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// This file is @generated by prost-build.
/// Permission resource grants user, group or the rest of the world access to the
/// PaLM API resource (e.g. a tuned model, file).
///
/// A role is a collection of permitted operations that allows users to perform
/// specific actions on PaLM API resources. To make them available to users,
/// groups, or service accounts, you assign roles. When you assign a role, you
/// grant permissions that the role contains.
///
/// There are three concentric roles. Each role is a superset of the previous
/// role's permitted operations:
/// - reader can use the resource (e.g. tuned model) for inference
/// - writer has reader's permissions and additionally can edit and share
/// - owner has writer's permissions and additionally can delete
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Permission {
/// Output only. The permission name. A unique name will be generated on
/// create. Example: tunedModels/{tuned_model}permssions/{permission} Output
/// only.
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
/// Required. Immutable. The type of the grantee.
#[prost(enumeration = "permission::GranteeType", optional, tag = "2")]
pub grantee_type: ::core::option::Option<i32>,
/// Optional. Immutable. The email address of the user of group which this
/// permission refers. Field is not set when permission's grantee type is
/// EVERYONE.
#[prost(string, optional, tag = "3")]
pub email_address: ::core::option::Option<::prost::alloc::string::String>,
/// Required. The role granted by this permission.
#[prost(enumeration = "permission::Role", optional, tag = "4")]
pub role: ::core::option::Option<i32>,
}
/// Nested message and enum types in `Permission`.
pub mod permission {
/// Defines types of the grantee of this permission.
#[derive(
Clone,
Copy,
Debug,
PartialEq,
Eq,
Hash,
PartialOrd,
Ord,
::prost::Enumeration
)]
#[repr(i32)]
pub enum GranteeType {
/// The default value. This value is unused.
Unspecified = 0,
/// Represents a user. When set, you must provide email_address for the user.
User = 1,
/// Represents a group. When set, you must provide email_address for the
/// group.
Group = 2,
/// Represents access to everyone. No extra information is required.
Everyone = 3,
}
impl GranteeType {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
GranteeType::Unspecified => "GRANTEE_TYPE_UNSPECIFIED",
GranteeType::User => "USER",
GranteeType::Group => "GROUP",
GranteeType::Everyone => "EVERYONE",
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"GRANTEE_TYPE_UNSPECIFIED" => Some(Self::Unspecified),
"USER" => Some(Self::User),
"GROUP" => Some(Self::Group),
"EVERYONE" => Some(Self::Everyone),
_ => None,
}
}
}
/// Defines the role granted by this permission.
#[derive(
Clone,
Copy,
Debug,
PartialEq,
Eq,
Hash,
PartialOrd,
Ord,
::prost::Enumeration
)]
#[repr(i32)]
pub enum Role {
/// The default value. This value is unused.
Unspecified = 0,
/// Owner can use, update, share and delete the resource.
Owner = 1,
/// Writer can use, update and share the resource.
Writer = 2,
/// Reader can use the resource.
Reader = 3,
}
impl Role {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
Role::Unspecified => "ROLE_UNSPECIFIED",
Role::Owner => "OWNER",
Role::Writer => "WRITER",
Role::Reader => "READER",
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"ROLE_UNSPECIFIED" => Some(Self::Unspecified),
"OWNER" => Some(Self::Owner),
"WRITER" => Some(Self::Writer),
"READER" => Some(Self::Reader),
_ => None,
}
}
}
}
/// Information about a Generative Language Model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Model {
/// Required. The resource name of the `Model`.
///
/// Format: `models/{model}` with a `{model}` naming convention of:
///
/// * "{base_model_id}-{version}"
///
/// Examples:
///
/// * `models/chat-bison-001`
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
/// Required. The name of the base model, pass this to the generation request.
///
/// Examples:
///
/// * `chat-bison`
#[prost(string, tag = "2")]
pub base_model_id: ::prost::alloc::string::String,
/// Required. The version number of the model.
///
/// This represents the major version
#[prost(string, tag = "3")]
pub version: ::prost::alloc::string::String,
/// The human-readable name of the model. E.g. "Chat Bison".
///
/// The name can be up to 128 characters long and can consist of any UTF-8
/// characters.
#[prost(string, tag = "4")]
pub display_name: ::prost::alloc::string::String,
/// A short description of the model.
#[prost(string, tag = "5")]
pub description: ::prost::alloc::string::String,
/// Maximum number of input tokens allowed for this model.
#[prost(int32, tag = "6")]
pub input_token_limit: i32,
/// Maximum number of output tokens available for this model.
#[prost(int32, tag = "7")]
pub output_token_limit: i32,
/// The model's supported generation methods.
///
/// The method names are defined as Pascal case
/// strings, such as `generateMessage` which correspond to API methods.
#[prost(string, repeated, tag = "8")]
pub supported_generation_methods: ::prost::alloc::vec::Vec<
::prost::alloc::string::String,
>,
/// Controls the randomness of the output.
///
/// Values can range over `\[0.0,1.0\]`, inclusive. A value closer to `1.0` will
/// produce responses that are more varied, while a value closer to `0.0` will
/// typically result in less surprising responses from the model.
/// This value specifies default to be used by the backend while making the
/// call to the model.
#[prost(float, optional, tag = "9")]
pub temperature: ::core::option::Option<f32>,
/// For Nucleus sampling.
///
/// Nucleus sampling considers the smallest set of tokens whose probability
/// sum is at least `top_p`.
/// This value specifies default to be used by the backend while making the
/// call to the model.
#[prost(float, optional, tag = "10")]
pub top_p: ::core::option::Option<f32>,
/// For Top-k sampling.
///
/// Top-k sampling considers the set of `top_k` most probable tokens.
/// This value specifies default to be used by the backend while making the
/// call to the model.
#[prost(int32, optional, tag = "11")]
pub top_k: ::core::option::Option<i32>,
}
/// A fine-tuned model created using ModelService.CreateTunedModel.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct TunedModel {
/// Output only. The tuned model name. A unique name will be generated on
/// create. Example: `tunedModels/az2mb0bpw6i` If display_name is set on
/// create, the id portion of the name will be set by concatenating the words
/// of the display_name with hyphens and adding a random portion for
/// uniqueness. Example:
/// display_name = "Sentence Translator"
/// name = "tunedModels/sentence-translator-u3b7m"
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
/// Optional. The name to display for this model in user interfaces.
/// The display name must be up to 40 characters including spaces.
#[prost(string, tag = "5")]
pub display_name: ::prost::alloc::string::String,
/// Optional. A short description of this model.
#[prost(string, tag = "6")]
pub description: ::prost::alloc::string::String,
/// Optional. Controls the randomness of the output.
///
/// Values can range over `\[0.0,1.0\]`, inclusive. A value closer to `1.0` will
/// produce responses that are more varied, while a value closer to `0.0` will
/// typically result in less surprising responses from the model.
///
/// This value specifies default to be the one used by the base model while
/// creating the model.
#[prost(float, optional, tag = "11")]
pub temperature: ::core::option::Option<f32>,
/// Optional. For Nucleus sampling.
///
/// Nucleus sampling considers the smallest set of tokens whose probability
/// sum is at least `top_p`.
///
/// This value specifies default to be the one used by the base model while
/// creating the model.
#[prost(float, optional, tag = "12")]
pub top_p: ::core::option::Option<f32>,
/// Optional. For Top-k sampling.
///
/// Top-k sampling considers the set of `top_k` most probable tokens.
/// This value specifies default to be used by the backend while making the
/// call to the model.
///
/// This value specifies default to be the one used by the base model while
/// creating the model.
#[prost(int32, optional, tag = "13")]
pub top_k: ::core::option::Option<i32>,
/// Output only. The state of the tuned model.
#[prost(enumeration = "tuned_model::State", tag = "7")]
pub state: i32,
/// Output only. The timestamp when this model was created.
#[prost(message, optional, tag = "8")]
pub create_time: ::core::option::Option<::prost_types::Timestamp>,
/// Output only. The timestamp when this model was updated.
