ai/generativelanguage/apiv1/generativelanguagepb/generative_service.pb.go

// Copyright 2023 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// 	protoc-gen-go v1.33.0
// 	protoc        v4.25.3
// source: google/ai/generativelanguage/v1/generative_service.proto

package generativelanguagepb

import (
	context "context"
	reflect "reflect"
	sync "sync"

	_ "google.golang.org/genproto/googleapis/api/annotations"
	grpc "google.golang.org/grpc"
	codes "google.golang.org/grpc/codes"
	status "google.golang.org/grpc/status"
	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
)

const (
	// Verify that this generated code is sufficiently up-to-date.
	_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
	// Verify that runtime/protoimpl is sufficiently up-to-date.
	_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)

// Type of task for which the embedding will be used.
type TaskType int32

const (
	// Unset value, which will default to one of the other enum values.
	TaskType_TASK_TYPE_UNSPECIFIED TaskType = 0
	// Specifies the given text is a query in a search/retrieval setting.
	TaskType_RETRIEVAL_QUERY TaskType = 1
	// Specifies the given text is a document from the corpus being searched.
	TaskType_RETRIEVAL_DOCUMENT TaskType = 2
	// Specifies the given text will be used for STS.
	TaskType_SEMANTIC_SIMILARITY TaskType = 3
	// Specifies that the given text will be classified.
	TaskType_CLASSIFICATION TaskType = 4
	// Specifies that the embeddings will be used for clustering.
	TaskType_CLUSTERING TaskType = 5
	// Specifies that the given text will be used for question answering.
	TaskType_QUESTION_ANSWERING TaskType = 6
	// Specifies that the given text will be used for fact verification.
	TaskType_FACT_VERIFICATION TaskType = 7
)

// Enum value maps for TaskType.
var (
	TaskType_name = map[int32]string{
		0: "TASK_TYPE_UNSPECIFIED",
		1: "RETRIEVAL_QUERY",
		2: "RETRIEVAL_DOCUMENT",
		3: "SEMANTIC_SIMILARITY",
		4: "CLASSIFICATION",
		5: "CLUSTERING",
		6: "QUESTION_ANSWERING",
		7: "FACT_VERIFICATION",
	}
	TaskType_value = map[string]int32{
		"TASK_TYPE_UNSPECIFIED": 0,
		"RETRIEVAL_QUERY":       1,
		"RETRIEVAL_DOCUMENT":    2,
		"SEMANTIC_SIMILARITY":   3,
		"CLASSIFICATION":        4,
		"CLUSTERING":            5,
		"QUESTION_ANSWERING":    6,
		"FACT_VERIFICATION":     7,
	}
)

func (x TaskType) Enum() *TaskType {
	p := new(TaskType)
	*p = x
	return p
}

func (x TaskType) String() string {
	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}

func (TaskType) Descriptor() protoreflect.EnumDescriptor {
	return file_google_ai_generativelanguage_v1_generative_service_proto_enumTypes[0].Descriptor()
}

func (TaskType) Type() protoreflect.EnumType {
	return &file_google_ai_generativelanguage_v1_generative_service_proto_enumTypes[0]
}

func (x TaskType) Number() protoreflect.EnumNumber {
	return protoreflect.EnumNumber(x)
}

// Deprecated: Use TaskType.Descriptor instead.
func (TaskType) EnumDescriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{0}
}

// Specifies what was the reason why prompt was blocked.
type GenerateContentResponse_PromptFeedback_BlockReason int32

const (
	// Default value. This value is unused.
	GenerateContentResponse_PromptFeedback_BLOCK_REASON_UNSPECIFIED GenerateContentResponse_PromptFeedback_BlockReason = 0
	// Prompt was blocked due to safety reasons. You can inspect
	// `safety_ratings` to understand which safety category blocked it.
	GenerateContentResponse_PromptFeedback_SAFETY GenerateContentResponse_PromptFeedback_BlockReason = 1
	// Prompt was blocked due to unknown reaasons.
	GenerateContentResponse_PromptFeedback_OTHER GenerateContentResponse_PromptFeedback_BlockReason = 2
)

// Enum value maps for GenerateContentResponse_PromptFeedback_BlockReason.
var (
	GenerateContentResponse_PromptFeedback_BlockReason_name = map[int32]string{
		0: "BLOCK_REASON_UNSPECIFIED",
		1: "SAFETY",
		2: "OTHER",
	}
	GenerateContentResponse_PromptFeedback_BlockReason_value = map[string]int32{
		"BLOCK_REASON_UNSPECIFIED": 0,
		"SAFETY":                   1,
		"OTHER":                    2,
	}
)

func (x GenerateContentResponse_PromptFeedback_BlockReason) Enum() *GenerateContentResponse_PromptFeedback_BlockReason {
	p := new(GenerateContentResponse_PromptFeedback_BlockReason)
	*p = x
	return p
}

func (x GenerateContentResponse_PromptFeedback_BlockReason) String() string {
	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}

func (GenerateContentResponse_PromptFeedback_BlockReason) Descriptor() protoreflect.EnumDescriptor {
	return file_google_ai_generativelanguage_v1_generative_service_proto_enumTypes[1].Descriptor()
}

func (GenerateContentResponse_PromptFeedback_BlockReason) Type() protoreflect.EnumType {
	return &file_google_ai_generativelanguage_v1_generative_service_proto_enumTypes[1]
}

func (x GenerateContentResponse_PromptFeedback_BlockReason) Number() protoreflect.EnumNumber {
	return protoreflect.EnumNumber(x)
}

// Deprecated: Use GenerateContentResponse_PromptFeedback_BlockReason.Descriptor instead.
func (GenerateContentResponse_PromptFeedback_BlockReason) EnumDescriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{2, 0, 0}
}

