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.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 os
import re
from typing import (
Callable,
Dict,
Mapping,
MutableMapping,
MutableSequence,
Optional,
Sequence,
Tuple,
Type,
Union,
cast,
)
import warnings
from google.api_core import client_options as client_options_lib
from google.api_core import exceptions as core_exceptions
from google.api_core import gapic_v1
from google.api_core import retry as retries
from google.auth import credentials as ga_credentials # type: ignore
from google.auth.exceptions import MutualTLSChannelError # type: ignore
from google.auth.transport import mtls # type: ignore
from google.auth.transport.grpc import SslCredentials # 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.Retry, gapic_v1.method._MethodDefault, None]
except AttributeError: # pragma: NO COVER
OptionalRetry = Union[retries.Retry, 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 .transports.base import DEFAULT_CLIENT_INFO, RetrieverServiceTransport
from .transports.grpc import RetrieverServiceGrpcTransport
from .transports.grpc_asyncio import RetrieverServiceGrpcAsyncIOTransport
from .transports.rest import RetrieverServiceRestTransport
class RetrieverServiceClientMeta(type):
"""Metaclass for the RetrieverService client.
This provides class-level methods for building and retrieving
support objects (e.g. transport) without polluting the client instance
objects.
"""
_transport_registry = (
OrderedDict()
) # type: Dict[str, Type[RetrieverServiceTransport]]
_transport_registry["grpc"] = RetrieverServiceGrpcTransport
_transport_registry["grpc_asyncio"] = RetrieverServiceGrpcAsyncIOTransport
_transport_registry["rest"] = RetrieverServiceRestTransport
def get_transport_class(
cls,
label: Optional[str] = None,
) -> Type[RetrieverServiceTransport]:
"""Returns an appropriate transport class.
Args:
label: The name of the desired transport. If none is
provided, then the first transport in the registry is used.
Returns:
The transport class to use.
"""
# If a specific transport is requested, return that one.
if label:
return cls._transport_registry[label]
# No transport is requested; return the default (that is, the first one
# in the dictionary).
return next(iter(cls._transport_registry.values()))
[docs]class RetrieverServiceClient(metaclass=RetrieverServiceClientMeta):
"""An API for semantic search over a corpus of user uploaded
content.
"""
@staticmethod
def _get_default_mtls_endpoint(api_endpoint):
"""Converts api endpoint to mTLS endpoint.
Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to
"*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively.
Args:
api_endpoint (Optional[str]): the api endpoint to convert.
Returns:
str: converted mTLS api endpoint.
"""
if not api_endpoint:
return api_endpoint
mtls_endpoint_re = re.compile(
r"(?P<name>[^.]+)(?P<mtls>\.mtls)?(?P<sandbox>\.sandbox)?(?P<googledomain>\.googleapis\.com)?"
)
m = mtls_endpoint_re.match(api_endpoint)
name, mtls, sandbox, googledomain = m.groups()
if mtls or not googledomain:
return api_endpoint
if sandbox:
return api_endpoint.replace(
"sandbox.googleapis.com", "mtls.sandbox.googleapis.com"
)
return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com")
# Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead.
DEFAULT_ENDPOINT = "generativelanguage.googleapis.com"
DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore
DEFAULT_ENDPOINT
)
_DEFAULT_ENDPOINT_TEMPLATE = "generativelanguage.{UNIVERSE_DOMAIN}"
_DEFAULT_UNIVERSE = "googleapis.com"
[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:
RetrieverServiceClient: The constructed client.
"""
credentials = service_account.Credentials.from_service_account_info(info)
kwargs["credentials"] = credentials
return cls(*args, **kwargs)
[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:
RetrieverServiceClient: The constructed client.
"""
credentials = service_account.Credentials.from_service_account_file(filename)
kwargs["credentials"] = credentials
return cls(*args, **kwargs)
from_service_account_json = from_service_account_file
@property
def transport(self) -> RetrieverServiceTransport:
"""Returns the transport used by the client instance.
Returns:
RetrieverServiceTransport: The transport used by the client
instance.
