Daniel Bedeleanu
ea49cd6e4a
- Create backend/services/image_storage.py with 4 core functions:
- sanitize_filename(): remove unsafe chars, limit to 255 chars, convert to lowercase
- get_unique_filename(): handle collisions with UUID suffix (format: {name}_{uuid8}_{variant}.jpg)
- ensure_image_directories(): create /images/ root and category subdirs on startup
- save_image(): save bytes to /images/{category}/{filename}, returns relative path
- Create comprehensive test suite (22 tests) covering all functionality
- Integrate ensure_image_directories() into FastAPI startup event
- Directory structure: /images/{category}/{filename}
- Collision handling: auto-suffix with UUID if filename exists
- All tests passing, pathlib.Path for safe operations
1951 lines
58 KiB
Python
1951 lines
58 KiB
Python
# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# Code generated by the Google Gen AI SDK generator DO NOT EDIT.
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import json
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import logging
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from typing import Any, Optional, Union
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from urllib.parse import urlencode
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from . import _api_module
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from . import _common
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from . import _transformers as t
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from . import types
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from ._api_client import BaseApiClient
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from ._common import get_value_by_path as getv
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from ._common import set_value_by_path as setv
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from .pagers import AsyncPager, Pager
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logger = logging.getLogger('google_genai.caches')
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def _AuthConfig_to_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['api_key']) is not None:
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setv(to_object, ['apiKey'], getv(from_object, ['api_key']))
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if getv(from_object, ['api_key_config']) is not None:
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raise ValueError('api_key_config parameter is not supported in Gemini API.')
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if getv(from_object, ['auth_type']) is not None:
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raise ValueError('auth_type parameter is not supported in Gemini API.')
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if getv(from_object, ['google_service_account_config']) is not None:
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raise ValueError(
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'google_service_account_config parameter is not supported in Gemini'
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' API.'
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)
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if getv(from_object, ['http_basic_auth_config']) is not None:
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raise ValueError(
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'http_basic_auth_config parameter is not supported in Gemini API.'
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)
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if getv(from_object, ['oauth_config']) is not None:
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raise ValueError('oauth_config parameter is not supported in Gemini API.')
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if getv(from_object, ['oidc_config']) is not None:
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raise ValueError('oidc_config parameter is not supported in Gemini API.')
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return to_object
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def _Blob_to_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['data']) is not None:
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setv(to_object, ['data'], getv(from_object, ['data']))
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if getv(from_object, ['display_name']) is not None:
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raise ValueError('display_name parameter is not supported in Gemini API.')
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if getv(from_object, ['mime_type']) is not None:
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setv(to_object, ['mimeType'], getv(from_object, ['mime_type']))
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return to_object
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def _Content_to_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['parts']) is not None:
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setv(
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to_object,
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['parts'],
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[
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_Part_to_mldev(item, to_object)
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for item in getv(from_object, ['parts'])
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],
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)
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if getv(from_object, ['role']) is not None:
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setv(to_object, ['role'], getv(from_object, ['role']))
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return to_object
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def _Content_to_vertex(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['parts']) is not None:
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setv(
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to_object,
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['parts'],
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[
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_Part_to_vertex(item, to_object)
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for item in getv(from_object, ['parts'])
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],
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)
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if getv(from_object, ['role']) is not None:
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setv(to_object, ['role'], getv(from_object, ['role']))
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return to_object
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def _CreateCachedContentConfig_to_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['ttl']) is not None:
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setv(parent_object, ['ttl'], getv(from_object, ['ttl']))
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if getv(from_object, ['expire_time']) is not None:
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setv(parent_object, ['expireTime'], getv(from_object, ['expire_time']))
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if getv(from_object, ['display_name']) is not None:
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setv(parent_object, ['displayName'], getv(from_object, ['display_name']))
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if getv(from_object, ['contents']) is not None:
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setv(
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parent_object,
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['contents'],
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[
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_Content_to_mldev(item, to_object)
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for item in t.t_contents(getv(from_object, ['contents']))
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],
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)
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if getv(from_object, ['system_instruction']) is not None:
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setv(
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parent_object,
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['systemInstruction'],
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_Content_to_mldev(
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t.t_content(getv(from_object, ['system_instruction'])), to_object
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),
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)
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if getv(from_object, ['tools']) is not None:
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setv(
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parent_object,
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['tools'],
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[
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_Tool_to_mldev(item, to_object)
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for item in getv(from_object, ['tools'])
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],
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)
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if getv(from_object, ['tool_config']) is not None:
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setv(
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parent_object,
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['toolConfig'],
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_ToolConfig_to_mldev(getv(from_object, ['tool_config']), to_object),
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)
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if getv(from_object, ['kms_key_name']) is not None:
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raise ValueError('kms_key_name parameter is not supported in Gemini API.')
