Class: MongoDBAtlasVectorSearch
Vector store that uses MongoDB Atlas for storage and vector search. This store uses the $vectorSearch aggregation stage to perform vector similarity search.
Extends
Implements
Constructors
new MongoDBAtlasVectorSearch()
new MongoDBAtlasVectorSearch(
init):MongoDBAtlasVectorSearch
Parameters
• init: Partial<MongoDBAtlasVectorSearch> & object
Returns
Overrides
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:97
Properties
embedModel
embedModel:
BaseEmbedding
Inherited from
Defined in
packages/llamaindex/src/storage/vectorStore/types.ts:103
embeddingKey
embeddingKey:
string
Name of the key containing the embedding vector.
Default: "embedding"
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:55
flatMetadata
flatMetadata:
boolean=true
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:36
idKey
idKey:
string
Name of the key containing the node id.
Default: "id"
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:62
indexName
indexName:
string
Name of the vector index. If invalid, Mongo will silently ignore this issue and return 0 results.
Default: "default"
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:48
insertOptions?
optionalinsertOptions:BulkWriteOptions
Options to pass to the insertMany function when adding nodes.
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:81
metadataKey
metadataKey:
string
Name of the key containing the node metadata.
Default: "metadata"
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:76
mongodbClient
mongodbClient:
MongoClient
The used MongoClient. If not given, a new MongoClient is created based on the MONGODB_URI env variable.
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:41
numCandidates()
numCandidates: (
query) =>number
Function to determine the number of candidates to retrieve for a given query. In case your results are not good, you might tune this value.
and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs
Default: query.similarityTopK * 10
Parameters
• query: VectorStoreQuery
Returns
number
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:94
storesText
storesText:
boolean=true
Implementation of
VectorStoreNoEmbedModel.storesText
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:35
textKey
textKey:
string
Name of the key containing the node text.
Default: "text"
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:69
Accessors
client
getclient():any
Returns
any
Implementation of
VectorStoreNoEmbedModel.client
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:180
Methods
add()
add(
nodes):Promise<string[]>
Add nodes to the vector store.
Parameters
Nodes to add to the vector store
Returns
Promise<string[]>
List of node ids that were added
Implementation of
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:136
delete()
delete(
refDocId,deleteOptions?):Promise<void>
Delete nodes from the vector store with the given redDocId.
Parameters
• refDocId: string
The refDocId of the nodes to delete
• deleteOptions?: any
Options to pass to the deleteOne function
Returns
Promise<void>
Implementation of
VectorStoreNoEmbedModel.delete
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:171
query()
query(
query,options?):Promise<VectorStoreQueryResult>
Perform a vector similarity search query.
Parameters
• query: VectorStoreQuery
The query to run
• options?: any
Returns
Promise<VectorStoreQueryResult>
List of nodes and their similarities
Implementation of
Defined in
packages/llamaindex/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:190