Package dev.langchain4j.store.embedding.opensearch

Class OpenSearchEmbeddingStore

java.lang.Object

dev.langchain4j.store.embedding.opensearch.OpenSearchEmbeddingStore

All Implemented Interfaces:

EmbeddingStore<TextSegment>

public class OpenSearchEmbeddingStore
extends Object
implements EmbeddingStore<TextSegment>

Represents an OpenSearch index as an embedding store. This implementation uses K-NN and the cosinesimil space type.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	OpenSearchEmbeddingStore.Builder

Constructor Summary

Constructors

Constructor	Description
OpenSearchEmbeddingStore(String serverUrl, String apiKey, String userName, String password, String indexName)	Creates an instance of OpenSearchEmbeddingStore to connect with OpenSearch clusters running locally and network reachable.
OpenSearchEmbeddingStore(String serverUrl, String serviceName, String region, org.opensearch.client.transport.aws.AwsSdk2TransportOptions options, String indexName)	Creates an instance of OpenSearchEmbeddingStore to connect with OpenSearch clusters running as a fully managed service at AWS.
OpenSearchEmbeddingStore(org.opensearch.client.opensearch.OpenSearchClient openSearchClient, String indexName)	Creates an instance of OpenSearchEmbeddingStore using provided OpenSearchClient

Method Summary

Modifier and Type	Method	Description
String	add(Embedding embedding)
String	add(Embedding embedding, TextSegment textSegment)
void	add(String id, Embedding embedding)
List<String>	addAll(List<Embedding> embeddings)
List<String>	addAll(List<Embedding> embeddings, List<TextSegment> embedded)
static OpenSearchEmbeddingStore.Builder	builder()
List<EmbeddingMatch<TextSegment>>	findRelevant(Embedding referenceEmbedding, int maxResults, double minScore)	This implementation uses the exact k-NN with scoring script to calculate See https://opensearch.org/docs/latest/search-plugins/knn/knn-score-script/

Methods inherited from class java.lang.Object

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

Methods inherited from interface dev.langchain4j.store.embedding.EmbeddingStore

findRelevant, findRelevant, findRelevant

Constructor Details

OpenSearchEmbeddingStore

public OpenSearchEmbeddingStore(String serverUrl,
 String apiKey,
 String userName,
 String password,
 String indexName)

Creates an instance of OpenSearchEmbeddingStore to connect with OpenSearch clusters running locally and network reachable.

Parameters:

serverUrl - OpenSearch Server URL.

apiKey - OpenSearch API key (optional)

userName - OpenSearch username (optional)

password - OpenSearch password (optional)

indexName - OpenSearch index name.

OpenSearchEmbeddingStore

public OpenSearchEmbeddingStore(String serverUrl,
 String serviceName,
 String region,
 org.opensearch.client.transport.aws.AwsSdk2TransportOptions options,
 String indexName)

Creates an instance of OpenSearchEmbeddingStore to connect with OpenSearch clusters running as a fully managed service at AWS.

Parameters:

serverUrl - OpenSearch Server URL.

serviceName - The AWS signing service name, one of `es` (Amazon OpenSearch) or `aoss` (Amazon OpenSearch Serverless).

region - The AWS region for which requests will be signed. This should typically match the region in `serverUrl`.

options - The options to establish connection with the service. It must include which credentials should be used.

indexName - OpenSearch index name.

OpenSearchEmbeddingStore

public OpenSearchEmbeddingStore(org.opensearch.client.opensearch.OpenSearchClient openSearchClient,
 String indexName)

Creates an instance of OpenSearchEmbeddingStore using provided OpenSearchClient

Parameters:

openSearchClient - OpenSearch client provided

indexName - OpenSearch index name.

Method Details

builder

public static OpenSearchEmbeddingStore.Builder builder()

add

public String add(Embedding embedding)

Specified by:

add in interface EmbeddingStore<TextSegment>

add

public void add(String id,
 Embedding embedding)

Specified by:

add in interface EmbeddingStore<TextSegment>

add

public String add(Embedding embedding,
 TextSegment textSegment)

Specified by:

add in interface EmbeddingStore<TextSegment>

addAll

public List<String> addAll(List<Embedding> embeddings)

Specified by:

addAll in interface EmbeddingStore<TextSegment>

addAll

public List<String> addAll(List<Embedding> embeddings,
 List<TextSegment> embedded)

Specified by:

addAll in interface EmbeddingStore<TextSegment>

findRelevant

public List<EmbeddingMatch<TextSegment>> findRelevant(Embedding referenceEmbedding,
 int maxResults,
 double minScore)

This implementation uses the exact k-NN with scoring script to calculate See https://opensearch.org/docs/latest/search-plugins/knn/knn-score-script/

Specified by:

findRelevant in interface EmbeddingStore<TextSegment>