#[prost(message, optional, tag = "9")]
pub update_time: ::core::option::Option<::prost_types::Timestamp>,
/// Required. The tuning task that creates the tuned model.
#[prost(message, optional, tag = "10")]
pub tuning_task: ::core::option::Option<TuningTask>,
/// The model used as the starting point for tuning.
#[prost(oneof = "tuned_model::SourceModel", tags = "3, 4")]
pub source_model: ::core::option::Option<tuned_model::SourceModel>,
}
/// Nested message and enum types in `TunedModel`.
pub mod tuned_model {
/// The state of the tuned model.
#[derive(
Clone,
Copy,
Debug,
PartialEq,
Eq,
Hash,
PartialOrd,
Ord,
::prost::Enumeration
)]
#[repr(i32)]
pub enum State {
/// The default value. This value is unused.
Unspecified = 0,
/// The model is being created.
Creating = 1,
/// The model is ready to be used.
Active = 2,
/// The model failed to be created.
Failed = 3,
}
impl State {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
State::Unspecified => "STATE_UNSPECIFIED",
State::Creating => "CREATING",
State::Active => "ACTIVE",
State::Failed => "FAILED",
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"STATE_UNSPECIFIED" => Some(Self::Unspecified),
"CREATING" => Some(Self::Creating),
"ACTIVE" => Some(Self::Active),
"FAILED" => Some(Self::Failed),
_ => None,
}
}
}
/// The model used as the starting point for tuning.
#[derive(Clone, PartialEq, ::prost::Oneof)]
pub enum SourceModel {
/// Optional. TunedModel to use as the starting point for training the new
/// model.
#[prost(message, tag = "3")]
TunedModelSource(super::TunedModelSource),
/// Immutable. The name of the `Model` to tune.
/// Example: `models/text-bison-001`
#[prost(string, tag = "4")]
BaseModel(::prost::alloc::string::String),
}
}
/// Tuned model as a source for training a new model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct TunedModelSource {
/// Immutable. The name of the `TunedModel` to use as the starting point for
/// training the new model.
/// Example: `tunedModels/my-tuned-model`
#[prost(string, tag = "1")]
pub tuned_model: ::prost::alloc::string::String,
/// Output only. The name of the base `Model` this `TunedModel` was tuned from.
/// Example: `models/text-bison-001`
#[prost(string, tag = "2")]
pub base_model: ::prost::alloc::string::String,
}
/// Tuning tasks that create tuned models.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct TuningTask {
/// Output only. The timestamp when tuning this model started.
#[prost(message, optional, tag = "1")]
pub start_time: ::core::option::Option<::prost_types::Timestamp>,
/// Output only. The timestamp when tuning this model completed.
#[prost(message, optional, tag = "2")]
pub complete_time: ::core::option::Option<::prost_types::Timestamp>,
/// Output only. Metrics collected during tuning.
#[prost(message, repeated, tag = "3")]
pub snapshots: ::prost::alloc::vec::Vec<TuningSnapshot>,
/// Required. Input only. Immutable. The model training data.
#[prost(message, optional, tag = "4")]
pub training_data: ::core::option::Option<Dataset>,
/// Immutable. Hyperparameters controlling the tuning process. If not provided,
/// default values will be used.
#[prost(message, optional, tag = "5")]
pub hyperparameters: ::core::option::Option<Hyperparameters>,
}
/// Hyperparameters controlling the tuning process.
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct Hyperparameters {
/// Immutable. The number of training epochs. An epoch is one pass through the
/// training data. If not set, a default of 10 will be used.
#[prost(int32, optional, tag = "14")]
pub epoch_count: ::core::option::Option<i32>,
/// Immutable. The batch size hyperparameter for tuning.
/// If not set, a default of 16 or 64 will be used based on the number of
/// training examples.
#[prost(int32, optional, tag = "15")]
pub batch_size: ::core::option::Option<i32>,
/// Immutable. The learning rate hyperparameter for tuning.
/// If not set, a default of 0.0002 or 0.002 will be calculated based on the
/// number of training examples.
#[prost(float, optional, tag = "16")]
pub learning_rate: ::core::option::Option<f32>,
}
/// Dataset for training or validation.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Dataset {
/// Inline data or a reference to the data.
#[prost(oneof = "dataset::Dataset", tags = "1")]
pub dataset: ::core::option::Option<dataset::Dataset>,
}
/// Nested message and enum types in `Dataset`.
pub mod dataset {
/// Inline data or a reference to the data.
#[derive(Clone, PartialEq, ::prost::Oneof)]
pub enum Dataset {
/// Optional. Inline examples.
#[prost(message, tag = "1")]
Examples(super::TuningExamples),
}
}
/// A set of tuning examples. Can be training or validatation data.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct TuningExamples {
/// Required. The examples. Example input can be for text or discuss, but all
/// examples in a set must be of the same type.
#[prost(message, repeated, tag = "1")]
pub examples: ::prost::alloc::vec::Vec<TuningExample>,
}
/// A single example for tuning.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct TuningExample {
/// Required. The expected model output.
#[prost(string, tag = "3")]
pub output: ::prost::alloc::string::String,
/// The input to the model for this example.
#[prost(oneof = "tuning_example::ModelInput", tags = "1")]
pub model_input: ::core::option::Option<tuning_example::ModelInput>,
}
/// Nested message and enum types in `TuningExample`.
pub mod tuning_example {
/// The input to the model for this example.
#[derive(Clone, PartialEq, ::prost::Oneof)]
pub enum ModelInput {
/// Optional. Text model input.
#[prost(string, tag = "1")]
TextInput(::prost::alloc::string::String),
}
}
/// Record for a single tuning step.
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct TuningSnapshot {
/// Output only. The tuning step.
#[prost(int32, tag = "1")]
pub step: i32,
/// Output only. The epoch this step was part of.
#[prost(int32, tag = "2")]
pub epoch: i32,
/// Output only. The mean loss of the training examples for this step.
#[prost(float, tag = "3")]
pub mean_loss: f32,
/// Output only. The timestamp when this metric was computed.
#[prost(message, optional, tag = "4")]
pub compute_time: ::core::option::Option<::prost_types::Timestamp>,
}
/// Request for getting information about a specific Model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct GetModelRequest {
/// Required. The resource name of the model.
///
/// This name should match a model name returned by the `ListModels` method.
///
/// Format: `models/{model}`
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
}
/// Request for listing all Models.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ListModelsRequest {
/// The maximum number of `Models` to return (per page).
///
/// The service may return fewer models.
/// If unspecified, at most 50 models will be returned per page.
/// This method returns at most 1000 models per page, even if you pass a larger
/// page_size.
#[prost(int32, tag = "2")]
pub page_size: i32,
/// A page token, received from a previous `ListModels` call.
///
/// Provide the `page_token` returned by one request as an argument to the next
/// request to retrieve the next page.
///
/// When paginating, all other parameters provided to `ListModels` must match
/// the call that provided the page token.
#[prost(string, tag = "3")]
pub page_token: ::prost::alloc::string::String,
}
/// Response from `ListModel` containing a paginated list of Models.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ListModelsResponse {
/// The returned Models.
#[prost(message, repeated, tag = "1")]
pub models: ::prost::alloc::vec::Vec<Model>,
/// A token, which can be sent as `page_token` to retrieve the next page.
///
/// If this field is omitted, there are no more pages.
#[prost(string, tag = "2")]
pub next_page_token: ::prost::alloc::string::String,
}
/// Request for getting information about a specific Model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct GetTunedModelRequest {
/// Required. The resource name of the model.
///
/// Format: `tunedModels/my-model-id`
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
}
/// Request for listing TunedModels.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ListTunedModelsRequest {
/// Optional. The maximum number of `TunedModels` to return (per page).
/// The service may return fewer tuned models.
///
/// If unspecified, at most 10 tuned models will be returned.
/// This method returns at most 1000 models per page, even if you pass a larger
/// page_size.
#[prost(int32, tag = "1")]
pub page_size: i32,
/// Optional. A page token, received from a previous `ListTunedModels` call.
