# Copyright 2024 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.
from typing import Optional, Union
from urllib.parse import urlencode
from . import _common
from . import _transformers as t
from . import types
from ._api_client import ApiClient
from ._common import get_value_by_path as getv
from ._common import set_value_by_path as setv
from .pagers import AsyncPager, Pager
def _Part_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['video_metadata']) is not None:
raise ValueError('video_metadata parameter is not supported in Google AI.')
if getv(from_object, ['thought']) is not None:
setv(to_object, ['thought'], getv(from_object, ['thought']))
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']))
return to_object
def _Part_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['video_metadata']) is not None:
setv(to_object, ['videoMetadata'], getv(from_object, ['video_metadata']))
if getv(from_object, ['thought']) is not None:
setv(to_object, ['thought'], getv(from_object, ['thought']))
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']))
return to_object
def _Content_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['parts']) is not None:
setv(
to_object,
['parts'],
[
_Part_to_mldev(api_client, item, to_object)
for item in getv(from_object, ['parts'])
],
)
if getv(from_object, ['role']) is not None:
setv(to_object, ['role'], getv(from_object, ['role']))
return to_object
def _Content_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['parts']) is not None:
setv(
to_object,
['parts'],
[
_Part_to_vertex(api_client, item, to_object)
for item in getv(from_object, ['parts'])
],
)
if getv(from_object, ['role']) is not None:
setv(to_object, ['role'], getv(from_object, ['role']))
return to_object
def _Schema_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['min_items']) is not None:
raise ValueError('min_items parameter is not supported in Google AI.')
if getv(from_object, ['example']) is not None:
raise ValueError('example parameter is not supported in Google AI.')
if getv(from_object, ['property_ordering']) is not None:
raise ValueError(
'property_ordering parameter is not supported in Google AI.'
)
if getv(from_object, ['pattern']) is not None:
raise ValueError('pattern parameter is not supported in Google AI.')
if getv(from_object, ['minimum']) is not None:
raise ValueError('minimum parameter is not supported in Google AI.')
if getv(from_object, ['default']) is not None:
raise ValueError('default parameter is not supported in Google AI.')
if getv(from_object, ['any_of']) is not None:
raise ValueError('any_of parameter is not supported in Google AI.')
if getv(from_object, ['max_length']) is not None:
raise ValueError('max_length parameter is not supported in Google AI.')
if getv(from_object, ['title']) is not None:
raise ValueError('title parameter is not supported in Google AI.')
if getv(from_object, ['min_length']) is not None:
raise ValueError('min_length parameter is not supported in Google AI.')
if getv(from_object, ['min_properties']) is not None:
raise ValueError('min_properties parameter is not supported in Google AI.')
if getv(from_object, ['max_items']) is not None:
raise ValueError('max_items parameter is not supported in Google AI.')
if getv(from_object, ['maximum']) is not None:
raise ValueError('maximum parameter is not supported in Google AI.')
if getv(from_object, ['nullable']) is not None:
raise ValueError('nullable parameter is not supported in Google AI.')
if getv(from_object, ['max_properties']) is not None:
raise ValueError('max_properties parameter is not supported in Google AI.')
