Reduce RAG Token Waste: Optimize Scraping to Markdown & JSON

Raw HTML bloats Retrieval-Augmented Generation (RAG) pipelines. An average web page consists of 80% markup and 20% actual content. Passing this raw Document Object Model (DOM) to a Large Language Model wastes tokens, increases latency, and severely degrades response quality. If you chunk and embed raw HTML, your vector database index becomes polluted with CSS class names, SVG paths, and tracking scripts. A similarity search for specific domain knowledge might incorrectly return a chunk containing layout classes instead of the actual textual content.