Package de.uni_trier.recap.arg_services.nlp.v1

Class NlpConfig.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderType>
com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>
de.uni_trier.recap.arg_services.nlp.v1.NlpConfig.Builder
All Implemented Interfaces:
com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, NlpConfigOrBuilder, Cloneable
Enclosing class:
NlpConfig
public static final class NlpConfig.Builder extends com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder> implements NlpConfigOrBuilder
 Common message for configuring spacy.
Protobuf type arg_services.nlp.v1.NlpConfig

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • clear

      public NlpConfig.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • getDefaultInstanceForType

      public NlpConfig getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public NlpConfig build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

      public NlpConfig buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder

    • clone

      public NlpConfig.Builder clone()
      Specified by:
      clone in interface com.google.protobuf.Message.Builder
      Specified by:
      clone in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clone in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • setField

      public NlpConfig.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
      Specified by:
      setField in interface com.google.protobuf.Message.Builder
      Overrides:
      setField in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • clearField

      public NlpConfig.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
      Specified by:
      clearField in interface com.google.protobuf.Message.Builder
      Overrides:
      clearField in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • clearOneof

      public NlpConfig.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
      Specified by:
      clearOneof in interface com.google.protobuf.Message.Builder
      Overrides:
      clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • setRepeatedField

      public NlpConfig.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
      Specified by:
      setRepeatedField in interface com.google.protobuf.Message.Builder
      Overrides:
      setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • addRepeatedField

      public NlpConfig.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
      Specified by:
      addRepeatedField in interface com.google.protobuf.Message.Builder
      Overrides:
      addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • mergeFrom

      public NlpConfig.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<NlpConfig.Builder>

    • mergeFrom

      public NlpConfig.Builder mergeFrom(NlpConfig other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • mergeFrom

      public NlpConfig.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<NlpConfig.Builder>
      Throws:
      IOException

    • getLanguage

      public String getLanguage()
       Any language supported by spacy (e.g., `en`).
 [Reference](https://spacy.io/usage/models#languages).
      string language = 1 [json_name = "language"];
      Specified by:
      getLanguage in interface NlpConfigOrBuilder
      Returns:
      The language.

    • getLanguageBytes

      public com.google.protobuf.ByteString getLanguageBytes()
       Any language supported by spacy (e.g., `en`).
 [Reference](https://spacy.io/usage/models#languages).
      string language = 1 [json_name = "language"];
      Specified by:
      getLanguageBytes in interface NlpConfigOrBuilder
      Returns:
      The bytes for language.

    • setLanguage

      public NlpConfig.Builder setLanguage(String value)
       Any language supported by spacy (e.g., `en`).
 [Reference](https://spacy.io/usage/models#languages).
      string language = 1 [json_name = "language"];
      Parameters:
      value - The language to set.
      Returns:
      This builder for chaining.

    • clearLanguage

      public NlpConfig.Builder clearLanguage()
       Any language supported by spacy (e.g., `en`).
 [Reference](https://spacy.io/usage/models#languages).
      string language = 1 [json_name = "language"];
      Returns:
      This builder for chaining.

    • setLanguageBytes

      public NlpConfig.Builder setLanguageBytes(com.google.protobuf.ByteString value)
       Any language supported by spacy (e.g., `en`).
 [Reference](https://spacy.io/usage/models#languages).
      string language = 1 [json_name = "language"];
      Parameters:
      value - The bytes for language to set.
      Returns:
      This builder for chaining.

    • getSpacyModel

      public String getSpacyModel()
       Name of the trained spacy pipeline (e.g., `en_core_web_lg`).
 If empty, a blank spacy model will be used (e.g., if you only need embeddings and provide custom `embedding_models`.
 [Example: English models](https://spacy.io/models/en).
      string spacy_model = 2 [json_name = "spacyModel"];
      Specified by:
      getSpacyModel in interface NlpConfigOrBuilder
      Returns:
      The spacyModel.

    • getSpacyModelBytes

      public com.google.protobuf.ByteString getSpacyModelBytes()
       Name of the trained spacy pipeline (e.g., `en_core_web_lg`).
 If empty, a blank spacy model will be used (e.g., if you only need embeddings and provide custom `embedding_models`.
 [Example: English models](https://spacy.io/models/en).
      string spacy_model = 2 [json_name = "spacyModel"];
      Specified by:
      getSpacyModelBytes in interface NlpConfigOrBuilder
      Returns:
      The bytes for spacyModel.

    • setSpacyModel

      public NlpConfig.Builder setSpacyModel(String value)
       Name of the trained spacy pipeline (e.g., `en_core_web_lg`).
 If empty, a blank spacy model will be used (e.g., if you only need embeddings and provide custom `embedding_models`.
 [Example: English models](https://spacy.io/models/en).
      string spacy_model = 2 [json_name = "spacyModel"];
      Parameters:
      value - The spacyModel to set.
      Returns:
      This builder for chaining.

    • clearSpacyModel

      public NlpConfig.Builder clearSpacyModel()
       Name of the trained spacy pipeline (e.g., `en_core_web_lg`).
 If empty, a blank spacy model will be used (e.g., if you only need embeddings and provide custom `embedding_models`.
 [Example: English models](https://spacy.io/models/en).
      string spacy_model = 2 [json_name = "spacyModel"];
      Returns:
      This builder for chaining.