if getv(from_object, ['type']) is not None:
setv(to_object, ['type'], getv(from_object, ['type']))
if getv(from_object, ['description']) is not None:
setv(to_object, ['description'], getv(from_object, ['description']))
if getv(from_object, ['enum']) is not None:
setv(to_object, ['enum'], getv(from_object, ['enum']))
if getv(from_object, ['format']) is not None:
setv(to_object, ['format'], getv(from_object, ['format']))
if getv(from_object, ['items']) is not None:
setv(to_object, ['items'], getv(from_object, ['items']))
if getv(from_object, ['properties']) is not None:
setv(to_object, ['properties'], getv(from_object, ['properties']))
if getv(from_object, ['required']) is not None:
setv(to_object, ['required'], getv(from_object, ['required']))
return to_object
def _Schema_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['min_items']) is not None:
setv(to_object, ['minItems'], getv(from_object, ['min_items']))
if getv(from_object, ['example']) is not None:
setv(to_object, ['example'], getv(from_object, ['example']))
if getv(from_object, ['property_ordering']) is not None:
setv(
to_object,
['propertyOrdering'],
getv(from_object, ['property_ordering']),
)
if getv(from_object, ['pattern']) is not None:
setv(to_object, ['pattern'], getv(from_object, ['pattern']))
if getv(from_object, ['minimum']) is not None:
setv(to_object, ['minimum'], getv(from_object, ['minimum']))
if getv(from_object, ['default']) is not None:
setv(to_object, ['default'], getv(from_object, ['default']))
if getv(from_object, ['any_of']) is not None:
setv(to_object, ['anyOf'], getv(from_object, ['any_of']))
if getv(from_object, ['max_length']) is not None:
setv(to_object, ['maxLength'], getv(from_object, ['max_length']))
if getv(from_object, ['title']) is not None:
setv(to_object, ['title'], getv(from_object, ['title']))
if getv(from_object, ['min_length']) is not None:
setv(to_object, ['minLength'], getv(from_object, ['min_length']))
if getv(from_object, ['min_properties']) is not None:
setv(to_object, ['minProperties'], getv(from_object, ['min_properties']))
if getv(from_object, ['max_items']) is not None:
setv(to_object, ['maxItems'], getv(from_object, ['max_items']))
if getv(from_object, ['maximum']) is not None:
setv(to_object, ['maximum'], getv(from_object, ['maximum']))
if getv(from_object, ['nullable']) is not None:
setv(to_object, ['nullable'], getv(from_object, ['nullable']))
if getv(from_object, ['max_properties']) is not None:
setv(to_object, ['maxProperties'], getv(from_object, ['max_properties']))
if getv(from_object, ['type']) is not None:
setv(to_object, ['type'], getv(from_object, ['type']))
if getv(from_object, ['description']) is not None:
setv(to_object, ['description'], getv(from_object, ['description']))
if getv(from_object, ['enum']) is not None:
setv(to_object, ['enum'], getv(from_object, ['enum']))
if getv(from_object, ['format']) is not None:
setv(to_object, ['format'], getv(from_object, ['format']))
if getv(from_object, ['items']) is not None:
setv(to_object, ['items'], getv(from_object, ['items']))
if getv(from_object, ['properties']) is not None:
setv(to_object, ['properties'], getv(from_object, ['properties']))
if getv(from_object, ['required']) is not None:
setv(to_object, ['required'], getv(from_object, ['required']))
return to_object
def _FunctionDeclaration_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['response']) is not None:
raise ValueError('response parameter is not supported in Google AI.')
