Class: VectorStoreIndex

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

Hierarchy

• BaseIndex<IndexDict>

  ↳ VectorStoreIndex

Constructors

constructor

• new VectorStoreIndex(init): VectorStoreIndex

Parameters

Name	Type
init	VectorIndexConstructorProps

Returns

VectorStoreIndex

Overrides

BaseIndex.constructor

Defined in

packages/core/src/indices/vectorStore/index.ts:73

Properties

docStore

• docStore: BaseDocumentStore

Inherited from

BaseIndex.docStore

Defined in

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

---

embedModel

• embedModel: BaseEmbedding

Defined in

packages/core/src/indices/vectorStore/index.ts:69

---

imageEmbedModel

• Optional imageEmbedModel: MultiModalEmbedding

Defined in

packages/core/src/indices/vectorStore/index.ts:71

---

imageVectorStore

• Optional imageVectorStore: VectorStore

Defined in

packages/core/src/indices/vectorStore/index.ts:70

---

indexStore

• indexStore: BaseIndexStore

Overrides

BaseIndex.indexStore

Defined in

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

---

indexStruct

• indexStruct: IndexDict

Inherited from

BaseIndex.indexStruct

Defined in

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

---

serviceContext

• Optional serviceContext: ServiceContext

Inherited from

BaseIndex.serviceContext

Defined in

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

---

storageContext

• storageContext: StorageContext

Inherited from

BaseIndex.storageContext

Defined in

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

---

vectorStore

• vectorStore: VectorStore

Overrides

BaseIndex.vectorStore

Defined in

packages/core/src/indices/vectorStore/index.ts:67

Methods

asQueryEngine

▸ asQueryEngine(options?): QueryEngine & RetrieverQueryEngine

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

Parameters

Name	Type
options?	Object
options.nodePostprocessors?	BaseNodePostprocessor[]
options.preFilters?	MetadataFilters
options.responseSynthesizer?	BaseSynthesizer
options.retriever?	BaseRetriever
options.similarityTopK?	number

Returns

QueryEngine & RetrieverQueryEngine

Overrides

BaseIndex.asQueryEngine

Defined in

packages/core/src/indices/vectorStore/index.ts:286

---

asRetriever

▸ asRetriever(options?): VectorIndexRetriever

Create a new retriever from the index.

Parameters

Name	Type
options?	Omit<VectorIndexRetrieverOptions, "index">

Returns

VectorIndexRetriever

Overrides

BaseIndex.asRetriever

Defined in

packages/core/src/indices/vectorStore/index.ts:276

---

buildIndexFromNodes

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

Get embeddings for nodes and place them into the index.

Parameters

Name	Type
nodes	BaseNode<Metadata>[]
options?	Object
options.logProgress?	boolean

Returns

Promise<void>

Defined in

packages/core/src/indices/vectorStore/index.ts:199

---

deleteRefDoc

▸ deleteRefDoc(refDocId, deleteFromDocStore?): Promise<void>

Parameters

Name	Type	Default value
refDocId	string	undefined
deleteFromDocStore	boolean	true

Returns

Promise<void>

Overrides

BaseIndex.deleteRefDoc

Defined in

packages/core/src/indices/vectorStore/index.ts:352

---

deleteRefDocFromStore

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

Parameters

Name	Type
vectorStore	VectorStore
refDocId	string

Returns

Promise<void>

Defined in

packages/core/src/indices/vectorStore/index.ts:366

---

getNodeEmbeddingResults

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

Calculates the embeddings for the given nodes.

Parameters

Name	Type	Description
nodes	BaseNode<Metadata>[]	An array of BaseNode objects representing the nodes for which embeddings are to be calculated.
options?	Object	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>[]>

Defined in

packages/core/src/indices/vectorStore/index.ts:173

---

insert

▸ insert(document): Promise<void>

Insert a document into the index.

Parameters

Name	Type
document	Document<Metadata>

Returns

Promise<void>

Inherited from

BaseIndex.insert

Defined in

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

---

insertNodes

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

Parameters

Name	Type
nodes	BaseNode<Metadata>[]
options?	Object
options.logProgress?	boolean

Returns

Promise<void>

Overrides

BaseIndex.insertNodes

Defined in

packages/core/src/indices/vectorStore/index.ts:333

---

insertNodesToStore

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

Parameters

Name	Type
vectorStore	VectorStore
nodes	BaseNode<Metadata>[]

Returns

Promise<void>

Defined in

packages/core/src/indices/vectorStore/index.ts:308

---

fromDocuments

▸ fromDocuments(documents, args?): Promise<VectorStoreIndex>

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

Parameters

Name	Type
documents	Document<Metadata>[]
args	VectorIndexOptions & { docStoreStrategy?: DocStoreStrategy }

Returns

Promise<VectorStoreIndex>

Defined in

packages/core/src/indices/vectorStore/index.ts:212

---

fromVectorStore

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

Parameters

Name	Type
vectorStore	VectorStore
serviceContext?	ServiceContext
imageVectorStore?	VectorStore

Returns

Promise<VectorStoreIndex>

Defined in

packages/core/src/indices/vectorStore/index.ts:251

---

init

▸ init(options): Promise<VectorStoreIndex>

The async init function creates a new VectorStoreIndex.

Parameters

Name	Type
options	VectorIndexOptions

Returns

Promise<VectorStoreIndex>

Defined in

packages/core/src/indices/vectorStore/index.ts:90

---

setupIndexStructFromStorage

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

Parameters

Name	Type
indexStore	BaseIndexStore
options	IndexStructOptions

Returns

Promise<undefined | IndexDict>

Defined in

packages/core/src/indices/vectorStore/index.ts:131