changes from kokoro

test
ldetmer 4 weeks ago
parent 1185fe543e
commit b5c17aa969
  1. 22
      google/cloud/aiplatform/v1/aiplatform_v1.yaml
  2. 6
      google/cloud/aiplatform/v1/api_auth.proto
  3. 8
      google/cloud/aiplatform/v1/cached_content.proto
  4. 101
      google/cloud/aiplatform/v1/content.proto
  5. 7
      google/cloud/aiplatform/v1/dataset.proto
  6. 7
      google/cloud/aiplatform/v1/dataset_version.proto
  7. 20
      google/cloud/aiplatform/v1/endpoint.proto
  8. 480
      google/cloud/aiplatform/v1/evaluation_service.proto
  9. 1
      google/cloud/aiplatform/v1/feature_registry_service.proto
  10. 1
      google/cloud/aiplatform/v1/featurestore_service.proto
  11. 1
      google/cloud/aiplatform/v1/index_endpoint_service.proto
  12. 44
      google/cloud/aiplatform/v1/job_service.proto
  13. 7
      google/cloud/aiplatform/v1/llm_utility_service.proto
  14. 64
      google/cloud/aiplatform/v1/machine_resources.proto
  15. 9
      google/cloud/aiplatform/v1/model.proto
  16. 16
      google/cloud/aiplatform/v1/model_service.proto
  17. 12
      google/cloud/aiplatform/v1/notebook_execution_job.proto
  18. 6
      google/cloud/aiplatform/v1/persistent_resource.proto
  19. 143
      google/cloud/aiplatform/v1/prediction_service.proto
  20. 16
      google/cloud/aiplatform/v1/publisher_model.proto
  21. 12
      google/cloud/aiplatform/v1/reasoning_engine.proto
  22. 4
      google/cloud/aiplatform/v1/reservation_affinity.proto
  23. 1
      google/cloud/aiplatform/v1/schedule_service.proto
  24. 32
      google/cloud/aiplatform/v1/tool.proto
  25. 31
      google/cloud/aiplatform/v1/tuning_job.proto
  26. 20
      google/cloud/aiplatform/v1/vertex_rag_data.proto

@ -33,6 +33,8 @@ apis:
- name: google.cloud.aiplatform.v1.ScheduleService
- name: google.cloud.aiplatform.v1.SpecialistPoolService
- name: google.cloud.aiplatform.v1.TensorboardService
- name: google.cloud.aiplatform.v1.VertexRagDataService
- name: google.cloud.aiplatform.v1.VertexRagService
- name: google.cloud.aiplatform.v1.VizierService
- name: google.cloud.location.Locations
- name: google.iam.v1.IAMPolicy
@ -353,6 +355,7 @@ http:
- delete: '/ui/{name=projects/*/locations/*/customJobs/*/operations/*}'
- delete: '/ui/{name=projects/*/locations/*/dataLabelingJobs/*/operations/*}'
- delete: '/ui/{name=projects/*/locations/*/hyperparameterTuningJobs/*/operations/*}'
- delete: '/ui/{name=projects/*/locations/*/tuningJobs/*/operations/*}'
- delete: '/ui/{name=projects/*/locations/*/indexes/*/operations/*}'
- delete: '/ui/{name=projects/*/locations/*/indexEndpoints/*/operations/*}'
- delete: '/ui/{name=projects/*/locations/*/metadataStores/*/operations/*}'
@ -397,6 +400,7 @@ http:
- delete: '/v1/{name=projects/*/locations/*/customJobs/*/operations/*}'
- delete: '/v1/{name=projects/*/locations/*/dataLabelingJobs/*/operations/*}'
- delete: '/v1/{name=projects/*/locations/*/hyperparameterTuningJobs/*/operations/*}'
- delete: '/v1/{name=projects/*/locations/*/tuningJobs/*/operations/*}'
- delete: '/v1/{name=projects/*/locations/*/indexes/*/operations/*}'
- delete: '/v1/{name=projects/*/locations/*/indexEndpoints/*/operations/*}'
- delete: '/v1/{name=projects/*/locations/*/metadataStores/*/operations/*}'
@ -737,6 +741,10 @@ authentication:
oauth:
canonical_scopes: |-
https://www.googleapis.com/auth/cloud-platform
- selector: google.cloud.aiplatform.v1.EvaluationService.EvaluateDataset
oauth:
canonical_scopes: |-
https://www.googleapis.com/auth/cloud-platform
- selector: google.cloud.aiplatform.v1.EvaluationService.EvaluateInstances
oauth:
canonical_scopes: |-
@ -953,25 +961,11 @@ publishing:
organization: CLOUD
library_settings:
- version: google.cloud.aiplatform.v1
java_settings:
common: {}
cpp_settings:
common: {}
php_settings:
common: {}
python_settings:
common: {}
experimental_features:
rest_async_io_enabled: true
node_settings:
common: {}
dotnet_settings:
common: {}
renamed_resources:
datalabeling.googleapis.com/Dataset: DataLabelingDataset
automl.googleapis.com/Dataset: AutoMLDataset
automl.googleapis.com/Model: AutoMLModel
ruby_settings:
common: {}
go_settings:
common: {}

@ -26,12 +26,10 @@ option java_outer_classname = "ApiAuthProto";
option java_package = "com.google.cloud.aiplatform.v1";
option php_namespace = "Google\\Cloud\\AIPlatform\\V1";
option ruby_package = "Google::Cloud::AIPlatform::V1";
option (google.api.resource_definition) = {
type: "secretmanager.googleapis.com/SecretVersion"
pattern: "projects/{project}/secrets/{secret}/versions/{secret_version}"
};
// The generic reusable api auth config.
// Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto)
// instead.
message ApiAuth {
// The API secret.
message ApiKeyConfig {

@ -87,9 +87,9 @@ message CachedContent {
(google.api.field_behavior) = IMMUTABLE
];
// Immutable. The name of the publisher model to use for cached content.
// Format:
// projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
// Immutable. The name of the `Model` to use for cached content. Currently,
// only the published Gemini base models are supported, in form of
// projects/{PROJECT}/locations/{LOCATION}/publishers/google/models/{MODEL}
string model = 2 [(google.api.field_behavior) = IMMUTABLE];
// Optional. Input only. Immutable. Developer set system instruction.
@ -123,7 +123,7 @@ message CachedContent {
(google.api.field_behavior) = INPUT_ONLY
];
// Output only. Creatation time of the cache entry.
// Output only. Creation time of the cache entry.
google.protobuf.Timestamp create_time = 7
[(google.api.field_behavior) = OUTPUT_ONLY];

