Class: VectorStoreIndex
The VectorStoreIndex, an index that stores the nodes only according to their vector embedings.
Extends
Constructors
new VectorStoreIndex()
private
new VectorStoreIndex(init
):VectorStoreIndex
Parameters
• init: VectorIndexConstructorProps
Returns
Overrides
Source
packages/core/src/indices/vectorStore/index.ts:68
Properties
docStore
docStore:
BaseDocumentStore
Inherited from
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
Source
packages/core/src/indices/vectorStore/index.ts:63
indexStruct
indexStruct:
IndexDict
Inherited from
Source
packages/core/src/indices/BaseIndex.ts:65
serviceContext?
optional
serviceContext:ServiceContext
Inherited from
Source
packages/core/src/indices/BaseIndex.ts:60
storageContext
storageContext:
StorageContext
Inherited from
Source
packages/core/src/indices/BaseIndex.ts:61
vectorStore
vectorStore:
VectorStore
Overrides
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
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
Overrides
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
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
>