughput quota, the function uses DSQ quota.
-                If you have purchased Provisioned Throughput quota, the function uses the Provisioned Throughput quota first. If requests exceed the Provisioned Throughput quota, the overflow traffic uses DSQ quota.
+            * "unspecified": If you haven't purchased Provisioned Throughput quota, the function uses DSQ quota. 
+            If you have purchased Provisioned Throughput quota, the function uses the Provisioned Throughput quota first. 
+            If requests exceed the Provisioned Throughput quota, the overflow traffic uses DSQ quota.
         model_params (Mapping[Any, Any]):
             Provides additional parameters to the model. The MODEL_PARAMS value must conform to the generateContent request body format.
 
     Returns:
         bigframes.series.Series: A new struct Series with the result data. The struct contains these fields:
         * "result": a BOOL value containing the model's response to the prompt. The result is None if the request fails or is filtered by responsible AI.
-        * "full_response": a STRING value containing the JSON response from the projects.locations.endpoints.generateContent call to the model. The generated text is in the text element.
+        * "full_response": a STRING value containing the JSON response from the projects.locations.endpoints.generateContent call to the model. 
+        The generated text is in the text element.
         * "status": a STRING value that contains the API response status for the corresponding row. This value is empty if the operation was successful.
     """
 

From 1f00e3c461c05222fccff4c22547959c3f7cce67 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Tue, 9 Sep 2025 05:13:42 +0000
Subject: [PATCH 05/11] fix format

---
 bigframes/bigquery/_operations/ai.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
index db581a89cf..43c640d17d 100644
--- a/bigframes/bigquery/_operations/ai.py
+++ b/bigframes/bigquery/_operations/ai.py
@@ -84,11 +84,11 @@ def ai_generate_bool(
             version of Gemini to use.
         request_type (Literal["dedicated", "shared", "unspecified"]):
             Specifies the type of inference request to send to the Gemini model. The request type determines what quota the request uses.
-            * "dedicated": function only uses Provisioned Throughput quota. The function returns the error Provisioned throughput is not 
+            * "dedicated": function only uses Provisioned Throughput quota. The function returns the error Provisioned throughput is not
             purchased or is not active if Provisioned Throughput quota isn't available.
             * "shared": the function only uses dynamic shared quota (DSQ), even if you have purchased Provisioned Throughput quota.
-            * "unspecified": If you haven't purchased Provisioned Throughput quota, the function uses DSQ quota. 
-            If you have purchased Provisioned Throughput quota, the function uses the Provisioned Throughput quota first. 
+            * "unspecified": If you haven't purchased Provisioned Throughput quota, the function uses DSQ quota.
+            If you have purchased Provisioned Throughput quota, the function uses the Provisioned Throughput quota first.
             If requests exceed the Provisioned Throughput quota, the overflow traffic uses DSQ quota.
         model_params (Mapping[Any, Any]):
             Provides additional parameters to the model. The MODEL_PARAMS value must conform to the generateContent request body format.
@@ -96,7 +96,7 @@ def ai_generate_bool(
     Returns:
         bigframes.series.Series: A new struct Series with the result data. The struct contains these fields:
         * "result": a BOOL value containing the model's response to the prompt. The result is None if the request fails or is filtered by responsible AI.
-        * "full_response": a STRING value containing the JSON response from the projects.locations.endpoints.generateContent call to the model. 
+        * "full_response": a STRING value containing the JSON response from the projects.locations.endpoints.generateContent call to the model.
         The generated text is in the text element.
         * "status": a STRING value that contains the API response status for the corresponding row. This value is empty if the operation was successful.
     """

From b2446abf3961ea17465a31929d9ec399ffc0b870 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Tue, 9 Sep 2025 05:52:34 +0000
Subject: [PATCH 06/11] fix code

---
 bigframes/bigquery/_operations/ai.py | 42 ++++++++++------------------
 1 file changed, 14 insertions(+), 28 deletions(-)

diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
index 43c640d17d..4b50d7051b 100644
--- a/bigframes/bigquery/_operations/ai.py
+++ b/bigframes/bigquery/_operations/ai.py
@@ -14,9 +14,8 @@
 
 from __future__ import annotations
 
-import functools
 import json
-from typing import Any, List, Literal, Mapping, Sequence, Tuple
+from typing import Any, List, Literal, Mapping, Tuple
 
 from bigframes import clients, dtypes, series
 from bigframes.operations import ai_ops
@@ -101,13 +100,8 @@ def ai_generate_bool(
         * "status": a STRING value that contains the API response status for the corresponding row. This value is empty if the operation was successful.
     """
 
