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llm4s-docs/org.llm4s/org.llm4s.vectorstore/org.llm4s.vectorstore.opensearch/OpenSearchVectorStore

OpenSearchVectorStore

org.llm4s.vectorstore.opensearch.OpenSearchVectorStore
See theOpenSearchVectorStore companion object
final class OpenSearchVectorStore extends VectorStore

A org.llm4s.vectorstore.VectorStore over one OpenSearch index with the k-NN plugin, through its REST API and org.llm4s.http.Llm4sHttpClient: no OpenSearch client library is involved.

It shares everything but the vector field and the kNN query with org.llm4s.vectorstore.elasticsearch.ElasticsearchVectorStore - OpenSearch keeps Elasticsearch 7.10's document, _bulk, _mget, _count, _delete_by_query and query DSL APIs - so records, writes, get, list, count, deletes, stats and every org.llm4s.vectorstore.MetadataFilter behave exactly as they do there.

What differs:

  • the index is created on the first upsert with index.knn: true and a knn_vector field sized to OpenSearchConfig#dimensions (or the first record), indexed as an HNSW graph with the configured OpenSearchSpaceType and OpenSearchEngine;
  • search is a knn query. On Lucene and Faiss the metadata filter goes inside it (efficient filtering), so topK results come back when that many match; on NMSLIB, which has no efficient filtering, the filter is applied to the k nearest neighbours afterwards, so a selective filter can return fewer than topK - raise OpenSearchConfig#numCandidates to compensate;
  • each _score is mapped onto [0, 1] per space type, as OpenSearchSpaceType describes;
  • authentication is basic or a bearer token (OpenSearchAuth); AWS SigV4 signing is not supported.

Every operation returns a Result: a transport failure is the client's org.llm4s.error.NetworkError or org.llm4s.error.TimeoutError, a 401 or 403 an org.llm4s.error.AuthenticationError, a 429 a org.llm4s.error.RateLimitError, any other non-2xx status a org.llm4s.error.ServiceError carrying the status and the (redacted) body.

Attributes

Companion
object
Graph
Supertypes
trait VectorStore
class Object
trait Matchable
class Any

Members list

Value members

Concrete methods

override def clear(): Result[Unit]

Clear all records from the store.

Clear all records from the store.

Attributes

Returns

Success or error

Definition Classes
override def close(): Unit

Closes the HTTP client when this store created it; a client passed in belongs to the caller.

Closes the HTTP client when this store created it; a client passed in belongs to the caller.

Attributes

Definition Classes
override def count(filter: Option[MetadataFilter]): Result[Long]

Count total records in the store.

Count total records in the store.

Value parameters

filter

Optional metadata filter

Attributes

Returns

Record count

Definition Classes
override def delete(id: String): Result[Unit]

Delete a record by its ID.

Delete a record by its ID.

Value parameters

id

The record identifier

Attributes

Returns

Success or error

Definition Classes
override def deleteBatch(ids: Seq[String]): Result[Unit]

Delete multiple records by their IDs.

Delete multiple records by their IDs.

Value parameters

ids

The record identifiers

Attributes

Returns

Success or error

Definition Classes
override def deleteByFilter(filter: MetadataFilter): Result[Long]

Delete all records matching a metadata filter.

Delete all records matching a metadata filter.

Value parameters

filter

The metadata filter

Attributes

Returns

Number of records deleted

Definition Classes
override def deleteByPrefix(prefix: String): Result[Long]

Delete all records with IDs starting with the given prefix.

Delete all records with IDs starting with the given prefix.

Value parameters

prefix

The ID prefix to match

Attributes

Returns

Number of records deleted

Definition Classes
override def get(id: String): Result[Option[VectorRecord]]

Retrieve a record by its ID.

Retrieve a record by its ID.

Value parameters

id

The record identifier

Attributes

Returns

The record if found

Definition Classes
override def getBatch(ids: Seq[String]): Result[Seq[VectorRecord]]

Retrieve multiple records by their IDs.

Retrieve multiple records by their IDs.

Value parameters

ids

The record identifiers

Attributes

Returns

The found records (missing IDs are silently skipped)

Definition Classes
override def list(limit: Int, offset: Int, filter: Option[MetadataFilter]): Result[Seq[VectorRecord]]

List records with pagination.

List records with pagination.

Value parameters

filter

Optional metadata filter

limit

Maximum records to return

offset

Number of records to skip

Attributes

Returns

Records in insertion order

Definition Classes
override def search(queryVector: Array[Float], topK: Int, filter: Option[MetadataFilter]): Result[Seq[ScoredRecord]]

Search for similar vectors using cosine similarity.

Search for similar vectors using cosine similarity.

Value parameters

filter

Optional metadata filter

queryVector

The query embedding

topK

Number of results to return

Attributes

Returns

Matching records with similarity scores

Definition Classes
override def stats(): Result[VectorStoreStats]

Get statistics about the vector store.

Get statistics about the vector store.

Attributes

Returns

Store statistics

Definition Classes
override def upsert(record: VectorRecord): Result[Unit]

Store a vector record.

Store a vector record.

If a record with the same ID exists, it will be replaced.

Value parameters

record

The record to store

Attributes

Returns

Success or error

Definition Classes
override def upsertBatch(records: Seq[VectorRecord]): Result[Unit]

Store multiple vector records in a batch.

Store multiple vector records in a batch.

More efficient than individual upserts for bulk operations.

Value parameters

records

The records to store

Attributes

Returns

Success or error

Definition Classes

Concrete fields

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