"""
return self._transport
[docs] @staticmethod
def chunk_path(
corpus: str,
document: str,
chunk: str,
) -> str:
"""Returns a fully-qualified chunk string."""
return "corpora/{corpus}/documents/{document}/chunks/{chunk}".format(
corpus=corpus,
document=document,
chunk=chunk,
)
[docs] @staticmethod
def parse_chunk_path(path: str) -> Dict[str, str]:
"""Parses a chunk path into its component segments."""
m = re.match(
r"^corpora/(?P<corpus>.+?)/documents/(?P<document>.+?)/chunks/(?P<chunk>.+?)$",
path,
)
return m.groupdict() if m else {}
[docs] @staticmethod
def corpus_path(
corpus: str,
) -> str:
"""Returns a fully-qualified corpus string."""
return "corpora/{corpus}".format(
corpus=corpus,
)
[docs] @staticmethod
def parse_corpus_path(path: str) -> Dict[str, str]:
"""Parses a corpus path into its component segments."""
m = re.match(r"^corpora/(?P<corpus>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def document_path(
corpus: str,
document: str,
) -> str:
"""Returns a fully-qualified document string."""
return "corpora/{corpus}/documents/{document}".format(
corpus=corpus,
document=document,
)
[docs] @staticmethod
def parse_document_path(path: str) -> Dict[str, str]:
"""Parses a document path into its component segments."""
m = re.match(r"^corpora/(?P<corpus>.+?)/documents/(?P<document>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_billing_account_path(
billing_account: str,
) -> str:
"""Returns a fully-qualified billing_account string."""
return "billingAccounts/{billing_account}".format(
billing_account=billing_account,
)
[docs] @staticmethod
def parse_common_billing_account_path(path: str) -> Dict[str, str]:
"""Parse a billing_account path into its component segments."""
m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_folder_path(
folder: str,
) -> str:
"""Returns a fully-qualified folder string."""
return "folders/{folder}".format(
folder=folder,
)
[docs] @staticmethod
def parse_common_folder_path(path: str) -> Dict[str, str]:
"""Parse a folder path into its component segments."""
m = re.match(r"^folders/(?P<folder>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_organization_path(
organization: str,
) -> str:
"""Returns a fully-qualified organization string."""
return "organizations/{organization}".format(
organization=organization,
)
[docs] @staticmethod
def parse_common_organization_path(path: str) -> Dict[str, str]:
"""Parse a organization path into its component segments."""
m = re.match(r"^organizations/(?P<organization>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_project_path(
project: str,
) -> str:
"""Returns a fully-qualified project string."""
return "projects/{project}".format(
project=project,
)
[docs] @staticmethod
def parse_common_project_path(path: str) -> Dict[str, str]:
"""Parse a project path into its component segments."""
m = re.match(r"^projects/(?P<project>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_location_path(
project: str,
location: str,
) -> str:
"""Returns a fully-qualified location string."""
return "projects/{project}/locations/{location}".format(
project=project,
location=location,
)
[docs] @staticmethod
def parse_common_location_path(path: str) -> Dict[str, str]:
"""Parse a location path into its component segments."""
m = re.match(r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)$", path)
return m.groupdict() if m else {}
[docs] @classmethod
def get_mtls_endpoint_and_cert_source(
cls, client_options: Optional[client_options_lib.ClientOptions] = None
):
"""Deprecated. 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.
"""
warnings.warn(
"get_mtls_endpoint_and_cert_source is deprecated. Use the api_endpoint property instead.",
DeprecationWarning,
)
if client_options is None:
client_options = client_options_lib.ClientOptions()
use_client_cert = os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")
use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto")
if use_client_cert not in ("true", "false"):
raise ValueError(
"Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
)
if use_mtls_endpoint not in ("auto", "never", "always"):
raise MutualTLSChannelError(
"Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
)
# Figure out the client cert source to use.
client_cert_source = None
if use_client_cert == "true":
if client_options.client_cert_source:
client_cert_source = client_options.client_cert_source
elif mtls.has_default_client_cert_source():
client_cert_source = mtls.default_client_cert_source()
# Figure out which api endpoint to use.
if client_options.api_endpoint is not None:
api_endpoint = client_options.api_endpoint
elif use_mtls_endpoint == "always" or (
use_mtls_endpoint == "auto" and client_cert_source
):
api_endpoint = cls.DEFAULT_MTLS_ENDPOINT
else:
api_endpoint = cls.DEFAULT_ENDPOINT
return api_endpoint, client_cert_source
@staticmethod
def _read_environment_variables():
"""Returns the environment variables used by the client.
Returns:
Tuple[bool, str, str]: returns the GOOGLE_API_USE_CLIENT_CERTIFICATE,
GOOGLE_API_USE_MTLS_ENDPOINT, and GOOGLE_CLOUD_UNIVERSE_DOMAIN environment variables.