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return to_object
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def _CreateCachedContentConfig_to_vertex(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['ttl']) is not None:
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setv(parent_object, ['ttl'], getv(from_object, ['ttl']))
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if getv(from_object, ['expire_time']) is not None:
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setv(parent_object, ['expireTime'], getv(from_object, ['expire_time']))
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if getv(from_object, ['display_name']) is not None:
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setv(parent_object, ['displayName'], getv(from_object, ['display_name']))
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if getv(from_object, ['contents']) is not None:
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setv(
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parent_object,
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['contents'],
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[
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_Content_to_vertex(item, to_object)
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for item in t.t_contents(getv(from_object, ['contents']))
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],
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)
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if getv(from_object, ['system_instruction']) is not None:
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setv(
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parent_object,
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['systemInstruction'],
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_Content_to_vertex(
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t.t_content(getv(from_object, ['system_instruction'])), to_object
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),
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)
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if getv(from_object, ['tools']) is not None:
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setv(
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parent_object,
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['tools'],
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[
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_Tool_to_vertex(item, to_object)
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for item in getv(from_object, ['tools'])
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],
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)
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if getv(from_object, ['tool_config']) is not None:
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setv(
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parent_object,
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['toolConfig'],
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_ToolConfig_to_vertex(getv(from_object, ['tool_config']), to_object),
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)
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if getv(from_object, ['kms_key_name']) is not None:
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setv(
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parent_object,
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['encryption_spec', 'kmsKeyName'],
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getv(from_object, ['kms_key_name']),
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)
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return to_object
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def _CreateCachedContentParameters_to_mldev(
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api_client: BaseApiClient,
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['model']) is not None:
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setv(
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to_object,
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['model'],
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t.t_caches_model(api_client, getv(from_object, ['model'])),
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)
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if getv(from_object, ['config']) is not None:
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_CreateCachedContentConfig_to_mldev(
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getv(from_object, ['config']), to_object
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)
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return to_object
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def _CreateCachedContentParameters_to_vertex(
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api_client: BaseApiClient,
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['model']) is not None:
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setv(
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to_object,
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['model'],
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t.t_caches_model(api_client, getv(from_object, ['model'])),
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)
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if getv(from_object, ['config']) is not None:
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_CreateCachedContentConfig_to_vertex(
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getv(from_object, ['config']), to_object
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)
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return to_object
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def _DeleteCachedContentParameters_to_mldev(
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api_client: BaseApiClient,
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['name']) is not None:
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setv(
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to_object,
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['_url', 'name'],
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t.t_cached_content_name(api_client, getv(from_object, ['name'])),
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)
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return to_object
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def _DeleteCachedContentParameters_to_vertex(
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api_client: BaseApiClient,
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['name']) is not None:
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setv(
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to_object,
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['_url', 'name'],
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t.t_cached_content_name(api_client, getv(from_object, ['name'])),
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)
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return to_object
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def _DeleteCachedContentResponse_from_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['sdkHttpResponse']) is not None:
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setv(
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to_object, ['sdk_http_response'], getv(from_object, ['sdkHttpResponse'])
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)
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return to_object
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def _DeleteCachedContentResponse_from_vertex(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['sdkHttpResponse']) is not None:
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setv(
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to_object, ['sdk_http_response'], getv(from_object, ['sdkHttpResponse'])
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)
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return to_object
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def _FileData_to_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['display_name']) is not None:
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raise ValueError('display_name parameter is not supported in Gemini API.')
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if getv(from_object, ['file_uri']) is not None:
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setv(to_object, ['fileUri'], getv(from_object, ['file_uri']))
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if getv(from_object, ['mime_type']) is not None:
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setv(to_object, ['mimeType'], getv(from_object, ['mime_type']))
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return to_object
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def _FunctionCall_to_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['id']) is not None:
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setv(to_object, ['id'], getv(from_object, ['id']))
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if getv(from_object, ['args']) is not None:
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setv(to_object, ['args'], getv(from_object, ['args']))
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if getv(from_object, ['name']) is not None:
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setv(to_object, ['name'], getv(from_object, ['name']))
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if getv(from_object, ['partial_args']) is not None:
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raise ValueError('partial_args parameter is not supported in Gemini API.')
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if getv(from_object, ['will_continue']) is not None:
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raise ValueError('will_continue parameter is not supported in Gemini API.')
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return to_object
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def _FunctionCallingConfig_to_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['allowed_function_names']) is not None:
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setv(
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to_object,
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['allowedFunctionNames'],
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getv(from_object, ['allowed_function_names']),
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)
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if getv(from_object, ['mode']) is not None:
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setv(to_object, ['mode'], getv(from_object, ['mode']))
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if getv(from_object, ['stream_function_call_arguments']) is not None:
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raise ValueError(
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'stream_function_call_arguments parameter is not supported in Gemini'
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' API.'
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)
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return to_object
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def _FunctionDeclaration_to_vertex(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['description']) is not None:
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setv(to_object, ['description'], getv(from_object, ['description']))
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if getv(from_object, ['name']) is not None:
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setv(to_object, ['name'], getv(from_object, ['name']))
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if getv(from_object, ['parameters']) is not None:
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setv(to_object, ['parameters'], getv(from_object, ['parameters']))
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if getv(from_object, ['parameters_json_schema']) is not None:
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setv(
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to_object,
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['parametersJsonSchema'],
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getv(from_object, ['parameters_json_schema']),
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)
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if getv(from_object, ['response']) is not None:
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setv(to_object, ['response'], getv(from_object, ['response']))
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if getv(from_object, ['response_json_schema']) is not None:
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setv(
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to_object,
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['responseJsonSchema'],
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getv(from_object, ['response_json_schema']),
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)
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if getv(from_object, ['behavior']) is not None:
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raise ValueError('behavior parameter is not supported in Vertex AI.')