if getv(from_object, ['description']) is not None:
setv(to_object, ['description'], getv(from_object, ['description']))
if getv(from_object, ['name']) is not None:
setv(to_object, ['name'], getv(from_object, ['name']))
if getv(from_object, ['parameters']) is not None:
setv(to_object, ['parameters'], getv(from_object, ['parameters']))
return to_object
def _FunctionDeclaration_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['response']) is not None:
setv(
to_object,
['response'],
_Schema_to_vertex(
api_client, getv(from_object, ['response']), to_object
),
)
if getv(from_object, ['description']) is not None:
setv(to_object, ['description'], getv(from_object, ['description']))
if getv(from_object, ['name']) is not None:
setv(to_object, ['name'], getv(from_object, ['name']))
if getv(from_object, ['parameters']) is not None:
setv(to_object, ['parameters'], getv(from_object, ['parameters']))
return to_object
def _GoogleSearch_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
return to_object
def _GoogleSearch_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
return to_object
def _DynamicRetrievalConfig_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['mode']) is not None:
setv(to_object, ['mode'], getv(from_object, ['mode']))
if getv(from_object, ['dynamic_threshold']) is not None:
setv(
to_object,
['dynamicThreshold'],
getv(from_object, ['dynamic_threshold']),
)
return to_object
def _DynamicRetrievalConfig_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['mode']) is not None:
setv(to_object, ['mode'], getv(from_object, ['mode']))
if getv(from_object, ['dynamic_threshold']) is not None:
setv(
to_object,
['dynamicThreshold'],
getv(from_object, ['dynamic_threshold']),
)
return to_object
def _GoogleSearchRetrieval_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['dynamic_retrieval_config']) is not None:
setv(
to_object,
['dynamicRetrievalConfig'],
_DynamicRetrievalConfig_to_mldev(
api_client,
getv(from_object, ['dynamic_retrieval_config']),
to_object,
),
)
return to_object
def _GoogleSearchRetrieval_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['dynamic_retrieval_config']) is not None:
setv(
to_object,
['dynamicRetrievalConfig'],
_DynamicRetrievalConfig_to_vertex(
api_client,
getv(from_object, ['dynamic_retrieval_config']),
to_object,
),
)
return to_object
def _Tool_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['function_declarations']) is not None:
setv(
to_object,
['functionDeclarations'],
[
_FunctionDeclaration_to_mldev(api_client, item, to_object)
for item in getv(from_object, ['function_declarations'])
],
)
if getv(from_object, ['retrieval']) is not None:
raise ValueError('retrieval parameter is not supported in Google AI.')
if getv(from_object, ['google_search']) is not None:
setv(
to_object,
['googleSearch'],
_GoogleSearch_to_mldev(
api_client, getv(from_object, ['google_search']), to_object
),
)
if getv(from_object, ['google_search_retrieval']) is not None:
setv(
to_object,
['googleSearchRetrieval'],
_GoogleSearchRetrieval_to_mldev(
api_client,
getv(from_object, ['google_search_retrieval']),
to_object,
),
)
if getv(from_object, ['code_execution']) is not None:
setv(to_object, ['codeExecution'], getv(from_object, ['code_execution']))
return to_object
def _Tool_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['function_declarations']) is not None:
setv(
to_object,
['functionDeclarations'],
[
_FunctionDeclaration_to_vertex(api_client, item, to_object)
for item in getv(from_object, ['function_declarations'])
],
)
if getv(from_object, ['retrieval']) is not None:
setv(to_object, ['retrieval'], getv(from_object, ['retrieval']))
if getv(from_object, ['google_search']) is not None:
setv(
to_object,
['googleSearch'],
_GoogleSearch_to_vertex(
api_client, getv(from_object, ['google_search']), to_object
),
)
if getv(from_object, ['google_search_retrieval']) is not None:
setv(
to_object,
['googleSearchRetrieval'],
_GoogleSearchRetrieval_to_vertex(
api_client,
getv(from_object, ['google_search_retrieval']),
to_object,
),
)
if getv(from_object, ['code_execution']) is not None:
setv(to_object, ['codeExecution'], getv(from_object, ['code_execution']))
return to_object
def _FunctionCallingConfig_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['mode']) is not None:
setv(to_object, ['mode'], getv(from_object, ['mode']))
if getv(from_object, ['allowed_function_names']) is not None:
setv(
to_object,
['allowedFunctionNames'],
getv(from_object, ['allowed_function_names']),
)
return to_object
def _FunctionCallingConfig_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['mode']) is not None:
setv(to_object, ['mode'], getv(from_object, ['mode']))
if getv(from_object, ['allowed_function_names']) is not None:
setv(
to_object,
['allowedFunctionNames'],
getv(from_object, ['allowed_function_names']),
)
return to_object
