As of January 1, 2020 this library no longer supports Python 2 on the latest released version.
Library versions released prior to that date will continue to be available. For more information please
visit Python 2 support on Google Cloud.
Source code for google.ai.generativelanguage_v1beta.services.retriever_service.async_client
# -*- coding: utf-8 -*-
# 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.
#
from collections import OrderedDict
import re
from typing import (
Callable,
Dict,
Mapping,
MutableMapping,
MutableSequence,
Optional,
Sequence,
Tuple,
Type,
Union,
)
from google.api_core import exceptions as core_exceptions
from google.api_core import gapic_v1
from google.api_core import retry_async as retries
from google.api_core.client_options import ClientOptions
from google.auth import credentials as ga_credentials # type: ignore
from google.oauth2 import service_account # type: ignore
from google.ai.generativelanguage_v1beta import gapic_version as package_version
try:
OptionalRetry = Union[retries.AsyncRetry, gapic_v1.method._MethodDefault, None]
except AttributeError: # pragma: NO COVER
OptionalRetry = Union[retries.AsyncRetry, object, None] # type: ignore
from google.longrunning import operations_pb2 # type: ignore
from google.protobuf import field_mask_pb2 # type: ignore
from google.protobuf import timestamp_pb2 # type: ignore
from google.ai.generativelanguage_v1beta.services.retriever_service import pagers
from google.ai.generativelanguage_v1beta.types import retriever, retriever_service
from .client import RetrieverServiceClient
from .transports.base import DEFAULT_CLIENT_INFO, RetrieverServiceTransport
from .transports.grpc_asyncio import RetrieverServiceGrpcAsyncIOTransport
[docs]class RetrieverServiceAsyncClient:
"""An API for semantic search over a corpus of user uploaded
content.
"""
_client: RetrieverServiceClient
# Copy defaults from the synchronous client for use here.
# Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead.
DEFAULT_ENDPOINT = RetrieverServiceClient.DEFAULT_ENDPOINT
DEFAULT_MTLS_ENDPOINT = RetrieverServiceClient.DEFAULT_MTLS_ENDPOINT
_DEFAULT_ENDPOINT_TEMPLATE = RetrieverServiceClient._DEFAULT_ENDPOINT_TEMPLATE
_DEFAULT_UNIVERSE = RetrieverServiceClient._DEFAULT_UNIVERSE
chunk_path = staticmethod(RetrieverServiceClient.chunk_path)
parse_chunk_path = staticmethod(RetrieverServiceClient.parse_chunk_path)
corpus_path = staticmethod(RetrieverServiceClient.corpus_path)
parse_corpus_path = staticmethod(RetrieverServiceClient.parse_corpus_path)
document_path = staticmethod(RetrieverServiceClient.document_path)
parse_document_path = staticmethod(RetrieverServiceClient.parse_document_path)
common_billing_account_path = staticmethod(
RetrieverServiceClient.common_billing_account_path
)
parse_common_billing_account_path = staticmethod(
RetrieverServiceClient.parse_common_billing_account_path
)
common_folder_path = staticmethod(RetrieverServiceClient.common_folder_path)
parse_common_folder_path = staticmethod(
RetrieverServiceClient.parse_common_folder_path
)
common_organization_path = staticmethod(
RetrieverServiceClient.common_organization_path
)
parse_common_organization_path = staticmethod(
RetrieverServiceClient.parse_common_organization_path
)
common_project_path = staticmethod(RetrieverServiceClient.common_project_path)
parse_common_project_path = staticmethod(
RetrieverServiceClient.parse_common_project_path
)
common_location_path = staticmethod(RetrieverServiceClient.common_location_path)
parse_common_location_path = staticmethod(
RetrieverServiceClient.parse_common_location_path
)
[docs] @classmethod
def from_service_account_info(cls, info: dict, *args, **kwargs):
"""Creates an instance of this client using the provided credentials
info.