///
/// Provide the `page_token` returned by one request as an argument to the next
/// request to retrieve the next page.
///
/// When paginating, all other parameters provided to `ListTunedModels`
/// must match the call that provided the page token.
#[prost(string, tag = "2")]
pub page_token: ::prost::alloc::string::String,
}
/// Response from `ListTunedModels` containing a paginated list of Models.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ListTunedModelsResponse {
/// The returned Models.
#[prost(message, repeated, tag = "1")]
pub tuned_models: ::prost::alloc::vec::Vec<TunedModel>,
/// A token, which can be sent as `page_token` to retrieve the next page.
///
/// If this field is omitted, there are no more pages.
#[prost(string, tag = "2")]
pub next_page_token: ::prost::alloc::string::String,
}
/// Request to create a TunedModel.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct CreateTunedModelRequest {
/// Optional. The unique id for the tuned model if specified.
/// This value should be up to 40 characters, the first character must be a
/// letter, the last could be a letter or a number. The id must match the
/// regular expression: [a-z](\[a-z0-9-\]{0,38}\[a-z0-9\])?.
#[prost(string, optional, tag = "1")]
pub tuned_model_id: ::core::option::Option<::prost::alloc::string::String>,
/// Required. The tuned model to create.
#[prost(message, optional, tag = "2")]
pub tuned_model: ::core::option::Option<TunedModel>,
}
/// Metadata about the state and progress of creating a tuned model returned from
/// the long-running operation
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct CreateTunedModelMetadata {
/// Name of the tuned model associated with the tuning operation.
#[prost(string, tag = "5")]
pub tuned_model: ::prost::alloc::string::String,
/// The total number of tuning steps.
#[prost(int32, tag = "1")]
pub total_steps: i32,
/// The number of steps completed.
#[prost(int32, tag = "2")]
pub completed_steps: i32,
/// The completed percentage for the tuning operation.
#[prost(float, tag = "3")]
pub completed_percent: f32,
/// Metrics collected during tuning.
#[prost(message, repeated, tag = "4")]
pub snapshots: ::prost::alloc::vec::Vec<TuningSnapshot>,
}
/// Request to update a TunedModel.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct UpdateTunedModelRequest {
/// Required. The tuned model to update.
#[prost(message, optional, tag = "1")]
pub tuned_model: ::core::option::Option<TunedModel>,
/// Required. The list of fields to update.
#[prost(message, optional, tag = "2")]
pub update_mask: ::core::option::Option<::prost_types::FieldMask>,
}
/// Request to delete a TunedModel.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct DeleteTunedModelRequest {
/// Required. The resource name of the model.
/// Format: `tunedModels/my-model-id`
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
}
/// Generated client implementations.
pub mod model_service_client {
#![allow(unused_variables, dead_code, missing_docs, clippy::let_unit_value)]
use tonic::codegen::*;
use tonic::codegen::http::Uri;
/// Provides methods for getting metadata information about Generative Models.
#[derive(Debug, Clone)]
pub struct ModelServiceClient<T> {
inner: tonic::client::Grpc<T>,
}
impl<T> ModelServiceClient<T>
where
T: tonic::client::GrpcService<tonic::body::BoxBody>,
T::Error: Into<StdError>,
T::ResponseBody: Body<Data = Bytes> + std::marker::Send + 'static,
<T::ResponseBody as Body>::Error: Into<StdError> + std::marker::Send,
{
pub fn new(inner: T) -> Self {
let inner = tonic::client::Grpc::new(inner);
Self { inner }
}
pub fn with_origin(inner: T, origin: Uri) -> Self {
let inner = tonic::client::Grpc::with_origin(inner, origin);
Self { inner }
}
pub fn with_interceptor<F>(
inner: T,
interceptor: F,
) -> ModelServiceClient<InterceptedService<T, F>>
where
F: tonic::service::Interceptor,
T::ResponseBody: Default,
T: tonic::codegen::Service<
http::Request<tonic::body::BoxBody>,
Response = http::Response<
<T as tonic::client::GrpcService<tonic::body::BoxBody>>::ResponseBody,
>,
>,
<T as tonic::codegen::Service<
http::Request<tonic::body::BoxBody>,
>>::Error: Into<StdError> + std::marker::Send + std::marker::Sync,
{
ModelServiceClient::new(InterceptedService::new(inner, interceptor))
}
/// Compress requests with the given encoding.
///
/// This requires the server to support it otherwise it might respond with an
/// error.
#[must_use]
pub fn send_compressed(mut self, encoding: CompressionEncoding) -> Self {
self.inner = self.inner.send_compressed(encoding);
self
}
/// Enable decompressing responses.
#[must_use]
pub fn accept_compressed(mut self, encoding: CompressionEncoding) -> Self {
self.inner = self.inner.accept_compressed(encoding);
self
}
/// Limits the maximum size of a decoded message.
///
/// Default: `4MB`
#[must_use]
pub fn max_decoding_message_size(mut self, limit: usize) -> Self {
self.inner = self.inner.max_decoding_message_size(limit);
self
}
/// Limits the maximum size of an encoded message.
///
/// Default: `usize::MAX`
#[must_use]
pub fn max_encoding_message_size(mut self, limit: usize) -> Self {
self.inner = self.inner.max_encoding_message_size(limit);
self
}
/// Gets information about a specific Model.
pub async fn get_model(
&mut self,
request: impl tonic::IntoRequest<super::GetModelRequest>,
) -> std::result::Result<tonic::Response<super::Model>, tonic::Status> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.ModelService/GetModel",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.ModelService",
"GetModel",
),
);
self.inner.unary(req, path, codec).await
}
/// Lists models available through the API.
pub async fn list_models(
&mut self,
request: impl tonic::IntoRequest<super::ListModelsRequest>,
) -> std::result::Result<
tonic::Response<super::ListModelsResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.ModelService/ListModels",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.ModelService",
"ListModels",
),
);
self.inner.unary(req, path, codec).await
}
/// Gets information about a specific TunedModel.
pub async fn get_tuned_model(
&mut self,
request: impl tonic::IntoRequest<super::GetTunedModelRequest>,
) -> std::result::Result<tonic::Response<super::TunedModel>, tonic::Status> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.ModelService/GetTunedModel",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.ModelService",
"GetTunedModel",
),
);
self.inner.unary(req, path, codec).await
}
/// Lists tuned models owned by the user.
pub async fn list_tuned_models(
&mut self,
request: impl tonic::IntoRequest<super::ListTunedModelsRequest>,
) -> std::result::Result<
tonic::Response<super::ListTunedModelsResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.ModelService/ListTunedModels",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.ModelService",
"ListTunedModels",
),
);
self.inner.unary(req, path, codec).await
}
/// Creates a tuned model.
/// Intermediate tuning progress (if any) is accessed through the
/// [google.longrunning.Operations] service.
///
/// Status and results can be accessed through the Operations service.
/// Example:
/// GET /v1/tunedModels/az2mb0bpw6i/operations/000-111-222
pub async fn create_tuned_model(
&mut self,
request: impl tonic::IntoRequest<super::CreateTunedModelRequest>,
) -> std::result::Result<
tonic::Response<super::super::super::super::longrunning::Operation>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.ModelService/CreateTunedModel",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.ModelService",
"CreateTunedModel",
),
);
self.inner.unary(req, path, codec).await
}
/// Updates a tuned model.
pub async fn update_tuned_model(
&mut self,
request: impl tonic::IntoRequest<super::UpdateTunedModelRequest>,
) -> std::result::Result<tonic::Response<super::TunedModel>, tonic::Status> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.ModelService/UpdateTunedModel",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.ModelService",
"UpdateTunedModel",
),
);
self.inner.unary(req, path, codec).await
}
/// Deletes a tuned model.
pub async fn delete_tuned_model(
&mut self,
request: impl tonic::IntoRequest<super::DeleteTunedModelRequest>,
) -> std::result::Result<tonic::Response<()>, tonic::Status> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.ModelService/DeleteTunedModel",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.ModelService",
"DeleteTunedModel",
),
);
self.inner.unary(req, path, codec).await
}
}
}
/// A collection of source attributions for a piece of content.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct CitationMetadata {
/// Citations to sources for a specific response.