Raises:
ValueError: If GOOGLE_API_USE_CLIENT_CERTIFICATE is not
any of ["true", "false"].
google.auth.exceptions.MutualTLSChannelError: If GOOGLE_API_USE_MTLS_ENDPOINT
is not any of ["auto", "never", "always"].
"""
use_client_cert = os.getenv(
"GOOGLE_API_USE_CLIENT_CERTIFICATE", "false"
).lower()
use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto").lower()
universe_domain_env = os.getenv("GOOGLE_CLOUD_UNIVERSE_DOMAIN")
if use_client_cert not in ("true", "false"):
raise ValueError(
"Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
)
if use_mtls_endpoint not in ("auto", "never", "always"):
raise MutualTLSChannelError(
"Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
)
return use_client_cert == "true", use_mtls_endpoint, universe_domain_env
@staticmethod
def _get_client_cert_source(provided_cert_source, use_cert_flag):
"""Return the client cert source to be used by the client.
Args:
provided_cert_source (bytes): The client certificate source provided.
use_cert_flag (bool): A flag indicating whether to use the client certificate.
Returns:
bytes or None: The client cert source to be used by the client.
"""
client_cert_source = None
if use_cert_flag:
if provided_cert_source:
client_cert_source = provided_cert_source
elif mtls.has_default_client_cert_source():
client_cert_source = mtls.default_client_cert_source()
return client_cert_source
@staticmethod
def _get_api_endpoint(
api_override, client_cert_source, universe_domain, use_mtls_endpoint
):
"""Return the API endpoint used by the client.
Args:
api_override (str): The API endpoint override. If specified, this is always
the return value of this function and the other arguments are not used.
client_cert_source (bytes): The client certificate source used by the client.
universe_domain (str): The universe domain used by the client.
use_mtls_endpoint (str): How to use the mTLS endpoint, which depends also on the other parameters.
Possible values are "always", "auto", or "never".
Returns:
str: The API endpoint to be used by the client.
"""
if api_override is not None:
api_endpoint = api_override
elif use_mtls_endpoint == "always" or (
use_mtls_endpoint == "auto" and client_cert_source
):
_default_universe = RetrieverServiceClient._DEFAULT_UNIVERSE
if universe_domain != _default_universe:
raise MutualTLSChannelError(
f"mTLS is not supported in any universe other than {_default_universe}."
)
api_endpoint = RetrieverServiceClient.DEFAULT_MTLS_ENDPOINT
else:
api_endpoint = RetrieverServiceClient._DEFAULT_ENDPOINT_TEMPLATE.format(
UNIVERSE_DOMAIN=universe_domain
)
return api_endpoint
@staticmethod
def _get_universe_domain(
client_universe_domain: Optional[str], universe_domain_env: Optional[str]
) -> str:
"""Return the universe domain used by the client.
Args:
client_universe_domain (Optional[str]): The universe domain configured via the client options.
universe_domain_env (Optional[str]): The universe domain configured via the "GOOGLE_CLOUD_UNIVERSE_DOMAIN" environment variable.
Returns:
str: The universe domain to be used by the client.
Raises:
ValueError: If the universe domain is an empty string.
"""
universe_domain = RetrieverServiceClient._DEFAULT_UNIVERSE
if client_universe_domain is not None:
universe_domain = client_universe_domain
elif universe_domain_env is not None:
universe_domain = universe_domain_env
if len(universe_domain.strip()) == 0:
raise ValueError("Universe Domain cannot be an empty string.")
return universe_domain
def _validate_universe_domain(self):
"""Validates client's and credentials' universe domains are consistent.
Returns:
bool: True iff the configured universe domain is valid.
Raises:
ValueError: If the configured universe domain is not valid.
"""
# NOTE (b/349488459): universe validation is disabled until further notice.
return True
@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._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._universe_domain
def __init__(
self,
*,
credentials: Optional[ga_credentials.Credentials] = None,
transport: Optional[
Union[
str, RetrieverServiceTransport, Callable[..., RetrieverServiceTransport]
]
] = None,
client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None,
client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
) -> None:
"""Instantiates the retriever service 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.