Args:
info (dict): The service account private key info.
args: Additional arguments to pass to the constructor.
kwargs: Additional arguments to pass to the constructor.
Returns:
RetrieverServiceAsyncClient: The constructed client.
"""
return RetrieverServiceClient.from_service_account_info.__func__(RetrieverServiceAsyncClient, info, *args, **kwargs) # type: ignore
[docs] @classmethod
def from_service_account_file(cls, filename: str, *args, **kwargs):
"""Creates an instance of this client using the provided credentials
file.
Args:
filename (str): The path to the service account private key json
file.
args: Additional arguments to pass to the constructor.
kwargs: Additional arguments to pass to the constructor.
Returns:
RetrieverServiceAsyncClient: The constructed client.
"""
return RetrieverServiceClient.from_service_account_file.__func__(RetrieverServiceAsyncClient, filename, *args, **kwargs) # type: ignore
from_service_account_json = from_service_account_file
[docs] @classmethod
def get_mtls_endpoint_and_cert_source(
cls, client_options: Optional[ClientOptions] = None
):
"""Return the API endpoint and client cert source for mutual TLS.
The client cert source is determined in the following order:
(1) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is not "true", the
client cert source is None.
(2) if `client_options.client_cert_source` is provided, use the provided one; if the
default client cert source exists, use the default one; otherwise the client cert
source is None.
The API endpoint is determined in the following order:
(1) if `client_options.api_endpoint` if provided, use the provided one.
(2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
default mTLS endpoint; if the environment variable is "never", use the default API
endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
use the default API endpoint.
More details can be found at https://google.aip.dev/auth/4114.
Args:
client_options (google.api_core.client_options.ClientOptions): Custom options for the
client. Only the `api_endpoint` and `client_cert_source` properties may be used
in this method.
Returns:
Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
client cert source to use.
Raises:
google.auth.exceptions.MutualTLSChannelError: If any errors happen.
"""
return RetrieverServiceClient.get_mtls_endpoint_and_cert_source(client_options) # type: ignore
@property
def transport(self) -> RetrieverServiceTransport:
"""Returns the transport used by the client instance.
Returns:
RetrieverServiceTransport: The transport used by the client instance.
"""
return self._client.transport
@property
def api_endpoint(self):
"""Return the API endpoint used by the client instance.
Returns:
str: The API endpoint used by the client instance.
"""
return self._client._api_endpoint
@property
def universe_domain(self) -> str:
"""Return the universe domain used by the client instance.
Returns:
str: The universe domain used
by the client instance.
"""
return self._client._universe_domain
get_transport_class = RetrieverServiceClient.get_transport_class
def __init__(
self,
*,
credentials: Optional[ga_credentials.Credentials] = None,
transport: Optional[
Union[
str, RetrieverServiceTransport, Callable[..., RetrieverServiceTransport]
]
] = "grpc_asyncio",
client_options: Optional[ClientOptions] = None,
client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
) -> None:
"""Instantiates the retriever service async client.
Args:
credentials (Optional[google.auth.credentials.Credentials]): The
authorization credentials to attach to requests. These
credentials identify the application to the service; if none
are specified, the client will attempt to ascertain the
credentials from the environment.
transport (Optional[Union[str,RetrieverServiceTransport,Callable[..., RetrieverServiceTransport]]]):
The transport to use, or a Callable that constructs and returns a new transport to use.
If a Callable is given, it will be called with the same set of initialization
arguments as used in the RetrieverServiceTransport constructor.
If set to None, a transport is chosen automatically.
client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]):
Custom options for the client.
1. The ``api_endpoint`` property can be used to override the
default endpoint provided by the client when ``transport`` is
not explicitly provided. Only if this property is not set and
``transport`` was not explicitly provided, the endpoint is
determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment
variable, which have one of the following values:
"always" (always use the default mTLS endpoint), "never" (always
use the default regular endpoint) and "auto" (auto-switch to the
default mTLS endpoint if client certificate is present; this is
the default value).