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return to_object
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def _GetCachedContentParameters_to_mldev(
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api_client: BaseApiClient,
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['name']) is not None:
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setv(
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to_object,
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['_url', 'name'],
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t.t_cached_content_name(api_client, getv(from_object, ['name'])),
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)
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return to_object
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def _GetCachedContentParameters_to_vertex(
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api_client: BaseApiClient,
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['name']) is not None:
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setv(
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to_object,
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['_url', 'name'],
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t.t_cached_content_name(api_client, getv(from_object, ['name'])),
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)
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return to_object
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def _GoogleMaps_to_mldev(
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from_object: Union[dict[str, Any], object],
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parent_object: Optional[dict[str, Any]] = None,
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) -> dict[str, Any]:
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to_object: dict[str, Any] = {}
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if getv(from_object, ['auth_config']) is not None:
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setv(
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to_object,
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['authConfig'],
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_AuthConfig_to_mldev(getv(from_object, ['auth_config']), to_object),
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)
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if getv(from_object, ['enable_widget']) is not None:
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setv(to_object, ['enableWidget'], getv(from_object, ['enable_widget']))
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return to_object
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def _GoogleSearch_to_mldev(
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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, ['search_types']) is not None:
|
|
setv(to_object, ['searchTypes'], getv(from_object, ['search_types']))
|
|
|
|
if getv(from_object, ['blocking_confidence']) is not None:
|
|
raise ValueError(
|
|
'blocking_confidence parameter is not supported in Gemini API.'
|
|
)
|
|
|
|
if getv(from_object, ['exclude_domains']) is not None:
|
|
raise ValueError(
|
|
'exclude_domains parameter is not supported in Gemini API.'
|
|
)
|
|
|
|
if getv(from_object, ['time_range_filter']) is not None:
|
|
setv(
|
|
to_object, ['timeRangeFilter'], getv(from_object, ['time_range_filter'])
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _ListCachedContentsConfig_to_mldev(
|
|
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, ['page_size']) is not None:
|
|
setv(
|
|
parent_object, ['_query', 'pageSize'], getv(from_object, ['page_size'])
|
|
)
|
|
|
|
if getv(from_object, ['page_token']) is not None:
|
|
setv(
|
|
parent_object,
|
|
['_query', 'pageToken'],
|
|
getv(from_object, ['page_token']),
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _ListCachedContentsConfig_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, ['page_size']) is not None:
|
|
setv(
|
|
parent_object, ['_query', 'pageSize'], getv(from_object, ['page_size'])
|
|
)
|
|
|
|
if getv(from_object, ['page_token']) is not None:
|
|
setv(
|
|
parent_object,
|
|
['_query', 'pageToken'],
|
|
getv(from_object, ['page_token']),
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _ListCachedContentsParameters_to_mldev(
|
|
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:
|
|
_ListCachedContentsConfig_to_mldev(getv(from_object, ['config']), to_object)
|
|
|
|
return to_object
|
|
|
|
|
|
def _ListCachedContentsParameters_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:
|
|
_ListCachedContentsConfig_to_vertex(
|
|
getv(from_object, ['config']), to_object
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _ListCachedContentsResponse_from_mldev(
|
|
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, ['sdkHttpResponse']) is not None:
|
|
setv(
|
|
to_object, ['sdk_http_response'], getv(from_object, ['sdkHttpResponse'])
|
|
)
|
|
|
|
if getv(from_object, ['nextPageToken']) is not None:
|
|
setv(to_object, ['next_page_token'], getv(from_object, ['nextPageToken']))
|
|
|
|
if getv(from_object, ['cachedContents']) is not None:
|
|
setv(
|
|
to_object,
|
|
['cached_contents'],
|
|
[item for item in getv(from_object, ['cachedContents'])],
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _ListCachedContentsResponse_from_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, ['sdkHttpResponse']) is not None:
|
|
setv(
|
|
to_object, ['sdk_http_response'], getv(from_object, ['sdkHttpResponse'])
|
|
)
|
|
|
|
if getv(from_object, ['nextPageToken']) is not None:
|
|
setv(to_object, ['next_page_token'], getv(from_object, ['nextPageToken']))
|
|
|
|
if getv(from_object, ['cachedContents']) is not None:
|
|
setv(
|
|
to_object,
|
|
['cached_contents'],
|
|
[item for item in getv(from_object, ['cachedContents'])],
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _Part_to_mldev(
|
|
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, ['media_resolution']) is not None:
|
|
setv(
|
|
to_object, ['mediaResolution'], getv(from_object, ['media_resolution'])
|
|
)
|
|
|
|
if getv(from_object, ['code_execution_result']) is not None:
|
|
setv(
|
|
to_object,
|
|
['codeExecutionResult'],
|
|
getv(from_object, ['code_execution_result']),
|
|
)
|
|
|
|
if getv(from_object, ['executable_code']) is not None:
|
|
setv(to_object, ['executableCode'], getv(from_object, ['executable_code']))
|
|
|
|
if getv(from_object, ['file_data']) is not None:
|
|
setv(
|
|
to_object,
|
|
['fileData'],
|
|
_FileData_to_mldev(getv(from_object, ['file_data']), to_object),
|
|
)
|
|
|
|
if getv(from_object, ['function_call']) is not None:
|
|
setv(
|
|
to_object,
|
|
['functionCall'],
|
|
_FunctionCall_to_mldev(getv(from_object, ['function_call']), to_object),
|
|
)
|
|
|
|
if getv(from_object, ['function_response']) is not None:
|
|
setv(
|
|
to_object,
|
|
['functionResponse'],
|
|
getv(from_object, ['function_response']),
|
|
)
|
|
|
|
if getv(from_object, ['inline_data']) is not None:
|
|
setv(
|
|
to_object,
|
|
['inlineData'],
|
|
_Blob_to_mldev(getv(from_object, ['inline_data']), to_object),
|
|
)
|
|
|
|
if getv(from_object, ['text']) is not None:
|
|
setv(to_object, ['text'], getv(from_object, ['text']))
|
|
|
|
if getv(from_object, ['thought']) is not None:
|
|
setv(to_object, ['thought'], getv(from_object, ['thought']))
|
|
|
|
if getv(from_object, ['thought_signature']) is not None:
|
|
setv(
|
|
to_object,
|
|
['thoughtSignature'],
|
|
getv(from_object, ['thought_signature']),
|
|
)
|
|
|
|
if getv(from_object, ['video_metadata']) is not None:
|
|
setv(to_object, ['videoMetadata'], getv(from_object, ['video_metadata']))
|
|
|
|
if getv(from_object, ['tool_call']) is not None:
|
|
setv(to_object, ['toolCall'], getv(from_object, ['tool_call']))
|
|
|
|
if getv(from_object, ['tool_response']) is not None:
|
|
setv(to_object, ['toolResponse'], getv(from_object, ['tool_response']))
|
|
|
|
if getv(from_object, ['part_metadata']) is not None:
|
|
setv(to_object, ['partMetadata'], getv(from_object, ['part_metadata']))
|
|
|
|
return to_object
|
|
|
|
|
|
def _Part_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, ['media_resolution']) is not None:
|
|
setv(
|
|
to_object, ['mediaResolution'], getv(from_object, ['media_resolution'])
|
|
)
|
|
|
|
if getv(from_object, ['code_execution_result']) is not None:
|
|
setv(
|
|
to_object,
|
|
['codeExecutionResult'],
|
|
getv(from_object, ['code_execution_result']),
|
|
)
|
|
|
|
if getv(from_object, ['executable_code']) is not None:
|
|
setv(to_object, ['executableCode'], getv(from_object, ['executable_code']))
|
|
|
|
if getv(from_object, ['file_data']) is not None:
|
|
setv(to_object, ['fileData'], getv(from_object, ['file_data']))
|
|
|
|
if getv(from_object, ['function_call']) is not None:
|
|
setv(to_object, ['functionCall'], getv(from_object, ['function_call']))
|
|
|
|
if getv(from_object, ['function_response']) is not None:
|
|
setv(
|
|
to_object,
|
|
['functionResponse'],
|
|
getv(from_object, ['function_response']),
|
|
)
|
|
|
|
if getv(from_object, ['inline_data']) is not None:
|
|
setv(to_object, ['inlineData'], getv(from_object, ['inline_data']))
|
|
|
|
if getv(from_object, ['text']) is not None:
|
|
setv(to_object, ['text'], getv(from_object, ['text']))
|
|
|
|
if getv(from_object, ['thought']) is not None:
|
|
setv(to_object, ['thought'], getv(from_object, ['thought']))
|
|
|
|
if getv(from_object, ['thought_signature']) is not None:
|
|
setv(
|
|
to_object,
|
|
['thoughtSignature'],
|
|
getv(from_object, ['thought_signature']),
|
|
)
|
|
|
|
if getv(from_object, ['video_metadata']) is not None:
|
|
setv(to_object, ['videoMetadata'], getv(from_object, ['video_metadata']))
|
|
|
|
if getv(from_object, ['tool_call']) is not None:
|
|
raise ValueError('tool_call parameter is not supported in Vertex AI.')
|
|
|
|
if getv(from_object, ['tool_response']) is not None:
|
|
raise ValueError('tool_response parameter is not supported in Vertex AI.')
|
|
|
|
if getv(from_object, ['part_metadata']) is not None:
|
|
raise ValueError('part_metadata parameter is not supported in Vertex AI.')
|
|
|
|
return to_object
|
|
|
|
|
|
def _ToolConfig_to_mldev(
|
|
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, ['retrieval_config']) is not None:
|
|
setv(
|
|
to_object, ['retrievalConfig'], getv(from_object, ['retrieval_config'])
|
|
)
|
|
|
|
if getv(from_object, ['function_calling_config']) is not None:
|
|
setv(
|
|
to_object,
|
|
['functionCallingConfig'],
|
|
_FunctionCallingConfig_to_mldev(
|
|
getv(from_object, ['function_calling_config']), to_object
|
|
),
|
|
)
|
|
|
|
if getv(from_object, ['include_server_side_tool_invocations']) is not None:
|
|
setv(
|
|
to_object,
|
|
['includeServerSideToolInvocations'],
|
|
getv(from_object, ['include_server_side_tool_invocations']),
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _ToolConfig_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, ['retrieval_config']) is not None:
|
|
setv(
|
|
to_object, ['retrievalConfig'], getv(from_object, ['retrieval_config'])
|
|
)
|
|
|
|
if getv(from_object, ['function_calling_config']) is not None:
|
|
setv(
|
|
to_object,
|
|
['functionCallingConfig'],
|
|
getv(from_object, ['function_calling_config']),
|
|
)
|
|
|
|
if getv(from_object, ['include_server_side_tool_invocations']) is not None:
|
|
raise ValueError(
|
|
'include_server_side_tool_invocations parameter is not supported in'
|
|
' Vertex AI.'
