com.google.cloud.aiplatform.v1beta1

Interface RagEmbeddingModelConfig.HybridSearchConfigOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

RagEmbeddingModelConfig.HybridSearchConfig, RagEmbeddingModelConfig.HybridSearchConfig.Builder

Enclosing class:

RagEmbeddingModelConfig

public static interface RagEmbeddingModelConfig.HybridSearchConfigOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
RagEmbeddingModelConfig.VertexPredictionEndpoint	getDenseEmbeddingModelPredictionEndpoint() Required.
RagEmbeddingModelConfig.VertexPredictionEndpointOrBuilder	getDenseEmbeddingModelPredictionEndpointOrBuilder() Required.
RagEmbeddingModelConfig.SparseEmbeddingConfig	getSparseEmbeddingConfig() Optional.
RagEmbeddingModelConfig.SparseEmbeddingConfigOrBuilder	getSparseEmbeddingConfigOrBuilder() Optional.
boolean	hasDenseEmbeddingModelPredictionEndpoint() Required.
boolean	hasSparseEmbeddingConfig() Optional.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

hasSparseEmbeddingConfig

boolean hasSparseEmbeddingConfig()

 Optional. The configuration for sparse embedding generation. This field
 is optional the default behavior depends on the vector database choice on
 the RagCorpus.
 

.google.cloud.aiplatform.v1beta1.RagEmbeddingModelConfig.SparseEmbeddingConfig sparse_embedding_config = 1 [(.google.api.field_behavior) = OPTIONAL];

Returns:

Whether the sparseEmbeddingConfig field is set.

getSparseEmbeddingConfig

RagEmbeddingModelConfig.SparseEmbeddingConfig getSparseEmbeddingConfig()

 Optional. The configuration for sparse embedding generation. This field
 is optional the default behavior depends on the vector database choice on
 the RagCorpus.
 

.google.cloud.aiplatform.v1beta1.RagEmbeddingModelConfig.SparseEmbeddingConfig sparse_embedding_config = 1 [(.google.api.field_behavior) = OPTIONAL];

Returns:

The sparseEmbeddingConfig.

getSparseEmbeddingConfigOrBuilder

RagEmbeddingModelConfig.SparseEmbeddingConfigOrBuilder getSparseEmbeddingConfigOrBuilder()

 Optional. The configuration for sparse embedding generation. This field
 is optional the default behavior depends on the vector database choice on
 the RagCorpus.
 

.google.cloud.aiplatform.v1beta1.RagEmbeddingModelConfig.SparseEmbeddingConfig sparse_embedding_config = 1 [(.google.api.field_behavior) = OPTIONAL];

hasDenseEmbeddingModelPredictionEndpoint

boolean hasDenseEmbeddingModelPredictionEndpoint()

 Required. The Vertex AI Prediction Endpoint that hosts the embedding
 model for dense embedding generations.
 

.google.cloud.aiplatform.v1beta1.RagEmbeddingModelConfig.VertexPredictionEndpoint dense_embedding_model_prediction_endpoint = 2 [(.google.api.field_behavior) = REQUIRED];

Returns:

Whether the denseEmbeddingModelPredictionEndpoint field is set.

getDenseEmbeddingModelPredictionEndpoint

RagEmbeddingModelConfig.VertexPredictionEndpoint getDenseEmbeddingModelPredictionEndpoint()

 Required. The Vertex AI Prediction Endpoint that hosts the embedding
 model for dense embedding generations.
 

.google.cloud.aiplatform.v1beta1.RagEmbeddingModelConfig.VertexPredictionEndpoint dense_embedding_model_prediction_endpoint = 2 [(.google.api.field_behavior) = REQUIRED];

Returns:

The denseEmbeddingModelPredictionEndpoint.

getDenseEmbeddingModelPredictionEndpointOrBuilder

RagEmbeddingModelConfig.VertexPredictionEndpointOrBuilder getDenseEmbeddingModelPredictionEndpointOrBuilder()

 Required. The Vertex AI Prediction Endpoint that hosts the embedding
 model for dense embedding generations.
 

.google.cloud.aiplatform.v1beta1.RagEmbeddingModelConfig.VertexPredictionEndpoint dense_embedding_model_prediction_endpoint = 2 [(.google.api.field_behavior) = REQUIRED];