@ -17,6 +17,7 @@ syntax = "proto3";
package google.cloud.aiplatform.v1;
import "google/api/field_behavior.proto";
import "google/api/resource.proto";
import "google/cloud/aiplatform/v1/openapi.proto";
import "google/cloud/aiplatform/v1/tool.proto";
import "google/protobuf/duration.proto";
@ -29,6 +30,10 @@ option java_outer_classname = "ContentProto";
option java_package = "com.google.cloud.aiplatform.v1";
option php_namespace = "Google\\Cloud\\AIPlatform\\V1";
option ruby_package = "Google::Cloud::AIPlatform::V1";
option (google.api.resource_definition) = {
type: "modelarmor.googleapis.com/Template"
pattern: "projects/{project}/locations/{location}/templates/{template}"
};
// Harm categories that will block the content.
enum HarmCategory {
@ -135,15 +140,20 @@ message Part {
}
// Content blob.
//
// It's preferred to send as [text][google.cloud.aiplatform.v1.Part.text]
// directly rather than raw bytes.
message Blob {
// Required. The IANA standard MIME type of the source data.
string mime_type = 1 [(google.api.field_behavior) = REQUIRED];
// Required. Raw bytes.
bytes data = 2 [(google.api.field_behavior) = REQUIRED];
// Optional. Display name of the blob.
//
// Used to provide a label or filename to distinguish blobs.
//
// This field is only returned in PromptMessage for prompt management.
// It is not currently used in the Gemini GenerateContent calls.
string display_name = 4 [(google.api.field_behavior) = OPTIONAL];
}
// URI based data.
@ -153,6 +163,14 @@ message FileData {
// Required. URI.
string file_uri = 2 [(google.api.field_behavior) = REQUIRED];
// Optional. Display name of the file data.
//
// Used to provide a label or filename to distinguish file datas.
//
// This field is only returned in PromptMessage for prompt management.
// It is not currently used in the Gemini GenerateContent calls.
string display_name = 3 [(google.api.field_behavior) = OPTIONAL];
}
// Metadata describes the input video content.
@ -166,6 +184,27 @@ message VideoMetadata {
[(google.api.field_behavior) = OPTIONAL];
}
// The configuration for the prebuilt speaker to use.
message PrebuiltVoiceConfig {
// The name of the preset voice to use.
optional string voice_name = 1;
}
// The configuration for the voice to use.
message VoiceConfig {
// The configuration for the speaker to use.
oneof voice_config {
// The configuration for the prebuilt voice to use.
PrebuiltVoiceConfig prebuilt_voice_config = 1;
}
}
// The speech generation config.
message SpeechConfig {
// The configuration for the speaker to use.
VoiceConfig voice_config = 1;
}
// Generation config.
message GenerationConfig {
// The configuration for routing the request to a specific model.
@ -210,6 +249,36 @@ message GenerationConfig {
}
}
// The modalities of the response.
enum Modality {
// Unspecified modality. Will be processed as text.
MODALITY_UNSPECIFIED = 0;
// Text modality.
TEXT = 1;
// Image modality.
IMAGE = 2;
// Audio modality.
AUDIO = 3;
}
// Media resolution for the input media.
enum MediaResolution {
// Media resolution has not been set.
MEDIA_RESOLUTION_UNSPECIFIED = 0;
// Media resolution set to low (64 tokens).
MEDIA_RESOLUTION_LOW = 1;
// Media resolution set to medium (256 tokens).
MEDIA_RESOLUTION_MEDIUM = 2;
// Media resolution set to high (zoomed reframing with 256 tokens).
MEDIA_RESOLUTION_HIGH = 3;
}
// Optional. Controls the randomness of predictions.
optional float temperature = 1 [(google.api.field_behavior) = OPTIONAL];
@ -264,6 +333,22 @@ message GenerationConfig {
// Optional. Routing configuration.
optional RoutingConfig routing_config = 17
[(google.api.field_behavior) = OPTIONAL];
// Optional. If enabled, audio timestamp will be included in the request to
// the model.
optional bool audio_timestamp = 20 [(google.api.field_behavior) = OPTIONAL];
// Optional. The modalities of the response.
repeated Modality response_modalities = 21
[(google.api.field_behavior) = OPTIONAL];
// Optional. If specified, the media resolution specified will be used.
optional MediaResolution media_resolution = 22
[(google.api.field_behavior) = OPTIONAL];
// Optional. The speech generation config.
optional SpeechConfig speech_config = 23
[(google.api.field_behavior) = OPTIONAL];
}
// Safety settings.
@ -419,8 +504,7 @@ message Candidate {
// content filters blocks the output.
SAFETY = 3;
// Token generation stopped because the content potentially contains
// copyright violations.
// The token generation stopped because of potential recitation.
RECITATION = 4;
// All other reasons that stopped the token generation.
@ -446,9 +530,6 @@ message Candidate {
// Output only. Content parts of the candidate.
Content content = 2 [(google.api.field_behavior) = OUTPUT_ONLY];
// Output only. Confidence score of the candidate.
double score = 8 [(google.api.field_behavior) = OUTPUT_ONLY];
// Output only. Average log probability score of the candidate.
double avg_logprobs = 9 [(google.api.field_behavior) = OUTPUT_ONLY];
@ -484,10 +565,10 @@ message Candidate {
message LogprobsResult {
// Candidate for the logprobs token and score.
message Candidate {
// The candidates token string value.
// The candidate's token string value.
optional string token = 1;
// The candidates token id value.
// The candidate's token id value.
optional int32 token_id = 3;
// The candidate's log probability.

@ -40,9 +40,14 @@ message Dataset {
};
// Output only. Identifier. The resource name of the Dataset.
// Format:
// `projects/{project}/locations/{location}/datasets/{dataset}`
string name = 1 [
(google.api.field_behavior) = OUTPUT_ONLY,
(google.api.field_behavior) = IDENTIFIER
(google.api.field_behavior) = IDENTIFIER,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Dataset"
}
];
// Required. The user-defined name of the Dataset.

@ -37,9 +37,14 @@ message DatasetVersion {
};
// Output only. Identifier. The resource name of the DatasetVersion.
// Format:
// `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`
string name = 1 [
(google.api.field_behavior) = OUTPUT_ONLY,
(google.api.field_behavior) = IDENTIFIER
(google.api.field_behavior) = IDENTIFIER,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/DatasetVersion"
}
];
// Output only. Timestamp when this DatasetVersion was created.

@ -176,6 +176,12 @@ message Endpoint {
// Output only. Reserved for future use.
bool satisfies_pzi = 28 [(google.api.field_behavior) = OUTPUT_ONLY];
// Optional. Configuration for GenAiAdvancedFeatures. If the endpoint is
// serving GenAI models, advanced features like native RAG integration can be
// configured. Currently, only Model Garden models are supported.
GenAiAdvancedFeaturesConfig gen_ai_advanced_features_config = 29
[(google.api.field_behavior) = OPTIONAL];
}
// A deployment of a Model. Endpoints contain one or more DeployedModels.
@ -377,6 +383,20 @@ message FasterDeploymentConfig {
bool fast_tryout_enabled = 2;
}
// Configuration for GenAiAdvancedFeatures.
message GenAiAdvancedFeaturesConfig {
// Configuration for Retrieval Augmented Generation feature.
message RagConfig {
// If true, enable Retrieval Augmented Generation in ChatCompletion request.
// Once enabled, the endpoint will be identified as GenAI endpoint and
// Arthedain router will be used.
bool enable_rag = 1;
}
// Configuration for Retrieval Augmented Generation feature.
RagConfig rag_config = 1;
}
// Configuration for Speculative Decoding.
message SpeculativeDecodingSpec {
// Draft model speculation works by using the smaller model to generate