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _Tool_to_mldev(
|
|
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, ['retrieval']) is not None:
|
|
raise ValueError('retrieval parameter is not supported in Gemini API.')
|
|
|
|
if getv(from_object, ['computer_use']) is not None:
|
|
setv(to_object, ['computerUse'], getv(from_object, ['computer_use']))
|
|
|
|
if getv(from_object, ['file_search']) is not None:
|
|
setv(to_object, ['fileSearch'], getv(from_object, ['file_search']))
|
|
|
|
if getv(from_object, ['google_search']) is not None:
|
|
setv(
|
|
to_object,
|
|
['googleSearch'],
|
|
_GoogleSearch_to_mldev(getv(from_object, ['google_search']), to_object),
|
|
)
|
|
|
|
if getv(from_object, ['google_maps']) is not None:
|
|
setv(
|
|
to_object,
|
|
['googleMaps'],
|
|
_GoogleMaps_to_mldev(getv(from_object, ['google_maps']), to_object),
|
|
)
|
|
|
|
if getv(from_object, ['code_execution']) is not None:
|
|
setv(to_object, ['codeExecution'], getv(from_object, ['code_execution']))
|
|
|
|
if getv(from_object, ['enterprise_web_search']) is not None:
|
|
raise ValueError(
|
|
'enterprise_web_search parameter is not supported in Gemini API.'
|
|
)
|
|
|
|
if getv(from_object, ['function_declarations']) is not None:
|
|
setv(
|
|
to_object,
|
|
['functionDeclarations'],
|
|
[item for item in getv(from_object, ['function_declarations'])],
|
|
)
|
|
|
|
if getv(from_object, ['google_search_retrieval']) is not None:
|
|
setv(
|
|
to_object,
|
|
['googleSearchRetrieval'],
|
|
getv(from_object, ['google_search_retrieval']),
|
|
)
|
|
|
|
if getv(from_object, ['parallel_ai_search']) is not None:
|
|
raise ValueError(
|
|
'parallel_ai_search parameter is not supported in Gemini API.'
|
|
)
|
|
|
|
if getv(from_object, ['url_context']) is not None:
|
|
setv(to_object, ['urlContext'], getv(from_object, ['url_context']))
|
|
|
|
if getv(from_object, ['mcp_servers']) is not None:
|
|
setv(
|
|
to_object,
|
|
['mcpServers'],
|
|
[item for item in getv(from_object, ['mcp_servers'])],
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _Tool_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, ['retrieval']) is not None:
|
|
setv(to_object, ['retrieval'], getv(from_object, ['retrieval']))
|
|
|
|
if getv(from_object, ['computer_use']) is not None:
|
|
setv(to_object, ['computerUse'], getv(from_object, ['computer_use']))
|
|
|
|
if getv(from_object, ['file_search']) is not None:
|
|
raise ValueError('file_search parameter is not supported in Vertex AI.')
|
|
|
|
if getv(from_object, ['google_search']) is not None:
|
|
setv(to_object, ['googleSearch'], getv(from_object, ['google_search']))
|
|
|
|
if getv(from_object, ['google_maps']) is not None:
|
|
setv(to_object, ['googleMaps'], getv(from_object, ['google_maps']))
|
|
|
|
if getv(from_object, ['code_execution']) is not None:
|
|
setv(to_object, ['codeExecution'], getv(from_object, ['code_execution']))
|
|
|
|
if getv(from_object, ['enterprise_web_search']) is not None:
|
|
setv(
|
|
to_object,
|
|
['enterpriseWebSearch'],
|
|
getv(from_object, ['enterprise_web_search']),
|
|
)
|
|
|
|
if getv(from_object, ['function_declarations']) is not None:
|
|
setv(
|
|
to_object,
|
|
['functionDeclarations'],
|
|
[
|
|
_FunctionDeclaration_to_vertex(item, to_object)
|
|
for item in getv(from_object, ['function_declarations'])
|
|
],
|
|
)
|
|
|
|
if getv(from_object, ['google_search_retrieval']) is not None:
|
|
setv(
|
|
to_object,
|
|
['googleSearchRetrieval'],
|
|
getv(from_object, ['google_search_retrieval']),
|
|
)
|
|
|
|
if getv(from_object, ['parallel_ai_search']) is not None:
|
|
setv(
|
|
to_object,
|
|
['parallelAiSearch'],
|
|
getv(from_object, ['parallel_ai_search']),
|
|
)
|
|
|
|
if getv(from_object, ['url_context']) is not None:
|
|
setv(to_object, ['urlContext'], getv(from_object, ['url_context']))
|
|
|
|
if getv(from_object, ['mcp_servers']) is not None:
|
|
raise ValueError('mcp_servers parameter is not supported in Vertex AI.')