2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
is "true", then the ``client_cert_source`` property can be used
to provide a client certificate for mTLS transport. If
not provided, the default SSL client certificate will be used if
present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not
set, no client certificate will be used.
3. The ``universe_domain`` property can be used to override the
default "googleapis.com" universe. Note that ``api_endpoint``
property still takes precedence; and ``universe_domain`` is
currently not supported for mTLS.
client_info (google.api_core.gapic_v1.client_info.ClientInfo):
The client info used to send a user-agent string along with
API requests. If ``None``, then default info will be used.
Generally, you only need to set this if you're developing
your own client library.
Raises:
google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport
creation failed for any reason.
"""
self._client = RetrieverServiceClient(
credentials=credentials,
transport=transport,
client_options=client_options,
client_info=client_info,
)
[docs] async def create_corpus(
self,
request: Optional[Union[retriever_service.CreateCorpusRequest, dict]] = None,
*,
corpus: Optional[retriever.Corpus] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Corpus:
r"""Creates an empty ``Corpus``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_create_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.CreateCorpusRequest(
)
# Make the request
response = await client.create_corpus(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.CreateCorpusRequest, dict]]):
The request object. Request to create a ``Corpus``.
corpus (:class:`google.ai.generativelanguage_v1beta.types.Corpus`):
Required. The ``Corpus`` to create.
This corresponds to the ``corpus`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Corpus:
A Corpus is a collection of Documents.
A project can create up to 5 corpora.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([corpus])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.CreateCorpusRequest):
request = retriever_service.CreateCorpusRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if corpus is not None:
request.corpus = corpus
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.create_corpus
]
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def get_corpus(
self,
request: Optional[Union[retriever_service.GetCorpusRequest, dict]] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Corpus:
r"""Gets information about a specific ``Corpus``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_get_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.GetCorpusRequest(
name="name_value",
)
# Make the request
response = await client.get_corpus(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.GetCorpusRequest, dict]]):
The request object. Request for getting information about a specific
``Corpus``.
name (:class:`str`):
Required. The name of the ``Corpus``. Example:
``corpora/my-corpus-123``
This corresponds to the ``name`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Corpus:
A Corpus is a collection of Documents.
A project can create up to 5 corpora.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.GetCorpusRequest):
request = retriever_service.GetCorpusRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.get_corpus
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def update_corpus(
self,
request: Optional[Union[retriever_service.UpdateCorpusRequest, dict]] = None,
*,
corpus: Optional[retriever.Corpus] = None,
update_mask: Optional[field_mask_pb2.FieldMask] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Corpus:
r"""Updates a ``Corpus``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_update_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.UpdateCorpusRequest(
)
# Make the request
response = await client.update_corpus(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.UpdateCorpusRequest, dict]]):
The request object. Request to update a ``Corpus``.
corpus (:class:`google.ai.generativelanguage_v1beta.types.Corpus`):
Required. The ``Corpus`` to update.
This corresponds to the ``corpus`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`):
Required. The list of fields to update. Currently, this
only supports updating ``display_name``.
This corresponds to the ``update_mask`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Corpus:
A Corpus is a collection of Documents.
A project can create up to 5 corpora.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([corpus, update_mask])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.UpdateCorpusRequest):
request = retriever_service.UpdateCorpusRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if corpus is not None:
request.corpus = corpus
if update_mask is not None:
request.update_mask = update_mask
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.update_corpus
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata(
(("corpus.name", request.corpus.name),)
),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def delete_corpus(
self,
request: Optional[Union[retriever_service.DeleteCorpusRequest, dict]] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> None:
r"""Deletes a ``Corpus``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_delete_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.DeleteCorpusRequest(
name="name_value",
)
# Make the request
await client.delete_corpus(request=request)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.DeleteCorpusRequest, dict]]):
The request object. Request to delete a ``Corpus``.
