Multimodal RAG Made Simple: RAG-Anything + Milvus Instead of 20 Separate Tools

What this post added

This post details the integration of Milvus with the RAG-Anything framework to build a multimodal RAG system. It explains how RAG-Anything's '1 + 3 + N' architecture parses and processes diverse content types (text, images, tables, equations) in parallel, and how Milvus serves as the scalable vector search backend for retrieving evidence across these modalities. It also provides a hands-on demo with code snippets and configuration for building a multimodal Q&A system using Milvus Lite, TongYi embedding model, and Alibaba Cloud services.