|
|
|
|
return to_object
|
|
|
|
|
|
def _UpdateCachedContentConfig_to_mldev(
|
|
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, ['ttl']) is not None:
|
|
setv(parent_object, ['ttl'], getv(from_object, ['ttl']))
|
|
|
|
if getv(from_object, ['expire_time']) is not None:
|
|
setv(parent_object, ['expireTime'], getv(from_object, ['expire_time']))
|
|
|
|
return to_object
|
|
|
|
|
|
def _UpdateCachedContentConfig_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, ['ttl']) is not None:
|
|
setv(parent_object, ['ttl'], getv(from_object, ['ttl']))
|
|
|
|
if getv(from_object, ['expire_time']) is not None:
|
|
setv(parent_object, ['expireTime'], getv(from_object, ['expire_time']))
|
|
|
|
return to_object
|
|
|
|
|
|
def _UpdateCachedContentParameters_to_mldev(
|
|
api_client: BaseApiClient,
|
|
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, ['name']) is not None:
|
|
setv(
|
|
to_object,
|
|
['_url', 'name'],
|
|
t.t_cached_content_name(api_client, getv(from_object, ['name'])),
|
|
)
|
|
|
|
if getv(from_object, ['config']) is not None:
|
|
_UpdateCachedContentConfig_to_mldev(
|
|
getv(from_object, ['config']), to_object
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
def _UpdateCachedContentParameters_to_vertex(
|
|
api_client: BaseApiClient,
|
|
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, ['name']) is not None:
|
|
setv(
|
|
to_object,
|
|
['_url', 'name'],
|
|
t.t_cached_content_name(api_client, getv(from_object, ['name'])),
|
|
)
|
|
|
|
if getv(from_object, ['config']) is not None:
|
|
_UpdateCachedContentConfig_to_vertex(
|
|
getv(from_object, ['config']), to_object
|
|
)
|
|
|
|
return to_object
|
|
|
|
|
|
class Caches(_api_module.BaseModule):
|
|
|
|
def create(
|
|
self,
|
|
*,
|
|
model: str,
|
|
config: Optional[types.CreateCachedContentConfigOrDict] = None,
|
|
) -> types.CachedContent:
|
|
"""Creates a cached contents resource.
|
|
|
|
Usage:
|
|
|
|
.. code-block:: python
|
|
|
|
contents = ... // Initialize the content to cache.
|
|
response = client.caches.create(
|
|
model= ... // The publisher model id
|
|
contents=contents,
|
|
config={
|
|
'display_name': 'test cache',
|
|
'system_instruction': 'What is the sum of the two pdfs?',
|
|
'ttl': '86400s',
|
|
},
|
|
)
|
|
"""
|
|
|
|
parameter_model = types._CreateCachedContentParameters(
|
|
model=model,
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _CreateCachedContentParameters_to_vertex(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = 'cachedContents'.format_map(request_url_dict)
|
|
else:
|
|
path = 'cachedContents'
|
|
else:
|
|
request_dict = _CreateCachedContentParameters_to_mldev(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = 'cachedContents'.format_map(request_url_dict)
|
|
else:
|
|
path = 'cachedContents'
|
|
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.CachedContent._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
def get(
|
|
self,
|
|
*,
|
|
name: str,
|
|
config: Optional[types.GetCachedContentConfigOrDict] = None,
|
|
) -> types.CachedContent:
|
|
"""Gets cached content configurations.
|
|
|
|
.. code-block:: python
|
|
|
|
client.caches.get(name= ... ) // The server-generated resource name.
|
|
"""
|
|
|
|
parameter_model = types._GetCachedContentParameters(
|
|
name=name,
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _GetCachedContentParameters_to_vertex(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
else:
|
|
request_dict = _GetCachedContentParameters_to_mldev(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
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('get', path, request_dict, http_options)
|
|
|
|
response_dict = {} if not response.body else json.loads(response.body)
|
|
|
|
return_value = types.CachedContent._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
def delete(
|
|
self,
|
|
*,
|
|
name: str,
|
|
config: Optional[types.DeleteCachedContentConfigOrDict] = None,
|
|
) -> types.DeleteCachedContentResponse:
|
|
"""Deletes cached content.
|
|
|
|
Usage:
|
|
|
|
.. code-block:: python
|
|
|
|
client.caches.delete(name= ... ) // The server-generated resource name.
|
|
"""
|
|
|
|
parameter_model = types._DeleteCachedContentParameters(
|
|
name=name,
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _DeleteCachedContentParameters_to_vertex(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
else:
|
|
request_dict = _DeleteCachedContentParameters_to_mldev(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
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(
|
|
'delete', path, request_dict, http_options
|
|
)
|
|
|
|
response_dict = {} if not response.body else json.loads(response.body)
|
|
|
|
if self._api_client.vertexai:
|
|
response_dict = _DeleteCachedContentResponse_from_vertex(response_dict)
|
|
|
|
if not self._api_client.vertexai:
|
|
response_dict = _DeleteCachedContentResponse_from_mldev(response_dict)
|
|
|
|
return_value = types.DeleteCachedContentResponse._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
return_value.sdk_http_response = types.HttpResponse(
|
|
headers=response.headers
|
|
)
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
def update(
|
|
self,
|
|
*,
|
|
name: str,
|
|
config: Optional[types.UpdateCachedContentConfigOrDict] = None,
|
|
) -> types.CachedContent:
|
|
"""Updates cached content configurations.