// Defines the reason why the model stopped generating tokens.
type Candidate_FinishReason int32

const (
	// Default value. This value is unused.
	Candidate_FINISH_REASON_UNSPECIFIED Candidate_FinishReason = 0
	// Natural stop point of the model or provided stop sequence.
	Candidate_STOP Candidate_FinishReason = 1
	// The maximum number of tokens as specified in the request was reached.
	Candidate_MAX_TOKENS Candidate_FinishReason = 2
	// The candidate content was flagged for safety reasons.
	Candidate_SAFETY Candidate_FinishReason = 3
	// The candidate content was flagged for recitation reasons.
	Candidate_RECITATION Candidate_FinishReason = 4
	// Unknown reason.
	Candidate_OTHER Candidate_FinishReason = 5
)

// Enum value maps for Candidate_FinishReason.
var (
	Candidate_FinishReason_name = map[int32]string{
		0: "FINISH_REASON_UNSPECIFIED",
		1: "STOP",
		2: "MAX_TOKENS",
		3: "SAFETY",
		4: "RECITATION",
		5: "OTHER",
	}
	Candidate_FinishReason_value = map[string]int32{
		"FINISH_REASON_UNSPECIFIED": 0,
		"STOP":                      1,
		"MAX_TOKENS":                2,
		"SAFETY":                    3,
		"RECITATION":                4,
		"OTHER":                     5,
	}
)

func (x Candidate_FinishReason) Enum() *Candidate_FinishReason {
	p := new(Candidate_FinishReason)
	*p = x
	return p
}

func (x Candidate_FinishReason) String() string {
	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}

func (Candidate_FinishReason) Descriptor() protoreflect.EnumDescriptor {
	return file_google_ai_generativelanguage_v1_generative_service_proto_enumTypes[2].Descriptor()
}

func (Candidate_FinishReason) Type() protoreflect.EnumType {
	return &file_google_ai_generativelanguage_v1_generative_service_proto_enumTypes[2]
}

func (x Candidate_FinishReason) Number() protoreflect.EnumNumber {
	return protoreflect.EnumNumber(x)
}

// Deprecated: Use Candidate_FinishReason.Descriptor instead.
func (Candidate_FinishReason) EnumDescriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{3, 0}
}

// Request to generate a completion from the model.
type GenerateContentRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Required. The name of the `Model` to use for generating the completion.
	//
	// Format: `name=models/{model}`.
	Model string `protobuf:"bytes,1,opt,name=model,proto3" json:"model,omitempty"`
	// Required. The content of the current conversation with the model.
	//
	// For single-turn queries, this is a single instance. For multi-turn queries,
	// this is a repeated field that contains conversation history + latest
	// request.
	Contents []*Content `protobuf:"bytes,2,rep,name=contents,proto3" json:"contents,omitempty"`
	// Optional. A list of unique `SafetySetting` instances for blocking unsafe
	// content.
	//
	// This will be enforced on the `GenerateContentRequest.contents` and
	// `GenerateContentResponse.candidates`. There should not be more than one
	// setting for each `SafetyCategory` type. The API will block any contents 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. Harm categories HARM_CATEGORY_HATE_SPEECH,
	// HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT,
	// HARM_CATEGORY_HARASSMENT are supported.
	SafetySettings []*SafetySetting `protobuf:"bytes,3,rep,name=safety_settings,json=safetySettings,proto3" json:"safety_settings,omitempty"`
	// Optional. Configuration options for model generation and outputs.
	GenerationConfig *GenerationConfig `protobuf:"bytes,4,opt,name=generation_config,json=generationConfig,proto3,oneof" json:"generation_config,omitempty"`
}

func (x *GenerateContentRequest) Reset() {
	*x = GenerateContentRequest{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[0]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *GenerateContentRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*GenerateContentRequest) ProtoMessage() {}

func (x *GenerateContentRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[0]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use GenerateContentRequest.ProtoReflect.Descriptor instead.
func (*GenerateContentRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{0}
}

func (x *GenerateContentRequest) GetModel() string {
	if x != nil {
		return x.Model
	}
	return ""
}

func (x *GenerateContentRequest) GetContents() []*Content {
	if x != nil {
		return x.Contents
	}
	return nil
}

func (x *GenerateContentRequest) GetSafetySettings() []*SafetySetting {
	if x != nil {
		return x.SafetySettings
	}
	return nil
}

func (x *GenerateContentRequest) GetGenerationConfig() *GenerationConfig {
	if x != nil {
		return x.GenerationConfig
	}
	return nil
}

// Configuration options for model generation and outputs. Not all parameters
// may be configurable for every model.
type GenerationConfig struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Optional. Number of generated responses to return.
	//
	// Currently, this value can only be set to 1. If unset, this will default
	// to 1.
	CandidateCount *int32 `protobuf:"varint,1,opt,name=candidate_count,json=candidateCount,proto3,oneof" json:"candidate_count,omitempty"`
	// Optional. 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.
	StopSequences []string `protobuf:"bytes,2,rep,name=stop_sequences,json=stopSequences,proto3" json:"stop_sequences,omitempty"`
	// Optional. The maximum number of tokens to include in a candidate.
	//
	// Note: The default value varies by model, see the `Model.output_token_limit`
	// attribute of the `Model` returned from the `getModel` function.
	MaxOutputTokens *int32 `protobuf:"varint,4,opt,name=max_output_tokens,json=maxOutputTokens,proto3,oneof" json:"max_output_tokens,omitempty"`
	// Optional. Controls the randomness of the output.
	//
	// Note: The default value varies by model, see the `Model.temperature`
	// attribute of the `Model` returned from the `getModel` function.
	//
	// Values can range from [0.0, 2.0].
	Temperature *float32 `protobuf:"fixed32,5,opt,name=temperature,proto3,oneof" json:"temperature,omitempty"`
	// 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 from the `getModel` function.
	TopP *float32 `protobuf:"fixed32,6,opt,name=top_p,json=topP,proto3,oneof" json:"top_p,omitempty"`
	// Optional. The maximum number of tokens to consider when sampling.
	//
	// Models use nucleus sampling or combined Top-k and nucleus sampling.
	// Top-k sampling considers the set of `top_k` most probable tokens.
	// Models running with nucleus sampling don't allow top_k setting.
	//
	// Note: The default value varies by model, see the `Model.top_k`
	// attribute of the `Model` returned from the `getModel` function. Empty
	// `top_k` field in `Model` indicates the model doesn't apply top-k sampling
	// and doesn't allow setting `top_k` on requests.
	TopK *int32 `protobuf:"varint,7,opt,name=top_k,json=topK,proto3,oneof" json:"top_k,omitempty"`
}