def _ToolConfig_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['function_calling_config']) is not None:
setv(
to_object,
['functionCallingConfig'],
_FunctionCallingConfig_to_mldev(
api_client,
getv(from_object, ['function_calling_config']),
to_object,
),
)
return to_object
def _ToolConfig_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['function_calling_config']) is not None:
setv(
to_object,
['functionCallingConfig'],
_FunctionCallingConfig_to_vertex(
api_client,
getv(from_object, ['function_calling_config']),
to_object,
),
)
return to_object
def _CreateCachedContentConfig_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['http_options']) is not None:
setv(to_object, ['httpOptions'], getv(from_object, ['http_options']))
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']))
if getv(from_object, ['display_name']) is not None:
setv(parent_object, ['displayName'], getv(from_object, ['display_name']))
if getv(from_object, ['contents']) is not None:
setv(
parent_object,
['contents'],
[
_Content_to_mldev(api_client, item, to_object)
for item in t.t_contents(
api_client, getv(from_object, ['contents'])
)
],
)
if getv(from_object, ['system_instruction']) is not None:
setv(
parent_object,
['systemInstruction'],
_Content_to_mldev(
api_client,
t.t_content(api_client, getv(from_object, ['system_instruction'])),
to_object,
),
)
if getv(from_object, ['tools']) is not None:
setv(
parent_object,
['tools'],
[
_Tool_to_mldev(api_client, item, to_object)
for item in getv(from_object, ['tools'])
],
)
if getv(from_object, ['tool_config']) is not None:
setv(
parent_object,
['toolConfig'],
_ToolConfig_to_mldev(
api_client, getv(from_object, ['tool_config']), to_object
),
)
return to_object
def _CreateCachedContentConfig_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['http_options']) is not None:
setv(to_object, ['httpOptions'], getv(from_object, ['http_options']))
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']))
if getv(from_object, ['display_name']) is not None:
setv(parent_object, ['displayName'], getv(from_object, ['display_name']))
if getv(from_object, ['contents']) is not None:
setv(
parent_object,
['contents'],
[
_Content_to_vertex(api_client, item, to_object)
for item in t.t_contents(
api_client, getv(from_object, ['contents'])
)
],
)
if getv(from_object, ['system_instruction']) is not None:
setv(
parent_object,
['systemInstruction'],
_Content_to_vertex(
api_client,
t.t_content(api_client, getv(from_object, ['system_instruction'])),
to_object,
),
)
if getv(from_object, ['tools']) is not None:
setv(
parent_object,
['tools'],
[
_Tool_to_vertex(api_client, item, to_object)
for item in getv(from_object, ['tools'])
],
)
if getv(from_object, ['tool_config']) is not None:
setv(
parent_object,
['toolConfig'],
_ToolConfig_to_vertex(
api_client, getv(from_object, ['tool_config']), to_object
),
)
return to_object
def _CreateCachedContentParameters_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['model']) is not None:
setv(
to_object,
['model'],
t.t_caches_model(api_client, getv(from_object, ['model'])),
)
if getv(from_object, ['config']) is not None:
setv(
to_object,
['config'],
_CreateCachedContentConfig_to_mldev(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _CreateCachedContentParameters_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['model']) is not None:
setv(
to_object,
['model'],
t.t_caches_model(api_client, getv(from_object, ['model'])),
)
if getv(from_object, ['config']) is not None:
setv(
to_object,
['config'],
_CreateCachedContentConfig_to_vertex(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _GetCachedContentConfig_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['http_options']) is not None:
setv(to_object, ['httpOptions'], getv(from_object, ['http_options']))
return to_object
def _GetCachedContentConfig_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['http_options']) is not None:
setv(to_object, ['httpOptions'], getv(from_object, ['http_options']))
return to_object
def _GetCachedContentParameters_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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:
setv(
to_object,
['config'],
_GetCachedContentConfig_to_mldev(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _GetCachedContentParameters_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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:
setv(
to_object,
['config'],
_GetCachedContentConfig_to_vertex(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _DeleteCachedContentConfig_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['http_options']) is not None:
setv(to_object, ['httpOptions'], getv(from_object, ['http_options']))
return to_object
def _DeleteCachedContentConfig_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['http_options']) is not None:
setv(to_object, ['httpOptions'], getv(from_object, ['http_options']))
