The Future of RAG will be with Vision: End to End Example with ColPali and a Vision Language Model

The post explores the concept of Retrieval-Augmented Generation (RAG) and its application in enterprise settings. It highlights the benefits and challenges of traditional text-based RAG and introduces Vision Language Models (VLMs) as a more effective solution. The post provides a detailed end-to-end example using the ColPali model for document retrieval and GPT-4o-mini for answer generation, emphasizing the advantages of integrating vision capabilities into RAG to handle complex document layouts and multimodal information.