func (x *GenerationConfig) Reset() {
	*x = GenerationConfig{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[1]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *GenerationConfig) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*GenerationConfig) ProtoMessage() {}

func (x *GenerationConfig) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[1]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use GenerationConfig.ProtoReflect.Descriptor instead.
func (*GenerationConfig) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{1}
}

func (x *GenerationConfig) GetCandidateCount() int32 {
	if x != nil && x.CandidateCount != nil {
		return *x.CandidateCount
	}
	return 0
}

func (x *GenerationConfig) GetStopSequences() []string {
	if x != nil {
		return x.StopSequences
	}
	return nil
}

func (x *GenerationConfig) GetMaxOutputTokens() int32 {
	if x != nil && x.MaxOutputTokens != nil {
		return *x.MaxOutputTokens
	}
	return 0
}

func (x *GenerationConfig) GetTemperature() float32 {
	if x != nil && x.Temperature != nil {
		return *x.Temperature
	}
	return 0
}

func (x *GenerationConfig) GetTopP() float32 {
	if x != nil && x.TopP != nil {
		return *x.TopP
	}
	return 0
}

func (x *GenerationConfig) GetTopK() int32 {
	if x != nil && x.TopK != nil {
		return *x.TopK
	}
	return 0
}

// Response from the model supporting multiple candidates.
//
// Note on safety ratings and content filtering. They are reported for both
// prompt in `GenerateContentResponse.prompt_feedback` and for each candidate
// in `finish_reason` and in `safety_ratings`. The API contract is that:
//   - either all requested candidates are returned or no candidates at all
//   - no candidates are returned only if there was something wrong with the
//     prompt (see `prompt_feedback`)
//   - feedback on each candidate is reported on `finish_reason` and
//     `safety_ratings`.
type GenerateContentResponse struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Candidate responses from the model.
	Candidates []*Candidate `protobuf:"bytes,1,rep,name=candidates,proto3" json:"candidates,omitempty"`
	// Returns the prompt's feedback related to the content filters.
	PromptFeedback *GenerateContentResponse_PromptFeedback `protobuf:"bytes,2,opt,name=prompt_feedback,json=promptFeedback,proto3" json:"prompt_feedback,omitempty"`
}

func (x *GenerateContentResponse) Reset() {
	*x = GenerateContentResponse{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[2]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *GenerateContentResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*GenerateContentResponse) ProtoMessage() {}

func (x *GenerateContentResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[2]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use GenerateContentResponse.ProtoReflect.Descriptor instead.
func (*GenerateContentResponse) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{2}
}

func (x *GenerateContentResponse) GetCandidates() []*Candidate {
	if x != nil {
		return x.Candidates
	}
	return nil
}

func (x *GenerateContentResponse) GetPromptFeedback() *GenerateContentResponse_PromptFeedback {
	if x != nil {
		return x.PromptFeedback
	}
	return nil
}

// A response candidate generated from the model.
type Candidate struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Output only. Index of the candidate in the list of candidates.
	Index *int32 `protobuf:"varint,3,opt,name=index,proto3,oneof" json:"index,omitempty"`
	// Output only. Generated content returned from the model.
	Content *Content `protobuf:"bytes,1,opt,name=content,proto3" json:"content,omitempty"`
	// Optional. Output only. The reason why the model stopped generating tokens.
	//
	// If empty, the model has not stopped generating the tokens.
	FinishReason Candidate_FinishReason `protobuf:"varint,2,opt,name=finish_reason,json=finishReason,proto3,enum=google.ai.generativelanguage.v1.Candidate_FinishReason" json:"finish_reason,omitempty"`
	// List of ratings for the safety of a response candidate.
	//
	// There is at most one rating per category.
	SafetyRatings []*SafetyRating `protobuf:"bytes,5,rep,name=safety_ratings,json=safetyRatings,proto3" json:"safety_ratings,omitempty"`
	// Output only. Citation information for model-generated candidate.
	//
	// This field may be populated with recitation information for any text
	// included in the `content`. These are passages that are "recited" from
	// copyrighted material in the foundational LLM's training data.
	CitationMetadata *CitationMetadata `protobuf:"bytes,6,opt,name=citation_metadata,json=citationMetadata,proto3" json:"citation_metadata,omitempty"`
	// Output only. Token count for this candidate.
	TokenCount int32 `protobuf:"varint,7,opt,name=token_count,json=tokenCount,proto3" json:"token_count,omitempty"`
}

func (x *Candidate) Reset() {
	*x = Candidate{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[3]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *Candidate) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*Candidate) ProtoMessage() {}

func (x *Candidate) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[3]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use Candidate.ProtoReflect.Descriptor instead.
func (*Candidate) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{3}
}

func (x *Candidate) GetIndex() int32 {
	if x != nil && x.Index != nil {
		return *x.Index
	}
	return 0
}

func (x *Candidate) GetContent() *Content {
	if x != nil {
		return x.Content
	}
	return nil
}

func (x *Candidate) GetFinishReason() Candidate_FinishReason {
	if x != nil {
		return x.FinishReason
	}
	return Candidate_FINISH_REASON_UNSPECIFIED
}

func (x *Candidate) GetSafetyRatings() []*SafetyRating {
	if x != nil {
		return x.SafetyRatings
	}
	return nil
}

func (x *Candidate) GetCitationMetadata() *CitationMetadata {
	if x != nil {
		return x.CitationMetadata
	}
	return nil
}

func (x *Candidate) GetTokenCount() int32 {
	if x != nil {
		return x.TokenCount
	}
	return 0
}