#[prost(message, repeated, tag = "1")]
pub citation_sources: ::prost::alloc::vec::Vec<CitationSource>,
}
/// A citation to a source for a portion of a specific response.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct CitationSource {
/// Optional. Start of segment of the response that is attributed to this
/// source.
///
/// Index indicates the start of the segment, measured in bytes.
#[prost(int32, optional, tag = "1")]
pub start_index: ::core::option::Option<i32>,
/// Optional. End of the attributed segment, exclusive.
#[prost(int32, optional, tag = "2")]
pub end_index: ::core::option::Option<i32>,
/// Optional. URI that is attributed as a source for a portion of the text.
#[prost(string, optional, tag = "3")]
pub uri: ::core::option::Option<::prost::alloc::string::String>,
/// Optional. License for the GitHub project that is attributed as a source for
/// segment.
///
/// License info is required for code citations.
#[prost(string, optional, tag = "4")]
pub license: ::core::option::Option<::prost::alloc::string::String>,
}
/// Content filtering metadata associated with processing a single request.
///
/// ContentFilter contains a reason and an optional supporting string. The reason
/// may be unspecified.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ContentFilter {
/// The reason content was blocked during request processing.
#[prost(enumeration = "content_filter::BlockedReason", tag = "1")]
pub reason: i32,
/// A string that describes the filtering behavior in more detail.
#[prost(string, optional, tag = "2")]
pub message: ::core::option::Option<::prost::alloc::string::String>,
}
/// Nested message and enum types in `ContentFilter`.
pub mod content_filter {
/// A list of reasons why content may have been blocked.
#[derive(
Clone,
Copy,
Debug,
PartialEq,
Eq,
Hash,
PartialOrd,
Ord,
::prost::Enumeration
)]
#[repr(i32)]
pub enum BlockedReason {
/// A blocked reason was not specified.
Unspecified = 0,
/// Content was blocked by safety settings.
Safety = 1,
/// Content was blocked, but the reason is uncategorized.
Other = 2,
}
impl BlockedReason {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
BlockedReason::Unspecified => "BLOCKED_REASON_UNSPECIFIED",
BlockedReason::Safety => "SAFETY",
BlockedReason::Other => "OTHER",
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"BLOCKED_REASON_UNSPECIFIED" => Some(Self::Unspecified),
"SAFETY" => Some(Self::Safety),
"OTHER" => Some(Self::Other),
_ => None,
}
}
}
}
/// Safety feedback for an entire request.
///
/// This field is populated if content in the input and/or response is blocked
/// due to safety settings. SafetyFeedback may not exist for every HarmCategory.
/// Each SafetyFeedback will return the safety settings used by the request as
/// well as the lowest HarmProbability that should be allowed in order to return
/// a result.
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct SafetyFeedback {
/// Safety rating evaluated from content.
#[prost(message, optional, tag = "1")]
pub rating: ::core::option::Option<SafetyRating>,
/// Safety settings applied to the request.
#[prost(message, optional, tag = "2")]
pub setting: ::core::option::Option<SafetySetting>,
}
/// Safety rating for a piece of content.
///
/// The safety rating contains the category of harm and the
/// harm probability level in that category for a piece of content.
/// Content is classified for safety across a number of
/// harm categories and the probability of the harm classification is included
/// here.
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct SafetyRating {
/// Required. The category for this rating.
#[prost(enumeration = "HarmCategory", tag = "3")]
pub category: i32,
/// Required. The probability of harm for this content.
#[prost(enumeration = "safety_rating::HarmProbability", tag = "4")]
pub probability: i32,
}
/// Nested message and enum types in `SafetyRating`.
pub mod safety_rating {
/// The probability that a piece of content is harmful.
///
/// The classification system gives the probability of the content being
/// unsafe. This does not indicate the severity of harm for a piece of content.
#[derive(
Clone,
Copy,
Debug,
PartialEq,
Eq,
Hash,
PartialOrd,
Ord,
::prost::Enumeration
)]
#[repr(i32)]
pub enum HarmProbability {
/// Probability is unspecified.
Unspecified = 0,
/// Content has a negligible chance of being unsafe.
Negligible = 1,
/// Content has a low chance of being unsafe.
Low = 2,
/// Content has a medium chance of being unsafe.
Medium = 3,
/// Content has a high chance of being unsafe.
High = 4,
}
impl HarmProbability {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
HarmProbability::Unspecified => "HARM_PROBABILITY_UNSPECIFIED",
HarmProbability::Negligible => "NEGLIGIBLE",
HarmProbability::Low => "LOW",
HarmProbability::Medium => "MEDIUM",
HarmProbability::High => "HIGH",
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"HARM_PROBABILITY_UNSPECIFIED" => Some(Self::Unspecified),
"NEGLIGIBLE" => Some(Self::Negligible),
"LOW" => Some(Self::Low),
"MEDIUM" => Some(Self::Medium),
"HIGH" => Some(Self::High),
_ => None,
}
}
}
}
/// Safety setting, affecting the safety-blocking behavior.
///
/// Passing a safety setting for a category changes the allowed proability that
/// content is blocked.
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct SafetySetting {
/// Required. The category for this setting.
#[prost(enumeration = "HarmCategory", tag = "3")]
pub category: i32,
/// Required. Controls the probability threshold at which harm is blocked.
#[prost(enumeration = "safety_setting::HarmBlockThreshold", tag = "4")]
pub threshold: i32,
}
/// Nested message and enum types in `SafetySetting`.
pub mod safety_setting {
/// Block at and beyond a specified harm probability.
#[derive(
Clone,
Copy,
Debug,
PartialEq,
Eq,
Hash,
PartialOrd,
Ord,
::prost::Enumeration
)]
#[repr(i32)]
pub enum HarmBlockThreshold {
/// Threshold is unspecified.
Unspecified = 0,
/// Content with NEGLIGIBLE will be allowed.
BlockLowAndAbove = 1,
/// Content with NEGLIGIBLE and LOW will be allowed.
BlockMediumAndAbove = 2,
/// Content with NEGLIGIBLE, LOW, and MEDIUM will be allowed.
BlockOnlyHigh = 3,
/// All content will be allowed.
BlockNone = 4,
}
impl HarmBlockThreshold {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
HarmBlockThreshold::Unspecified => "HARM_BLOCK_THRESHOLD_UNSPECIFIED",
HarmBlockThreshold::BlockLowAndAbove => "BLOCK_LOW_AND_ABOVE",
HarmBlockThreshold::BlockMediumAndAbove => "BLOCK_MEDIUM_AND_ABOVE",
HarmBlockThreshold::BlockOnlyHigh => "BLOCK_ONLY_HIGH",
HarmBlockThreshold::BlockNone => "BLOCK_NONE",
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"HARM_BLOCK_THRESHOLD_UNSPECIFIED" => Some(Self::Unspecified),
"BLOCK_LOW_AND_ABOVE" => Some(Self::BlockLowAndAbove),
"BLOCK_MEDIUM_AND_ABOVE" => Some(Self::BlockMediumAndAbove),
"BLOCK_ONLY_HIGH" => Some(Self::BlockOnlyHigh),
"BLOCK_NONE" => Some(Self::BlockNone),
_ => None,
}
}
}
}
/// The category of a rating.
///
/// These categories cover various kinds of harms that developers
/// may wish to adjust.
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)]
#[repr(i32)]
pub enum HarmCategory {
/// Category is unspecified.
Unspecified = 0,
/// Negative or harmful comments targeting identity and/or protected attribute.
Derogatory = 1,
/// Content that is rude, disrepspectful, or profane.
Toxicity = 2,
/// Describes scenarios depictng violence against an individual or group, or
/// general descriptions of gore.
Violence = 3,
/// Contains references to sexual acts or other lewd content.