@ -20,6 +20,9 @@ import "google/api/annotations.proto";
import "google/api/client.proto";
import "google/api/field_behavior.proto";
import "google/api/resource.proto";
import "google/cloud/aiplatform/v1/io.proto";
import "google/cloud/aiplatform/v1/operation.proto";
import "google/longrunning/operations.proto";
option csharp_namespace = "Google.Cloud.AIPlatform.V1";
option go_package = "cloud.google.com/go/aiplatform/apiv1/aiplatformpb;aiplatformpb";
@ -43,6 +46,19 @@ service EvaluationService {
body: "*"
};
}
// Evaluates a dataset based on a set of given metrics.
rpc EvaluateDataset(EvaluateDatasetRequest)
returns (google.longrunning.Operation) {
option (google.api.http) = {
post: "/v1/{location=projects/*/locations/*}:evaluateDataset"
body: "*"
};
option (google.longrunning.operation_info) = {
response_type: "EvaluateDatasetResponse"
metadata_type: "EvaluateDatasetOperationMetadata"
};
}
}
// Pairwise prediction autorater preference.
@ -60,6 +76,161 @@ enum PairwiseChoice {
TIE = 3;
}
// Operation metadata for Dataset Evaluation.
message EvaluateDatasetOperationMetadata {
// Generic operation metadata.
GenericOperationMetadata generic_metadata = 1;
}
// Response in LRO for EvaluationService.EvaluateDataset.
message EvaluateDatasetResponse {
// Output only. Output info for EvaluationService.EvaluateDataset.
OutputInfo output_info = 3 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Describes the info for output of EvaluationService.EvaluateDataset.
message OutputInfo {
// The output location into which evaluation output is written.
oneof output_location {
// Output only. The full path of the Cloud Storage directory created, into
// which the evaluation results and aggregation results are written.
string gcs_output_directory = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
}
}
// Request message for EvaluationService.EvaluateDataset.
message EvaluateDatasetRequest {
// Required. The resource name of the Location to evaluate the dataset.
// Format: `projects/{project}/locations/{location}`
string location = 1 [
(google.api.field_behavior) = REQUIRED,
(google.api.resource_reference) = {
type: "locations.googleapis.com/Location"
}
];
// Required. The dataset used for evaluation.
EvaluationDataset dataset = 2 [(google.api.field_behavior) = REQUIRED];
// Required. The metrics used for evaluation.
repeated Metric metrics = 3 [(google.api.field_behavior) = REQUIRED];
// Required. Config for evaluation output.
OutputConfig output_config = 4 [(google.api.field_behavior) = REQUIRED];
// Optional. Autorater config used for evaluation.
AutoraterConfig autorater_config = 5 [(google.api.field_behavior) = OPTIONAL];
}
// Config for evaluation output.
message OutputConfig {
// The destination for evaluation output.
oneof destination {
// Cloud storage destination for evaluation output.
GcsDestination gcs_destination = 1;
}
}
// The metric used for dataset level evaluation.
message Metric {
// The aggregation metrics supported by EvaluationService.EvaluateDataset.
enum AggregationMetric {
// Unspecified aggregation metric.
AGGREGATION_METRIC_UNSPECIFIED = 0;
// Average aggregation metric.
AVERAGE = 1;
// Mode aggregation metric.
MODE = 2;
// Standard deviation aggregation metric.
STANDARD_DEVIATION = 3;
// Variance aggregation metric.
VARIANCE = 4;
// Minimum aggregation metric.
MINIMUM = 5;
// Maximum aggregation metric.
MAXIMUM = 6;
// Median aggregation metric.
MEDIAN = 7;
// 90th percentile aggregation metric.
PERCENTILE_P90 = 8;
// 95th percentile aggregation metric.
PERCENTILE_P95 = 9;
// 99th percentile aggregation metric.
PERCENTILE_P99 = 10;
}
// The metric spec used for evaluation.
oneof metric_spec {
// Spec for pointwise metric.
PointwiseMetricSpec pointwise_metric_spec = 2;
// Spec for pairwise metric.
PairwiseMetricSpec pairwise_metric_spec = 3;
// Spec for exact match metric.
ExactMatchSpec exact_match_spec = 4;
// Spec for bleu metric.
BleuSpec bleu_spec = 5;
// Spec for rouge metric.
RougeSpec rouge_spec = 6;
}
// Optional. The aggregation metrics to use.
repeated AggregationMetric aggregation_metrics = 1
[(google.api.field_behavior) = OPTIONAL];
}
// The dataset used for evaluation.
message EvaluationDataset {
// The source of the dataset.
oneof source {
// Cloud storage source holds the dataset.
GcsSource gcs_source = 1;
// BigQuery source holds the dataset.
BigQuerySource bigquery_source = 2;
}
}
// The configs for autorater. This is applicable to both EvaluateInstances and
// EvaluateDataset.
message AutoraterConfig {
// Optional. Number of samples for each instance in the dataset.
// If not specified, the default is 4. Minimum value is 1, maximum value
// is 32.
optional int32 sampling_count = 1 [(google.api.field_behavior) = OPTIONAL];
// Optional. Whether to flip the candidate and baseline responses.
// This is only applicable to the pairwise metric. If enabled, also provide
// PairwiseMetricSpec.candidate_response_field_name and
// PairwiseMetricSpec.baseline_response_field_name. When rendering
// PairwiseMetricSpec.metric_prompt_template, the candidate and baseline
// fields will be flipped for half of the samples to reduce bias.
optional bool flip_enabled = 2 [(google.api.field_behavior) = OPTIONAL];
// Optional. The fully qualified name of the publisher model or tuned
// autorater endpoint to use.
//
// Publisher model format:
// `projects/{project}/locations/{location}/publishers/*/models/*`
//
// Tuned model endpoint format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
string autorater_model = 3 [(google.api.field_behavior) = OPTIONAL];
}
// Request message for EvaluationService.EvaluateInstances.
message EvaluateInstancesRequest {
// Instances and specs for evaluation
@ -146,6 +317,24 @@ message EvaluateInstancesRequest {
// Input for Metricx metric.
MetricxInput metricx_input = 32;
// Input for trajectory exact match metric.
TrajectoryExactMatchInput trajectory_exact_match_input = 33;
// Input for trajectory in order match metric.
TrajectoryInOrderMatchInput trajectory_in_order_match_input = 34;
// Input for trajectory match any order metric.
TrajectoryAnyOrderMatchInput trajectory_any_order_match_input = 35;
// Input for trajectory precision metric.
TrajectoryPrecisionInput trajectory_precision_input = 37;
// Input for trajectory recall metric.
TrajectoryRecallInput trajectory_recall_input = 38;
// Input for trajectory single tool use metric.
TrajectorySingleToolUseInput trajectory_single_tool_use_input = 39;
}
// Required. The resource name of the Location to evaluate the instances.
@ -156,6 +345,10 @@ message EvaluateInstancesRequest {
type: "locations.googleapis.com/Location"
}
];
// Optional. Autorater config used for evaluation.
AutoraterConfig autorater_config = 30
[(google.api.field_behavior) = OPTIONAL];
}
// Response message for EvaluationService.EvaluateInstances.
@ -249,6 +442,24 @@ message EvaluateInstancesResponse {
// Result for Metricx metric.
MetricxResult metricx_result = 30;
// Result for trajectory exact match metric.
TrajectoryExactMatchResults trajectory_exact_match_results = 31;
// Result for trajectory in order match metric.
TrajectoryInOrderMatchResults trajectory_in_order_match_results = 32;
// Result for trajectory any order match metric.
TrajectoryAnyOrderMatchResults trajectory_any_order_match_results = 33;
// Result for trajectory precision metric.
TrajectoryPrecisionResults trajectory_precision_results = 35;
// Results for trajectory recall metric.
TrajectoryRecallResults trajectory_recall_results = 36;
// Results for trajectory single tool use metric.
TrajectorySingleToolUseResults trajectory_single_tool_use_results = 37;
}
}
@ -1010,6 +1221,10 @@ message PointwiseMetricSpec {
// Required. Metric prompt template for pointwise metric.
optional string metric_prompt_template = 1
[(google.api.field_behavior) = REQUIRED];
// Optional. System instructions for pointwise metric.
optional string system_instruction = 2
[(google.api.field_behavior) = OPTIONAL];
}
// Spec for pointwise metric result.
@ -1047,6 +1262,18 @@ message PairwiseMetricSpec {
// Required. Metric prompt template for pairwise metric.
optional string metric_prompt_template = 1
[(google.api.field_behavior) = REQUIRED];
// Optional. The field name of the candidate response.
string candidate_response_field_name = 2
[(google.api.field_behavior) = OPTIONAL];
// Optional. The field name of the baseline response.
string baseline_response_field_name = 3
[(google.api.field_behavior) = OPTIONAL];
// Optional. System instructions for pairwise metric.
optional string system_instruction = 4
[(google.api.field_behavior) = OPTIONAL];
}
// Spec for pairwise metric result.
@ -1315,3 +1542,256 @@ message MetricxResult {
// Output only. MetricX score. Range depends on version.