// Request containing the `Content` for the model to embed.
type EmbedContentRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// 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}`
	Model string `protobuf:"bytes,1,opt,name=model,proto3" json:"model,omitempty"`
	// Required. The content to embed. Only the `parts.text` fields will be
	// counted.
	Content *Content `protobuf:"bytes,2,opt,name=content,proto3" json:"content,omitempty"`
	// Optional. Optional task type for which the embeddings will be used. Can
	// only be set for `models/embedding-001`.
	TaskType *TaskType `protobuf:"varint,3,opt,name=task_type,json=taskType,proto3,enum=google.ai.generativelanguage.v1.TaskType,oneof" json:"task_type,omitempty"`
	// Optional. An optional title for the text. Only applicable when TaskType is
	// `RETRIEVAL_DOCUMENT`.
	//
	// Note: Specifying a `title` for `RETRIEVAL_DOCUMENT` provides better quality
	// embeddings for retrieval.
	Title *string `protobuf:"bytes,4,opt,name=title,proto3,oneof" json:"title,omitempty"`
	// Optional. Optional reduced dimension for the output embedding. If set,
	// excessive values in the output embedding are truncated from the end.
	// Supported by `models/text-embedding-latest`.
	OutputDimensionality *int32 `protobuf:"varint,5,opt,name=output_dimensionality,json=outputDimensionality,proto3,oneof" json:"output_dimensionality,omitempty"`
}

func (x *EmbedContentRequest) Reset() {
	*x = EmbedContentRequest{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[4]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *EmbedContentRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*EmbedContentRequest) ProtoMessage() {}

func (x *EmbedContentRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[4]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use EmbedContentRequest.ProtoReflect.Descriptor instead.
func (*EmbedContentRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{4}
}

func (x *EmbedContentRequest) GetModel() string {
	if x != nil {
		return x.Model
	}
	return ""
}

func (x *EmbedContentRequest) GetContent() *Content {
	if x != nil {
		return x.Content
	}
	return nil
}

func (x *EmbedContentRequest) GetTaskType() TaskType {
	if x != nil && x.TaskType != nil {
		return *x.TaskType
	}
	return TaskType_TASK_TYPE_UNSPECIFIED
}

func (x *EmbedContentRequest) GetTitle() string {
	if x != nil && x.Title != nil {
		return *x.Title
	}
	return ""
}

func (x *EmbedContentRequest) GetOutputDimensionality() int32 {
	if x != nil && x.OutputDimensionality != nil {
		return *x.OutputDimensionality
	}
	return 0
}

// A list of floats representing an embedding.
type ContentEmbedding struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// The embedding values.
	Values []float32 `protobuf:"fixed32,1,rep,packed,name=values,proto3" json:"values,omitempty"`
}

func (x *ContentEmbedding) Reset() {
	*x = ContentEmbedding{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[5]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *ContentEmbedding) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*ContentEmbedding) ProtoMessage() {}

func (x *ContentEmbedding) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[5]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use ContentEmbedding.ProtoReflect.Descriptor instead.
func (*ContentEmbedding) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{5}
}

func (x *ContentEmbedding) GetValues() []float32 {
	if x != nil {
		return x.Values
	}
	return nil
}

// The response to an `EmbedContentRequest`.
type EmbedContentResponse struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Output only. The embedding generated from the input content.
	Embedding *ContentEmbedding `protobuf:"bytes,1,opt,name=embedding,proto3" json:"embedding,omitempty"`
}

func (x *EmbedContentResponse) Reset() {
	*x = EmbedContentResponse{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[6]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *EmbedContentResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*EmbedContentResponse) ProtoMessage() {}

func (x *EmbedContentResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[6]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use EmbedContentResponse.ProtoReflect.Descriptor instead.
func (*EmbedContentResponse) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{6}
}

func (x *EmbedContentResponse) GetEmbedding() *ContentEmbedding {
	if x != nil {
		return x.Embedding
	}
	return nil
}

// Batch request to get embeddings from the model for a list of prompts.
type BatchEmbedContentsRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// 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}`
	Model string `protobuf:"bytes,1,opt,name=model,proto3" json:"model,omitempty"`
	// Required. Embed requests for the batch. The model in each of these requests
	// must match the model specified `BatchEmbedContentsRequest.model`.
	Requests []*EmbedContentRequest `protobuf:"bytes,2,rep,name=requests,proto3" json:"requests,omitempty"`
}

func (x *BatchEmbedContentsRequest) Reset() {
	*x = BatchEmbedContentsRequest{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[7]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *BatchEmbedContentsRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*BatchEmbedContentsRequest) ProtoMessage() {}

func (x *BatchEmbedContentsRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[7]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use BatchEmbedContentsRequest.ProtoReflect.Descriptor instead.
func (*BatchEmbedContentsRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{7}
}

func (x *BatchEmbedContentsRequest) GetModel() string {
	if x != nil {
		return x.Model
	}
	return ""
}

func (x *BatchEmbedContentsRequest) GetRequests() []*EmbedContentRequest {
	if x != nil {
		return x.Requests
	}
	return nil
}

// The response to a `BatchEmbedContentsRequest`.
type BatchEmbedContentsResponse struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Output only. The embeddings for each request, in the same order as provided
	// in the batch request.
	Embeddings []*ContentEmbedding `protobuf:"bytes,1,rep,name=embeddings,proto3" json:"embeddings,omitempty"`
}

func (x *BatchEmbedContentsResponse) Reset() {
	*x = BatchEmbedContentsResponse{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[8]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *BatchEmbedContentsResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*BatchEmbedContentsResponse) ProtoMessage() {}

func (x *BatchEmbedContentsResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[8]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use BatchEmbedContentsResponse.ProtoReflect.Descriptor instead.
func (*BatchEmbedContentsResponse) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{8}
}

func (x *BatchEmbedContentsResponse) GetEmbeddings() []*ContentEmbedding {
	if x != nil {
		return x.Embeddings
	}
	return nil
}

