Class: Google::Cloud::AIPlatform::V1::EmbedContentRequest

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/cloud/aiplatform/v1/prediction_service.rb

Overview

Request message for PredictionService.EmbedContent.

Defined Under Namespace

Modules: EmbeddingTaskType

Instance Attribute Summary collapse

Instance Attribute Details

#auto_truncate ⇒ ::Boolean 



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# File 'proto_docs/google/cloud/aiplatform/v1/prediction_service.rb', line 696

class EmbedContentRequest
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a downstream task the embeddings will be used for.
  module EmbeddingTaskType
    # Unset value, which will default to one of the other enum values.
    UNSPECIFIED = 0

    # Specifies the given text is a query in a search/retrieval setting.
    RETRIEVAL_QUERY = 2

    # Specifies the given text is a document from the corpus being searched.
    RETRIEVAL_DOCUMENT = 3

    # Specifies the given text will be used for STS.
    SEMANTIC_SIMILARITY = 4

    # Specifies that the given text will be classified.
    CLASSIFICATION = 5

    # Specifies that the embeddings will be used for clustering.
    CLUSTERING = 6

    # Specifies that the embeddings will be used for question answering.
    QUESTION_ANSWERING = 7

    # Specifies that the embeddings will be used for fact verification.
    FACT_VERIFICATION = 8

    # Specifies that the embeddings will be used for code retrieval.
    CODE_RETRIEVAL_QUERY = 9
  end
end

#content ⇒ ::Google::Cloud::AIPlatform::V1::Content 



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# File 'proto_docs/google/cloud/aiplatform/v1/prediction_service.rb', line 696

class EmbedContentRequest
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a downstream task the embeddings will be used for.
  module EmbeddingTaskType
    # Unset value, which will default to one of the other enum values.
    UNSPECIFIED = 0

    # Specifies the given text is a query in a search/retrieval setting.
    RETRIEVAL_QUERY = 2

    # Specifies the given text is a document from the corpus being searched.
    RETRIEVAL_DOCUMENT = 3

    # Specifies the given text will be used for STS.
    SEMANTIC_SIMILARITY = 4

    # Specifies that the given text will be classified.
    CLASSIFICATION = 5

    # Specifies that the embeddings will be used for clustering.
    CLUSTERING = 6

    # Specifies that the embeddings will be used for question answering.
    QUESTION_ANSWERING = 7

    # Specifies that the embeddings will be used for fact verification.
    FACT_VERIFICATION = 8

    # Specifies that the embeddings will be used for code retrieval.
    CODE_RETRIEVAL_QUERY = 9
  end
end

#model ⇒ ::String 



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# File 'proto_docs/google/cloud/aiplatform/v1/prediction_service.rb', line 696

class EmbedContentRequest
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a downstream task the embeddings will be used for.
  module EmbeddingTaskType
    # Unset value, which will default to one of the other enum values.
    UNSPECIFIED = 0

    # Specifies the given text is a query in a search/retrieval setting.
    RETRIEVAL_QUERY = 2

    # Specifies the given text is a document from the corpus being searched.
    RETRIEVAL_DOCUMENT = 3

    # Specifies the given text will be used for STS.
    SEMANTIC_SIMILARITY = 4

    # Specifies that the given text will be classified.
    CLASSIFICATION = 5

    # Specifies that the embeddings will be used for clustering.
    CLUSTERING = 6

    # Specifies that the embeddings will be used for question answering.
    QUESTION_ANSWERING = 7

    # Specifies that the embeddings will be used for fact verification.
    FACT_VERIFICATION = 8

    # Specifies that the embeddings will be used for code retrieval.
    CODE_RETRIEVAL_QUERY = 9
  end
end

#output_dimensionality ⇒ ::Integer 



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# File 'proto_docs/google/cloud/aiplatform/v1/prediction_service.rb', line 696

class EmbedContentRequest
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a downstream task the embeddings will be used for.
  module EmbeddingTaskType
    # Unset value, which will default to one of the other enum values.
    UNSPECIFIED = 0

    # Specifies the given text is a query in a search/retrieval setting.
    RETRIEVAL_QUERY = 2

    # Specifies the given text is a document from the corpus being searched.
    RETRIEVAL_DOCUMENT = 3

    # Specifies the given text will be used for STS.
    SEMANTIC_SIMILARITY = 4

    # Specifies that the given text will be classified.
    CLASSIFICATION = 5

    # Specifies that the embeddings will be used for clustering.
    CLUSTERING = 6

    # Specifies that the embeddings will be used for question answering.
    QUESTION_ANSWERING = 7

    # Specifies that the embeddings will be used for fact verification.
    FACT_VERIFICATION = 8

    # Specifies that the embeddings will be used for code retrieval.
    CODE_RETRIEVAL_QUERY = 9
  end
end

#task_type ⇒ ::Google::Cloud::AIPlatform::V1::EmbedContentRequest::EmbeddingTaskType 



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# File 'proto_docs/google/cloud/aiplatform/v1/prediction_service.rb', line 696

class EmbedContentRequest
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a downstream task the embeddings will be used for.
  module EmbeddingTaskType
    # Unset value, which will default to one of the other enum values.
    UNSPECIFIED = 0

    # Specifies the given text is a query in a search/retrieval setting.
    RETRIEVAL_QUERY = 2

    # Specifies the given text is a document from the corpus being searched.
    RETRIEVAL_DOCUMENT = 3

    # Specifies the given text will be used for STS.
    SEMANTIC_SIMILARITY = 4

    # Specifies that the given text will be classified.
    CLASSIFICATION = 5

    # Specifies that the embeddings will be used for clustering.
    CLUSTERING = 6

    # Specifies that the embeddings will be used for question answering.
    QUESTION_ANSWERING = 7

    # Specifies that the embeddings will be used for fact verification.
    FACT_VERIFICATION = 8

    # Specifies that the embeddings will be used for code retrieval.
    CODE_RETRIEVAL_QUERY = 9
  end
end

#title ⇒ ::String 



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# File 'proto_docs/google/cloud/aiplatform/v1/prediction_service.rb', line 696

class EmbedContentRequest
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # Represents a downstream task the embeddings will be used for.
  module EmbeddingTaskType
    # Unset value, which will default to one of the other enum values.
    UNSPECIFIED = 0

    # Specifies the given text is a query in a search/retrieval setting.
    RETRIEVAL_QUERY = 2

    # Specifies the given text is a document from the corpus being searched.
    RETRIEVAL_DOCUMENT = 3

    # Specifies the given text will be used for STS.
    SEMANTIC_SIMILARITY = 4

    # Specifies that the given text will be classified.
    CLASSIFICATION = 5

    # Specifies that the embeddings will be used for clustering.
    CLUSTERING = 6

    # Specifies that the embeddings will be used for question answering.
    QUESTION_ANSWERING = 7

    # Specifies that the embeddings will be used for fact verification.
    FACT_VERIFICATION = 8

    # Specifies that the embeddings will be used for code retrieval.
    CODE_RETRIEVAL_QUERY = 9
  end
end