name (:class:`str`):
Required. The resource name of the ``Corpus``. Example:
``corpora/my-corpus-123``
This corresponds to the ``name`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.DeleteCorpusRequest):
request = retriever_service.DeleteCorpusRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.delete_corpus
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] async def list_corpora(
self,
request: Optional[Union[retriever_service.ListCorporaRequest, dict]] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.ListCorporaAsyncPager:
r"""Lists all ``Corpora`` owned by the user.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_list_corpora():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.ListCorporaRequest(
)
# Make the request
page_result = client.list_corpora(request=request)
# Handle the response
async for response in page_result:
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.ListCorporaRequest, dict]]):
The request object. Request for listing ``Corpora``.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.services.retriever_service.pagers.ListCorporaAsyncPager:
Response from ListCorpora containing a paginated list of Corpora.
The results are sorted by ascending
corpus.create_time.
Iterating over this object will yield results and
resolve additional pages automatically.
"""
# Create or coerce a protobuf request object.
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.ListCorporaRequest):
request = retriever_service.ListCorporaRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.list_corpora
]
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# This method is paged; wrap the response in a pager, which provides
# an `__aiter__` convenience method.
response = pagers.ListCorporaAsyncPager(
method=rpc,
request=request,
response=response,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def query_corpus(
self,
request: Optional[Union[retriever_service.QueryCorpusRequest, dict]] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever_service.QueryCorpusResponse:
r"""Performs semantic search over a ``Corpus``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_query_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.QueryCorpusRequest(
name="name_value",
query="query_value",
)
# Make the request
response = await client.query_corpus(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.QueryCorpusRequest, dict]]):
The request object. Request for querying a ``Corpus``.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.QueryCorpusResponse:
Response from QueryCorpus containing a list of relevant
chunks.
"""
# Create or coerce a protobuf request object.
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.QueryCorpusRequest):
request = retriever_service.QueryCorpusRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.query_corpus
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def create_document(
self,
request: Optional[Union[retriever_service.CreateDocumentRequest, dict]] = None,
*,
parent: Optional[str] = None,
document: Optional[retriever.Document] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Document:
r"""Creates an empty ``Document``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_create_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.CreateDocumentRequest(
parent="parent_value",
)
# Make the request
response = await client.create_document(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.CreateDocumentRequest, dict]]):
The request object. Request to create a ``Document``.
parent (:class:`str`):
Required. The name of the ``Corpus`` where this
``Document`` will be created. Example:
``corpora/my-corpus-123``
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
document (:class:`google.ai.generativelanguage_v1beta.types.Document`):
Required. The ``Document`` to create.
This corresponds to the ``document`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Document:
A Document is a collection of Chunks.
A Corpus can have a maximum of 10,000 Documents.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent, document])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.CreateDocumentRequest):
request = retriever_service.CreateDocumentRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
if document is not None:
request.document = document
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.create_document
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def get_document(
self,
request: Optional[Union[retriever_service.GetDocumentRequest, dict]] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Document:
r"""Gets information about a specific ``Document``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_get_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.GetDocumentRequest(
name="name_value",
)
# Make the request
response = await client.get_document(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.GetDocumentRequest, dict]]):
The request object. Request for getting information about a specific
``Document``.
name (:class:`str`):
Required. The name of the ``Document`` to retrieve.
Example: ``corpora/my-corpus-123/documents/the-doc-abc``
This corresponds to the ``name`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Document:
A Document is a collection of Chunks.
A Corpus can have a maximum of 10,000 Documents.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.GetDocumentRequest):
request = retriever_service.GetDocumentRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.get_document
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def update_document(
self,
request: Optional[Union[retriever_service.UpdateDocumentRequest, dict]] = None,
*,
document: Optional[retriever.Document] = None,
update_mask: Optional[field_mask_pb2.FieldMask] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Document:
r"""Updates a ``Document``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_update_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.UpdateDocumentRequest(
)
# Make the request
response = await client.update_document(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.UpdateDocumentRequest, dict]]):
The request object. Request to update a ``Document``.
document (:class:`google.ai.generativelanguage_v1beta.types.Document`):
Required. The ``Document`` to update.