optional float score = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Instances and metric spec for TrajectoryExactMatch metric.
message TrajectoryExactMatchInput {
// Required. Spec for TrajectoryExactMatch metric.
TrajectoryExactMatchSpec metric_spec = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Repeated TrajectoryExactMatch instance.
repeated TrajectoryExactMatchInstance instances = 2
[(google.api.field_behavior) = REQUIRED];
}
// Spec for TrajectoryExactMatch metric - returns 1 if tool calls in the
// reference trajectory exactly match the predicted trajectory, else 0.
message TrajectoryExactMatchSpec {}
// Spec for TrajectoryExactMatch instance.
message TrajectoryExactMatchInstance {
// Required. Spec for predicted tool call trajectory.
optional Trajectory predicted_trajectory = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Spec for reference tool call trajectory.
optional Trajectory reference_trajectory = 2
[(google.api.field_behavior) = REQUIRED];
}
// Results for TrajectoryExactMatch metric.
message TrajectoryExactMatchResults {
// Output only. TrajectoryExactMatch metric values.
repeated TrajectoryExactMatchMetricValue
trajectory_exact_match_metric_values = 1
[(google.api.field_behavior) = OUTPUT_ONLY];
}
// TrajectoryExactMatch metric value for an instance.
message TrajectoryExactMatchMetricValue {
// Output only. TrajectoryExactMatch score.
optional float score = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Instances and metric spec for TrajectoryInOrderMatch metric.
message TrajectoryInOrderMatchInput {
// Required. Spec for TrajectoryInOrderMatch metric.
TrajectoryInOrderMatchSpec metric_spec = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Repeated TrajectoryInOrderMatch instance.
repeated TrajectoryInOrderMatchInstance instances = 2
[(google.api.field_behavior) = REQUIRED];
}
// Spec for TrajectoryInOrderMatch metric - returns 1 if tool calls in the
// reference trajectory appear in the predicted trajectory in the same order,
// else 0.
message TrajectoryInOrderMatchSpec {}
// Spec for TrajectoryInOrderMatch instance.
message TrajectoryInOrderMatchInstance {
// Required. Spec for predicted tool call trajectory.
optional Trajectory predicted_trajectory = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Spec for reference tool call trajectory.
optional Trajectory reference_trajectory = 2
[(google.api.field_behavior) = REQUIRED];
}
// Results for TrajectoryInOrderMatch metric.
message TrajectoryInOrderMatchResults {
// Output only. TrajectoryInOrderMatch metric values.
repeated TrajectoryInOrderMatchMetricValue
trajectory_in_order_match_metric_values = 1
[(google.api.field_behavior) = OUTPUT_ONLY];
}
// TrajectoryInOrderMatch metric value for an instance.
message TrajectoryInOrderMatchMetricValue {
// Output only. TrajectoryInOrderMatch score.
optional float score = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Instances and metric spec for TrajectoryAnyOrderMatch metric.
message TrajectoryAnyOrderMatchInput {
// Required. Spec for TrajectoryAnyOrderMatch metric.
TrajectoryAnyOrderMatchSpec metric_spec = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Repeated TrajectoryAnyOrderMatch instance.
repeated TrajectoryAnyOrderMatchInstance instances = 2
[(google.api.field_behavior) = REQUIRED];
}
// Spec for TrajectoryAnyOrderMatch metric - returns 1 if all tool calls in the
// reference trajectory appear in the predicted trajectory in any order, else
// 0.
message TrajectoryAnyOrderMatchSpec {}
// Spec for TrajectoryAnyOrderMatch instance.
message TrajectoryAnyOrderMatchInstance {
// Required. Spec for predicted tool call trajectory.
optional Trajectory predicted_trajectory = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Spec for reference tool call trajectory.
optional Trajectory reference_trajectory = 2
[(google.api.field_behavior) = REQUIRED];
}
// Results for TrajectoryAnyOrderMatch metric.
message TrajectoryAnyOrderMatchResults {
// Output only. TrajectoryAnyOrderMatch metric values.
repeated TrajectoryAnyOrderMatchMetricValue
trajectory_any_order_match_metric_values = 1
[(google.api.field_behavior) = OUTPUT_ONLY];
}
// TrajectoryAnyOrderMatch metric value for an instance.
message TrajectoryAnyOrderMatchMetricValue {
// Output only. TrajectoryAnyOrderMatch score.
optional float score = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Instances and metric spec for TrajectoryPrecision metric.
message TrajectoryPrecisionInput {
// Required. Spec for TrajectoryPrecision metric.
TrajectoryPrecisionSpec metric_spec = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Repeated TrajectoryPrecision instance.
repeated TrajectoryPrecisionInstance instances = 2
[(google.api.field_behavior) = REQUIRED];
}
// Spec for TrajectoryPrecision metric - returns a float score based on average
// precision of individual tool calls.
message TrajectoryPrecisionSpec {}
// Spec for TrajectoryPrecision instance.
message TrajectoryPrecisionInstance {
// Required. Spec for predicted tool call trajectory.
optional Trajectory predicted_trajectory = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Spec for reference tool call trajectory.
optional Trajectory reference_trajectory = 2
[(google.api.field_behavior) = REQUIRED];
}
// Results for TrajectoryPrecision metric.
message TrajectoryPrecisionResults {
// Output only. TrajectoryPrecision metric values.
repeated TrajectoryPrecisionMetricValue trajectory_precision_metric_values = 1
[(google.api.field_behavior) = OUTPUT_ONLY];
}
// TrajectoryPrecision metric value for an instance.
message TrajectoryPrecisionMetricValue {
// Output only. TrajectoryPrecision score.
optional float score = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Instances and metric spec for TrajectoryRecall metric.
message TrajectoryRecallInput {
// Required. Spec for TrajectoryRecall metric.
TrajectoryRecallSpec metric_spec = 1 [(google.api.field_behavior) = REQUIRED];
// Required. Repeated TrajectoryRecall instance.
repeated TrajectoryRecallInstance instances = 2
[(google.api.field_behavior) = REQUIRED];
}
// Spec for TrajectoryRecall metric - returns a float score based on average
// recall of individual tool calls.
message TrajectoryRecallSpec {}
// Spec for TrajectoryRecall instance.
message TrajectoryRecallInstance {
// Required. Spec for predicted tool call trajectory.
optional Trajectory predicted_trajectory = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Spec for reference tool call trajectory.
optional Trajectory reference_trajectory = 2
[(google.api.field_behavior) = REQUIRED];
}
// Results for TrajectoryRecall metric.
message TrajectoryRecallResults {
// Output only. TrajectoryRecall metric values.
repeated TrajectoryRecallMetricValue trajectory_recall_metric_values = 1
[(google.api.field_behavior) = OUTPUT_ONLY];
}
// TrajectoryRecall metric value for an instance.
message TrajectoryRecallMetricValue {
// Output only. TrajectoryRecall score.
optional float score = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Instances and metric spec for TrajectorySingleToolUse metric.
message TrajectorySingleToolUseInput {
// Required. Spec for TrajectorySingleToolUse metric.
TrajectorySingleToolUseSpec metric_spec = 1
[(google.api.field_behavior) = REQUIRED];
// Required. Repeated TrajectorySingleToolUse instance.
repeated TrajectorySingleToolUseInstance instances = 2
[(google.api.field_behavior) = REQUIRED];
}
// Spec for TrajectorySingleToolUse metric - returns 1 if tool is present in the
// predicted trajectory, else 0.
message TrajectorySingleToolUseSpec {
// Required. Spec for tool name to be checked for in the predicted trajectory.
optional string tool_name = 1 [(google.api.field_behavior) = REQUIRED];
}
// Spec for TrajectorySingleToolUse instance.
message TrajectorySingleToolUseInstance {
// Required. Spec for predicted tool call trajectory.
optional Trajectory predicted_trajectory = 1
[(google.api.field_behavior) = REQUIRED];
}
// Results for TrajectorySingleToolUse metric.
message TrajectorySingleToolUseResults {
// Output only. TrajectorySingleToolUse metric values.
repeated TrajectorySingleToolUseMetricValue
trajectory_single_tool_use_metric_values = 1
[(google.api.field_behavior) = OUTPUT_ONLY];
}
// TrajectorySingleToolUse metric value for an instance.
message TrajectorySingleToolUseMetricValue {
// Output only. TrajectorySingleToolUse score.
optional float score = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Spec for trajectory.
message Trajectory {
// Required. Tool calls in the trajectory.
repeated ToolCall tool_calls = 1 [(google.api.field_behavior) = REQUIRED];
}
// Spec for tool call.
message ToolCall {
// Required. Spec for tool name
optional string tool_name = 1 [(google.api.field_behavior) = REQUIRED];
// Optional. Spec for tool input
optional string tool_input = 2 [(google.api.field_behavior) = OPTIONAL];
}