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 the ``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_options = client_options
if isinstance(self._client_options, dict):
self._client_options = client_options_lib.from_dict(self._client_options)
if self._client_options is None:
self._client_options = client_options_lib.ClientOptions()
self._client_options = cast(
client_options_lib.ClientOptions, self._client_options
)
universe_domain_opt = getattr(self._client_options, "universe_domain", None)
(
self._use_client_cert,
self._use_mtls_endpoint,
self._universe_domain_env,
) = RetrieverServiceClient._read_environment_variables()
self._client_cert_source = RetrieverServiceClient._get_client_cert_source(
self._client_options.client_cert_source, self._use_client_cert
)
self._universe_domain = RetrieverServiceClient._get_universe_domain(
universe_domain_opt, self._universe_domain_env
)
self._api_endpoint = None # updated below, depending on `transport`
# Initialize the universe domain validation.
self._is_universe_domain_valid = False
api_key_value = getattr(self._client_options, "api_key", None)
if api_key_value and credentials:
raise ValueError(
"client_options.api_key and credentials are mutually exclusive"
)
# Save or instantiate the transport.
# Ordinarily, we provide the transport, but allowing a custom transport
# instance provides an extensibility point for unusual situations.
transport_provided = isinstance(transport, RetrieverServiceTransport)
if transport_provided:
# transport is a RetrieverServiceTransport instance.
if credentials or self._client_options.credentials_file or api_key_value:
raise ValueError(
"When providing a transport instance, "
"provide its credentials directly."
)
if self._client_options.scopes:
raise ValueError(
"When providing a transport instance, provide its scopes "
"directly."
)
self._transport = cast(RetrieverServiceTransport, transport)
self._api_endpoint = self._transport.host
self._api_endpoint = (
self._api_endpoint
or RetrieverServiceClient._get_api_endpoint(
self._client_options.api_endpoint,
self._client_cert_source,
self._universe_domain,
self._use_mtls_endpoint,
)
)
if not transport_provided:
import google.auth._default # type: ignore
if api_key_value and hasattr(
google.auth._default, "get_api_key_credentials"
):
credentials = google.auth._default.get_api_key_credentials(
api_key_value
)
transport_init: Union[
Type[RetrieverServiceTransport],
Callable[..., RetrieverServiceTransport],
] = (
RetrieverServiceClient.get_transport_class(transport)
if isinstance(transport, str) or transport is None
else cast(Callable[..., RetrieverServiceTransport], transport)
)
# initialize with the provided callable or the passed in class
self._transport = transport_init(
credentials=credentials,
credentials_file=self._client_options.credentials_file,
host=self._api_endpoint,
scopes=self._client_options.scopes,
client_cert_source_for_mtls=self._client_cert_source,
quota_project_id=self._client_options.quota_project_id,
client_info=client_info,
always_use_jwt_access=True,
api_audience=self._client_options.api_audience,
)
[docs] 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
def sample_create_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.CreateCorpusRequest(
)
# Make the request
response = client.create_corpus(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.CreateCorpusRequest, dict]):
The request object. Request to create a ``Corpus``.
corpus (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.Retry): 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._transport._wrapped_methods[self._transport.create_corpus]
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_get_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.GetCorpusRequest(
name="name_value",
)
# Make the request
response = client.get_corpus(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.GetCorpusRequest, dict]):
The request object. Request for getting information about a specific
``Corpus``.
name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_update_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.UpdateCorpusRequest(
)
# Make the request
response = client.update_corpus(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.UpdateCorpusRequest, dict]):
The request object. Request to update a ``Corpus``.
corpus (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 (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_delete_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.DeleteCorpusRequest(
name="name_value",
)
# Make the request
client.delete_corpus(request=request)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.DeleteCorpusRequest, dict]):
The request object. Request to delete a ``Corpus``.
name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] 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.ListCorporaPager:
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
def sample_list_corpora():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.ListCorporaRequest(
)
# Make the request
page_result = client.list_corpora(request=request)
# Handle the response
for response in page_result:
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.ListCorporaRequest, dict]):
The request object. Request for listing ``Corpora``.
retry (google.api_core.retry.Retry): 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.ListCorporaPager:
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._transport._wrapped_methods[self._transport.list_corpora]
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# This method is paged; wrap the response in a pager, which provides
# an `__iter__` convenience method.
response = pagers.ListCorporaPager(
method=rpc,
request=request,
response=response,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_query_corpus():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.QueryCorpusRequest(
name="name_value",
query="query_value",
)
# Make the request
response = client.query_corpus(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.QueryCorpusRequest, dict]):
The request object. Request for querying a ``Corpus``.