This corresponds to the ``document`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`):
Required. The list of fields to update. Currently, this
only supports updating ``display_name`` and
``custom_metadata``.
This corresponds to the ``update_mask`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Document:
A Document is a collection of Chunks.
A Corpus can have a maximum of 10,000 Documents.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([document, update_mask])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.UpdateDocumentRequest):
request = retriever_service.UpdateDocumentRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if document is not None:
request.document = document
if update_mask is not None:
request.update_mask = update_mask
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.update_document
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata(
(("document.name", request.document.name),)
),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def delete_document(
self,
request: Optional[Union[retriever_service.DeleteDocumentRequest, dict]] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> None:
r"""Deletes a ``Document``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_delete_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.DeleteDocumentRequest(
name="name_value",
)
# Make the request
await client.delete_document(request=request)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.DeleteDocumentRequest, dict]]):
The request object. Request to delete a ``Document``.
name (:class:`str`):
Required. The resource name of the ``Document`` to
delete. Example:
``corpora/my-corpus-123/documents/the-doc-abc``
This corresponds to the ``name`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.DeleteDocumentRequest):
request = retriever_service.DeleteDocumentRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.delete_document
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] async def list_documents(
self,
request: Optional[Union[retriever_service.ListDocumentsRequest, dict]] = None,
*,
parent: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.ListDocumentsAsyncPager:
r"""Lists all ``Document``\ s in a ``Corpus``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_list_documents():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.ListDocumentsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_documents(request=request)
# Handle the response
async for response in page_result:
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.ListDocumentsRequest, dict]]):
The request object. Request for listing ``Document``\ s.
parent (:class:`str`):
Required. The name of the ``Corpus`` containing
``Document``\ s. Example: ``corpora/my-corpus-123``
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.services.retriever_service.pagers.ListDocumentsAsyncPager:
Response from ListDocuments containing a paginated list of Documents.
The Documents are sorted by ascending
document.create_time.
Iterating over this object will yield results and
resolve additional pages automatically.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.ListDocumentsRequest):
request = retriever_service.ListDocumentsRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.list_documents
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# This method is paged; wrap the response in a pager, which provides
# an `__aiter__` convenience method.
response = pagers.ListDocumentsAsyncPager(
method=rpc,
request=request,
response=response,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def query_document(
self,
request: Optional[Union[retriever_service.QueryDocumentRequest, dict]] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever_service.QueryDocumentResponse:
r"""Performs semantic search over a ``Document``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_query_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.QueryDocumentRequest(
name="name_value",
query="query_value",
)
# Make the request
response = await client.query_document(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.QueryDocumentRequest, dict]]):
The request object. Request for querying a ``Document``.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.QueryDocumentResponse:
Response from QueryDocument containing a list of
relevant chunks.
"""
# Create or coerce a protobuf request object.
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.QueryDocumentRequest):
request = retriever_service.QueryDocumentRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.query_document
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def create_chunk(
self,
request: Optional[Union[retriever_service.CreateChunkRequest, dict]] = None,
*,
parent: Optional[str] = None,
chunk: Optional[retriever.Chunk] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Chunk:
r"""Creates a ``Chunk``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_create_chunk():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
chunk = generativelanguage_v1beta.Chunk()
chunk.data.string_value = "string_value_value"
request = generativelanguage_v1beta.CreateChunkRequest(
parent="parent_value",
chunk=chunk,
)
# Make the request
response = await client.create_chunk(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.CreateChunkRequest, dict]]):
The request object. Request to create a ``Chunk``.
parent (:class:`str`):
Required. The name of the ``Document`` where this
``Chunk`` will be created. Example:
``corpora/my-corpus-123/documents/the-doc-abc``
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
chunk (:class:`google.ai.generativelanguage_v1beta.types.Chunk`):
Required. The ``Chunk`` to create.
