How to Use Multimodal RAG to Extract Text, Images, & Tables (with Demos)

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Published Feb 20, 2025

In this video, you'll learn how to use Multimodal RAG (Retrieval Augmented Generation) to extract information from documents containing text, images, and tables.

First, we'll extract these different data modalities using Python libraries like PyMuPDF. Then, we'll create embeddings for the extracted data using the Titan model from Amazon Bedrock. After storing the embeddings in a vector database, we can use a language model to retrieve relevant information and generate responses to queries.

You'll see examples of asking questions related to text, images, and table data, showcasing Multimodal RAG's capability to handle multimodal inputs intelligently. Whether your data contains just text or a mix of modalities, this technique enables effective information retrieval and question answering.