return to_object
def _DeleteCachedContentParameters_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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:
setv(
to_object,
['config'],
_DeleteCachedContentConfig_to_mldev(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _DeleteCachedContentParameters_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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:
setv(
to_object,
['config'],
_DeleteCachedContentConfig_to_vertex(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _UpdateCachedContentConfig_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['http_options']) is not None:
setv(to_object, ['httpOptions'], getv(from_object, ['http_options']))
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(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['http_options']) is not None:
setv(to_object, ['httpOptions'], getv(from_object, ['http_options']))
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: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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:
setv(
to_object,
['config'],
_UpdateCachedContentConfig_to_mldev(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _UpdateCachedContentParameters_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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:
setv(
to_object,
['config'],
_UpdateCachedContentConfig_to_vertex(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _ListCachedContentsConfig_to_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['config']) is not None:
setv(
to_object,
['config'],
_ListCachedContentsConfig_to_mldev(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _ListCachedContentsParameters_to_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['config']) is not None:
setv(
to_object,
['config'],
_ListCachedContentsConfig_to_vertex(
api_client, getv(from_object, ['config']), to_object
),
)
return to_object
def _CachedContent_from_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['name']) is not None:
setv(to_object, ['name'], getv(from_object, ['name']))
if getv(from_object, ['displayName']) is not None:
setv(to_object, ['display_name'], getv(from_object, ['displayName']))
if getv(from_object, ['model']) is not None:
setv(to_object, ['model'], getv(from_object, ['model']))
if getv(from_object, ['createTime']) is not None:
setv(to_object, ['create_time'], getv(from_object, ['createTime']))
if getv(from_object, ['updateTime']) is not None:
setv(to_object, ['update_time'], getv(from_object, ['updateTime']))
if getv(from_object, ['expireTime']) is not None:
setv(to_object, ['expire_time'], getv(from_object, ['expireTime']))
if getv(from_object, ['usageMetadata']) is not None:
setv(to_object, ['usage_metadata'], getv(from_object, ['usageMetadata']))
return to_object
def _CachedContent_from_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
if getv(from_object, ['name']) is not None:
setv(to_object, ['name'], getv(from_object, ['name']))
if getv(from_object, ['displayName']) is not None:
setv(to_object, ['display_name'], getv(from_object, ['displayName']))
if getv(from_object, ['model']) is not None:
setv(to_object, ['model'], getv(from_object, ['model']))
if getv(from_object, ['createTime']) is not None:
setv(to_object, ['create_time'], getv(from_object, ['createTime']))
if getv(from_object, ['updateTime']) is not None:
setv(to_object, ['update_time'], getv(from_object, ['updateTime']))
if getv(from_object, ['expireTime']) is not None:
setv(to_object, ['expire_time'], getv(from_object, ['expireTime']))
if getv(from_object, ['usageMetadata']) is not None:
setv(to_object, ['usage_metadata'], getv(from_object, ['usageMetadata']))
return to_object
def _DeleteCachedContentResponse_from_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
return to_object
def _DeleteCachedContentResponse_from_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
return to_object
def _ListCachedContentsResponse_from_mldev(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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'],
[
_CachedContent_from_mldev(api_client, item, to_object)
for item in getv(from_object, ['cachedContents'])
],
)
return to_object
def _ListCachedContentsResponse_from_vertex(
api_client: ApiClient,
from_object: Union[dict, object],
parent_object: dict = None,
) -> dict:
to_object = {}
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'],
[
_CachedContent_from_vertex(api_client, item, to_object)
for item in getv(from_object, ['cachedContents'])
],
)
return to_object
class Caches(_common.BaseModule):
def create(
self,
*,
model: str,
config: Optional[types.CreateCachedContentConfigOrDict] = None,
) -> types.CachedContent:
"""Creates cached content, this call will initialize the cached
content in the data storage, and users need to pay for the cache data
storage.