// 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`.
type CountTokensRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// 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}`
	Model string `protobuf:"bytes,1,opt,name=model,proto3" json:"model,omitempty"`
	// Required. The input given to the model as a prompt.
	Contents []*Content `protobuf:"bytes,2,rep,name=contents,proto3" json:"contents,omitempty"`
}

func (x *CountTokensRequest) Reset() {
	*x = CountTokensRequest{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[9]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *CountTokensRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*CountTokensRequest) ProtoMessage() {}

func (x *CountTokensRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[9]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use CountTokensRequest.ProtoReflect.Descriptor instead.
func (*CountTokensRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{9}
}

func (x *CountTokensRequest) GetModel() string {
	if x != nil {
		return x.Model
	}
	return ""
}

func (x *CountTokensRequest) GetContents() []*Content {
	if x != nil {
		return x.Contents
	}
	return nil
}

// A response from `CountTokens`.
//
// It returns the model's `token_count` for the `prompt`.
type CountTokensResponse struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// The number of tokens that the `model` tokenizes the `prompt` into.
	//
	// Always non-negative.
	TotalTokens int32 `protobuf:"varint,1,opt,name=total_tokens,json=totalTokens,proto3" json:"total_tokens,omitempty"`
}

func (x *CountTokensResponse) Reset() {
	*x = CountTokensResponse{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[10]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *CountTokensResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*CountTokensResponse) ProtoMessage() {}

func (x *CountTokensResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[10]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use CountTokensResponse.ProtoReflect.Descriptor instead.
func (*CountTokensResponse) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{10}
}

func (x *CountTokensResponse) GetTotalTokens() int32 {
	if x != nil {
		return x.TotalTokens
	}
	return 0
}

// A set of the feedback metadata the prompt specified in
// `GenerateContentRequest.content`.
type GenerateContentResponse_PromptFeedback struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Optional. If set, the prompt was blocked and no candidates are returned.
	// Rephrase your prompt.
	BlockReason GenerateContentResponse_PromptFeedback_BlockReason `protobuf:"varint,1,opt,name=block_reason,json=blockReason,proto3,enum=google.ai.generativelanguage.v1.GenerateContentResponse_PromptFeedback_BlockReason" json:"block_reason,omitempty"`
	// Ratings for safety of the prompt.
	// There is at most one rating per category.
	SafetyRatings []*SafetyRating `protobuf:"bytes,2,rep,name=safety_ratings,json=safetyRatings,proto3" json:"safety_ratings,omitempty"`
}

func (x *GenerateContentResponse_PromptFeedback) Reset() {
	*x = GenerateContentResponse_PromptFeedback{}
	if protoimpl.UnsafeEnabled {
		mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[11]
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		ms.StoreMessageInfo(mi)
	}
}

func (x *GenerateContentResponse_PromptFeedback) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*GenerateContentResponse_PromptFeedback) ProtoMessage() {}

func (x *GenerateContentResponse_PromptFeedback) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[11]
	if protoimpl.UnsafeEnabled && x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use GenerateContentResponse_PromptFeedback.ProtoReflect.Descriptor instead.
func (*GenerateContentResponse_PromptFeedback) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP(), []int{2, 0}
}

func (x *GenerateContentResponse_PromptFeedback) GetBlockReason() GenerateContentResponse_PromptFeedback_BlockReason {
	if x != nil {
		return x.BlockReason
	}
	return GenerateContentResponse_PromptFeedback_BLOCK_REASON_UNSPECIFIED
}

func (x *GenerateContentResponse_PromptFeedback) GetSafetyRatings() []*SafetyRating {
	if x != nil {
		return x.SafetyRatings
	}
	return nil
}

var File_google_ai_generativelanguage_v1_generative_service_proto protoreflect.FileDescriptor

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var (
	file_google_ai_generativelanguage_v1_generative_service_proto_rawDescOnce sync.Once
	file_google_ai_generativelanguage_v1_generative_service_proto_rawDescData = file_google_ai_generativelanguage_v1_generative_service_proto_rawDesc
)

func file_google_ai_generativelanguage_v1_generative_service_proto_rawDescGZIP() []byte {
	file_google_ai_generativelanguage_v1_generative_service_proto_rawDescOnce.Do(func() {
		file_google_ai_generativelanguage_v1_generative_service_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_ai_generativelanguage_v1_generative_service_proto_rawDescData)
	})
	return file_google_ai_generativelanguage_v1_generative_service_proto_rawDescData
}