retry (google.api_core.retry.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_create_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.CreateDocumentRequest(
parent="parent_value",
)
# Make the request
response = client.create_document(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.CreateDocumentRequest, dict]):
The request object. Request to create a ``Document``.
parent (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 (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_get_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.GetDocumentRequest(
name="name_value",
)
# Make the request
response = client.get_document(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.GetDocumentRequest, dict]):
The request object. Request for getting information about a specific
``Document``.
name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_update_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.UpdateDocumentRequest(
)
# Make the request
response = client.update_document(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.UpdateDocumentRequest, dict]):
The request object. Request to update a ``Document``.
document (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 (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_delete_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.DeleteDocumentRequest(
name="name_value",
)
# Make the request
client.delete_document(request=request)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.DeleteDocumentRequest, dict]):
The request object. Request to delete a ``Document``.
name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] 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.ListDocumentsPager:
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
def sample_list_documents():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.ListDocumentsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_documents(request=request)
# Handle the response
for response in page_result:
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.ListDocumentsRequest, dict]):
The request object. Request for listing ``Document``\ s.
parent (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.Retry): 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.ListDocumentsPager:
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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# This method is paged; wrap the response in a pager, which provides
# an `__iter__` convenience method.
response = pagers.ListDocumentsPager(
method=rpc,
request=request,
response=response,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_query_document():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.QueryDocumentRequest(
name="name_value",
query="query_value",
)
# Make the request
response = client.query_document(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.QueryDocumentRequest, dict]):
The request object. Request for querying a ``Document``.
retry (google.api_core.retry.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_create_chunk():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# 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 = client.create_chunk(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.CreateChunkRequest, dict]):
The request object. Request to create a ``Chunk``.
parent (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 (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_batch_create_chunks():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# 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 = client.batch_create_chunks(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.BatchCreateChunksRequest, dict]):
The request object. Request to batch create ``Chunk``\ s.
retry (google.api_core.retry.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_get_chunk():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.GetChunkRequest(
name="name_value",
)
# Make the request
response = client.get_chunk(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.GetChunkRequest, dict]):
The request object. Request for getting information about a specific
``Chunk``.
name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_update_chunk():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# 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 = client.update_chunk(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.UpdateChunkRequest, dict]):
The request object. Request to update a ``Chunk``.
chunk (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 (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_batch_update_chunks():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# 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 = client.batch_update_chunks(request=request)
# Handle the response
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.BatchUpdateChunksRequest, dict]):
The request object. Request to batch update ``Chunk``\ s.
retry (google.api_core.retry.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] 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
def sample_delete_chunk():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.DeleteChunkRequest(
name="name_value",
)
# Make the request
client.delete_chunk(request=request)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.DeleteChunkRequest, dict]):
The request object. Request to delete a ``Chunk``.
name (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.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] 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
def sample_batch_delete_chunks():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
requests = generativelanguage_v1beta.DeleteChunkRequest()
requests.name = "name_value"
request = generativelanguage_v1beta.BatchDeleteChunksRequest(
requests=requests,
)
# Make the request
client.batch_delete_chunks(request=request)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.BatchDeleteChunksRequest, dict]):
The request object. Request to batch delete ``Chunk``\ s.
retry (google.api_core.retry.Retry): 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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] 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.ListChunksPager:
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
def sample_list_chunks():
# Create a client
client = generativelanguage_v1beta.RetrieverServiceClient()
# Initialize request argument(s)
request = generativelanguage_v1beta.ListChunksRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_chunks(request=request)
# Handle the response
for response in page_result:
print(response)
Args:
request (Union[google.ai.generativelanguage_v1beta.types.ListChunksRequest, dict]):
The request object. Request for listing ``Chunk``\ s.
parent (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.Retry): 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.ListChunksPager:
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._transport._wrapped_methods[self._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._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# This method is paged; wrap the response in a pager, which provides
# an `__iter__` convenience method.
response = pagers.ListChunksPager(
method=rpc,
request=request,
response=response,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
def __enter__(self) -> "RetrieverServiceClient":
return self
[docs] def __exit__(self, type, value, traceback):
"""Releases underlying transport's resources.
.. warning::
ONLY use as a context manager if the transport is NOT shared
with other clients! Exiting the with block will CLOSE the transport
and may cause errors in other clients!
"""
self.transport.close()
DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
gapic_version=package_version.__version__
)
__all__ = ("RetrieverServiceClient",)