@ -303,6 +303,7 @@ message UpdateFeatureGroupRequest {
// * `description`
// * `big_query`
// * `big_query.entity_id_columns`
// * `service_agent_type`
google.protobuf.FieldMask update_mask = 2;
}

@ -1176,7 +1176,6 @@ message SearchFeaturesRequest {
// containing the substring `foo` and description containing the substring
// `bar`.
//
//
// Besides field queries, the following exact-match filters are
// supported. The exact-match filters do not support wildcards. Unlike
// field-restricted queries, exact-match filters are case-sensitive.

@ -95,7 +95,6 @@ service IndexEndpointService {
// Deploys an Index into this IndexEndpoint, creating a DeployedIndex within
// it.
// Only non-empty Indexes can be deployed.
rpc DeployIndex(DeployIndexRequest) returns (google.longrunning.Operation) {
option (google.api.http) = {
post: "/v1/{index_endpoint=projects/*/locations/*/indexEndpoints/*}:deployIndex"

@ -1293,31 +1293,33 @@ message UpdateModelDeploymentMonitoringJobRequest {
[(google.api.field_behavior) = REQUIRED];
// Required. The update mask is used to specify the fields to be overwritten
// in the ModelDeploymentMonitoringJob resource by the update. The fields
// specified in the update_mask are relative to the resource, not the full
// request. A field will be overwritten if it is in the mask. If the user does
// not provide a mask then only the non-empty fields present in the request
// will be overwritten. Set the update_mask to `*` to override all fields. For
// the objective config, the user can either provide the update mask for
// model_deployment_monitoring_objective_configs or any combination of its
// nested fields, such as:
// model_deployment_monitoring_objective_configs.objective_config.training_dataset.
// in the
// ModelDeploymentMonitoringJob resource by the update.
// The fields specified in the update_mask are relative to the resource, not
// the full request. A field will be overwritten if it is in the mask. If the
// user does not provide a mask then only the non-empty fields present in the
// request will be overwritten. Set the update_mask to `*` to override all
// fields.
// For the objective config, the user can either provide the update mask for
// model_deployment_monitoring_objective_configs or any combination of its
// nested fields, such as:
// model_deployment_monitoring_objective_configs.objective_config.training_dataset.
//
// Updatable fields:
// Updatable fields:
//
// * `display_name`
// * `model_deployment_monitoring_schedule_config`
// * `model_monitoring_alert_config`
// * `logging_sampling_strategy`
// * `labels`
// * `log_ttl`
// * `enable_monitoring_pipeline_logs`
// * `display_name`
// * `model_deployment_monitoring_schedule_config`
// * `model_monitoring_alert_config`
// * `logging_sampling_strategy`
// * `labels`
// * `log_ttl`
// * `enable_monitoring_pipeline_logs`
// . and
// * `model_deployment_monitoring_objective_configs`
// * `model_deployment_monitoring_objective_configs`
// . or
// * `model_deployment_monitoring_objective_configs.objective_config.training_dataset`
// * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config`
// * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`
// * `model_deployment_monitoring_objective_configs.objective_config.training_dataset`
// * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config`
// * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`
google.protobuf.FieldMask update_mask = 2
[(google.api.field_behavior) = REQUIRED];
}

@ -101,7 +101,12 @@ message ComputeTokensRequest {
// Optional. The name of the publisher model requested to serve the
// prediction. Format:
// projects/{project}/locations/{location}/publishers/*/models/*
string model = 3 [(google.api.field_behavior) = OPTIONAL];
string model = 3 [
(google.api.field_behavior) = OPTIONAL,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Endpoint"
}
];
// Optional. Input content.
repeated Content contents = 4 [(google.api.field_behavior) = OPTIONAL];

