Vector Search - Embedding Queries & Similarity Search

Codifies the project's dual vector search systems (Memory Store for agent domain knowledge, RAG Pipeline for document retrieval), the multi-provider embedding abstraction, pgvector indexing, hybrid search scoring, and chunking strategies. All patterns are built on Supabase/PostgreSQL with pgvector.

Description

Codifies pgvector embedding queries, similarity search, hybrid search, and multi-provider embedding generation for NodeJS-Starter-V1's Supabase/PostgreSQL stack, covering the Memory Store and RAG Pipeline vector infrastructure, indexing strategies, and chunking patterns.

When to Apply

Positive Triggers