From 91c8df52669f8072a60cc1555cba5c4d8c0d41c0 Mon Sep 17 00:00:00 2001 From: Ben Kazemi Date: Fri, 24 Oct 2025 15:47:55 -0700 Subject: [PATCH] chore: GenAI SDK client(multimodal) - Remove unused experimental code. PiperOrigin-RevId: 823692177 --- vertexai/_genai/multimodal.py | 197 ---------------------------------- 1 file changed, 197 deletions(-) delete mode 100644 vertexai/_genai/multimodal.py diff --git a/vertexai/_genai/multimodal.py b/vertexai/_genai/multimodal.py deleted file mode 100644 index 12c865f0ae..0000000000 --- a/vertexai/_genai/multimodal.py +++ /dev/null @@ -1,197 +0,0 @@ -# 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. -# - -# Code generated by the Google Gen AI SDK generator DO NOT EDIT. - -import json -import logging -from typing import Any, Optional, Union -from urllib.parse import urlencode - -from google.genai import _api_module -from google.genai import _common -from google.genai import types as genai_types -from google.genai._common import get_value_by_path as getv -from google.genai._common import set_value_by_path as setv - -from . import types - - -logger = logging.getLogger("vertexai_genai.multimodal") - - -def _CreateMultimodalDatasetParameters_to_vertex( - from_object: Union[dict[str, Any], object], - parent_object: Optional[dict[str, Any]] = None, -) -> dict[str, Any]: - to_object: dict[str, Any] = {} - if getv(from_object, ["config"]) is not None: - setv(to_object, ["config"], getv(from_object, ["config"])) - - if getv(from_object, ["name"]) is not None: - setv(to_object, ["name"], getv(from_object, ["name"])) - - if getv(from_object, ["display_name"]) is not None: - setv(to_object, ["displayName"], getv(from_object, ["display_name"])) - - if getv(from_object, ["metadata_schema_uri"]) is not None: - setv( - to_object, ["metadataSchemaUri"], getv(from_object, ["metadata_schema_uri"]) - ) - - if getv(from_object, ["metadata"]) is not None: - setv(to_object, ["metadata"], getv(from_object, ["metadata"])) - - if getv(from_object, ["description"]) is not None: - setv(to_object, ["description"], getv(from_object, ["description"])) - - if getv(from_object, ["encryption_spec"]) is not None: - setv(to_object, ["encryptionSpec"], getv(from_object, ["encryption_spec"])) - - return to_object - - -class Multimodal(_api_module.BaseModule): - - def _create_multimodal_dataset( - self, - *, - config: Optional[types.CreateMultimodalDatasetConfigOrDict] = None, - name: Optional[str] = None, - display_name: Optional[str] = None, - metadata_schema_uri: Optional[str] = None, - metadata: Optional[types.SchemaTablesDatasetMetadataOrDict] = None, - description: Optional[str] = None, - encryption_spec: Optional[genai_types.EncryptionSpecOrDict] = None, - ) -> types.MultimodalDatasetOperation: - """ - Creates a dataset resource to store multimodal datasets. - """ - - parameter_model = types._CreateMultimodalDatasetParameters( - config=config, - name=name, - display_name=display_name, - metadata_schema_uri=metadata_schema_uri, - metadata=metadata, - description=description, - encryption_spec=encryption_spec, - ) - - request_url_dict: Optional[dict[str, str]] - if not self._api_client.vertexai: - raise ValueError("This method is only supported in the Vertex AI client.") - else: - request_dict = _CreateMultimodalDatasetParameters_to_vertex(parameter_model) - request_url_dict = request_dict.get("_url") - if request_url_dict: - path = "datasets".format_map(request_url_dict) - else: - path = "datasets" - - query_params = request_dict.get("_query") - if query_params: - path = f"{path}?{urlencode(query_params)}" - # TODO: remove the hack that pops config. - request_dict.pop("config", None) - - http_options: Optional[types.HttpOptions] = None - if ( - parameter_model.config is not None - and parameter_model.config.http_options is not None - ): - http_options = parameter_model.config.http_options - - request_dict = _common.convert_to_dict(request_dict) - request_dict = _common.encode_unserializable_types(request_dict) - - response = self._api_client.request("post", path, request_dict, http_options) - - response_dict = {} if not response.body else json.loads(response.body) - - return_value = types.MultimodalDatasetOperation._from_response( - response=response_dict, kwargs=parameter_model.model_dump() - ) - - self._api_client._verify_response(return_value) - return return_value - - -class AsyncMultimodal(_api_module.BaseModule): - - async def _create_multimodal_dataset( - self, - *, - config: Optional[types.CreateMultimodalDatasetConfigOrDict] = None, - name: Optional[str] = None, - display_name: Optional[str] = None, - metadata_schema_uri: Optional[str] = None, - metadata: Optional[types.SchemaTablesDatasetMetadataOrDict] = None, - description: Optional[str] = None, - encryption_spec: Optional[genai_types.EncryptionSpecOrDict] = None, - ) -> types.MultimodalDatasetOperation: - """ - Creates a dataset resource to store multimodal datasets. - """ - - parameter_model = types._CreateMultimodalDatasetParameters( - config=config, - name=name, - display_name=display_name, - metadata_schema_uri=metadata_schema_uri, - metadata=metadata, - description=description, - encryption_spec=encryption_spec, - ) - - request_url_dict: Optional[dict[str, str]] - if not self._api_client.vertexai: - raise ValueError("This method is only supported in the Vertex AI client.") - else: - request_dict = _CreateMultimodalDatasetParameters_to_vertex(parameter_model) - request_url_dict = request_dict.get("_url") - if request_url_dict: - path = "datasets".format_map(request_url_dict) - else: - path = "datasets" - - query_params = request_dict.get("_query") - if query_params: - path = f"{path}?{urlencode(query_params)}" - # TODO: remove the hack that pops config. - request_dict.pop("config", None) - - http_options: Optional[types.HttpOptions] = None - if ( - parameter_model.config is not None - and parameter_model.config.http_options is not None - ): - http_options = parameter_model.config.http_options - - request_dict = _common.convert_to_dict(request_dict) - request_dict = _common.encode_unserializable_types(request_dict) - - response = await self._api_client.async_request( - "post", path, request_dict, http_options - ) - - response_dict = {} if not response.body else json.loads(response.body) - - return_value = types.MultimodalDatasetOperation._from_response( - response=response_dict, kwargs=parameter_model.model_dump() - ) - - self._api_client._verify_response(return_value) - return return_value