|
|
|
|
.. code-block:: python
|
|
|
|
response = client.caches.update(
|
|
name= ... // The server-generated resource name.
|
|
config={
|
|
'ttl': '7600s',
|
|
},
|
|
)
|
|
"""
|
|
|
|
parameter_model = types._UpdateCachedContentParameters(
|
|
name=name,
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _UpdateCachedContentParameters_to_vertex(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
else:
|
|
request_dict = _UpdateCachedContentParameters_to_mldev(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
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(
|
|
'patch', path, request_dict, http_options
|
|
)
|
|
|
|
response_dict = {} if not response.body else json.loads(response.body)
|
|
|
|
return_value = types.CachedContent._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
def _list(
|
|
self, *, config: Optional[types.ListCachedContentsConfigOrDict] = None
|
|
) -> types.ListCachedContentsResponse:
|
|
parameter_model = types._ListCachedContentsParameters(
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _ListCachedContentsParameters_to_vertex(parameter_model)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = 'cachedContents'.format_map(request_url_dict)
|
|
else:
|
|
path = 'cachedContents'
|
|
else:
|
|
request_dict = _ListCachedContentsParameters_to_mldev(parameter_model)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = 'cachedContents'.format_map(request_url_dict)
|
|
else:
|
|
path = 'cachedContents'
|
|
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('get', path, request_dict, http_options)
|
|
|
|
response_dict = {} if not response.body else json.loads(response.body)
|
|
|
|
if self._api_client.vertexai:
|
|
response_dict = _ListCachedContentsResponse_from_vertex(response_dict)
|
|
|
|
if not self._api_client.vertexai:
|
|
response_dict = _ListCachedContentsResponse_from_mldev(response_dict)
|
|
|
|
return_value = types.ListCachedContentsResponse._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
return_value.sdk_http_response = types.HttpResponse(
|
|
headers=response.headers
|
|
)
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
def list(
|
|
self, *, config: Optional[types.ListCachedContentsConfigOrDict] = None
|
|
) -> Pager[types.CachedContent]:
|
|
"""Lists cached contents.
|
|
|
|
Args:
|
|
config (ListCachedContentsConfig): Optional configuration for the list
|
|
request.
|
|
|
|
Returns:
|
|
A Pager object that contains one page of cached contents. When iterating
|
|
over
|
|
the pager, it automatically fetches the next page if there are more.
|
|
|
|
Usage:
|
|
|
|
.. code-block:: python
|
|
for cached_content in client.caches.list():
|
|
print(cached_content.name)
|
|
"""
|
|
|
|
list_request = self._list
|
|
return Pager(
|
|
'cached_contents',
|
|
list_request,
|
|
self._list(config=config),
|
|
config,
|
|
)
|
|
|
|
|
|
class AsyncCaches(_api_module.BaseModule):
|
|
|
|
async def create(
|
|
self,
|
|
*,
|
|
model: str,
|
|
config: Optional[types.CreateCachedContentConfigOrDict] = None,
|
|
) -> types.CachedContent:
|
|
"""Creates a cached contents resource.
|
|
|
|
Usage:
|
|
|
|
.. code-block:: python
|
|
|
|
contents = ... // Initialize the content to cache.
|
|
response = await client.aio.caches.create(
|
|
model= ... // The publisher model id
|
|
contents=contents,
|
|
config={
|
|
'display_name': 'test cache',
|
|
'system_instruction': 'What is the sum of the two pdfs?',
|
|
'ttl': '86400s',
|
|
},
|
|
)
|
|
"""
|
|
|
|
parameter_model = types._CreateCachedContentParameters(
|
|
model=model,
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _CreateCachedContentParameters_to_vertex(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = 'cachedContents'.format_map(request_url_dict)
|
|
else:
|
|
path = 'cachedContents'
|
|
else:
|
|
request_dict = _CreateCachedContentParameters_to_mldev(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = 'cachedContents'.format_map(request_url_dict)
|
|
else:
|
|
path = 'cachedContents'
|
|
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.CachedContent._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
async def get(
|
|
self,
|
|
*,
|
|
name: str,
|
|
config: Optional[types.GetCachedContentConfigOrDict] = None,
|
|
) -> types.CachedContent:
|
|
"""Gets cached content configurations.
|
|
|
|
.. code-block:: python
|
|
|
|
await client.aio.caches.get(name= ... ) // The server-generated resource
|
|
name.
|
|
"""
|
|
|
|
parameter_model = types._GetCachedContentParameters(
|
|
name=name,
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _GetCachedContentParameters_to_vertex(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
else:
|
|
request_dict = _GetCachedContentParameters_to_mldev(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
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(
|
|
'get', path, request_dict, http_options
|
|
)
|
|
|
|
response_dict = {} if not response.body else json.loads(response.body)
|
|
|
|
return_value = types.CachedContent._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
async def delete(
|
|
self,
|
|
*,
|
|
name: str,
|
|
config: Optional[types.DeleteCachedContentConfigOrDict] = None,
|
|
) -> types.DeleteCachedContentResponse:
|
|
"""Deletes cached content.