-    if request_type not in ("dedicated", "shared", "unspecified"):
-        raise ValueError(f"Unsupported request type: {request_type}")
-
     prompt_context, series_list = _separate_context_and_series(prompt)
-
-    if not series_list:
-        raise ValueError("Please provide at least one Series in the prompt")
+    assert len(series_list) > 0
 
     operator = ai_ops.AIGenerateBool(
         prompt_context=tuple(prompt_context),
@@ -120,9 +114,8 @@ def ai_generate_bool(
     return series_list[0]._apply_nary_op(operator, series_list[1:])
 
 
-@functools.singledispatch
 def _separate_context_and_series(
-    prompt: Any,
+    prompt: series.Series | List[str | series.Series] | Tuple[str | series.Series, ...],
 ) -> Tuple[List[str | None], List[series.Series]]:
     """
     Returns the two values. The first value is the prompt with all series replaced by None. The second value is all the series
@@ -131,24 +124,14 @@ def _separate_context_and_series(
     Input: ("str1", series1, "str2", "str3", series2)
     Output: ["str1", None, "str2", "str3", None], [series1, series2]
     """
-    raise ValueError(f"Unsupported prompt type: {type(prompt)}")
-
+    if not isinstance(prompt, (list, tuple, series.Series)):
+        raise ValueError(f"Unsupported prompt type: {type(prompt)}")
 
-@_separate_context_and_series.register
-def _(
-    prompt: series.Series,
-) -> Tuple[List[str | None], List[series.Series]]:
-    if prompt.dtype == dtypes.OBJ_REF_DTYPE:
-        # Multi-model support
-        return [None], [prompt.blob.read_url()]
-    return [None], [prompt]
-
-
-@_separate_context_and_series.register(list)
-@_separate_context_and_series.register(tuple)
-def _(
-    prompt: Sequence[str | series.Series],
-) -> Tuple[List[str | None], List[series.Series]]:
+    if isinstance(prompt, series.Series):
+        if prompt.dtype == dtypes.OBJ_REF_DTYPE:
+            # Multi-model support
+            return [None], [prompt.blob.read_url()]
+        return [None], [prompt]
 
     prompt_context: List[str | None] = []
     series_list: List[series.Series] = []
@@ -166,7 +149,10 @@ def _(
             series_list.append(item)
 
         else:
-            raise ValueError(f"Unsupported type in prompt: {type(item)}")
+            raise TypeError(f"Unsupported type in prompt: {type(item)}")
+
+    if not series_list:
+        raise ValueError("Please provide at least one Series in the prompt")
 
     return prompt_context, series_list
 

From 79b96511be7992597a718bd2ce2c999874700066 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Wed, 10 Sep 2025 18:15:11 +0000
Subject: [PATCH 07/11] expose ai module and rename the function

---
 bigframes/bigquery/__init__.py         | 6 ++----
 bigframes/bigquery/_operations/ai.py   | 4 +++-
 tests/system/large/bigquery/test_ai.py | 2 +-
 tests/system/small/bigquery/test_ai.py | 2 +-
 4 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/bigframes/bigquery/__init__.py b/bigframes/bigquery/__init__.py
index c82306c764..c9b81d191b 100644
--- a/bigframes/bigquery/__init__.py
+++ b/bigframes/bigquery/__init__.py
@@ -18,7 +18,7 @@
 
 import sys
 
-from bigframes.bigquery._operations.ai import ai_generate_bool
+from bigframes.bigquery._operations import ai
 from bigframes.bigquery._operations.approx_agg import approx_top_count
 from bigframes.bigquery._operations.array import (
     array_agg,
@@ -58,8 +58,6 @@
 from bigframes.core import log_adapter
 
 _functions = [
-    # ai ops
-    ai_generate_bool,
     # approximate aggregate ops
     approx_top_count,
     # array ops
@@ -99,7 +97,7 @@
     struct,
 ]
 
-__all__ = [f.__name__ for f in _functions]
+__all__ = [f.__name__ for f in _functions] + ["ai"]
 
