Compressing PDFs into Video for LLM Memory

This article describes an innovative approach to storing and retrieving information for Retrieval-Augmented Generation (RAG) systems. The author cleverly uses video compression techniques (H.264/H.265) to encode PDF documents into a video file, significantly reducing storage space and RAM usage compared to traditional vector databases. The trade-off is a slightly slower search latency. The project's offline nature and lack of API dependencies are significant advantages.