Class: VectorStoreIndex

The VectorStoreIndex, an index that stores the nodes only according to their vector embedings.

Extends

• BaseIndex <IndexDict>

Constructors

new VectorStoreIndex()

private new VectorStoreIndex(init): VectorStoreIndex

Parameters

• init: VectorIndexConstructorProps

Returns

VectorStoreIndex

Overrides

BaseIndex . constructor

Source

packages/core/src/indices/vectorStore/index.ts:68

Properties

docStore

docStore: BaseDocumentStore

Inherited from

BaseIndex . docStore

Source

packages/core/src/indices/BaseIndex.ts:62

---

embedModel

embedModel: BaseEmbedding

Source

packages/core/src/indices/vectorStore/index.ts:64

---

imageEmbedModel?

optional imageEmbedModel: MultiModalEmbedding

Source

packages/core/src/indices/vectorStore/index.ts:66

---

imageVectorStore?

optional imageVectorStore: VectorStore

Source

packages/core/src/indices/vectorStore/index.ts:65

---

indexStore

indexStore: BaseIndexStore

Overrides

BaseIndex . indexStore

Source

packages/core/src/indices/vectorStore/index.ts:63

---

indexStruct

indexStruct: IndexDict

Inherited from

BaseIndex . indexStruct

Source

packages/core/src/indices/BaseIndex.ts:65

---

serviceContext?

optional serviceContext: ServiceContext

Inherited from

BaseIndex . serviceContext

Source

packages/core/src/indices/BaseIndex.ts:60

---

storageContext

storageContext: StorageContext

Inherited from

BaseIndex . storageContext

Source

packages/core/src/indices/BaseIndex.ts:61

---

vectorStore

vectorStore: VectorStore

Overrides

BaseIndex . vectorStore

Source

packages/core/src/indices/vectorStore/index.ts:62

Methods

asQueryEngine()

asQueryEngine(options?): QueryEngine & RetrieverQueryEngine

Create a RetrieverQueryEngine. similarityTopK is only used if no existing retriever is provided.

Parameters

• options?

• options.nodePostprocessors?: BaseNodePostprocessor[]

• options.preFilters?: MetadataFilters

• options.responseSynthesizer?: BaseSynthesizer

• options.retriever?: BaseRetriever

• options.similarityTopK?: number

Returns

QueryEngine & RetrieverQueryEngine

Overrides

BaseIndex . asQueryEngine

Source

packages/core/src/indices/vectorStore/index.ts:281

---

asRetriever()

asRetriever(options?): VectorIndexRetriever

Create a new retriever from the index.

Parameters

• options?: Omit <VectorIndexRetrieverOptions, "index">

Returns

VectorIndexRetriever

Overrides

BaseIndex . asRetriever

Source

packages/core/src/indices/vectorStore/index.ts:271

---

buildIndexFromNodes()

buildIndexFromNodes(nodes, options?): Promise<void>

Get embeddings for nodes and place them into the index.

Parameters

• nodes: BaseNode <Metadata>[]

• options?

• options.logProgress?: boolean

Returns

Promise<void>

Source

packages/core/src/indices/vectorStore/index.ts:194

---

deleteRefDoc()

deleteRefDoc(refDocId, deleteFromDocStore): Promise<void>

Parameters

• refDocId: string

• deleteFromDocStore: boolean= true

Returns

Promise<void>

Overrides

BaseIndex . deleteRefDoc

Source

packages/core/src/indices/vectorStore/index.ts:347

---

deleteRefDocFromStore()

protected deleteRefDocFromStore(vectorStore, refDocId): Promise<void>

Parameters

• vectorStore: VectorStore

• refDocId: string

Returns

Promise<void>

Source

packages/core/src/indices/vectorStore/index.ts:361

---

getNodeEmbeddingResults()

getNodeEmbeddingResults(nodes, options?): Promise <BaseNode <Metadata>[]>

Calculates the embeddings for the given nodes.

Parameters

• nodes: BaseNode <Metadata>[]

An array of BaseNode objects representing the nodes for which embeddings are to be calculated.

• options?

An optional object containing additional parameters.

• options.logProgress?: boolean

A boolean indicating whether to log progress to the console (useful for debugging).

Returns

Promise <BaseNode <Metadata>[]>

Source

packages/core/src/indices/vectorStore/index.ts:168

---

insert()

insert(document): Promise<void>

Insert a document into the index.

Parameters

• document: Document <Metadata>

Returns

Promise<void>

Inherited from

BaseIndex . insert

Source

packages/core/src/indices/BaseIndex.ts:96

---

insertNodes()

insertNodes(nodes, options?): Promise<void>

Parameters

• nodes: BaseNode <Metadata>[]

• options?

• options.logProgress?: boolean

Returns

Promise<void>

Overrides

BaseIndex . insertNodes

Source

packages/core/src/indices/vectorStore/index.ts:328

---

insertNodesToStore()

protected insertNodesToStore(vectorStore, nodes): Promise<void>

Parameters

• vectorStore: VectorStore

• nodes: BaseNode <Metadata>[]

Returns

Promise<void>

Source

packages/core/src/indices/vectorStore/index.ts:303

---

fromDocuments()

static fromDocuments(documents, args): Promise <VectorStoreIndex>

High level API: split documents, get embeddings, and build index.

Parameters

• documents: Document <Metadata>[]

• args: VectorIndexOptions & object= {}

Returns

Promise <VectorStoreIndex>

Source

packages/core/src/indices/vectorStore/index.ts:207

---

fromVectorStore()

static fromVectorStore(vectorStore, serviceContext?, imageVectorStore?): Promise <VectorStoreIndex>

Parameters

• vectorStore: VectorStore

• serviceContext?: ServiceContext

• imageVectorStore?: VectorStore

Returns

Promise <VectorStoreIndex>

Source

packages/core/src/indices/vectorStore/index.ts:246

---

init()

static init(options): Promise <VectorStoreIndex>

The async init function creates a new VectorStoreIndex.

Parameters

• options: VectorIndexOptions

Returns

Promise <VectorStoreIndex>

Source

packages/core/src/indices/vectorStore/index.ts:85

---

setupIndexStructFromStorage()

static private setupIndexStructFromStorage(indexStore, options): Promise<undefined | IndexDict>

Parameters

• indexStore: BaseIndexStore

• options: IndexStructOptions

Returns

Promise<undefined | IndexDict>

Source

packages/core/src/indices/vectorStore/index.ts:126