Multi-Dimensional Vector Support in CocoIndex – Underneath Explained

Hi I've been working on adding multi-vector support natively in cocoindex for multi-modal RAG at scale. I wrote blog to help understand the concept of multi-vector and how it works underneath.

The framework itself automatically infers types, so when defining a flow, we don’t need to explicitly specify any types. Felt these concept are fundamental to multimodal data processing so just wanted to share. This unlocks at scale: images, text, audio, video — all can be represented as structured multi-vectors that preserve the unique semantics of each modality.

breakdown + Python examples: https://cocoindex.io/blogs/multi-vector/ Star GitHub if you like it! https://github.com/cocoindex-io/cocoindex