Sexual = 4,
/// Promotes unchecked medical advice.
Medical = 5,
/// Dangerous content that promotes, facilitates, or encourages harmful acts.
Dangerous = 6,
}
impl HarmCategory {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
HarmCategory::Unspecified => "HARM_CATEGORY_UNSPECIFIED",
HarmCategory::Derogatory => "HARM_CATEGORY_DEROGATORY",
HarmCategory::Toxicity => "HARM_CATEGORY_TOXICITY",
HarmCategory::Violence => "HARM_CATEGORY_VIOLENCE",
HarmCategory::Sexual => "HARM_CATEGORY_SEXUAL",
HarmCategory::Medical => "HARM_CATEGORY_MEDICAL",
HarmCategory::Dangerous => "HARM_CATEGORY_DANGEROUS",
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"HARM_CATEGORY_UNSPECIFIED" => Some(Self::Unspecified),
"HARM_CATEGORY_DEROGATORY" => Some(Self::Derogatory),
"HARM_CATEGORY_TOXICITY" => Some(Self::Toxicity),
"HARM_CATEGORY_VIOLENCE" => Some(Self::Violence),
"HARM_CATEGORY_SEXUAL" => Some(Self::Sexual),
"HARM_CATEGORY_MEDICAL" => Some(Self::Medical),
"HARM_CATEGORY_DANGEROUS" => Some(Self::Dangerous),
_ => None,
}
}
}
/// Request to generate a text completion response from the model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct GenerateTextRequest {
/// Required. The name of the `Model` or `TunedModel` to use for generating the
/// completion.
/// Examples:
/// models/text-bison-001
/// tunedModels/sentence-translator-u3b7m
#[prost(string, tag = "1")]
pub model: ::prost::alloc::string::String,
/// Required. The free-form input text given to the model as a prompt.
///
/// Given a prompt, the model will generate a TextCompletion response it
/// predicts as the completion of the input text.
#[prost(message, optional, tag = "2")]
pub prompt: ::core::option::Option<TextPrompt>,
/// Optional. Controls the randomness of the output.
/// Note: The default value varies by model, see the `Model.temperature`
/// attribute of the `Model` returned the `getModel` function.
///
/// Values can range from \[0.0,1.0\],
/// inclusive. A value closer to 1.0 will produce responses that are more
/// varied and creative, while a value closer to 0.0 will typically result in
/// more straightforward responses from the model.
#[prost(float, optional, tag = "3")]
pub temperature: ::core::option::Option<f32>,
/// Optional. Number of generated responses to return.
///
/// This value must be between \[1, 8\], inclusive. If unset, this will default
/// to 1.
#[prost(int32, optional, tag = "4")]
pub candidate_count: ::core::option::Option<i32>,
/// Optional. The maximum number of tokens to include in a candidate.
///
/// If unset, this will default to output_token_limit specified in the `Model`
/// specification.
#[prost(int32, optional, tag = "5")]
pub max_output_tokens: ::core::option::Option<i32>,
/// Optional. The maximum cumulative probability of tokens to consider when
/// sampling.
///
/// The model uses combined Top-k and nucleus sampling.
///
/// Tokens are sorted based on their assigned probabilities so that only the
/// most likely tokens are considered. Top-k sampling directly limits the
/// maximum number of tokens to consider, while Nucleus sampling limits number
/// of tokens based on the cumulative probability.
///
/// Note: The default value varies by model, see the `Model.top_p`
/// attribute of the `Model` returned the `getModel` function.
#[prost(float, optional, tag = "6")]
pub top_p: ::core::option::Option<f32>,
/// Optional. The maximum number of tokens to consider when sampling.
///
/// The model uses combined Top-k and nucleus sampling.
///
/// Top-k sampling considers the set of `top_k` most probable tokens.
/// Defaults to 40.
///
/// Note: The default value varies by model, see the `Model.top_k`
/// attribute of the `Model` returned the `getModel` function.
#[prost(int32, optional, tag = "7")]
pub top_k: ::core::option::Option<i32>,
/// A list of unique `SafetySetting` instances for blocking unsafe content.
///
/// that will be enforced on the `GenerateTextRequest.prompt` and
/// `GenerateTextResponse.candidates`. There should not be more than one
/// setting for each `SafetyCategory` type. The API will block any prompts and
/// responses that fail to meet the thresholds set by these settings. This list
/// overrides the default settings for each `SafetyCategory` specified in the
/// safety_settings. If there is no `SafetySetting` for a given
/// `SafetyCategory` provided in the list, the API will use the default safety
/// setting for that category.
#[prost(message, repeated, tag = "8")]
pub safety_settings: ::prost::alloc::vec::Vec<SafetySetting>,
/// The set of character sequences (up to 5) that will stop output generation.
/// If specified, the API will stop at the first appearance of a stop
/// sequence. The stop sequence will not be included as part of the response.
#[prost(string, repeated, tag = "9")]
pub stop_sequences: ::prost::alloc::vec::Vec<::prost::alloc::string::String>,
}
/// The response from the model, including candidate completions.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct GenerateTextResponse {
/// Candidate responses from the model.
#[prost(message, repeated, tag = "1")]
pub candidates: ::prost::alloc::vec::Vec<TextCompletion>,
/// A set of content filtering metadata for the prompt and response
/// text.
///
/// This indicates which `SafetyCategory`(s) blocked a
/// candidate from this response, the lowest `HarmProbability`
/// that triggered a block, and the HarmThreshold setting for that category.
/// This indicates the smallest change to the `SafetySettings` that would be
/// necessary to unblock at least 1 response.
///
/// The blocking is configured by the `SafetySettings` in the request (or the
/// default `SafetySettings` of the API).
#[prost(message, repeated, tag = "3")]
pub filters: ::prost::alloc::vec::Vec<ContentFilter>,
/// Returns any safety feedback related to content filtering.
#[prost(message, repeated, tag = "4")]
pub safety_feedback: ::prost::alloc::vec::Vec<SafetyFeedback>,
}
/// Text given to the model as a prompt.
///
/// The Model will use this TextPrompt to Generate a text completion.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct TextPrompt {
/// Required. The prompt text.
#[prost(string, tag = "1")]
pub text: ::prost::alloc::string::String,
}
/// Output text returned from a model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct TextCompletion {
/// Output only. The generated text returned from the model.
#[prost(string, tag = "1")]
pub output: ::prost::alloc::string::String,
/// Ratings for the safety of a response.
///
/// There is at most one rating per category.
#[prost(message, repeated, tag = "2")]
pub safety_ratings: ::prost::alloc::vec::Vec<SafetyRating>,
/// Output only. Citation information for model-generated `output` in this
/// `TextCompletion`.
///
/// This field may be populated with attribution information for any text
/// included in the `output`.
#[prost(message, optional, tag = "3")]
pub citation_metadata: ::core::option::Option<CitationMetadata>,
}
/// Request to get a text embedding from the model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct EmbedTextRequest {
/// Required. The model name to use with the format model=models/{model}.
#[prost(string, tag = "1")]
pub model: ::prost::alloc::string::String,
/// Required. The free-form input text that the model will turn into an
/// embedding.
#[prost(string, tag = "2")]
pub text: ::prost::alloc::string::String,
}
/// The response to a EmbedTextRequest.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct EmbedTextResponse {
/// Output only. The embedding generated from the input text.
#[prost(message, optional, tag = "1")]
pub embedding: ::core::option::Option<Embedding>,
}
/// Batch request to get a text embedding from the model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct BatchEmbedTextRequest {
/// Required. The name of the `Model` to use for generating the embedding.
/// Examples:
/// models/embedding-gecko-001
#[prost(string, tag = "1")]
pub model: ::prost::alloc::string::String,
/// Required. The free-form input texts that the model will turn into an
/// embedding. The current limit is 100 texts, over which an error will be
/// thrown.
#[prost(string, repeated, tag = "2")]
pub texts: ::prost::alloc::vec::Vec<::prost::alloc::string::String>,
}
/// The response to a EmbedTextRequest.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct BatchEmbedTextResponse {
/// Output only. The embeddings generated from the input text.
