KnowledgeBaseVectorSearchConfiguration¶
Structure Class¶
dataclass
¶
The configuration details for returning the results from the knowledge base vector search.
Attributes¶
class-attribute
instance-attribute
¶
filter: RetrievalFilter | None = field(repr=False, default=None)
Specifies the filters to use on the metadata fields in the knowledge base data sources before returning results.
class-attribute
instance-attribute
¶
implicit_filter_configuration: ImplicitFilterConfiguration | None = None
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.
class-attribute
instance-attribute
¶
number_of_results: int | None = None
The number of text chunks to retrieve; the number of results to return.
class-attribute
instance-attribute
¶
override_search_type: SearchType | None = None
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.
class-attribute
instance-attribute
¶
reranking_configuration: VectorSearchRerankingConfiguration | None = None
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.