    • setSpacyModelBytes

      public NlpConfig.Builder setSpacyModelBytes(com.google.protobuf.ByteString value)
       Name of the trained spacy pipeline (e.g., `en_core_web_lg`).
 If empty, a blank spacy model will be used (e.g., if you only need embeddings and provide custom `embedding_models`.
 [Example: English models](https://spacy.io/models/en).
      string spacy_model = 2 [json_name = "spacyModel"];
      Parameters:
      value - The bytes for spacyModel to set.
      Returns:
      This builder for chaining.

    • getEmbeddingModelsList

      public List<EmbeddingModel> getEmbeddingModelsList()
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];
      Specified by:
      getEmbeddingModelsList in interface NlpConfigOrBuilder

    • getEmbeddingModelsCount

      public int getEmbeddingModelsCount()
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];
      Specified by:
      getEmbeddingModelsCount in interface NlpConfigOrBuilder

    • getEmbeddingModels

      public EmbeddingModel getEmbeddingModels(int index)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];
      Specified by:
      getEmbeddingModels in interface NlpConfigOrBuilder

    • setEmbeddingModels

      public NlpConfig.Builder setEmbeddingModels(int index, EmbeddingModel value)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • setEmbeddingModels

      public NlpConfig.Builder setEmbeddingModels(int index, EmbeddingModel.Builder builderForValue)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • addEmbeddingModels

      public NlpConfig.Builder addEmbeddingModels(EmbeddingModel value)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • addEmbeddingModels

      public NlpConfig.Builder addEmbeddingModels(int index, EmbeddingModel value)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • addEmbeddingModels

      public NlpConfig.Builder addEmbeddingModels(EmbeddingModel.Builder builderForValue)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • addEmbeddingModels

      public NlpConfig.Builder addEmbeddingModels(int index, EmbeddingModel.Builder builderForValue)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • addAllEmbeddingModels

      public NlpConfig.Builder addAllEmbeddingModels(Iterable<? extends EmbeddingModel> values)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • clearEmbeddingModels

      public NlpConfig.Builder clearEmbeddingModels()
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • removeEmbeddingModels

      public NlpConfig.Builder removeEmbeddingModels(int index)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • getEmbeddingModelsBuilder

      public EmbeddingModel.Builder getEmbeddingModelsBuilder(int index)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • getEmbeddingModelsOrBuilder

      public EmbeddingModelOrBuilder getEmbeddingModelsOrBuilder(int index)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];
      Specified by:
      getEmbeddingModelsOrBuilder in interface NlpConfigOrBuilder

    • getEmbeddingModelsOrBuilderList

      public List<? extends EmbeddingModelOrBuilder> getEmbeddingModelsOrBuilderList()
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];
      Specified by:
      getEmbeddingModelsOrBuilderList in interface NlpConfigOrBuilder

    • addEmbeddingModelsBuilder

      public EmbeddingModel.Builder addEmbeddingModelsBuilder()
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • addEmbeddingModelsBuilder

      public EmbeddingModel.Builder addEmbeddingModelsBuilder(int index)
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • getEmbeddingModelsBuilderList

      public List<EmbeddingModel.Builder> getEmbeddingModelsBuilderList()
       List of embeddings to use for computing word/sentence vectors.
 If given, these embeddings will **override** the embeddings of the specified `spacy_model`.
 Multiple models are concatenated to each other, increasing the length of the resulting vector.
      repeated .arg_services.nlp.v1.EmbeddingModel embedding_models = 3 [json_name = "embeddingModels"];

    • getSimilarityMethodValue

      public int getSimilarityMethodValue()
       Mathematical function to determine a similarity score given two strings.
      .arg_services.nlp.v1.SimilarityMethod similarity_method = 4 [json_name = "similarityMethod"];
      Specified by:
      getSimilarityMethodValue in interface NlpConfigOrBuilder
      Returns:
      The enum numeric value on the wire for similarityMethod.

    • setSimilarityMethodValue

      public NlpConfig.Builder setSimilarityMethodValue(int value)
       Mathematical function to determine a similarity score given two strings.
      .arg_services.nlp.v1.SimilarityMethod similarity_method = 4 [json_name = "similarityMethod"];
      Parameters:
      value - The enum numeric value on the wire for similarityMethod to set.
      Returns:
      This builder for chaining.

    • getSimilarityMethod

      public SimilarityMethod getSimilarityMethod()
       Mathematical function to determine a similarity score given two strings.
      .arg_services.nlp.v1.SimilarityMethod similarity_method = 4 [json_name = "similarityMethod"];
      Specified by:
      getSimilarityMethod in interface NlpConfigOrBuilder
      Returns:
      The similarityMethod.

    • setSimilarityMethod

      public NlpConfig.Builder setSimilarityMethod(SimilarityMethod value)
       Mathematical function to determine a similarity score given two strings.
      .arg_services.nlp.v1.SimilarityMethod similarity_method = 4 [json_name = "similarityMethod"];
      Parameters:
      value - The similarityMethod to set.
      Returns:
      This builder for chaining.

    • clearSimilarityMethod

      public NlpConfig.Builder clearSimilarityMethod()
       Mathematical function to determine a similarity score given two strings.
      .arg_services.nlp.v1.SimilarityMethod similarity_method = 4 [json_name = "similarityMethod"];
      Returns:
      This builder for chaining.

    • setUnknownFields

      public final NlpConfig.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
      Specified by:
      setUnknownFields in interface com.google.protobuf.Message.Builder
      Overrides:
      setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>

    • mergeUnknownFields

      public final NlpConfig.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
      Specified by:
      mergeUnknownFields in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<NlpConfig.Builder>