feat: Add BigQuery ML CREATE MODEL support

- Refactor `bigframes.core.sql` to a package.
- Add `bigframes.core.sql.ml` for DDL generation.
- Add `bigframes.bigquery.ml` module with `create_model` function.
- Add unit tests for SQL generation.
- Use `_start_query_ml_ddl` for execution.
- Return the created model object using `read_gbq_model`.
- Remove `query` argument, simplify SQL generation logic.
- Fix linting and mypy errors.

Author: google-labs-jules[bot]

bigframes/bigquery/_operations/ml.py

@@ -15,13 +15,15 @@
 from __future__ import annotations
 
 import typing
-from typing import Mapping, Optional, Union
+from typing import Mapping, Optional, TYPE_CHECKING, Union
 
 import bigframes.core.log_adapter as log_adapter
 import bigframes.core.sql.ml
 import bigframes.dataframe as dataframe
-import bigframes.ml.base
-import bigframes.session
+
+if TYPE_CHECKING:
+    import bigframes.ml.base
+    import bigframes.session
 
 
 # Helper to convert DataFrame to SQL string
@@ -47,7 +49,7 @@ def create_model(
     training_data: Optional[Union[dataframe.DataFrame, str]] = None,
     custom_holiday: Optional[Union[dataframe.DataFrame, str]] = None,
     session: Optional[bigframes.session.Session] = None,
-) -> bigframes.ml.base.BaseModel:
+) -> bigframes.ml.base.BaseEstimator:
     """
     Creates a BigQuery ML model.
     """

tests/unit/core/sql/test_ml.py

@@ -13,8 +13,10 @@
 # limitations under the License.
 
 import pytest
+
 import bigframes.core.sql.ml
 
+
 def test_create_model_basic(snapshot):
     sql = bigframes.core.sql.ml.create_model_ddl(
         model_name="my_project.my_dataset.my_model",