@ -58,6 +58,13 @@ message MachineSpec {
// available from GKE. (Example: tpu_topology: "2x2x1").
string tpu_topology = 4 [(google.api.field_behavior) = IMMUTABLE];
// Optional. Immutable. The number of nodes per replica for multihost GPU
// deployments.
int32 multihost_gpu_node_count = 6 [
(google.api.field_behavior) = IMMUTABLE,
(google.api.field_behavior) = OPTIONAL
];
// Optional. Immutable. Configuration controlling how this resource pool
// consumes reservation.
ReservationAffinity reservation_affinity = 5 [
@ -66,35 +73,31 @@ message MachineSpec {
];
}
// A description of resources that are dedicated to a DeployedModel, and
// that need a higher degree of manual configuration.
// A description of resources that are dedicated to a DeployedModel or
// DeployedIndex, and that need a higher degree of manual configuration.
message DedicatedResources {
// Required. Immutable. The specification of a single machine used by the
// prediction.
// Required. Immutable. The specification of a single machine being used.
MachineSpec machine_spec = 1 [
(google.api.field_behavior) = REQUIRED,
(google.api.field_behavior) = IMMUTABLE
];
// Required. Immutable. The minimum number of machine replicas this
// DeployedModel will be always deployed on. This value must be greater than
// or equal to 1.
// Required. Immutable. The minimum number of machine replicas that will be
// always deployed on. This value must be greater than or equal to 1.
//
// If traffic against the DeployedModel increases, it may dynamically be
// deployed onto more replicas, and as traffic decreases, some of these extra
// replicas may be freed.
// If traffic increases, it may dynamically be deployed onto more replicas,
// and as traffic decreases, some of these extra replicas may be freed.
int32 min_replica_count = 2 [
(google.api.field_behavior) = REQUIRED,
(google.api.field_behavior) = IMMUTABLE
];
// Immutable. The maximum number of replicas this DeployedModel may be
// deployed on when the traffic against it increases. If the requested value
// is too large, the deployment will error, but if deployment succeeds then
// the ability to scale the model to that many replicas is guaranteed (barring
// service outages). If traffic against the DeployedModel increases beyond
// what its replicas at maximum may handle, a portion of the traffic will be
// dropped. If this value is not provided, will use
// Immutable. The maximum number of replicas that may be deployed on when the
// traffic against it increases. If the requested value is too large, the
// deployment will error, but if deployment succeeds then the ability to scale
// to that many replicas is guaranteed (barring service outages). If traffic
// increases beyond what its replicas at maximum may handle, a portion of the
// traffic will be dropped. If this value is not provided, will use
// [min_replica_count][google.cloud.aiplatform.v1.DedicatedResources.min_replica_count]
// as the default value.
//
@ -105,8 +108,8 @@ message DedicatedResources {
int32 max_replica_count = 3 [(google.api.field_behavior) = IMMUTABLE];
// Optional. Number of required available replicas for the deployment to
// succeed. This field is only needed when partial model deployment/mutation
// is desired. If set, the model deploy/mutate operation will succeed once
// succeed. This field is only needed when partial deployment/mutation is
// desired. If set, the deploy/mutate operation will succeed once
// available_replica_count reaches required_replica_count, and the rest of
// the replicas will be retried. If not set, the default
// required_replica_count will be min_replica_count.
@ -147,23 +150,22 @@ message DedicatedResources {
// and require only a modest additional configuration.
// Each Model supporting these resources documents its specific guidelines.
message AutomaticResources {
// Immutable. The minimum number of replicas this DeployedModel will be always
// deployed on. If traffic against it increases, it may dynamically be
// deployed onto more replicas up to
// Immutable. The minimum number of replicas that will be always deployed on.
// If traffic against it increases, it may dynamically be deployed onto more
// replicas up to
// [max_replica_count][google.cloud.aiplatform.v1.AutomaticResources.max_replica_count],
// and as traffic decreases, some of these extra replicas may be freed. If the
// requested value is too large, the deployment will error.
int32 min_replica_count = 1 [(google.api.field_behavior) = IMMUTABLE];
// Immutable. The maximum number of replicas this DeployedModel may be
// deployed on when the traffic against it increases. If the requested value
// is too large, the deployment will error, but if deployment succeeds then
// the ability to scale the model to that many replicas is guaranteed (barring
// service outages). If traffic against the DeployedModel increases beyond
// what its replicas at maximum may handle, a portion of the traffic will be
// dropped. If this value is not provided, a no upper bound for scaling under
// heavy traffic will be assume, though Vertex AI may be unable to scale
// beyond certain replica number.
// Immutable. The maximum number of replicas that may be deployed on when the
// traffic against it increases. If the requested value is too large, the
// deployment will error, but if deployment succeeds then the ability to scale
// to that many replicas is guaranteed (barring service outages). If traffic
// increases beyond what its replicas at maximum may handle, a portion of the
// traffic will be dropped. If this value is not provided, a no upper bound
// for scaling under heavy traffic will be assume, though Vertex AI may be
// unable to scale beyond certain replica number.
int32 max_replica_count = 2 [(google.api.field_behavior) = IMMUTABLE];
}

@ -84,6 +84,9 @@ message Model {
//
// * `custom-trained`
// A Model that was uploaded or trained by custom code.
//
// * `genie`
// A tuned Model Garden model.
string id = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
// Output only. The content of this Model that may be exported.
@ -493,6 +496,12 @@ message LargeModelReference {
message ModelGardenSource {
// Required. The model garden source model resource name.
string public_model_name = 1 [(google.api.field_behavior) = REQUIRED];
// Optional. The model garden source model version ID.
string version_id = 3 [(google.api.field_behavior) = OPTIONAL];
// Optional. Whether to avoid pulling the model from the HF cache.
bool skip_hf_model_cache = 4 [(google.api.field_behavior) = OPTIONAL];
}
// Contains information about the source of the models generated from Generative

@ -27,6 +27,7 @@ import "google/cloud/aiplatform/v1/io.proto";
import "google/cloud/aiplatform/v1/model.proto";
import "google/cloud/aiplatform/v1/model_evaluation.proto";
import "google/cloud/aiplatform/v1/model_evaluation_slice.proto";
import "google/cloud/aiplatform/v1/model_version_checkpoint.proto";
import "google/cloud/aiplatform/v1/operation.proto";
import "google/longrunning/operations.proto";
import "google/protobuf/empty.proto";
@ -509,24 +510,11 @@ message ListModelVersionCheckpointsRequest {
string page_token = 3 [(google.api.field_behavior) = OPTIONAL];
}
// A proto representation of a Spanner-stored ModelVersionCheckpoint.
// The meaning of the fields is equivalent to their in-Spanner counterparts.
message ModelVersionCheckpoint {
// The ID of the checkpoint.
string checkpoint_id = 1;
// The epoch of the checkpoint.
int64 epoch = 2;
// The step of the checkpoint.
int64 step = 3;
}
// Response message for
// [ModelService.ListModelVersionCheckpoints][google.cloud.aiplatform.v1.ModelService.ListModelVersionCheckpoints]
message ListModelVersionCheckpointsResponse {
// List of Model Version checkpoints.
repeated ModelVersionCheckpoint checkpoints = 1;
repeated google.cloud.aiplatform.v1.ModelVersionCheckpoint checkpoints = 1;
// A token to retrieve the next page of results.
// Pass to

@ -146,15 +146,11 @@ message NotebookExecutionJob {
// Max running time of the execution job in seconds (default 86400s / 24 hrs).
google.protobuf.Duration execution_timeout = 5;
// Output only. The Schedule resource name if this job is triggered by one.
// Format:
// The Schedule resource name if this job is triggered by one. Format:
// `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
string schedule_resource_name = 6 [
(google.api.field_behavior) = OUTPUT_ONLY,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Schedule"
}
];
string schedule_resource_name = 6 [(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Schedule"
}];
// Output only. The state of the NotebookExecutionJob.
JobState job_state = 10 [(google.api.field_behavior) = OUTPUT_ONLY];

@ -155,6 +155,12 @@ message PersistentResource {
// Example: ['vertex-ai-ip-range'].
repeated string reserved_ip_ranges = 15
[(google.api.field_behavior) = OPTIONAL];
// Output only. Reserved for future use.
bool satisfies_pzs = 18 [(google.api.field_behavior) = OUTPUT_ONLY];
// Output only. Reserved for future use.
bool satisfies_pzi = 19 [(google.api.field_behavior) = OUTPUT_ONLY];
}
// Represents the spec of a group of resources of the same type,

