In Relation To

@Entity
@Indexed
public class Book {

        @Id
        private Integer id;

        @VectorField(dimension = 512)
        private float[] coverImageEmbeddings;

        // Other properties ...
}

float[] coverImageEmbeddingsVector = /*...*/

List<Book> hits = searchSession.search( Book.class )
.where( f ->
    // provide the number of similar documents to look for:
    f.knn( 5 )
        // the name of the vector field:
        .field( "coverImageEmbeddings" )
         // matched documents will be the ones whose indexed vector
         // is "most similar" to this vector
        .matching( coverImageEmbeddingsVector )
    // additionally an optional filter can be supplied
    // to provide a regular fulltext search predicate
    .filter( f.match().field( "authors.firstName" ).matching( "arthur" ) )
).fetchHits( 20 );

SearchMapping mapping = /*...*/ ;
// Retrieve a SearchIndexedEntity:
SearchIndexedEntity<Book> bookEntity = mapping.indexedEntity( Book.class );
// Get the descriptor for that index.
// The descriptor exposes the index metamodel:
IndexDescriptor indexDescriptor = bookEntity.indexManager().descriptor();

// Retrieve a field by name
// and inspect its capabilities if such field is present:
indexDescriptor.field( "releaseDate" ).ifPresent( field -> {
        if ( field.isValueField() ) {
                // Get the descriptor for the field type:
                IndexValueFieldTypeDescriptor type = field.toValueField().type();
                // Inspect the "traits" of a field type:
                // each trait represents a predicate/sort/projection/aggregation
                // that can be used on fields of that type.
                Set<String> traits = type.traits();
                if ( traits.contains( IndexFieldTraits.Aggregations.RANGE ) ) {
                        // ...
                }
                if ( traits.contains( IndexFieldTraits.Predicates.EXISTS ) ) {
                        // ...
                }
                // ...
        }
} );