#[prost(message, repeated, tag = "1")]
pub embeddings: ::prost::alloc::vec::Vec<Embedding>,
}
/// A list of floats representing the embedding.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Embedding {
/// The embedding values.
#[prost(float, repeated, tag = "1")]
pub value: ::prost::alloc::vec::Vec<f32>,
}
/// Counts the number of tokens in the `prompt` sent to a model.
///
/// Models may tokenize text differently, so each model may return a different
/// `token_count`.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct CountTextTokensRequest {
/// Required. The model's resource name. This serves as an ID for the Model to
/// use.
///
/// This name should match a model name returned by the `ListModels` method.
///
/// Format: `models/{model}`
#[prost(string, tag = "1")]
pub model: ::prost::alloc::string::String,
/// Required. The free-form input text given to the model as a prompt.
#[prost(message, optional, tag = "2")]
pub prompt: ::core::option::Option<TextPrompt>,
}
/// A response from `CountTextTokens`.
///
/// It returns the model's `token_count` for the `prompt`.
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct CountTextTokensResponse {
/// The number of tokens that the `model` tokenizes the `prompt` into.
///
/// Always non-negative.
#[prost(int32, tag = "1")]
pub token_count: i32,
}
/// Generated client implementations.
pub mod text_service_client {
#![allow(unused_variables, dead_code, missing_docs, clippy::let_unit_value)]
use tonic::codegen::*;
use tonic::codegen::http::Uri;
/// API for using Generative Language Models (GLMs) trained to generate text.
///
/// Also known as Large Language Models (LLM)s, these generate text given an
/// input prompt from the user.
#[derive(Debug, Clone)]
pub struct TextServiceClient<T> {
inner: tonic::client::Grpc<T>,
}
impl<T> TextServiceClient<T>
where
T: tonic::client::GrpcService<tonic::body::BoxBody>,
T::Error: Into<StdError>,
T::ResponseBody: Body<Data = Bytes> + std::marker::Send + 'static,
<T::ResponseBody as Body>::Error: Into<StdError> + std::marker::Send,
{
pub fn new(inner: T) -> Self {
let inner = tonic::client::Grpc::new(inner);
Self { inner }
}
pub fn with_origin(inner: T, origin: Uri) -> Self {
let inner = tonic::client::Grpc::with_origin(inner, origin);
Self { inner }
}
pub fn with_interceptor<F>(
inner: T,
interceptor: F,
) -> TextServiceClient<InterceptedService<T, F>>
where
F: tonic::service::Interceptor,
T::ResponseBody: Default,
T: tonic::codegen::Service<
http::Request<tonic::body::BoxBody>,
Response = http::Response<
<T as tonic::client::GrpcService<tonic::body::BoxBody>>::ResponseBody,
>,
>,
<T as tonic::codegen::Service<
http::Request<tonic::body::BoxBody>,
>>::Error: Into<StdError> + std::marker::Send + std::marker::Sync,
{
TextServiceClient::new(InterceptedService::new(inner, interceptor))
}
/// Compress requests with the given encoding.
///
/// This requires the server to support it otherwise it might respond with an
/// error.
#[must_use]
pub fn send_compressed(mut self, encoding: CompressionEncoding) -> Self {
self.inner = self.inner.send_compressed(encoding);
self
}
/// Enable decompressing responses.
#[must_use]
pub fn accept_compressed(mut self, encoding: CompressionEncoding) -> Self {
self.inner = self.inner.accept_compressed(encoding);
self
}
/// Limits the maximum size of a decoded message.
///
/// Default: `4MB`
#[must_use]
pub fn max_decoding_message_size(mut self, limit: usize) -> Self {
self.inner = self.inner.max_decoding_message_size(limit);
self
}
/// Limits the maximum size of an encoded message.
///
/// Default: `usize::MAX`
#[must_use]
pub fn max_encoding_message_size(mut self, limit: usize) -> Self {
self.inner = self.inner.max_encoding_message_size(limit);
self
}
/// Generates a response from the model given an input message.
pub async fn generate_text(
&mut self,
request: impl tonic::IntoRequest<super::GenerateTextRequest>,
) -> std::result::Result<
tonic::Response<super::GenerateTextResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.TextService/GenerateText",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.TextService",
"GenerateText",
),
);
self.inner.unary(req, path, codec).await
}
/// Generates an embedding from the model given an input message.
pub async fn embed_text(
&mut self,
request: impl tonic::IntoRequest<super::EmbedTextRequest>,
) -> std::result::Result<
tonic::Response<super::EmbedTextResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.TextService/EmbedText",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.TextService",
"EmbedText",
),
);
self.inner.unary(req, path, codec).await
}
/// Generates multiple embeddings from the model given input text in a
/// synchronous call.
pub async fn batch_embed_text(
&mut self,
request: impl tonic::IntoRequest<super::BatchEmbedTextRequest>,
) -> std::result::Result<
tonic::Response<super::BatchEmbedTextResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.TextService/BatchEmbedText",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.TextService",
"BatchEmbedText",
),
);
self.inner.unary(req, path, codec).await
}
/// Runs a model's tokenizer on a text and returns the token count.
pub async fn count_text_tokens(
&mut self,
request: impl tonic::IntoRequest<super::CountTextTokensRequest>,
) -> std::result::Result<
tonic::Response<super::CountTextTokensResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.TextService/CountTextTokens",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.TextService",
"CountTextTokens",
),
);
self.inner.unary(req, path, codec).await
}
}
}
/// Request to generate a message response from the model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct GenerateMessageRequest {
/// Required. The name of the model to use.
///
/// Format: `name=models/{model}`.
#[prost(string, tag = "1")]
pub model: ::prost::alloc::string::String,
/// Required. The structured textual input given to the model as a prompt.
///
/// Given a
/// prompt, the model will return what it predicts is the next message in the
/// discussion.
#[prost(message, optional, tag = "2")]
pub prompt: ::core::option::Option<MessagePrompt>,
/// Optional. Controls the randomness of the output.
///
/// Values can range over `\[0.0,1.0\]`,
/// inclusive. A value closer to `1.0` will produce responses that are more
/// varied, while a value closer to `0.0` will typically result in
/// less surprising responses from the model.
#[prost(float, optional, tag = "3")]
pub temperature: ::core::option::Option<f32>,
/// Optional. The number of generated response messages to return.
///
/// This value must be between
/// `\[1, 8\]`, inclusive. If unset, this will default to `1`.
#[prost(int32, optional, tag = "4")]
pub candidate_count: ::core::option::Option<i32>,
/// Optional. The maximum cumulative probability of tokens to consider when
/// sampling.
///
/// The model uses combined Top-k and nucleus sampling.
///
/// Nucleus sampling considers the smallest set of tokens whose probability
/// sum is at least `top_p`.
#[prost(float, optional, tag = "5")]
pub top_p: ::core::option::Option<f32>,
/// Optional. The maximum number of tokens to consider when sampling.
///
/// The model uses combined Top-k and nucleus sampling.
///
/// Top-k sampling considers the set of `top_k` most probable tokens.
#[prost(int32, optional, tag = "6")]
pub top_k: ::core::option::Option<i32>,
}
/// The response from the model.
///
/// This includes candidate messages and
/// conversation history in the form of chronologically-ordered messages.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct GenerateMessageResponse {
/// Candidate response messages from the model.
#[prost(message, repeated, tag = "1")]
pub candidates: ::prost::alloc::vec::Vec<Message>,
/// The conversation history used by the model.
#[prost(message, repeated, tag = "2")]
pub messages: ::prost::alloc::vec::Vec<Message>,
/// A set of content filtering metadata for the prompt and response
/// text.
///
/// This indicates which `SafetyCategory`(s) blocked a
/// candidate from this response, the lowest `HarmProbability`
/// that triggered a block, and the HarmThreshold setting for that category.
#[prost(message, repeated, tag = "3")]
pub filters: ::prost::alloc::vec::Vec<ContentFilter>,
}
/// The base unit of structured text.
