Package dev.langchain4j.store.embedding.astradb

Class AstraDbEmbeddingStore

java.lang.Object

dev.langchain4j.store.embedding.astradb.AstraDbEmbeddingStore

All Implemented Interfaces:

EmbeddingStore<TextSegment>

public class AstraDbEmbeddingStore
extends Object
implements EmbeddingStore<TextSegment>

Implementation of EmbeddingStore using AstraDB.

See Also:

• EmbeddingStore

Field Summary

Fields

Modifier and Type	Field	Description
static final String	KEY_ATTRIBUTES_BLOB	Saving the text chunk as an attribut.
static final String	KEY_SIMILARITY	Metadata used for similarity.

Constructor Summary

Constructors

Constructor	Description
AstraDbEmbeddingStore(@NonNull com.dtsx.astra.sdk.AstraDBCollection client)	Initialization of the store with an EXISTING collection.
AstraDbEmbeddingStore(@NonNull com.dtsx.astra.sdk.AstraDBCollection client, int itemsPerChunk, int concurrentThreads)	Initialization of the store with an EXISTING collection.

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> embeddingList, List<TextSegment> textSegmentList)	Add multiple embeddings as a single action.
void	clear()	Delete all records from the table.
List<EmbeddingMatch<TextSegment>>	findRelevant(Embedding referenceEmbedding, int maxResults, double minScore)
List<EmbeddingMatch<TextSegment>>	findRelevant(Embedding referenceEmbedding, io.stargate.sdk.data.domain.query.Filter metaDatafilter, int maxResults, double minScore)	Semantic search with metadata filtering.

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

Field Details

KEY_ATTRIBUTES_BLOB

public static final String KEY_ATTRIBUTES_BLOB

Saving the text chunk as an attribut.

See Also:

• Constant Field Values

KEY_SIMILARITY

public static final String KEY_SIMILARITY

Metadata used for similarity.

See Also:

• Constant Field Values

Constructor Details

AstraDbEmbeddingStore

public AstraDbEmbeddingStore(@NonNull
 @NonNull com.dtsx.astra.sdk.AstraDBCollection client)

Initialization of the store with an EXISTING collection.

Parameters:

client - astra db collection client

AstraDbEmbeddingStore

public AstraDbEmbeddingStore(@NonNull
 @NonNull com.dtsx.astra.sdk.AstraDBCollection client,
 int itemsPerChunk,
 int concurrentThreads)

Initialization of the store with an EXISTING collection.

Parameters:

client - astra db collection client

itemsPerChunk - size of 1 chunk in between 1 and 20

Method Details

clear

public void clear()

Delete all records from the table.

add

public String add(Embedding embedding)

Specified by:

add in interface EmbeddingStore<TextSegment>

add

public String add(Embedding embedding,
 TextSegment textSegment)

Specified by:

add in interface EmbeddingStore<TextSegment>

add

public void add(String id,
 Embedding embedding)

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> embeddingList,
 List<TextSegment> textSegmentList)

Add multiple embeddings as a single action.

Specified by:

addAll in interface EmbeddingStore<TextSegment>

Parameters:

embeddingList - list of embeddings

textSegmentList - list of text segment

Returns:

list of new row if (same order as the input)

findRelevant

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

Specified by:

findRelevant in interface EmbeddingStore<TextSegment>

findRelevant

public List<EmbeddingMatch<TextSegment>> findRelevant(Embedding referenceEmbedding,
 io.stargate.sdk.data.domain.query.Filter metaDatafilter,
 int maxResults,
 double minScore)

Semantic search with metadata filtering.

Parameters:

referenceEmbedding - vector

metaDatafilter - fileter for metadata

maxResults - limit

minScore - threshold

Returns:

records