Optimizing Web Scraping Data to Reduce RAG Token Costs

Feeding raw HTML into a Retrieval-Augmented Generation (RAG) pipeline is a fast way to burn through your LLM token budget. When building data pipelines that rely on publicly accessible web data, the difference between a cost-effective architecture and an expensive one often comes down to pre-processing. A standard public news article or e-commerce product page can easily exceed 2MB of raw HTML. Run that through a tokenizer like tiktoken (used by OpenAI models), and you are looking at roughly 300