var file_google_ai_generativelanguage_v1_generative_service_proto_enumTypes = make([]protoimpl.EnumInfo, 3)
var file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes = make([]protoimpl.MessageInfo, 12)
var file_google_ai_generativelanguage_v1_generative_service_proto_goTypes = []interface{}{
	(TaskType)(0), // 0: google.ai.generativelanguage.v1.TaskType
	(GenerateContentResponse_PromptFeedback_BlockReason)(0), // 1: google.ai.generativelanguage.v1.GenerateContentResponse.PromptFeedback.BlockReason
	(Candidate_FinishReason)(0),                             // 2: google.ai.generativelanguage.v1.Candidate.FinishReason
	(*GenerateContentRequest)(nil),                          // 3: google.ai.generativelanguage.v1.GenerateContentRequest
	(*GenerationConfig)(nil),                                // 4: google.ai.generativelanguage.v1.GenerationConfig
	(*GenerateContentResponse)(nil),                         // 5: google.ai.generativelanguage.v1.GenerateContentResponse
	(*Candidate)(nil),                                       // 6: google.ai.generativelanguage.v1.Candidate
	(*EmbedContentRequest)(nil),                             // 7: google.ai.generativelanguage.v1.EmbedContentRequest
	(*ContentEmbedding)(nil),                                // 8: google.ai.generativelanguage.v1.ContentEmbedding
	(*EmbedContentResponse)(nil),                            // 9: google.ai.generativelanguage.v1.EmbedContentResponse
	(*BatchEmbedContentsRequest)(nil),                       // 10: google.ai.generativelanguage.v1.BatchEmbedContentsRequest
	(*BatchEmbedContentsResponse)(nil),                      // 11: google.ai.generativelanguage.v1.BatchEmbedContentsResponse
	(*CountTokensRequest)(nil),                              // 12: google.ai.generativelanguage.v1.CountTokensRequest
	(*CountTokensResponse)(nil),                             // 13: google.ai.generativelanguage.v1.CountTokensResponse
	(*GenerateContentResponse_PromptFeedback)(nil),          // 14: google.ai.generativelanguage.v1.GenerateContentResponse.PromptFeedback
	(*Content)(nil),                                         // 15: google.ai.generativelanguage.v1.Content
	(*SafetySetting)(nil),                                   // 16: google.ai.generativelanguage.v1.SafetySetting
	(*SafetyRating)(nil),                                    // 17: google.ai.generativelanguage.v1.SafetyRating
	(*CitationMetadata)(nil),                                // 18: google.ai.generativelanguage.v1.CitationMetadata
}
var file_google_ai_generativelanguage_v1_generative_service_proto_depIdxs = []int32{
	15, // 0: google.ai.generativelanguage.v1.GenerateContentRequest.contents:type_name -> google.ai.generativelanguage.v1.Content
	16, // 1: google.ai.generativelanguage.v1.GenerateContentRequest.safety_settings:type_name -> google.ai.generativelanguage.v1.SafetySetting
	4,  // 2: google.ai.generativelanguage.v1.GenerateContentRequest.generation_config:type_name -> google.ai.generativelanguage.v1.GenerationConfig
	6,  // 3: google.ai.generativelanguage.v1.GenerateContentResponse.candidates:type_name -> google.ai.generativelanguage.v1.Candidate
	14, // 4: google.ai.generativelanguage.v1.GenerateContentResponse.prompt_feedback:type_name -> google.ai.generativelanguage.v1.GenerateContentResponse.PromptFeedback
	15, // 5: google.ai.generativelanguage.v1.Candidate.content:type_name -> google.ai.generativelanguage.v1.Content
	2,  // 6: google.ai.generativelanguage.v1.Candidate.finish_reason:type_name -> google.ai.generativelanguage.v1.Candidate.FinishReason
	17, // 7: google.ai.generativelanguage.v1.Candidate.safety_ratings:type_name -> google.ai.generativelanguage.v1.SafetyRating
	18, // 8: google.ai.generativelanguage.v1.Candidate.citation_metadata:type_name -> google.ai.generativelanguage.v1.CitationMetadata
	15, // 9: google.ai.generativelanguage.v1.EmbedContentRequest.content:type_name -> google.ai.generativelanguage.v1.Content
	0,  // 10: google.ai.generativelanguage.v1.EmbedContentRequest.task_type:type_name -> google.ai.generativelanguage.v1.TaskType
	8,  // 11: google.ai.generativelanguage.v1.EmbedContentResponse.embedding:type_name -> google.ai.generativelanguage.v1.ContentEmbedding
	7,  // 12: google.ai.generativelanguage.v1.BatchEmbedContentsRequest.requests:type_name -> google.ai.generativelanguage.v1.EmbedContentRequest
	8,  // 13: google.ai.generativelanguage.v1.BatchEmbedContentsResponse.embeddings:type_name -> google.ai.generativelanguage.v1.ContentEmbedding
	15, // 14: google.ai.generativelanguage.v1.CountTokensRequest.contents:type_name -> google.ai.generativelanguage.v1.Content
	1,  // 15: google.ai.generativelanguage.v1.GenerateContentResponse.PromptFeedback.block_reason:type_name -> google.ai.generativelanguage.v1.GenerateContentResponse.PromptFeedback.BlockReason
	17, // 16: google.ai.generativelanguage.v1.GenerateContentResponse.PromptFeedback.safety_ratings:type_name -> google.ai.generativelanguage.v1.SafetyRating
	3,  // 17: google.ai.generativelanguage.v1.GenerativeService.GenerateContent:input_type -> google.ai.generativelanguage.v1.GenerateContentRequest
	3,  // 18: google.ai.generativelanguage.v1.GenerativeService.StreamGenerateContent:input_type -> google.ai.generativelanguage.v1.GenerateContentRequest
	7,  // 19: google.ai.generativelanguage.v1.GenerativeService.EmbedContent:input_type -> google.ai.generativelanguage.v1.EmbedContentRequest
	10, // 20: google.ai.generativelanguage.v1.GenerativeService.BatchEmbedContents:input_type -> google.ai.generativelanguage.v1.BatchEmbedContentsRequest
	12, // 21: google.ai.generativelanguage.v1.GenerativeService.CountTokens:input_type -> google.ai.generativelanguage.v1.CountTokensRequest
	5,  // 22: google.ai.generativelanguage.v1.GenerativeService.GenerateContent:output_type -> google.ai.generativelanguage.v1.GenerateContentResponse
	5,  // 23: google.ai.generativelanguage.v1.GenerativeService.StreamGenerateContent:output_type -> google.ai.generativelanguage.v1.GenerateContentResponse
	9,  // 24: google.ai.generativelanguage.v1.GenerativeService.EmbedContent:output_type -> google.ai.generativelanguage.v1.EmbedContentResponse
	11, // 25: google.ai.generativelanguage.v1.GenerativeService.BatchEmbedContents:output_type -> google.ai.generativelanguage.v1.BatchEmbedContentsResponse
	13, // 26: google.ai.generativelanguage.v1.GenerativeService.CountTokens:output_type -> google.ai.generativelanguage.v1.CountTokensResponse
	22, // [22:27] is the sub-list for method output_type
	17, // [17:22] is the sub-list for method input_type
	17, // [17:17] is the sub-list for extension type_name
	17, // [17:17] is the sub-list for extension extendee
	0,  // [0:17] is the sub-list for field type_name
}