@ -25,6 +25,7 @@ import "google/cloud/aiplatform/v1/content.proto";
import "google/cloud/aiplatform/v1/explanation.proto";
import "google/cloud/aiplatform/v1/tool.proto";
import "google/cloud/aiplatform/v1/types.proto";
import "google/longrunning/operations.proto";
import "google/protobuf/struct.proto";
import "google/protobuf/timestamp.proto";
@ -52,6 +53,14 @@ service PredictionService {
post: "/v1/{endpoint=projects/*/locations/*/publishers/*/models/*}:predict"
body: "*"
}
additional_bindings {
post: "/v1/{endpoint=endpoints/*}:predict"
body: "*"
}
additional_bindings {
post: "/v1/{endpoint=publishers/*/models/*}:predict"
body: "*"
}
};
option (google.api.method_signature) = "endpoint,instances,parameters";
}
@ -145,6 +154,33 @@ service PredictionService {
rpc StreamingRawPredict(stream StreamingRawPredictRequest)
returns (stream StreamingRawPredictResponse) {}
rpc PredictLongRunning(PredictLongRunningRequest)
returns (google.longrunning.Operation) {
option (google.api.http) = {
post: "/v1/{endpoint=projects/*/locations/*/endpoints/*}:predictLongRunning"
body: "*"
additional_bindings {
post: "/v1/{endpoint=projects/*/locations/*/publishers/*/models/*}:predictLongRunning"
body: "*"
}
};
option (google.api.method_signature) = "endpoint,instances,parameters";
}
// Fetch an asynchronous online prediction operation.
rpc FetchPredictOperation(FetchPredictOperationRequest)
returns (google.longrunning.Operation) {
option (google.api.http) = {
post: "/v1/{endpoint=projects/*/locations/*/endpoints/*}:fetchPredictOperation"
body: "*"
additional_bindings {
post: "/v1/{endpoint=projects/*/locations/*/publishers/*/models/*}:fetchPredictOperation"
body: "*"
}
};
option (google.api.method_signature) = "endpoint,operation_name";
}
// Perform an online explanation.
//
// If
@ -208,6 +244,16 @@ service PredictionService {
};
option (google.api.method_signature) = "model,contents";
}
// Exposes an OpenAI-compatible endpoint for chat completions.
rpc ChatCompletions(ChatCompletionsRequest)
returns (stream google.api.HttpBody) {
option (google.api.http) = {
post: "/v1/{endpoint=projects/*/locations/*/endpoints/*}/chat/completions"
body: "http_body"
};
option (google.api.method_signature) = "endpoint,http_body";
}
}
// Request message for
@ -548,6 +594,60 @@ message StreamingRawPredictResponse {
bytes output = 1;
}
// Request message for
// [PredictionService.PredictLongRunning][google.cloud.aiplatform.v1.PredictionService.PredictLongRunning].
message PredictLongRunningRequest {
// Required. The name of the Endpoint requested to serve the prediction.
// Format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
// or
// `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`
string endpoint = 1 [
(google.api.field_behavior) = REQUIRED,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Endpoint"
}
];
// Required. The instances that are the input to the prediction call.
// A DeployedModel may have an upper limit on the number of instances it
// supports per request, and when it is exceeded the prediction call errors
// in case of AutoML Models, or, in case of customer created Models, the
// behaviour is as documented by that Model.
// The schema of any single instance may be specified via Endpoint's
// DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
// [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
// [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
repeated google.protobuf.Value instances = 2
[(google.api.field_behavior) = REQUIRED];
// Optional. The parameters that govern the prediction. The schema of the
// parameters may be specified via Endpoint's DeployedModels' [Model's
// ][google.cloud.aiplatform.v1.DeployedModel.model]
// [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
// [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
google.protobuf.Value parameters = 3 [(google.api.field_behavior) = OPTIONAL];
}
// Request message for
// [PredictionService.FetchPredictOperation][google.cloud.aiplatform.v1.PredictionService.FetchPredictOperation].
message FetchPredictOperationRequest {
// Required. The name of the Endpoint requested to serve the prediction.
// Format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
// or
// `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`
string endpoint = 1 [
(google.api.field_behavior) = REQUIRED,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Endpoint"
}
];
// Required. The server-assigned name for the operation.
string operation_name = 2 [(google.api.field_behavior) = REQUIRED];
}
// Request message for
// [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
message ExplainRequest {
@ -631,7 +731,12 @@ message CountTokensRequest {
// Optional. The name of the publisher model requested to serve the
// prediction. Format:
// `projects/{project}/locations/{location}/publishers/*/models/*`
string model = 3 [(google.api.field_behavior) = OPTIONAL];
string model = 3 [
(google.api.field_behavior) = OPTIONAL,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Endpoint"
}
];
// Optional. The instances that are the input to token counting call.
// Schema is identical to the prediction schema of the underlying model.
@ -685,7 +790,12 @@ message GenerateContentRequest {
//
// Tuned model endpoint format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
string model = 5 [(google.api.field_behavior) = REQUIRED];
string model = 5 [
(google.api.field_behavior) = REQUIRED,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Endpoint"
}
];
// Required. The content of the current conversation with the model.
//
@ -787,7 +897,12 @@ message GenerateContentResponse {
// Number of tokens in the response(s).
int32 candidates_token_count = 2;
// Total token count for prompt and response candidates.
// Output only. Number of tokens present in tool-use prompt(s).
int32 tool_use_prompt_token_count = 13
[(google.api.field_behavior) = OUTPUT_ONLY];
// Total token count for prompt, response candidates, and tool-use prompts
// (if present).
int32 total_token_count = 3;
// Output only. Number of tokens in the cached part in the input (the cached
@ -807,6 +922,11 @@ message GenerateContentResponse {
// Output only. List of modalities that were returned in the response.
repeated ModalityTokenCount candidates_tokens_details = 11
[(google.api.field_behavior) = OUTPUT_ONLY];
// Output only. List of modalities that were processed for tool-use request
// inputs.
repeated ModalityTokenCount tool_use_prompt_tokens_details = 12
[(google.api.field_behavior) = OUTPUT_ONLY];
}
// Output only. Generated candidates.
@ -832,3 +952,20 @@ message GenerateContentResponse {
// Usage metadata about the response(s).
UsageMetadata usage_metadata = 4;
}
// Request message for [PredictionService.ChatCompletions]
message ChatCompletionsRequest {
// Required. The name of the endpoint requested to serve the prediction.
// Format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
string endpoint = 1 [
(google.api.field_behavior) = REQUIRED,
(google.api.resource_reference) = {
type: "aiplatform.googleapis.com/Endpoint"
}
];
// Optional. The prediction input. Supports HTTP headers and arbitrary data
// payload.
google.api.HttpBody http_body = 2 [(google.api.field_behavior) = OPTIONAL];
}

@ -112,14 +112,21 @@ message PublisherModel {
[(google.api.field_behavior) = REQUIRED];
}
// Multiple setups to deploy the PublisherModel.
message DeployVertex {
// Optional. One click deployment configurations.
repeated Deploy multi_deploy_vertex = 1
[(google.api.field_behavior) = OPTIONAL];
}
// Model metadata that is needed for UploadModel or
// DeployModel/CreateEndpoint requests.
message Deploy {
// Metadata information about the deployment for managing deployment
// config.
message DeployMetadata {
// Optional. Labels for the deployment. For managing deployment config
// like verifying, source of deployment config, etc.
// Optional. Labels for the deployment config. For managing deployment
// config like verifying, source of deployment config, etc.
map<string, string> labels = 1 [(google.api.field_behavior) = OPTIONAL];
// Optional. Sample request for deployed endpoint.
@ -218,6 +225,11 @@ message PublisherModel {
// Optional. Deploy the PublisherModel to Vertex Endpoint.
Deploy deploy = 7 [(google.api.field_behavior) = OPTIONAL];
// Optional. Multiple setups to deploy the PublisherModel to Vertex
// Endpoint.
DeployVertex multi_deploy_vertex = 16
[(google.api.field_behavior) = OPTIONAL];
// Optional. Deploy PublisherModel to Google Kubernetes Engine.
DeployGke deploy_gke = 14 [(google.api.field_behavior) = OPTIONAL];

@ -18,6 +18,7 @@ package google.cloud.aiplatform.v1;
import "google/api/field_behavior.proto";
import "google/api/resource.proto";
import "google/cloud/aiplatform/v1/env_var.proto";
import "google/protobuf/struct.proto";
import "google/protobuf/timestamp.proto";
@ -48,9 +49,20 @@ message ReasoningEngineSpec {
string python_version = 4 [(google.api.field_behavior) = OPTIONAL];
}
// The specification of a Reasoning Engine deployment.
message DeploymentSpec {
// Optional. Environment variables to be set with the Reasoning Engine
// deployment. The environment variables can be updated through the
// UpdateReasoningEngine API.
repeated EnvVar env = 1 [(google.api.field_behavior) = OPTIONAL];
}
// Required. User provided package spec of the ReasoningEngine.
PackageSpec package_spec = 2 [(google.api.field_behavior) = REQUIRED];
// Optional. The specification of a Reasoning Engine deployment.
DeploymentSpec deployment_spec = 4 [(google.api.field_behavior) = OPTIONAL];
// Optional. Declarations for object class methods in OpenAPI specification
// format.
repeated google.protobuf.Struct class_methods = 3