This corresponds to the ``chunk`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Chunk:
A Chunk is a subpart of a Document that is treated as an independent unit
for the purposes of vector representation and
storage. A Corpus can have a maximum of 1 million
Chunks.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent, chunk])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.CreateChunkRequest):
request = retriever_service.CreateChunkRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
if chunk is not None:
request.chunk = chunk
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.create_chunk
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def batch_create_chunks(
self,
request: Optional[
Union[retriever_service.BatchCreateChunksRequest, dict]
] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever_service.BatchCreateChunksResponse:
r"""Batch create ``Chunk``\ s.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_batch_create_chunks():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
requests = generativelanguage_v1beta.CreateChunkRequest()
requests.parent = "parent_value"
requests.chunk.data.string_value = "string_value_value"
request = generativelanguage_v1beta.BatchCreateChunksRequest(
requests=requests,
)
# Make the request
response = await client.batch_create_chunks(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.BatchCreateChunksRequest, dict]]):
The request object. Request to batch create ``Chunk``\ s.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.BatchCreateChunksResponse:
Response from BatchCreateChunks containing a list of
created Chunks.
"""
# Create or coerce a protobuf request object.
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.BatchCreateChunksRequest):
request = retriever_service.BatchCreateChunksRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.batch_create_chunks
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def get_chunk(
self,
request: Optional[Union[retriever_service.GetChunkRequest, dict]] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Chunk:
r"""Gets information about a specific ``Chunk``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_get_chunk():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.GetChunkRequest(
name="name_value",
)
# Make the request
response = await client.get_chunk(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.GetChunkRequest, dict]]):
The request object. Request for getting information about a specific
``Chunk``.
name (:class:`str`):
Required. The name of the ``Chunk`` to retrieve.
Example:
``corpora/my-corpus-123/documents/the-doc-abc/chunks/some-chunk``
This corresponds to the ``name`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Chunk:
A Chunk is a subpart of a Document that is treated as an independent unit
for the purposes of vector representation and
storage. A Corpus can have a maximum of 1 million
Chunks.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.GetChunkRequest):
request = retriever_service.GetChunkRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.get_chunk
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def update_chunk(
self,
request: Optional[Union[retriever_service.UpdateChunkRequest, dict]] = None,
*,
chunk: Optional[retriever.Chunk] = None,
update_mask: Optional[field_mask_pb2.FieldMask] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever.Chunk:
r"""Updates a ``Chunk``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_update_chunk():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
chunk = generativelanguage_v1beta.Chunk()
chunk.data.string_value = "string_value_value"
request = generativelanguage_v1beta.UpdateChunkRequest(
chunk=chunk,
)
# Make the request
response = await client.update_chunk(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.UpdateChunkRequest, dict]]):
The request object. Request to update a ``Chunk``.
chunk (:class:`google.ai.generativelanguage_v1beta.types.Chunk`):
Required. The ``Chunk`` to update.
This corresponds to the ``chunk`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`):
Required. The list of fields to update. Currently, this
only supports updating ``custom_metadata`` and ``data``.
This corresponds to the ``update_mask`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.Chunk:
A Chunk is a subpart of a Document that is treated as an independent unit
for the purposes of vector representation and
storage. A Corpus can have a maximum of 1 million
Chunks.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([chunk, update_mask])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.UpdateChunkRequest):
request = retriever_service.UpdateChunkRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if chunk is not None:
request.chunk = chunk
if update_mask is not None:
request.update_mask = update_mask
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.update_chunk
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata(
(("chunk.name", request.chunk.name),)
),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def batch_update_chunks(
self,
request: Optional[
Union[retriever_service.BatchUpdateChunksRequest, dict]
] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> retriever_service.BatchUpdateChunksResponse:
r"""Batch update ``Chunk``\ s.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_batch_update_chunks():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
requests = generativelanguage_v1beta.UpdateChunkRequest()
requests.chunk.data.string_value = "string_value_value"
request = generativelanguage_v1beta.BatchUpdateChunksRequest(
requests=requests,
)
# Make the request
response = await client.batch_update_chunks(request=request)
# Handle the response
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.BatchUpdateChunksRequest, dict]]):
The request object. Request to batch update ``Chunk``\ s.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.types.BatchUpdateChunksResponse:
Response from BatchUpdateChunks containing a list of
updated Chunks.
