Class AbstractAzureAiSearchEmbeddingStore

java.lang.Object

dev.langchain4j.store.embedding.azure.search.AbstractAzureAiSearchEmbeddingStore

All Implemented Interfaces:

EmbeddingStore<TextSegment>

Direct Known Subclasses:

AzureAiSearchContentRetriever, AzureAiSearchEmbeddingStore

public abstract class AbstractAzureAiSearchEmbeddingStore
extends Object
implements EmbeddingStore<TextSegment>

Field Summary

Fields

Modifier and Type	Field	Description
protected static final String	DEFAULT_FIELD_CONTENT
protected final String	DEFAULT_FIELD_CONTENT_VECTOR
protected static final String	DEFAULT_FIELD_METADATA
protected static final String	DEFAULT_FIELD_METADATA_ATTRS
protected static final String	DEFAULT_FIELD_METADATA_SOURCE
static final String	DEFAULT_INDEX_NAME
protected AzureAiSearchFilterMapper	filterMapper
protected com.azure.search.documents.SearchClient	searchClient
protected static final String	SEMANTIC_SEARCH_CONFIG_NAME
protected static final String	VECTOR_ALGORITHM_NAME
protected static final String	VECTOR_SEARCH_PROFILE_NAME

Constructor Summary

Constructors

Constructor	Description
AbstractAzureAiSearchEmbeddingStore()

Method Summary

Modifier and Type	Method	Description
String	add(Embedding embedding)	Add an embedding to the store.
String	add(Embedding embedding, TextSegment textSegment)	Add an embedding and the related content to the store.
void	add(String id, Embedding embedding)	Add an embedding to the store.
List<String>	addAll(List<Embedding> embeddings)	Add a list of embeddings to the store.
void	addAll(List<String> ids, List<Embedding> embeddings, List<TextSegment> embedded)
void	createOrUpdateIndex(int dimensions)	Creates or updates the index using a ready-made index.
void	deleteIndex()
protected static double	fromAzureScoreToRelevanceScore(double score)	Calculates LangChain4j's RelevanceScore from Azure AI Search's score.
static double	fromAzureScoreToRelevanceScore(com.azure.search.documents.models.SearchResult searchResult, AzureAiSearchQueryType azureAiSearchQueryType)	Calculates LangChain4j's RelevanceScore from Azure AI Search's score, for the 4 types of search.
protected List<EmbeddingMatch<TextSegment>>	getEmbeddingMatches(com.azure.search.documents.util.SearchPagedIterable searchResults, Double minScore, AzureAiSearchQueryType azureAiSearchQueryType)
protected void	initialize(String endpoint, com.azure.core.credential.AzureKeyCredential keyCredential, com.azure.core.credential.TokenCredential tokenCredential, boolean createOrUpdateIndex, int dimensions, com.azure.search.documents.indexes.models.SearchIndex index, String indexName, AzureAiSearchFilterMapper filterMapper)
void	remove(String id)
void	removeAll()
void	removeAll(Filter filter)
void	removeAll(Collection<String> ids)
EmbeddingSearchResult<TextSegment>	search(EmbeddingSearchRequest request)

Methods inherited from class Object

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

Methods inherited from interface EmbeddingStore

addAll, generateIds

Field Details

DEFAULT_INDEX_NAME

public static final String DEFAULT_INDEX_NAME

See Also:

• Constant Field Values

DEFAULT_FIELD_CONTENT

protected static final String DEFAULT_FIELD_CONTENT

See Also:

• Constant Field Values

DEFAULT_FIELD_CONTENT_VECTOR

protected final String DEFAULT_FIELD_CONTENT_VECTOR

See Also:

• Constant Field Values

DEFAULT_FIELD_METADATA

protected static final String DEFAULT_FIELD_METADATA

See Also:

• Constant Field Values

DEFAULT_FIELD_METADATA_SOURCE

protected static final String DEFAULT_FIELD_METADATA_SOURCE

See Also:

• Constant Field Values

DEFAULT_FIELD_METADATA_ATTRS

protected static final String DEFAULT_FIELD_METADATA_ATTRS

See Also:

• Constant Field Values

SEMANTIC_SEARCH_CONFIG_NAME

protected static final String SEMANTIC_SEARCH_CONFIG_NAME

See Also:

• Constant Field Values

VECTOR_ALGORITHM_NAME

protected static final String VECTOR_ALGORITHM_NAME

See Also:

• Constant Field Values

VECTOR_SEARCH_PROFILE_NAME

protected static final String VECTOR_SEARCH_PROFILE_NAME

See Also:

• Constant Field Values

searchClient

protected com.azure.search.documents.SearchClient searchClient

filterMapper

protected AzureAiSearchFilterMapper filterMapper

Constructor Details

AbstractAzureAiSearchEmbeddingStore

public AbstractAzureAiSearchEmbeddingStore()

Method Details

initialize

protected void initialize(String endpoint,
 com.azure.core.credential.AzureKeyCredential keyCredential,
 com.azure.core.credential.TokenCredential tokenCredential,
 boolean createOrUpdateIndex,
 int dimensions,
 com.azure.search.documents.indexes.models.SearchIndex index,
 String indexName,
 AzureAiSearchFilterMapper filterMapper)

createOrUpdateIndex

public void createOrUpdateIndex(int dimensions)

Creates or updates the index using a ready-made index.

Parameters:

dimensions - The number of dimensions of the embeddings.

deleteIndex

public void deleteIndex()

add

public String add(Embedding embedding)

Add an embedding to the store.

Specified by:

add in interface EmbeddingStore<TextSegment>

add

public void add(String id,
 Embedding embedding)

Add an embedding to the store.

Specified by:

add in interface EmbeddingStore<TextSegment>

add

public String add(Embedding embedding,
 TextSegment textSegment)

Add an embedding and the related content to the store.

Specified by:

add in interface EmbeddingStore<TextSegment>

addAll

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

Add a list of embeddings to the store.

Specified by:

addAll in interface EmbeddingStore<TextSegment>

remove

public void remove(String id)

Specified by:

remove in interface EmbeddingStore<TextSegment>

removeAll

public void removeAll(Collection<String> ids)

Specified by:

removeAll in interface EmbeddingStore<TextSegment>

removeAll

public void removeAll()

Specified by:

removeAll in interface EmbeddingStore<TextSegment>

removeAll

public void removeAll(Filter filter)

Specified by:

removeAll in interface EmbeddingStore<TextSegment>

search

public EmbeddingSearchResult<TextSegment> search(EmbeddingSearchRequest request)

Specified by:

search in interface EmbeddingStore<TextSegment>

getEmbeddingMatches

protected List<EmbeddingMatch<TextSegment>> getEmbeddingMatches(com.azure.search.documents.util.SearchPagedIterable searchResults,
 Double minScore,
 AzureAiSearchQueryType azureAiSearchQueryType)

addAll

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

Specified by:

addAll in interface EmbeddingStore<TextSegment>

fromAzureScoreToRelevanceScore

protected static double fromAzureScoreToRelevanceScore(double score)

Calculates LangChain4j's RelevanceScore from Azure AI Search's score.

Score in Azure AI Search is transformed into a cosine similarity as described here: https://learn.microsoft.com/en-us/azure/search/vector-search-ranking#scores-in-a-vector-search-results

RelevanceScore in LangChain4j is a derivative of cosine similarity, but it compresses it into 0..1 range (instead of -1..1) for ease of use.

fromAzureScoreToRelevanceScore

public static double fromAzureScoreToRelevanceScore(com.azure.search.documents.models.SearchResult searchResult,
 AzureAiSearchQueryType azureAiSearchQueryType)

Calculates LangChain4j's RelevanceScore from Azure AI Search's score, for the 4 types of search.