kdrant-core/dev.kdrant.dsl/SearchBuilder

SearchBuilder

DSL for search (/points/query). Provide a query (vector, id, fusion, order-by, sample) and/or one or more prefetch sub-requests, plus a positive limit.

Constructors

SearchBuilder

constructor()

Properties

limit

var limit: Int

Maximum number of hits to return.

offset

var offset: Int?

Number of hits to skip (paging; costly for large offsets).

scoreThreshold

var scoreThreshold: Double?

Drop hits scoring below this threshold.

shardKey

var shardKey: ShardKey?

Search only the shards holding this key. null (default) searches every shard.

using

var using: String?

Name of the vector to search when the collection has named vectors.

withPayload

var withPayload: WithPayload?

Which payload to return (defaults to the server's behavior).

withVector

var withVector: Boolean?

Whether to return the stored vectors.

Functions

context

fun context(configure: ContextBuilder.() -> Unit)

Context search: steer results by positive/negative example pairs, without a target.

dbsf

fun dbsf()

Distribution-Based Score Fusion over the prefetch sources.

discover

fun discover(configure: DiscoverBuilder.() -> Unit)

Guided (discovery) search: rank by a target, constrained by context example pairs.

filter

fun filter(filter: Filter)

Restrict the search to points matching an already-built Filter — for filters produced by a translator.

fun filter(configure: FilterBuilder.() -> Unit)

Restrict the search to points matching this filter.

formula

fun formula(expression: Expression, defaults: Map<String, JsonPrimitive> = emptyMap())

Rescore the candidates with an arithmetic formula rather than by distance. Pair it with prefetch to narrow the candidates first: a formula over the whole collection is a full scan.

lookupFrom

fun lookupFrom(collection: String, vector: String? = null)

Look up query-by-id vectors from another collection.

mmr

fun mmr(diversity: Float? = null, candidatesLimit: Int? = null)

Rerank with Maximal Marginal Relevance, trading some relevance for variety. Applies to a vector query and is rejected on any other kind, because MMR needs the query vector to measure dissimilarity against.

orderBy

fun orderBy(key: String, direction: Direction? = null)

Order points by a payload key.

params

fun params(configure: SearchParamsBuilder.() -> Unit)

Tune the accuracy/speed trade-off.

prefetch

fun prefetch(configure: PrefetchBuilder.() -> Unit)

Add a prefetch sub-request (repeatable; prefetches may nest for multi-stage retrieval).

query

fun query(id: PointId)

Search by the stored vector of an existing point (a "more like this" query).

fun query(query: QueryInterface)

Set the query directly (e.g. a prebuilt QueryInterface).

fun query(values: List<Float>)

fun query(vararg values: Float)

Search by an explicit dense query vector.

queryDocument

fun queryDocument(text: String, model: String, options: Map<String, JsonElement>? = null)

Search by text the server embeds with model, instead of by a vector the caller computed. Needs a Qdrant with an inference provider configured. See InferenceInput.

queryMulti

fun queryMulti(vectors: List<List<Float>>)

Search by a multi-vector / late-interaction (ColBERT) query.

querySparse

fun querySparse(indices: List<Int>, values: List<Float>)

Search by a sparse query vector (set using to the sparse vector's name).

recommend

fun recommend(configure: RecommendBuilder.() -> Unit)

Recommend points close to positive examples and far from negative ones.

rrf

fun rrf(k: Int? = null, weights: List<Float>? = null)

Reciprocal Rank Fusion over the prefetch sources — hybrid search.

sample

fun sample()

Return a random sample of points.