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Interface: AzureAISearchOptions<T>

Embeddings and documents are stored in an Azure AI Search index, a merge or upload approach is used when adding embeddings. When adding multiple embeddings the index is updated by this vector store in batches of 10 documents, very large nodes may result in failure due to the batch byte size being exceeded.

Type Parameters​

• T extends R

Properties​

chunkFieldKey?​

optional chunkFieldKey: string

Index field storing the node text

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:124

compressionType?​

optional compressionType: KnownVectorSearchCompressionKind

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:114

credential?​

optional credential: DefaultAzureCredential | AzureKeyCredential | ManagedIdentityCredential

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:102

docIdFieldKey?​

optional docIdFieldKey: string

Index field storing doc_id

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:139

embeddingDimensionality?​

optional embeddingDimensionality: number

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:115

embeddingFieldKey?​

optional embeddingFieldKey: string

Index field storing the embedding vector

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:128

endpoint?​

optional endpoint: string

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:106

filterableMetadataFieldKeys?​

optional filterableMetadataFieldKeys: FilterableMetadataFieldKeysType

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:146

hiddenFieldKeys?​

optional hiddenFieldKeys: string[]

List of index fields that should be hidden from the client. This is useful for fields that are not needed for retrieving, but are used for similarity search, like the embedding field.

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:145

idFieldKey?​

optional idFieldKey: string

Index field storing the id

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:120

indexClient?​

optional indexClient: SearchIndexClient

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:110

indexManagement?​

optional indexManagement: IndexManagement

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:111

indexMapping()?​

optional indexMapping: (enrichedDoc, metadata) => T

(Optional) function used to map document fields to the AI search index fields If none is specified a default mapping is provided which uses the field keys. The keys in the enriched document are: ["id", "chunk", "embedding", "metadata"].

The default mapping is:

  • "id" to idFieldKey
  • "chunk" to chunkFieldKey
  • "embedding" to embeddingFieldKey
  • "metadata" to metadataFieldKey

Parameters​

• enrichedDoc: BaseNode<Metadata>

The enriched document

• metadata: Record<string, unknown>

The metadata of the document

Returns​

T

The mapped index document

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:162

indexName?​

optional indexName: string

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:109

key?​

optional key: string

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:107

languageAnalyzer?​

optional languageAnalyzer: string

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:113

metadataStringFieldKey?​

optional metadataStringFieldKey: string

Index field storing node metadata as a json string. Schema is arbitrary, to filter on metadata values they must be stored as separate fields in the index, use filterable_metadata_field_keys to specify the metadata values that should be stored in these filterable fields

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:135

searchClient?​

optional searchClient: SearchClient<T>

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:112

serviceApiVersion?​

optional serviceApiVersion: string

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:108

userAgent?​

optional userAgent: string

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:101

vectorAlgorithmType?​

optional vectorAlgorithmType: KnownVectorSearchAlgorithmKind

Defined in​

packages/llamaindex/src/vector-store/azure/AzureAISearchVectorStore.ts:116