Zain Hasan – ColPali’s Vision-Powered RAG for Enterprise Documents | PyData Global 2024
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Traditional document processing for Retrieval-Augmented Generation (RAG) often involves cumbersome, error-prone extraction pipelines, hampering AI’s ability to retrieve high-quality information from complex formats like PDFs and PowerPoint decks. ColPali disrupts this process by embedding entire pages—text, visuals, and layout—into rich, multi-vector representations using Vision Language Models (VLMs). This talk explores how ColPali, paired with multimodal models like the Llama 3.2 Vision series, enables RAG systems to “see” and reason over documents, dramatically improving retrieval performance. Attendees will learn to implement ColPali for enhanced, scalable, and robust enterprise knowledge retrieval.
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