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,
)
if self._api_client.vertexai:
request_dict = _CreateCachedContentParameters_to_vertex(
self._api_client, parameter_model
)
path = 'cachedContents'.format_map(request_dict.get('_url'))
else:
request_dict = _CreateCachedContentParameters_to_mldev(
self._api_client, parameter_model
)
path = 'cachedContents'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = self._api_client.request(
'post', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _CachedContent_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _CachedContent_from_mldev(self._api_client, response_dict)
return_value = types.CachedContent._from_response(
response_dict, parameter_model
)
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
await client.aio.caches.get(name= ... ) // The server-generated resource
name.
"""
parameter_model = types._GetCachedContentParameters(
name=name,
config=config,
)
if self._api_client.vertexai:
request_dict = _GetCachedContentParameters_to_vertex(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
else:
request_dict = _GetCachedContentParameters_to_mldev(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = self._api_client.request(
'get', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _CachedContent_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _CachedContent_from_mldev(self._api_client, response_dict)
return_value = types.CachedContent._from_response(
response_dict, parameter_model
)
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
await client.aio.caches.delete(name= ... ) // The server-generated
resource name.
"""
parameter_model = types._DeleteCachedContentParameters(
name=name,
config=config,
)
if self._api_client.vertexai:
request_dict = _DeleteCachedContentParameters_to_vertex(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
else:
request_dict = _DeleteCachedContentParameters_to_mldev(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = self._api_client.request(
'delete', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _DeleteCachedContentResponse_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _DeleteCachedContentResponse_from_mldev(
self._api_client, response_dict
)
return_value = types.DeleteCachedContentResponse._from_response(
response_dict, parameter_model
)
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 = await client.aio.caches.update(
name= ... // The server-generated resource name.
config={
'ttl': '7600s',
},
)
"""
parameter_model = types._UpdateCachedContentParameters(
name=name,
config=config,
)
if self._api_client.vertexai:
request_dict = _UpdateCachedContentParameters_to_vertex(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
else:
request_dict = _UpdateCachedContentParameters_to_mldev(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = self._api_client.request(
'patch', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _CachedContent_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _CachedContent_from_mldev(self._api_client, response_dict)
return_value = types.CachedContent._from_response(
response_dict, parameter_model
)
self._api_client._verify_response(return_value)
return return_value
def _list(
self, *, config: Optional[types.ListCachedContentsConfigOrDict] = None
) -> types.ListCachedContentsResponse:
"""Lists cached content configurations.
.. code-block:: python
cached_contents = await client.aio.caches.list(config={'page_size': 2})
async for cached_content in cached_contents:
print(cached_content)
"""
parameter_model = types._ListCachedContentsParameters(
config=config,
)
if self._api_client.vertexai:
request_dict = _ListCachedContentsParameters_to_vertex(
self._api_client, parameter_model
)
path = 'cachedContents'.format_map(request_dict.get('_url'))
else:
request_dict = _ListCachedContentsParameters_to_mldev(
self._api_client, parameter_model
)
path = 'cachedContents'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = self._api_client.request(
'get', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _ListCachedContentsResponse_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _ListCachedContentsResponse_from_mldev(
self._api_client, response_dict
)
return_value = types.ListCachedContentsResponse._from_response(
response_dict, parameter_model
)
self._api_client._verify_response(return_value)
return return_value
def list(
self, *, config: Optional[types.ListCachedContentsConfigOrDict] = None
) -> Pager[types.CachedContent]:
return Pager(
'cached_contents',
self._list,
self._list(config=config),
config,
)
class AsyncCaches(_common.BaseModule):
async def create(
self,
*,
model: str,
config: Optional[types.CreateCachedContentConfigOrDict] = None,
) -> types.CachedContent:
"""Creates cached content, this call will initialize the cached
content in the data storage, and users need to pay for the cache data
storage.
