Class: Aws::Bedrock::Types::KnowledgeBaseVectorSearchConfiguration

Inherits:

Struct

• Object
• Struct
• Aws::Bedrock::Types::KnowledgeBaseVectorSearchConfiguration

Defined in:

gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/types.rb

Overview

The configuration details for returning the results from the knowledge base vector search.

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[:filter]

Instance Attribute Summary

• #filter ⇒ Types::RetrievalFilter

  Specifies the filters to use on the metadata fields in the knowledge base data sources before returning results.

• #implicit_filter_configuration ⇒ Types::ImplicitFilterConfiguration

  Configuration for implicit filtering in Knowledge Base vector searches.

• #number_of_results ⇒ Integer

  The number of text chunks to retrieve; the number of results to return.

• #override_search_type ⇒ String

  By default, Amazon Bedrock decides a search strategy for you.

• #reranking_configuration ⇒ Types::VectorSearchRerankingConfiguration

  Configuration for reranking search results in Knowledge Base vector searches.

Instance Attribute Details

#filter ⇒ Types::RetrievalFilter

Specifies the filters to use on the metadata fields in the knowledge base data sources before returning results.

Returns:

• (Types::RetrievalFilter)

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/types.rb', line 6120

class KnowledgeBaseVectorSearchConfiguration < Struct.new(
  :number_of_results,
  :override_search_type,
  :filter,
  :implicit_filter_configuration,
  :reranking_configuration)
  SENSITIVE = [:filter]
  include Aws::Structure
end

#implicit_filter_configuration ⇒ Types::ImplicitFilterConfiguration

Configuration for implicit filtering in Knowledge Base vector searches. This allows the system to automatically apply filters based on the query context without requiring explicit filter expressions.

Returns:

• (Types::ImplicitFilterConfiguration)

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/types.rb', line 6120

class KnowledgeBaseVectorSearchConfiguration < Struct.new(
  :number_of_results,
  :override_search_type,
  :filter,
  :implicit_filter_configuration,
  :reranking_configuration)
  SENSITIVE = [:filter]
  include Aws::Structure
end

#number_of_results ⇒ Integer

The number of text chunks to retrieve; the number of results to return.

Returns:

• (Integer)

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/types.rb', line 6120

class KnowledgeBaseVectorSearchConfiguration < Struct.new(
  :number_of_results,
  :override_search_type,
  :filter,
  :implicit_filter_configuration,
  :reranking_configuration)
  SENSITIVE = [:filter]
  include Aws::Structure
end

#override_search_type ⇒ String

By default, Amazon Bedrock decides a search strategy for you. If you're using an Amazon OpenSearch Serverless vector store that contains a filterable text field, you can specify whether to query the knowledge base with a HYBRID search using both vector embeddings and raw text, or SEMANTIC search using only vector embeddings. For other vector store configurations, only SEMANTIC search is available.

Returns:

• (String)

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/types.rb', line 6120

class KnowledgeBaseVectorSearchConfiguration < Struct.new(
  :number_of_results,
  :override_search_type,
  :filter,
  :implicit_filter_configuration,
  :reranking_configuration)
  SENSITIVE = [:filter]
  include Aws::Structure
end

#reranking_configuration ⇒ Types::VectorSearchRerankingConfiguration

Configuration for reranking search results in Knowledge Base vector searches. Reranking improves search relevance by reordering initial vector search results using more sophisticated relevance models.

Returns:

• (Types::VectorSearchRerankingConfiguration)

# File 'gems/aws-sdk-bedrock/lib/aws-sdk-bedrock/types.rb', line 6120

class KnowledgeBaseVectorSearchConfiguration < Struct.new(
  :number_of_results,
  :override_search_type,
  :filter,
  :implicit_filter_configuration,
  :reranking_configuration)
  SENSITIVE = [:filter]
  include Aws::Structure
end