|
|
|
|
Usage:
|
|
|
|
.. code-block:: python
|
|
|
|
await client.aio.caches.delete(name= ... ) // The server-generated
|
|
resource name.
|
|
"""
|
|
|
|
parameter_model = types._DeleteCachedContentParameters(
|
|
name=name,
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _DeleteCachedContentParameters_to_vertex(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
else:
|
|
request_dict = _DeleteCachedContentParameters_to_mldev(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
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(
|
|
'delete', path, request_dict, http_options
|
|
)
|
|
|
|
response_dict = {} if not response.body else json.loads(response.body)
|
|
|
|
if self._api_client.vertexai:
|
|
response_dict = _DeleteCachedContentResponse_from_vertex(response_dict)
|
|
|
|
if not self._api_client.vertexai:
|
|
response_dict = _DeleteCachedContentResponse_from_mldev(response_dict)
|
|
|
|
return_value = types.DeleteCachedContentResponse._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
return_value.sdk_http_response = types.HttpResponse(
|
|
headers=response.headers
|
|
)
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
async def update(
|
|
self,
|
|
*,
|
|
name: str,
|
|
config: Optional[types.UpdateCachedContentConfigOrDict] = None,
|
|
) -> types.CachedContent:
|
|
"""Updates cached content configurations.
|
|
|
|
.. code-block:: python
|
|
|
|
response = await client.aio.caches.update(
|
|
name= ... // The server-generated resource name.
|
|
config={
|
|
'ttl': '7600s',
|
|
},
|
|
)
|
|
"""
|
|
|
|
parameter_model = types._UpdateCachedContentParameters(
|
|
name=name,
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _UpdateCachedContentParameters_to_vertex(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
else:
|
|
request_dict = _UpdateCachedContentParameters_to_mldev(
|
|
self._api_client, parameter_model
|
|
)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = '{name}'.format_map(request_url_dict)
|
|
else:
|
|
path = '{name}'
|
|
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(
|
|
'patch', path, request_dict, http_options
|
|
)
|
|
|
|
response_dict = {} if not response.body else json.loads(response.body)
|
|
|
|
return_value = types.CachedContent._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
async def _list(
|
|
self, *, config: Optional[types.ListCachedContentsConfigOrDict] = None
|
|
) -> types.ListCachedContentsResponse:
|
|
parameter_model = types._ListCachedContentsParameters(
|
|
config=config,
|
|
)
|
|
|
|
request_url_dict: Optional[dict[str, str]]
|
|
|
|
if self._api_client.vertexai:
|
|
request_dict = _ListCachedContentsParameters_to_vertex(parameter_model)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = 'cachedContents'.format_map(request_url_dict)
|
|
else:
|
|
path = 'cachedContents'
|
|
else:
|
|
request_dict = _ListCachedContentsParameters_to_mldev(parameter_model)
|
|
request_url_dict = request_dict.get('_url')
|
|
if request_url_dict:
|
|
path = 'cachedContents'.format_map(request_url_dict)
|
|
else:
|
|
path = 'cachedContents'
|
|
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(
|
|
'get', path, request_dict, http_options
|
|
)
|
|
|
|
response_dict = {} if not response.body else json.loads(response.body)
|
|
|
|
if self._api_client.vertexai:
|
|
response_dict = _ListCachedContentsResponse_from_vertex(response_dict)
|
|
|
|
if not self._api_client.vertexai:
|
|
response_dict = _ListCachedContentsResponse_from_mldev(response_dict)
|
|
|
|
return_value = types.ListCachedContentsResponse._from_response(
|
|
response=response_dict,
|
|
kwargs={
|
|
'config': {
|
|
'response_schema': getattr(
|
|
parameter_model.config, 'response_schema', None
|
|
),
|
|
'response_json_schema': getattr(
|
|
parameter_model.config, 'response_json_schema', None
|
|
),
|
|
'include_all_fields': getattr(
|
|
parameter_model.config, 'include_all_fields', None
|
|
),
|
|
}
|
|
}
|
|
if getattr(parameter_model, 'config', None)
|
|
else {},
|
|
)
|
|
return_value.sdk_http_response = types.HttpResponse(
|
|
headers=response.headers
|
|
)
|
|
self._api_client._verify_response(return_value)
|
|
return return_value
|
|
|
|
async def list(
|
|
self, *, config: Optional[types.ListCachedContentsConfigOrDict] = None
|
|
) -> AsyncPager[types.CachedContent]:
|
|
"""Lists cached contents asynchronously.
|
|
|
|
Args:
|
|
config (ListCachedContentsConfig): Optional configuration for the list
|
|
request.
|
|
|
|
Returns:
|
|
A Pager object that contains one page of cached contents. When iterating
|
|
over
|
|
the pager, it automatically fetches the next page if there are more.
|
|
|
|
Usage:
|
|
|
|
.. code-block:: python
|
|
async for cached_content in await client.aio.caches.list():
|
|
print(cached_content.name)
|
|
"""
|
|
|
|
list_request = self._list
|
|
return AsyncPager(
|
|
'cached_contents',
|
|
list_request,
|
|
await self._list(config=config),
|
|
config,
|
|
)
|