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,
)
if self._api_client.vertexai:
request_dict = _CreateCachedContentParameters_to_vertex(
self._api_client, parameter_model
)
path = 'cachedContents'.format_map(request_dict.get('_url'))
else:
request_dict = _CreateCachedContentParameters_to_mldev(
self._api_client, parameter_model
)
path = 'cachedContents'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = await self._api_client.async_request(
'post', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _CachedContent_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _CachedContent_from_mldev(self._api_client, response_dict)
return_value = types.CachedContent._from_response(
response_dict, parameter_model
)
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,
)
if self._api_client.vertexai:
request_dict = _GetCachedContentParameters_to_vertex(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
else:
request_dict = _GetCachedContentParameters_to_mldev(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = await self._api_client.async_request(
'get', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _CachedContent_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _CachedContent_from_mldev(self._api_client, response_dict)
return_value = types.CachedContent._from_response(
response_dict, parameter_model
)
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,
)
if self._api_client.vertexai:
request_dict = _DeleteCachedContentParameters_to_vertex(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
else:
request_dict = _DeleteCachedContentParameters_to_mldev(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = await self._api_client.async_request(
'delete', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _DeleteCachedContentResponse_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _DeleteCachedContentResponse_from_mldev(
self._api_client, response_dict
)
return_value = types.DeleteCachedContentResponse._from_response(
response_dict, parameter_model
)
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,
)
if self._api_client.vertexai:
request_dict = _UpdateCachedContentParameters_to_vertex(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
else:
request_dict = _UpdateCachedContentParameters_to_mldev(
self._api_client, parameter_model
)
path = '{name}'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = await self._api_client.async_request(
'patch', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _CachedContent_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _CachedContent_from_mldev(self._api_client, response_dict)
return_value = types.CachedContent._from_response(
response_dict, parameter_model
)
self._api_client._verify_response(return_value)
return return_value
async def _list(
self, *, config: Optional[types.ListCachedContentsConfigOrDict] = None
) -> types.ListCachedContentsResponse:
"""Lists cached content configurations.
.. code-block:: python
cached_contents = await client.aio.caches.list(config={'page_size': 2})
async for cached_content in cached_contents:
print(cached_content)
"""
parameter_model = types._ListCachedContentsParameters(
config=config,
)
if self._api_client.vertexai:
request_dict = _ListCachedContentsParameters_to_vertex(
self._api_client, parameter_model
)
path = 'cachedContents'.format_map(request_dict.get('_url'))
else:
request_dict = _ListCachedContentsParameters_to_mldev(
self._api_client, parameter_model
)
path = 'cachedContents'.format_map(request_dict.get('_url'))
query_params = request_dict.get('_query')
if query_params:
path = f'{path}?{urlencode(query_params)}'
# TODO: remove the hack that pops config.
config = request_dict.pop('config', None)
http_options = config.pop('httpOptions', None) if config else None
request_dict = _common.convert_to_dict(request_dict)
request_dict = _common.encode_unserializable_types(request_dict)
response_dict = await self._api_client.async_request(
'get', path, request_dict, http_options
)
if self._api_client.vertexai:
response_dict = _ListCachedContentsResponse_from_vertex(
self._api_client, response_dict
)
else:
response_dict = _ListCachedContentsResponse_from_mldev(
self._api_client, response_dict
)
return_value = types.ListCachedContentsResponse._from_response(
response_dict, parameter_model
)
self._api_client._verify_response(return_value)
return return_value
async def list(
self, *, config: Optional[types.ListCachedContentsConfigOrDict] = None
) -> AsyncPager[types.CachedContent]:
return AsyncPager(
'cached_contents',
self._list,
await self._list(config=config),
config,
)