 _module = sys.modules[__name__]
 for f in _functions:
diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
index 4b50d7051b..00d12dc7e2 100644
--- a/bigframes/bigquery/_operations/ai.py
+++ b/bigframes/bigquery/_operations/ai.py
@@ -18,10 +18,12 @@
 from typing import Any, List, Literal, Mapping, Tuple
 
 from bigframes import clients, dtypes, series
+from bigframes.core import log_adapter
 from bigframes.operations import ai_ops
 
 
-def ai_generate_bool(
+@log_adapter.method_logger(custom_base_name="bigquery_ai")
+def generate_bool(
     prompt: series.Series | List[str | series.Series] | Tuple[str | series.Series, ...],
     *,
     connection_id: str | None = None,
diff --git a/tests/system/large/bigquery/test_ai.py b/tests/system/large/bigquery/test_ai.py
index 447105148e..be0216a526 100644
--- a/tests/system/large/bigquery/test_ai.py
+++ b/tests/system/large/bigquery/test_ai.py
@@ -23,7 +23,7 @@ def test_ai_generate_bool_multi_model(session):
         "gs://bigframes-dev-testing/a_multimodel/images/*", name="image"
     )
 
-    result = bbq.ai_generate_bool((df["image"], " contains an animal")).struct.field(
+    result = bbq.ai.generate_bool((df["image"], " contains an animal")).struct.field(
         "result"
     )
 
diff --git a/tests/system/small/bigquery/test_ai.py b/tests/system/small/bigquery/test_ai.py
index 42cbaee7ed..06c31fad03 100644
--- a/tests/system/small/bigquery/test_ai.py
+++ b/tests/system/small/bigquery/test_ai.py
@@ -25,7 +25,7 @@ def test_ai_generate_bool(session):
     prompt = (s1, " is a ", s2)
     model_params = {"generation_config": {"thinking_config": {"thinking_budget": 0}}}
 
-    result = bbq.ai_generate_bool(
+    result = bbq.ai.generate_bool(
         prompt, endpoint="gemini-2.5-flash", model_params=model_params
     ).struct.field("result")
 

From 99555441ebed79f0699512b24c1162ddba4bd72a Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Wed, 10 Sep 2025 20:13:05 +0000
Subject: [PATCH 08/11] add ai module to doc

---
 bigframes/bigquery/_operations/ai.py        | 4 ++++
 docs/reference/bigframes.bigquery/ai.rst    | 7 +++++++
 docs/reference/bigframes.bigquery/index.rst | 6 +++++-
 docs/templates/toc.yml                      | 2 ++
 4 files changed, 18 insertions(+), 1 deletion(-)
 create mode 100644 docs/reference/bigframes.bigquery/ai.rst

diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
index 00d12dc7e2..e53960070b 100644
--- a/bigframes/bigquery/_operations/ai.py
+++ b/bigframes/bigquery/_operations/ai.py
@@ -12,6 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+"""This module integrates BigQuery built-in AI functions for use with Series/DataFrame objects,
+such as AI.GENERTAL_BOOL:
+https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate-bool"""
+
 from __future__ import annotations
 
 import json
diff --git a/docs/reference/bigframes.bigquery/ai.rst b/docs/reference/bigframes.bigquery/ai.rst
new file mode 100644
index 0000000000..2134125d6f
--- /dev/null
+++ b/docs/reference/bigframes.bigquery/ai.rst
@@ -0,0 +1,7 @@
+bigframes.bigquery.ai
+=============================
+
+.. automodule:: bigframes.bigquery._operations.ai
+    :members:
+    :inherited-members:
+    :undoc-members:
\ No newline at end of file
diff --git a/docs/reference/bigframes.bigquery/index.rst b/docs/reference/bigframes.bigquery/index.rst
index 03e9bb48a4..f9d34f379d 100644
--- a/docs/reference/bigframes.bigquery/index.rst
+++ b/docs/reference/bigframes.bigquery/index.rst
@@ -5,5 +5,9 @@ BigQuery Built-in Functions
 
