ChromaDB

Package: chromadb · 8 nodes · Vector database for AI applications

Store and query vector embeddings for RAG pipelines, semantic search, and AI memory systems.

Node Reference

NodeTypeInputsOutputs
Create Clientstatement-Client (chroma.Client)
Get CollectionstatementClient (chroma.Client)Collection (chroma.Collection)
Add DocumentsstatementCollection (chroma.Collection), Documents (list<any>), IDs (list<any>), Metadatas (list<any>)-
QuerystatementCollection (chroma.Collection), Query Texts (list<any>)Results (chroma.QueryResult)
DeletestatementCollection (chroma.Collection), IDs (list<any>)-
UpsertstatementCollection (chroma.Collection), Documents (list<any>), IDs (list<any>), Metadatas (list<any>)-
CountexpressionCollection (chroma.Collection)Count (int)
Get FieldexpressionResults (chroma.QueryResult)Result (list<any>)

Typical Pipeline

Create Client → Get Collection → Add Documents / Query → Get Field to extract results.