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
Source
packages/core/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:97
Properties
collection
private
collection:Collection
<Document
>
Source
packages/core/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:95
embedModel
embedModel:
BaseEmbedding
Inherited from
Source
packages/core/src/storage/vectorStore/types.ts:86
embeddingKey
embeddingKey:
string
Name of the key containing the embedding vector.
Default: "embedding"
Source
packages/core/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:55
flatMetadata
flatMetadata:
boolean
=true
Source
packages/core/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:36
idKey
idKey:
string
Name of the key containing the node id.
Default: "id"
Source
packages/core/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"
Source
packages/core/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:48
insertOptions?
optional
insertOptions:BulkWriteOptions
Options to pass to the insertMany function when adding nodes.
Source
packages/core/src/storage/vectorStore/MongoDBAtlasVectorStore.ts:81
metadataKey
metadataKey:
string
Name of the key containing the node metadata.
Default: "metadata"
Source
packages/core/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.
Source
packages/core/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