@ -26,10 +26,6 @@ option java_outer_classname = "ReservationAffinityProto";
option java_package = "com.google.cloud.aiplatform.v1";
option php_namespace = "Google\\Cloud\\AIPlatform\\V1";
option ruby_package = "Google::Cloud::AIPlatform::V1";
option (google.api.resource_definition) = {
type: "compute.googleapis.com/Reservation"
pattern: "projects/{project_id_or_number}/zones/{zone}/reservations/{reservation_name}"
};
// A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a
// DeployedModel) to draw its Compute Engine resources from a Shared

@ -184,7 +184,6 @@ message ListSchedulesRequest {
// * `next_run_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=`
// comparisons. Values must be in RFC 3339 format.
//
//
// Filter expressions can be combined together using logical operators
// (`NOT`, `AND` & `OR`).
// The syntax to define filter expression is based on

@ -38,6 +38,10 @@ option ruby_package = "Google::Cloud::AIPlatform::V1";
// one type of Tool (e.g FunctionDeclaration, Retrieval or
// GoogleSearchRetrieval).
message Tool {
// GoogleSearch tool type.
// Tool to support Google Search in Model. Powered by Google.
message GoogleSearch {}
// Tool that executes code generated by the model, and automatically returns
// the result to the model.
//
@ -48,11 +52,12 @@ message Tool {
// Optional. Function tool type.
// One or more function declarations to be passed to the model along with the
// current user query. Model may decide to call a subset of these functions
// by populating [FunctionCall][content.part.function_call] in the response.
// User should provide a [FunctionResponse][content.part.function_response]
// for each function call in the next turn. Based on the function responses,
// Model will generate the final response back to the user.
// Maximum 128 function declarations can be provided.
// by populating [FunctionCall][google.cloud.aiplatform.v1.Part.function_call]
// in the response. User should provide a
// [FunctionResponse][google.cloud.aiplatform.v1.Part.function_response] for
// each function call in the next turn. Based on the function responses, Model
// will generate the final response back to the user. Maximum 128 function
// declarations can be provided.
repeated FunctionDeclaration function_declarations = 1
[(google.api.field_behavior) = OPTIONAL];
@ -62,6 +67,10 @@ message Tool {
// model for generation.
Retrieval retrieval = 2 [(google.api.field_behavior) = OPTIONAL];
// Optional. GoogleSearch tool type.
// Tool to support Google Search in Model. Powered by Google.
GoogleSearch google_search = 7 [(google.api.field_behavior) = OPTIONAL];
// Optional. GoogleSearchRetrieval tool type.
// Specialized retrieval tool that is powered by Google search.
GoogleSearchRetrieval google_search_retrieval = 3
@ -69,7 +78,6 @@ message Tool {
// Optional. CodeExecution tool type.
// Enables the model to execute code as part of generation.
// This field is only used by the Gemini Developer API services.
CodeExecution code_execution = 4 [(google.api.field_behavior) = OPTIONAL];
}
@ -299,17 +307,17 @@ message FunctionCallingConfig {
// Unspecified function calling mode. This value should not be used.
MODE_UNSPECIFIED = 0;
// Default model behavior, model decides to predict either a function call
// or a natural language response.
// Default model behavior, model decides to predict either function calls
// or natural language response.
AUTO = 1;
// Model is constrained to always predicting a function call only.
// If "allowed_function_names" are set, the predicted function call will be
// Model is constrained to always predicting function calls only.
// If "allowed_function_names" are set, the predicted function calls will be
// limited to any one of "allowed_function_names", else the predicted
// function call will be any one of the provided "function_declarations".
// function calls will be any one of the provided "function_declarations".
ANY = 2;
// Model will not predict any function call. Model behavior is same as when
// Model will not predict any function calls. Model behavior is same as when
// not passing any function declarations.
NONE = 3;
}

@ -43,6 +43,7 @@ message TuningJob {
oneof source_model {
// The base model that is being tuned, e.g., "gemini-1.0-pro-002".
// .
string base_model = 4;
}
@ -118,7 +119,7 @@ message TuningJob {
}
];
// Output only. The tuned model resources assiociated with this
// Output only. The tuned model resources associated with this
// [TuningJob][google.cloud.aiplatform.v1.TuningJob].
TunedModel tuned_model = 14 [(google.api.field_behavior) = OUTPUT_ONLY];
@ -142,7 +143,7 @@ message TuningJob {
string service_account = 22;
}
// The Model Registry Model and Online Prediction Endpoint assiociated with
// The Model Registry Model and Online Prediction Endpoint associated with
// this [TuningJob][google.cloud.aiplatform.v1.TuningJob].
message TunedModel {
// Output only. The resource name of the TunedModel. Format:
@ -245,13 +246,21 @@ message SupervisedTuningDataStats {
repeated Content user_dataset_examples = 8
[(google.api.field_behavior) = OUTPUT_ONLY];
// The number of examples in the dataset that have been truncated by any
// amount.
int64 total_truncated_example_count = 10;
// Output only. The number of examples in the dataset that have been dropped.
// An example can be dropped for reasons including: too many tokens, contains
// an invalid image, contains too many images, etc.
int64 total_truncated_example_count = 10
[(google.api.field_behavior) = OUTPUT_ONLY];
// Output only. A partial sample of the indices (starting from 1) of the
// dropped examples.
repeated int64 truncated_example_indices = 11
[(google.api.field_behavior) = OUTPUT_ONLY];
// A partial sample of the indices (starting from 1) of the truncated
// examples.
repeated int64 truncated_example_indices = 11;
// Output only. For each index in `truncated_example_indices`, the user-facing
// reason why the example was dropped. Must not include example itself.
repeated string dropped_example_reasons = 12
[(google.api.field_behavior) = OUTPUT_ONLY];
}
// The tuning data statistic values for
@ -273,6 +282,9 @@ message SupervisedHyperParameters {
// Adapter size 1.
ADAPTER_SIZE_ONE = 1;
// Adapter size 2.
ADAPTER_SIZE_TWO = 6;
// Adapter size 4.
ADAPTER_SIZE_FOUR = 2;
@ -281,6 +293,9 @@ message SupervisedHyperParameters {
// Adapter size 16.
ADAPTER_SIZE_SIXTEEN = 4;
// Adapter size 32.
ADAPTER_SIZE_THIRTY_TWO = 5;
}
// Optional. Number of complete passes the model makes over the entire

@ -177,6 +177,16 @@ message RagCorpus {
singular: "ragCorpus"
};
// The backend config of the RagCorpus.
// It can be data store and/or retrieval engine.
oneof backend_config {
// Optional. Immutable. The config for the Vector DBs.
RagVectorDbConfig vector_db_config = 9 [
(google.api.field_behavior) = OPTIONAL,
(google.api.field_behavior) = IMMUTABLE
];
}
// Output only. The resource name of the RagCorpus.
string name = 1 [(google.api.field_behavior) = OUTPUT_ONLY];
@ -198,16 +208,6 @@ message RagCorpus {
// Output only. RagCorpus state.
CorpusStatus corpus_status = 8 [(google.api.field_behavior) = OUTPUT_ONLY];
// The backend config of the RagCorpus.
// It can be data store and/or retrieval engine.
oneof backend_config {
// Optional. Immutable. The config for the Vector DBs.
RagVectorDbConfig vector_db_config = 9 [
(google.api.field_behavior) = OPTIONAL,
(google.api.field_behavior) = IMMUTABLE
];
}
}
// A RagFile contains user data for chunking, embedding and indexing.

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