 .. automodule:: bigframes.bigquery
     :members:
-    :inherited-members:
     :undoc-members:
+
+.. toctree::
+    :maxdepth: 2
+
+    ai
diff --git a/docs/templates/toc.yml b/docs/templates/toc.yml
index a27f162a9a..ad96977152 100644
--- a/docs/templates/toc.yml
+++ b/docs/templates/toc.yml
@@ -218,6 +218,8 @@
   - items:
     - name: BigQuery built-in functions
       uid: bigframes.bigquery
+    - name: BigQuery AI Functions
+      uid: bigframes.bigquery.ai
     name: bigframes.bigquery
   - items:
     - name: GeoSeries

From ce5cc3877aa625304556f32c40f3076e33ebb2dc Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Wed, 10 Sep 2025 20:48:06 +0000
Subject: [PATCH 09/11] fix test

---
 tests/system/small/bigquery/test_ai.py | 26 ++++++++++++++++++++++++++
 1 file changed, 26 insertions(+)

diff --git a/tests/system/small/bigquery/test_ai.py b/tests/system/small/bigquery/test_ai.py
index 06c31fad03..616ba970db 100644
--- a/tests/system/small/bigquery/test_ai.py
+++ b/tests/system/small/bigquery/test_ai.py
@@ -12,8 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import sys
+
 import pandas as pd
 import pandas.testing
+import pytest
 
 import bigframes.bigquery as bbq
 import bigframes.pandas as bpd
@@ -35,3 +38,26 @@ def test_ai_generate_bool(session):
         check_dtype=False,
         check_index=False,
     )
+
+
+def test_ai_generate_bool_with_model_params(session):
+    if sys.version_info < (3, 12):
+        pytest.skip(
+            "Skip test because SQLGLot cannot compile model params to JSON at this env."
+        )
+
+    s1 = bpd.Series(["apple", "bear"], session=session)
+    s2 = bpd.Series(["fruit", "tree"], session=session)
+    prompt = (s1, " is a ", s2)
+    model_params = {"generation_config": {"thinking_config": {"thinking_budget": 0}}}
+
+    result = bbq.ai.generate_bool(
+        prompt, endpoint="gemini-2.5-flash", model_params=model_params
+    ).struct.field("result")
+
+    pandas.testing.assert_series_equal(
+        result.to_pandas(),
+        pd.Series([True, False], name="result"),
+        check_dtype=False,
+        check_index=False,
+    )

From 61e10ce69734fafe72851ba0ef8282dbb3a18884 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Thu, 11 Sep 2025 03:10:49 +0000
Subject: [PATCH 10/11] fix test

---
 tests/system/small/bigquery/test_ai.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/tests/system/small/bigquery/test_ai.py b/tests/system/small/bigquery/test_ai.py
index 616ba970db..01050ade04 100644
--- a/tests/system/small/bigquery/test_ai.py
+++ b/tests/system/small/bigquery/test_ai.py
@@ -26,11 +26,10 @@ def test_ai_generate_bool(session):
     s1 = bpd.Series(["apple", "bear"], session=session)
     s2 = bpd.Series(["fruit", "tree"], session=session)
     prompt = (s1, " is a ", s2)
-    model_params = {"generation_config": {"thinking_config": {"thinking_budget": 0}}}
 
-    result = bbq.ai.generate_bool(
-        prompt, endpoint="gemini-2.5-flash", model_params=model_params
-    ).struct.field("result")
+    result = bbq.ai.generate_bool(prompt, endpoint="gemini-2.5-flash").struct.field(
+        "result"
+    )
 
     pandas.testing.assert_series_equal(
         result.to_pandas(),

From 48563158a81ba745c1d57337baf89c7dce9bb4f3 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@users.noreply.github.com>
Date: Mon, 15 Sep 2025 11:35:29 -0700
Subject: [PATCH 11/11] Update bigframes/bigquery/_operations/ai.py
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Tim Sweña (Swast) <swast@google.com>
---
 bigframes/bigquery/_operations/ai.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/bigframes/bigquery/_operations/ai.py b/bigframes/bigquery/_operations/ai.py
index e53960070b..d7ea29322d 100644
--- a/bigframes/bigquery/_operations/ai.py
+++ b/bigframes/bigquery/_operations/ai.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 
 """This module integrates BigQuery built-in AI functions for use with Series/DataFrame objects,
-such as AI.GENERTAL_BOOL:
+such as AI.GENERATE_BOOL:
 https://cloud.google.com/bigquery/docs/reference/standard-sql/bigqueryml-syntax-ai-generate-bool"""
 
 from __future__ import annotations