func init() { file_google_ai_generativelanguage_v1_generative_service_proto_init() }
func file_google_ai_generativelanguage_v1_generative_service_proto_init() {
	if File_google_ai_generativelanguage_v1_generative_service_proto != nil {
		return
	}
	file_google_ai_generativelanguage_v1_citation_proto_init()
	file_google_ai_generativelanguage_v1_content_proto_init()
	file_google_ai_generativelanguage_v1_safety_proto_init()
	if !protoimpl.UnsafeEnabled {
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*GenerateContentRequest); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*GenerationConfig); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*GenerateContentResponse); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*Candidate); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*EmbedContentRequest); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*ContentEmbedding); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*EmbedContentResponse); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[7].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*BatchEmbedContentsRequest); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[8].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*BatchEmbedContentsResponse); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[9].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*CountTokensRequest); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[10].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*CountTokensResponse); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
		file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[11].Exporter = func(v interface{}, i int) interface{} {
			switch v := v.(*GenerateContentResponse_PromptFeedback); i {
			case 0:
				return &v.state
			case 1:
				return &v.sizeCache
			case 2:
				return &v.unknownFields
			default:
				return nil
			}
		}
	}
	file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[0].OneofWrappers = []interface{}{}
	file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[1].OneofWrappers = []interface{}{}
	file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[3].OneofWrappers = []interface{}{}
	file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes[4].OneofWrappers = []interface{}{}
	type x struct{}
	out := protoimpl.TypeBuilder{
		File: protoimpl.DescBuilder{
			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
			RawDescriptor: file_google_ai_generativelanguage_v1_generative_service_proto_rawDesc,
			NumEnums:      3,
			NumMessages:   12,
			NumExtensions: 0,
			NumServices:   1,
		},
		GoTypes:           file_google_ai_generativelanguage_v1_generative_service_proto_goTypes,
		DependencyIndexes: file_google_ai_generativelanguage_v1_generative_service_proto_depIdxs,
		EnumInfos:         file_google_ai_generativelanguage_v1_generative_service_proto_enumTypes,
		MessageInfos:      file_google_ai_generativelanguage_v1_generative_service_proto_msgTypes,
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	file_google_ai_generativelanguage_v1_generative_service_proto_rawDesc = nil
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	file_google_ai_generativelanguage_v1_generative_service_proto_depIdxs = nil
}

// Reference imports to suppress errors if they are not otherwise used.
var _ context.Context
var _ grpc.ClientConnInterface

// This is a compile-time assertion to ensure that this generated file
// is compatible with the grpc package it is being compiled against.
const _ = grpc.SupportPackageIsVersion6

// GenerativeServiceClient is the client API for GenerativeService service.
//
// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.
type GenerativeServiceClient interface {
	// Generates a response from the model given an input
	// `GenerateContentRequest`.
	GenerateContent(ctx context.Context, in *GenerateContentRequest, opts ...grpc.CallOption) (*GenerateContentResponse, error)
	// Generates a streamed response from the model given an input
	// `GenerateContentRequest`.
	StreamGenerateContent(ctx context.Context, in *GenerateContentRequest, opts ...grpc.CallOption) (GenerativeService_StreamGenerateContentClient, error)
	// Generates an embedding from the model given an input `Content`.
	EmbedContent(ctx context.Context, in *EmbedContentRequest, opts ...grpc.CallOption) (*EmbedContentResponse, error)
	// Generates multiple embeddings from the model given input text in a
	// synchronous call.
	BatchEmbedContents(ctx context.Context, in *BatchEmbedContentsRequest, opts ...grpc.CallOption) (*BatchEmbedContentsResponse, error)
	// Runs a model's tokenizer on input content and returns the token count.
	CountTokens(ctx context.Context, in *CountTokensRequest, opts ...grpc.CallOption) (*CountTokensResponse, error)
}

type generativeServiceClient struct {
	cc grpc.ClientConnInterface
}

func NewGenerativeServiceClient(cc grpc.ClientConnInterface) GenerativeServiceClient {
	return &generativeServiceClient{cc}
}

func (c *generativeServiceClient) GenerateContent(ctx context.Context, in *GenerateContentRequest, opts ...grpc.CallOption) (*GenerateContentResponse, error) {
	out := new(GenerateContentResponse)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1.GenerativeService/GenerateContent", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *generativeServiceClient) StreamGenerateContent(ctx context.Context, in *GenerateContentRequest, opts ...grpc.CallOption) (GenerativeService_StreamGenerateContentClient, error) {
	stream, err := c.cc.NewStream(ctx, &_GenerativeService_serviceDesc.Streams[0], "/google.ai.generativelanguage.v1.GenerativeService/StreamGenerateContent", opts...)
	if err != nil {
		return nil, err
	}
	x := &generativeServiceStreamGenerateContentClient{stream}
	if err := x.ClientStream.SendMsg(in); err != nil {
		return nil, err
	}
	if err := x.ClientStream.CloseSend(); err != nil {
		return nil, err
	}
	return x, nil
}

type GenerativeService_StreamGenerateContentClient interface {
	Recv() (*GenerateContentResponse, error)
	grpc.ClientStream
}

type generativeServiceStreamGenerateContentClient struct {
	grpc.ClientStream
}

func (x *generativeServiceStreamGenerateContentClient) Recv() (*GenerateContentResponse, error) {
	m := new(GenerateContentResponse)
	if err := x.ClientStream.RecvMsg(m); err != nil {
		return nil, err
	}
	return m, nil
}

func (c *generativeServiceClient) EmbedContent(ctx context.Context, in *EmbedContentRequest, opts ...grpc.CallOption) (*EmbedContentResponse, error) {
	out := new(EmbedContentResponse)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1.GenerativeService/EmbedContent", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *generativeServiceClient) BatchEmbedContents(ctx context.Context, in *BatchEmbedContentsRequest, opts ...grpc.CallOption) (*BatchEmbedContentsResponse, error) {
	out := new(BatchEmbedContentsResponse)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1.GenerativeService/BatchEmbedContents", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *generativeServiceClient) CountTokens(ctx context.Context, in *CountTokensRequest, opts ...grpc.CallOption) (*CountTokensResponse, error) {
	out := new(CountTokensResponse)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1.GenerativeService/CountTokens", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

