Uses of Class
org.springframework.ai.vectorstore.SearchRequest

Packages that use SearchRequest

Package	Description
org.springframework.ai.vectorstore

Uses of SearchRequest in org.springframework.ai.vectorstore

Methods in org.springframework.ai.vectorstore that return SearchRequest

Modifier and Type	Method	Description
static SearchRequest	SearchRequest.defaults()	Create a new SearchRequest builder instance with an empty embedding query string.
static SearchRequest	SearchRequest.from(SearchRequest originalSearchRequest)	Copy an existing SearchRequest instance.
static SearchRequest	SearchRequest.query(String query)	Create a new SearchRequest builder instance with specified embedding query string.
SearchRequest	SearchRequest.withFilterExpression(String textExpression)	Document metadata filter expression.
SearchRequest	SearchRequest.withFilterExpression(Filter.Expression expression)	Retrieves documents by query embedding similarity and matching the filters.
SearchRequest	SearchRequest.withQuery(String query)
SearchRequest	SearchRequest.withSimilarityThreshold(double threshold)	Similarity threshold score to filter the search response by.
SearchRequest	SearchRequest.withSimilarityThresholdAll()	Sets disables the similarity threshold by setting it to 0.0 - all results are accepted.
SearchRequest	SearchRequest.withTopK(int topK)

Methods in org.springframework.ai.vectorstore with parameters of type SearchRequest

Modifier and Type	Method	Description
static SearchRequest	SearchRequest.from(SearchRequest originalSearchRequest)	Copy an existing SearchRequest instance.
List<Document>	InMemoryVectorStore.similaritySearch(SearchRequest request)
List<Document>	MilvusVectorStore.similaritySearch(SearchRequest request)
List<Document>	Neo4jVectorStore.similaritySearch(SearchRequest request)
List<Document>	PgVectorStore.similaritySearch(SearchRequest request)
List<Document>	PineconeVectorStore.similaritySearch(SearchRequest request)
List<Document>	VectorStore.similaritySearch(SearchRequest request)	Retrieves documents by query embedding similarity and metadata filters to retrieve exactly the number of nearest-neighbor results that match the request criteria.