- Vector Retriever data source (
type: 'vectorretriever'indataSources[]) — configure directly on a chat to query a vector store as part of multi-source RAG - Flow Designer tool nodes (
integrationType: 'vector_store') — use a vector store as a tool inside a Flow Designer workflow
IDataConnection registry for managing credentials and endpoints.
Supported Providers
All vector stores are first-classDataPlatformType values in IDataConnection (see VECTOR_STORE_TYPES in dataConnectionTypes.ts).
Tier 1 — Core:
Tier 2 — Enterprise / Cloud:
Tier 3 — Specialized:
Data Connection Fields (Vector Stores)
Vector store connections are managed via the unifiedIDataConnection interface in the dataconnections Cosmos container. When type is a vector store platform, these additional fields apply:
Authentication types vary by provider — see
getAuthTypesForPlatform() in dataConnectionTypes.ts.
Vector Retriever Data Source
To query a vector store directly from a chat’s RAG pipeline, add avectorretriever entry to the chat’s dataSources[]:
The orchestrator queries the vector store in parallel with other data sources and merges results into the RAG context.
Flow Designer Vector Store Config (IVectorStoreConfig)
For Flow Designer tool nodes with integrationType: 'vector_store', the configuration has three parts:
Connection (IVectorStoreConnectionConfig):
endpoint,apiKey,index,environment,projectId,region- SSL/TLS, connection pool settings
IVectorStoreSearchConfig):
topK,minScore,searchType(vector / semantic / hybrid / keyword)similarityMetric(cosine / euclidean / dotProduct / l2)- Metadata filters, namespace filters
- Reranking support (
enableReranking,rerankingModel) - Query expansion (
enableQueryExpansion,expansionPrompt) - Hybrid weights (
keywordWeight,vectorWeight)
modelEndpointId— FK to AI model endpoint for query vectorizationembeddingDimensions,batchSize