///
/// A `Message` includes an `author` and the `content` of
/// the `Message`.
///
/// The `author` is used to tag messages when they are fed to the
/// model as text.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Message {
/// Optional. The author of this Message.
///
/// This serves as a key for tagging
/// the content of this Message when it is fed to the model as text.
///
/// The author can be any alphanumeric string.
#[prost(string, tag = "1")]
pub author: ::prost::alloc::string::String,
/// Required. The text content of the structured `Message`.
#[prost(string, tag = "2")]
pub content: ::prost::alloc::string::String,
/// Output only. Citation information for model-generated `content` in this
/// `Message`.
///
/// If this `Message` was generated as output from the model, this field may be
/// populated with attribution information for any text included in the
/// `content`. This field is used only on output.
#[prost(message, optional, tag = "3")]
pub citation_metadata: ::core::option::Option<CitationMetadata>,
}
/// All of the structured input text passed to the model as a prompt.
///
/// A `MessagePrompt` contains a structured set of fields that provide context
/// for the conversation, examples of user input/model output message pairs that
/// prime the model to respond in different ways, and the conversation history
/// or list of messages representing the alternating turns of the conversation
/// between the user and the model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct MessagePrompt {
/// Optional. Text that should be provided to the model first to ground the
/// response.
///
/// If not empty, this `context` will be given to the model first before the
/// `examples` and `messages`. When using a `context` be sure to provide it
/// with every request to maintain continuity.
///
/// This field can be a description of your prompt to the model to help provide
/// context and guide the responses. Examples: "Translate the phrase from
/// English to French." or "Given a statement, classify the sentiment as happy,
/// sad or neutral."
///
/// Anything included in this field will take precedence over message history
/// if the total input size exceeds the model's `input_token_limit` and the
/// input request is truncated.
#[prost(string, tag = "1")]
pub context: ::prost::alloc::string::String,
/// Optional. Examples of what the model should generate.
///
/// This includes both user input and the response that the model should
/// emulate.
///
/// These `examples` are treated identically to conversation messages except
/// that they take precedence over the history in `messages`:
/// If the total input size exceeds the model's `input_token_limit` the input
/// will be truncated. Items will be dropped from `messages` before `examples`.
#[prost(message, repeated, tag = "2")]
pub examples: ::prost::alloc::vec::Vec<Example>,
/// Required. A snapshot of the recent conversation history sorted
/// chronologically.
///
/// Turns alternate between two authors.
///
/// If the total input size exceeds the model's `input_token_limit` the input
/// will be truncated: The oldest items will be dropped from `messages`.
#[prost(message, repeated, tag = "3")]
pub messages: ::prost::alloc::vec::Vec<Message>,
}
/// An input/output example used to instruct the Model.
///
/// It demonstrates how the model should respond or format its response.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Example {
/// Required. An example of an input `Message` from the user.
#[prost(message, optional, tag = "1")]
pub input: ::core::option::Option<Message>,
/// Required. An example of what the model should output given the input.
#[prost(message, optional, tag = "2")]
pub output: ::core::option::Option<Message>,
}
/// Counts the number of tokens in the `prompt` sent to a model.
///
/// Models may tokenize text differently, so each model may return a different
/// `token_count`.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct CountMessageTokensRequest {
/// Required. The model's resource name. This serves as an ID for the Model to
/// use.
///
/// This name should match a model name returned by the `ListModels` method.
///
/// Format: `models/{model}`
#[prost(string, tag = "1")]
pub model: ::prost::alloc::string::String,
/// Required. The prompt, whose token count is to be returned.
#[prost(message, optional, tag = "2")]
pub prompt: ::core::option::Option<MessagePrompt>,
}
/// A response from `CountMessageTokens`.
///
/// It returns the model's `token_count` for the `prompt`.
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct CountMessageTokensResponse {
/// The number of tokens that the `model` tokenizes the `prompt` into.
///
/// Always non-negative.
#[prost(int32, tag = "1")]
pub token_count: i32,
}
/// Generated client implementations.
pub mod discuss_service_client {
#![allow(unused_variables, dead_code, missing_docs, clippy::let_unit_value)]
use tonic::codegen::*;
use tonic::codegen::http::Uri;
/// An API for using Generative Language Models (GLMs) in dialog applications.
///
/// Also known as large language models (LLMs), this API provides models that
/// are trained for multi-turn dialog.
#[derive(Debug, Clone)]
pub struct DiscussServiceClient<T> {
inner: tonic::client::Grpc<T>,
}
impl<T> DiscussServiceClient<T>
where
T: tonic::client::GrpcService<tonic::body::BoxBody>,
T::Error: Into<StdError>,
T::ResponseBody: Body<Data = Bytes> + std::marker::Send + 'static,
<T::ResponseBody as Body>::Error: Into<StdError> + std::marker::Send,
{
pub fn new(inner: T) -> Self {
let inner = tonic::client::Grpc::new(inner);
Self { inner }
}
pub fn with_origin(inner: T, origin: Uri) -> Self {
let inner = tonic::client::Grpc::with_origin(inner, origin);
Self { inner }
}
pub fn with_interceptor<F>(
inner: T,
interceptor: F,
) -> DiscussServiceClient<InterceptedService<T, F>>
where
F: tonic::service::Interceptor,
T::ResponseBody: Default,
T: tonic::codegen::Service<
http::Request<tonic::body::BoxBody>,
Response = http::Response<
<T as tonic::client::GrpcService<tonic::body::BoxBody>>::ResponseBody,
>,
>,
<T as tonic::codegen::Service<
http::Request<tonic::body::BoxBody>,
>>::Error: Into<StdError> + std::marker::Send + std::marker::Sync,
{
DiscussServiceClient::new(InterceptedService::new(inner, interceptor))
}
/// Compress requests with the given encoding.
///
/// This requires the server to support it otherwise it might respond with an
/// error.
#[must_use]
pub fn send_compressed(mut self, encoding: CompressionEncoding) -> Self {
self.inner = self.inner.send_compressed(encoding);
self
}
/// Enable decompressing responses.
#[must_use]
pub fn accept_compressed(mut self, encoding: CompressionEncoding) -> Self {
self.inner = self.inner.accept_compressed(encoding);
self
}
/// Limits the maximum size of a decoded message.
///
/// Default: `4MB`
#[must_use]
pub fn max_decoding_message_size(mut self, limit: usize) -> Self {
self.inner = self.inner.max_decoding_message_size(limit);
self
}
/// Limits the maximum size of an encoded message.
///
/// Default: `usize::MAX`
#[must_use]
pub fn max_encoding_message_size(mut self, limit: usize) -> Self {
self.inner = self.inner.max_encoding_message_size(limit);
self
}
/// Generates a response from the model given an input `MessagePrompt`.
pub async fn generate_message(
&mut self,
request: impl tonic::IntoRequest<super::GenerateMessageRequest>,
) -> std::result::Result<
tonic::Response<super::GenerateMessageResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.DiscussService/GenerateMessage",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.DiscussService",
"GenerateMessage",
),
);
self.inner.unary(req, path, codec).await
}
/// Runs a model's tokenizer on a string and returns the token count.
pub async fn count_message_tokens(
&mut self,
request: impl tonic::IntoRequest<super::CountMessageTokensRequest>,
) -> std::result::Result<
tonic::Response<super::CountMessageTokensResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.DiscussService/CountMessageTokens",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.DiscussService",
"CountMessageTokens",
),
);
self.inner.unary(req, path, codec).await
}
}
}
/// Request to create a `Permission`.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct CreatePermissionRequest {
/// Required. The parent resource of the `Permission`.
/// Format: tunedModels/{tuned_model}
#[prost(string, tag = "1")]
pub parent: ::prost::alloc::string::String,
/// Required. The permission to create.
#[prost(message, optional, tag = "2")]
pub permission: ::core::option::Option<Permission>,
}
/// Request for getting information about a specific `Permission`.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct GetPermissionRequest {
/// Required. The resource name of the permission.
