io.lettuce.core.search.arguments

Class VectorFieldArgs.Builder<K>

java.lang.Object

io.lettuce.core.search.arguments.FieldArgs.Builder<K,VectorFieldArgs<K>,VectorFieldArgs.Builder<K>>

io.lettuce.core.search.arguments.VectorFieldArgs.Builder<K>

Type Parameters:

K - Key type

Enclosing class:

VectorFieldArgs<K>

public static class VectorFieldArgs.Builder<K>
extends FieldArgs.Builder<K,VectorFieldArgs<K>,VectorFieldArgs.Builder<K>>

Builder for VectorFieldArgs.

Field Summary

Fields inherited from class io.lettuce.core.search.arguments.FieldArgs.Builder

instance

Constructor Summary

Constructors

Constructor and Description
Builder()

Method Summary

Modifier and Type	Method and Description
VectorFieldArgs.Builder<K>	algorithm(VectorFieldArgs.Algorithm algorithm) Set the vector similarity index algorithm.
VectorFieldArgs.Builder<K>	attribute(String name, Object value) Add a custom attribute.
VectorFieldArgs.Builder<K>	dimensions(int dimensions) Set the vector dimensionality.
VectorFieldArgs.Builder<K>	distanceMetric(VectorFieldArgs.DistanceMetric metric) Set the distance metric.
VectorFieldArgs.Builder<K>	flat() Use the FLAT (brute force) algorithm.
VectorFieldArgs.Builder<K>	hnsw() Use the HNSW (hierarchical, navigable, small world) algorithm.
VectorFieldArgs.Builder<K>	svsVamana() Use the SVS-VAMANA algorithm for high-performance approximate vector search.
VectorFieldArgs.Builder<K>	type(VectorFieldArgs.VectorType type) Set the vector data type.

Methods inherited from class io.lettuce.core.search.arguments.FieldArgs.Builder

as, build, indexEmpty, indexMissing, name, noIndex, self, sortable, unNormalizedForm

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Builder

public Builder()

Method Detail

algorithm

public VectorFieldArgs.Builder<K> algorithm(VectorFieldArgs.Algorithm algorithm)

Set the vector similarity index algorithm.

Parameters:

algorithm - the algorithm

Returns:

the instance of the VectorFieldArgs.Builder for the purpose of method chaining

flat

public VectorFieldArgs.Builder<K> flat()

Use the FLAT (brute force) algorithm.

Returns:

the instance of the VectorFieldArgs.Builder for the purpose of method chaining

hnsw

public VectorFieldArgs.Builder<K> hnsw()

Use the HNSW (hierarchical, navigable, small world) algorithm.

Returns:

the instance of the VectorFieldArgs.Builder for the purpose of method chaining

svsVamana

public VectorFieldArgs.Builder<K> svsVamana()

Use the SVS-VAMANA algorithm for high-performance approximate vector search.

SVS-VAMANA provides advanced features including:

• Vector compression support (LVQ, LeanVec)
• Configurable graph construction parameters
• Runtime search optimization
• Intel platform optimizations

Returns:

the instance of the VectorFieldArgs.Builder for the purpose of method chaining

Since:

Redis 8.2

type

public VectorFieldArgs.Builder<K> type(VectorFieldArgs.VectorType type)

Set the vector data type.

Parameters:

type - the vector data type

Returns:

the instance of the VectorFieldArgs.Builder for the purpose of method chaining

dimensions

public VectorFieldArgs.Builder<K> dimensions(int dimensions)

Set the vector dimensionality.

Parameters:

dimensions - the number of dimensions

Returns:

the instance of the VectorFieldArgs.Builder for the purpose of method chaining

distanceMetric

public VectorFieldArgs.Builder<K> distanceMetric(VectorFieldArgs.DistanceMetric metric)

Set the distance metric.

Parameters:

metric - the distance metric

Returns:

the instance of the VectorFieldArgs.Builder for the purpose of method chaining

attribute

public VectorFieldArgs.Builder<K> attribute(String name,
                                            Object value)

Add a custom attribute.

Parameters:

name - the attribute name

value - the attribute value

Returns:

the instance of the VectorFieldArgs.Builder for the purpose of method chaining