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

Node	Type	Inputs	Outputs
Create Client	statement	-	Client (chroma.Client)
Get Collection	statement	Client (chroma.Client)	Collection (chroma.Collection)
Add Documents	statement	Collection (chroma.Collection), Documents (list), IDs (list), Metadatas (list)	-
Query	statement	Collection (chroma.Collection), Query Texts (list)	Results (chroma.QueryResult)
Delete	statement	Collection (chroma.Collection), IDs (list)	-
Upsert	statement	Collection (chroma.Collection), Documents (list), IDs (list), Metadatas (list)	-
Count	expression	Collection (chroma.Collection)	Count (int)
Get Field	expression	Results (chroma.QueryResult)	Result (list)

Typical Pipeline

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