// GenerativeServiceServer is the server API for GenerativeService service.
type GenerativeServiceServer interface {
	// Generates a response from the model given an input
	// `GenerateContentRequest`.
	GenerateContent(context.Context, *GenerateContentRequest) (*GenerateContentResponse, error)
	// Generates a streamed response from the model given an input
	// `GenerateContentRequest`.
	StreamGenerateContent(*GenerateContentRequest, GenerativeService_StreamGenerateContentServer) error
	// Generates an embedding from the model given an input `Content`.
	EmbedContent(context.Context, *EmbedContentRequest) (*EmbedContentResponse, error)
	// Generates multiple embeddings from the model given input text in a
	// synchronous call.
	BatchEmbedContents(context.Context, *BatchEmbedContentsRequest) (*BatchEmbedContentsResponse, error)
	// Runs a model's tokenizer on input content and returns the token count.
	CountTokens(context.Context, *CountTokensRequest) (*CountTokensResponse, error)
}

// UnimplementedGenerativeServiceServer can be embedded to have forward compatible implementations.
type UnimplementedGenerativeServiceServer struct {
}

func (*UnimplementedGenerativeServiceServer) GenerateContent(context.Context, *GenerateContentRequest) (*GenerateContentResponse, error) {
	return nil, status.Errorf(codes.Unimplemented, "method GenerateContent not implemented")
}
func (*UnimplementedGenerativeServiceServer) StreamGenerateContent(*GenerateContentRequest, GenerativeService_StreamGenerateContentServer) error {
	return status.Errorf(codes.Unimplemented, "method StreamGenerateContent not implemented")
}
func (*UnimplementedGenerativeServiceServer) EmbedContent(context.Context, *EmbedContentRequest) (*EmbedContentResponse, error) {
	return nil, status.Errorf(codes.Unimplemented, "method EmbedContent not implemented")
}
func (*UnimplementedGenerativeServiceServer) BatchEmbedContents(context.Context, *BatchEmbedContentsRequest) (*BatchEmbedContentsResponse, error) {
	return nil, status.Errorf(codes.Unimplemented, "method BatchEmbedContents not implemented")
}
func (*UnimplementedGenerativeServiceServer) CountTokens(context.Context, *CountTokensRequest) (*CountTokensResponse, error) {
	return nil, status.Errorf(codes.Unimplemented, "method CountTokens not implemented")
}

func RegisterGenerativeServiceServer(s *grpc.Server, srv GenerativeServiceServer) {
	s.RegisterService(&_GenerativeService_serviceDesc, srv)
}

func _GenerativeService_GenerateContent_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(GenerateContentRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(GenerativeServiceServer).GenerateContent(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1.GenerativeService/GenerateContent",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(GenerativeServiceServer).GenerateContent(ctx, req.(*GenerateContentRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _GenerativeService_StreamGenerateContent_Handler(srv interface{}, stream grpc.ServerStream) error {
	m := new(GenerateContentRequest)
	if err := stream.RecvMsg(m); err != nil {
		return err
	}
	return srv.(GenerativeServiceServer).StreamGenerateContent(m, &generativeServiceStreamGenerateContentServer{stream})
}

type GenerativeService_StreamGenerateContentServer interface {
	Send(*GenerateContentResponse) error
	grpc.ServerStream
}

type generativeServiceStreamGenerateContentServer struct {
	grpc.ServerStream
}

func (x *generativeServiceStreamGenerateContentServer) Send(m *GenerateContentResponse) error {
	return x.ServerStream.SendMsg(m)
}

func _GenerativeService_EmbedContent_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(EmbedContentRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(GenerativeServiceServer).EmbedContent(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1.GenerativeService/EmbedContent",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(GenerativeServiceServer).EmbedContent(ctx, req.(*EmbedContentRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _GenerativeService_BatchEmbedContents_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(BatchEmbedContentsRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(GenerativeServiceServer).BatchEmbedContents(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1.GenerativeService/BatchEmbedContents",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(GenerativeServiceServer).BatchEmbedContents(ctx, req.(*BatchEmbedContentsRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _GenerativeService_CountTokens_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(CountTokensRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(GenerativeServiceServer).CountTokens(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1.GenerativeService/CountTokens",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(GenerativeServiceServer).CountTokens(ctx, req.(*CountTokensRequest))
	}
	return interceptor(ctx, in, info, handler)
}

var _GenerativeService_serviceDesc = grpc.ServiceDesc{
	ServiceName: "google.ai.generativelanguage.v1.GenerativeService",
	HandlerType: (*GenerativeServiceServer)(nil),
	Methods: []grpc.MethodDesc{
		{
			MethodName: "GenerateContent",
			Handler:    _GenerativeService_GenerateContent_Handler,
		},
		{
			MethodName: "EmbedContent",
			Handler:    _GenerativeService_EmbedContent_Handler,
		},
		{
			MethodName: "BatchEmbedContents",
			Handler:    _GenerativeService_BatchEmbedContents_Handler,
		},
		{
			MethodName: "CountTokens",
			Handler:    _GenerativeService_CountTokens_Handler,
		},
	},
	Streams: []grpc.StreamDesc{
		{
			StreamName:    "StreamGenerateContent",
			Handler:       _GenerativeService_StreamGenerateContent_Handler,
			ServerStreams: true,
		},
	},
	Metadata: "google/ai/generativelanguage/v1/generative_service.proto",
}