Class: VectorStoreIndex
The VectorStoreIndex, an index that stores the nodes only according to their vector embeddings.
Extends
Constructors
new VectorStoreIndex()
private
new VectorStoreIndex(init
):VectorStoreIndex
Parameters
• init: VectorIndexConstructorProps
Returns
Overrides
Source
packages/llamaindex/src/indices/vectorStore/index.ts:69
Properties
docStore
docStore:
BaseDocumentStore
Inherited from
Source
packages/llamaindex/src/indices/BaseIndex.ts:60
embedModel?
optional
embedModel:BaseEmbedding
Source
packages/llamaindex/src/indices/vectorStore/index.ts:66
indexStore
indexStore:
BaseIndexStore
Overrides
Source
packages/llamaindex/src/indices/vectorStore/index.ts:65
indexStruct
indexStruct:
IndexDict
Inherited from
Source
packages/llamaindex/src/indices/BaseIndex.ts:62
serviceContext?
optional
serviceContext:ServiceContext
Inherited from
Source
packages/llamaindex/src/indices/BaseIndex.ts:58
storageContext
storageContext:
StorageContext
Inherited from
Source
packages/llamaindex/src/indices/BaseIndex.ts:59
vectorStores
vectorStores:
VectorStoreByType
Source
packages/llamaindex/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
• options?
• options.nodePostprocessors?: BaseNodePostprocessor
[]
• options.preFilters?: MetadataFilters
• options.responseSynthesizer?: BaseSynthesizer
• options.retriever?: BaseRetriever
• options.similarityTopK?: number
Returns
QueryEngine
& RetrieverQueryEngine
Overrides
Source
packages/llamaindex/src/indices/vectorStore/index.ts:283
asRetriever()
asRetriever(
options
?):VectorIndexRetriever
Create a new retriever from the index.
Parameters
• options?: Omit
<VectorIndexRetrieverOptions
, "index"
>
Returns
Overrides
Source
packages/llamaindex/src/indices/vectorStore/index.ts:273
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/llamaindex/src/indices/vectorStore/index.ts:186
deleteRefDoc()
deleteRefDoc(
refDocId
,deleteFromDocStore
):Promise
<void
>
Parameters
• refDocId: string
• deleteFromDocStore: boolean
= true
Returns
Promise
<void
>
Overrides
Source
packages/llamaindex/src/indices/vectorStore/index.ts:345
deleteRefDocFromStore()
protected
deleteRefDocFromStore(vectorStore
,refDocId
):Promise
<void
>
Parameters
• vectorStore: VectorStore
• refDocId: string
Returns
Promise
<void
>
Source
packages/llamaindex/src/indices/vectorStore/index.ts:357
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/llamaindex/src/indices/vectorStore/index.ts:163
insert()
insert(
document
):Promise
<void
>
Insert a document into the index.
Parameters
• document: Document
<Metadata
>
Returns
Promise
<void
>
Inherited from
Source
packages/llamaindex/src/indices/BaseIndex.ts:92
insertNodes()
insertNodes(
nodes
,options
?):Promise
<void
>
Parameters
• nodes: BaseNode
<Metadata
>[]
• options?
• options.logProgress?: boolean
Returns
Promise
<void
>
Overrides
Source
packages/llamaindex/src/indices/vectorStore/index.ts:329
insertNodesToStore()
protected
insertNodesToStore(newIds
,nodes
,vectorStore
):Promise
<void
>
Parameters
• newIds: string
[]
• nodes: BaseNode
<Metadata
>[]
• vectorStore: VectorStore
Returns
Promise
<void
>
Source
packages/llamaindex/src/indices/vectorStore/index.ts:305
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/llamaindex/src/indices/vectorStore/index.ts:199
fromVectorStore()
static
fromVectorStore(vectorStore
,serviceContext
?):Promise
<VectorStoreIndex
>
Parameters
• vectorStore: VectorStore
• serviceContext?: ServiceContext
Returns
Promise
<VectorStoreIndex
>
Source
packages/llamaindex/src/indices/vectorStore/index.ts:263
fromVectorStores()
static
fromVectorStores(vectorStores
,serviceContext
?):Promise
<VectorStoreIndex
>
Parameters
• vectorStores: VectorStoreByType
• serviceContext?: ServiceContext
Returns
Promise
<VectorStoreIndex
>
Source
packages/llamaindex/src/indices/vectorStore/index.ts:240
init()
static
init(options
):Promise
<VectorStoreIndex
>
The async init function creates a new VectorStoreIndex.
Parameters
• options: VectorIndexOptions
Returns
Promise
<VectorStoreIndex
>
Source
packages/llamaindex/src/indices/vectorStore/index.ts:81
setupIndexStructFromStorage()
static
private
setupIndexStructFromStorage(indexStore
,options
):Promise
<undefined
|IndexDict
>
Parameters
• indexStore: BaseIndexStore
• options: IndexStructOptions
Returns
Promise
<undefined
| IndexDict
>