///
/// Format: `tunedModels/{tuned_model}permissions/{permission}`
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
}
/// Request for listing permissions.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ListPermissionsRequest {
/// Required. The parent resource of the permissions.
/// Format: tunedModels/{tuned_model}
#[prost(string, tag = "1")]
pub parent: ::prost::alloc::string::String,
/// Optional. The maximum number of `Permission`s to return (per page).
/// The service may return fewer permissions.
///
/// If unspecified, at most 10 permissions will be returned.
/// This method returns at most 1000 permissions per page, even if you pass
/// larger page_size.
#[prost(int32, tag = "2")]
pub page_size: i32,
/// Optional. A page token, received from a previous `ListPermissions` call.
///
/// Provide the `page_token` returned by one request as an argument to the
/// next request to retrieve the next page.
///
/// When paginating, all other parameters provided to `ListPermissions`
/// must match the call that provided the page token.
#[prost(string, tag = "3")]
pub page_token: ::prost::alloc::string::String,
}
/// Response from `ListPermissions` containing a paginated list of
/// permissions.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ListPermissionsResponse {
/// Returned permissions.
#[prost(message, repeated, tag = "1")]
pub permissions: ::prost::alloc::vec::Vec<Permission>,
/// A token, which can be sent as `page_token` to retrieve the next page.
///
/// If this field is omitted, there are no more pages.
#[prost(string, tag = "2")]
pub next_page_token: ::prost::alloc::string::String,
}
/// Request to update the `Permission`.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct UpdatePermissionRequest {
/// Required. The permission to update.
///
/// The permission's `name` field is used to identify the permission to update.
#[prost(message, optional, tag = "1")]
pub permission: ::core::option::Option<Permission>,
/// Required. The list of fields to update. Accepted ones:
/// - role (`Permission.role` field)
#[prost(message, optional, tag = "2")]
pub update_mask: ::core::option::Option<::prost_types::FieldMask>,
}
/// Request to delete the `Permission`.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct DeletePermissionRequest {
/// Required. The resource name of the permission.
/// Format: `tunedModels/{tuned_model}/permissions/{permission}`
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
}
/// Request to transfer the ownership of the tuned model.
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct TransferOwnershipRequest {
/// Required. The resource name of the tuned model to transfer ownership .
///
/// Format: `tunedModels/my-model-id`
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
/// Required. The email address of the user to whom the tuned model is being
/// transferred to.
#[prost(string, tag = "2")]
pub email_address: ::prost::alloc::string::String,
}
/// Response from `TransferOwnership`.
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct TransferOwnershipResponse {}
/// Generated client implementations.
pub mod permission_service_client {
#![allow(unused_variables, dead_code, missing_docs, clippy::let_unit_value)]
use tonic::codegen::*;
use tonic::codegen::http::Uri;
/// Provides methods for managing permissions to PaLM API resources.
#[derive(Debug, Clone)]
pub struct PermissionServiceClient<T> {
inner: tonic::client::Grpc<T>,
}
impl<T> PermissionServiceClient<T>
where
T: tonic::client::GrpcService<tonic::body::BoxBody>,
T::Error: Into<StdError>,
T::ResponseBody: Body<Data = Bytes> + std::marker::Send + 'static,
<T::ResponseBody as Body>::Error: Into<StdError> + std::marker::Send,
{
pub fn new(inner: T) -> Self {
let inner = tonic::client::Grpc::new(inner);
Self { inner }
}
pub fn with_origin(inner: T, origin: Uri) -> Self {
let inner = tonic::client::Grpc::with_origin(inner, origin);
Self { inner }
}
pub fn with_interceptor<F>(
inner: T,
interceptor: F,
) -> PermissionServiceClient<InterceptedService<T, F>>
where
F: tonic::service::Interceptor,
T::ResponseBody: Default,
T: tonic::codegen::Service<
http::Request<tonic::body::BoxBody>,
Response = http::Response<
<T as tonic::client::GrpcService<tonic::body::BoxBody>>::ResponseBody,
>,
>,
<T as tonic::codegen::Service<
http::Request<tonic::body::BoxBody>,
>>::Error: Into<StdError> + std::marker::Send + std::marker::Sync,
{
PermissionServiceClient::new(InterceptedService::new(inner, interceptor))
}
/// Compress requests with the given encoding.
///
/// This requires the server to support it otherwise it might respond with an
/// error.
#[must_use]
pub fn send_compressed(mut self, encoding: CompressionEncoding) -> Self {
self.inner = self.inner.send_compressed(encoding);
self
}
/// Enable decompressing responses.
#[must_use]
pub fn accept_compressed(mut self, encoding: CompressionEncoding) -> Self {
self.inner = self.inner.accept_compressed(encoding);
self
}
/// Limits the maximum size of a decoded message.
///
/// Default: `4MB`
#[must_use]
pub fn max_decoding_message_size(mut self, limit: usize) -> Self {
self.inner = self.inner.max_decoding_message_size(limit);
self
}
/// Limits the maximum size of an encoded message.
///
/// Default: `usize::MAX`
#[must_use]
pub fn max_encoding_message_size(mut self, limit: usize) -> Self {
self.inner = self.inner.max_encoding_message_size(limit);
self
}
/// Create a permission to a specific resource.
pub async fn create_permission(
&mut self,
request: impl tonic::IntoRequest<super::CreatePermissionRequest>,
) -> std::result::Result<tonic::Response<super::Permission>, tonic::Status> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.PermissionService/CreatePermission",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.PermissionService",
"CreatePermission",
),
);
self.inner.unary(req, path, codec).await
}
/// Gets information about a specific Permission.
pub async fn get_permission(
&mut self,
request: impl tonic::IntoRequest<super::GetPermissionRequest>,
) -> std::result::Result<tonic::Response<super::Permission>, tonic::Status> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.PermissionService/GetPermission",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.PermissionService",
"GetPermission",
),
);
self.inner.unary(req, path, codec).await
}
/// Lists permissions for the specific resource.
pub async fn list_permissions(
&mut self,
request: impl tonic::IntoRequest<super::ListPermissionsRequest>,
) -> std::result::Result<
tonic::Response<super::ListPermissionsResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.PermissionService/ListPermissions",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.PermissionService",
"ListPermissions",
),
);
self.inner.unary(req, path, codec).await
}
/// Updates the permission.
pub async fn update_permission(
&mut self,
request: impl tonic::IntoRequest<super::UpdatePermissionRequest>,
) -> std::result::Result<tonic::Response<super::Permission>, tonic::Status> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.PermissionService/UpdatePermission",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.PermissionService",
"UpdatePermission",
),
);
self.inner.unary(req, path, codec).await
}
/// Deletes the permission.
pub async fn delete_permission(
&mut self,
request: impl tonic::IntoRequest<super::DeletePermissionRequest>,
) -> std::result::Result<tonic::Response<()>, tonic::Status> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.PermissionService/DeletePermission",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.PermissionService",
"DeletePermission",
),
);
self.inner.unary(req, path, codec).await
}
/// Transfers ownership of the tuned model.
/// This is the only way to change ownership of the tuned model.
/// The current owner will be downgraded to writer role.
pub async fn transfer_ownership(
&mut self,
request: impl tonic::IntoRequest<super::TransferOwnershipRequest>,
) -> std::result::Result<
tonic::Response<super::TransferOwnershipResponse>,
tonic::Status,
> {
self.inner
.ready()
.await
.map_err(|e| {
tonic::Status::new(
tonic::Code::Unknown,
format!("Service was not ready: {}", e.into()),
)
})?;
let codec = tonic::codec::ProstCodec::default();
let path = http::uri::PathAndQuery::from_static(
"/google.ai.generativelanguage.v1beta3.PermissionService/TransferOwnership",
);
let mut req = request.into_request();
req.extensions_mut()
.insert(
GrpcMethod::new(
"google.ai.generativelanguage.v1beta3.PermissionService",
"TransferOwnership",
),
);
self.inner.unary(req, path, codec).await
}
}
}