Node type proposal: Embedding #21
Description
Generate vector embeddings from text using configurable embedding models (OpenAI text-embedding-3-small/large, Cohere embed, local models via Ollama). Properties: model selection, input text (from previous node or template), batch embedding support, dimension configuration. Output: embedding vector(s) that can be stored, compared (cosine similarity), or passed to a vector store. Building block for RAG workflows, semantic search, content classification, and duplicate detection.