# RAG-Anything Tutorial: Build a Multimodal Retrieval Pipeline for Text, Tables, Equations, and Images in Colab

> Source: <https://www.marktechpost.com/2026/07/02/rag-anything-tutorial-build-a-multimodal-retrieval-pipeline-for-text-tables-equations-and-images-in-colab/>
> Published: 2026-07-02 21:38:34+00:00

In this tutorial, we build a RAG-Anything workflow to explore how multimodal retrieval works across text, tables, equations, and images. We prepare a Colab environment, enter our OpenAI API key at runtime, and generate a synthetic report with a chart and PDF. We convert that content into RAG-Anything's direct content_list format and insert it into the retrieval system. We then configure OpenAI chat, vision, and embedding functions and test naive, local, global, and hybrid modes.

The post [RAG-Anything Tutorial: Build a Multimodal Retrieval Pipeline for Text, Tables, Equations, and Images in Colab](https://www.marktechpost.com/2026/07/02/rag-anything-tutorial-build-a-multimodal-retrieval-pipeline-for-text-tables-equations-and-images-in-colab/) appeared first on [MarkTechPost](https://www.marktechpost.com).