"""
# Create or coerce a protobuf request object.
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.BatchUpdateChunksRequest):
request = retriever_service.BatchUpdateChunksRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.batch_update_chunks
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] async def delete_chunk(
self,
request: Optional[Union[retriever_service.DeleteChunkRequest, dict]] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> None:
r"""Deletes a ``Chunk``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_delete_chunk():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.DeleteChunkRequest(
name="name_value",
)
# Make the request
await client.delete_chunk(request=request)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.DeleteChunkRequest, dict]]):
The request object. Request to delete a ``Chunk``.
name (:class:`str`):
Required. The resource name of the ``Chunk`` to delete.
Example:
``corpora/my-corpus-123/documents/the-doc-abc/chunks/some-chunk``
This corresponds to the ``name`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([name])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.DeleteChunkRequest):
request = retriever_service.DeleteChunkRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.delete_chunk
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] async def batch_delete_chunks(
self,
request: Optional[
Union[retriever_service.BatchDeleteChunksRequest, dict]
] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> None:
r"""Batch delete ``Chunk``\ s.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_batch_delete_chunks():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
requests = generativelanguage_v1beta.DeleteChunkRequest()
requests.name = "name_value"
request = generativelanguage_v1beta.BatchDeleteChunksRequest(
requests=requests,
)
# Make the request
await client.batch_delete_chunks(request=request)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.BatchDeleteChunksRequest, dict]]):
The request object. Request to batch delete ``Chunk``\ s.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
"""
# Create or coerce a protobuf request object.
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.BatchDeleteChunksRequest):
request = retriever_service.BatchDeleteChunksRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.batch_delete_chunks
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] async def list_chunks(
self,
request: Optional[Union[retriever_service.ListChunksRequest, dict]] = None,
*,
parent: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.ListChunksAsyncPager:
r"""Lists all ``Chunk``\ s in a ``Document``.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta
async def sample_list_chunks():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceAsyncClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.ListChunksRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_chunks(request=request)
# Handle the response
async for response in page_result:
print(response)
Args:
request (Optional[Union[google.ai.generativelanguage_v1beta.types.ListChunksRequest, dict]]):
The request object. Request for listing ``Chunk``\ s.
parent (:class:`str`):
Required. The name of the ``Document`` containing
``Chunk``\ s. Example:
``corpora/my-corpus-123/documents/the-doc-abc``
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ai.generativelanguage_v1beta.services.retriever_service.pagers.ListChunksAsyncPager:
Response from ListChunks containing a paginated list of Chunks.
The Chunks are sorted by ascending chunk.create_time.
Iterating over this object will yield results and
resolve additional pages automatically.
"""
# Create or coerce a protobuf request object.
# - Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([parent])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, retriever_service.ListChunksRequest):
request = retriever_service.ListChunksRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._client._transport._wrapped_methods[
self._client._transport.list_chunks
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("parent", request.parent),)),
)
# Validate the universe domain.
self._client._validate_universe_domain()
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# This method is paged; wrap the response in a pager, which provides
# an `__aiter__` convenience method.
response = pagers.ListChunksAsyncPager(
method=rpc,
request=request,
response=response,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
async def __aenter__(self) -> "RetrieverServiceAsyncClient":
return self
async def __aexit__(self, exc_type, exc, tb):
await self.transport.close()
DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
gapic_version=package_version.__version__
)
__all__ = ("RetrieverServiceAsyncClient",)
