Implementing a RAG system: Walk

Now that we've established the basics in our "Crawl" phase, it's time to pick up the pace. In this guid, we'll move beyond the initial setup to focus on optimizing core architectural components for better performance and accuracy. Walk We ended the previous "Crawl" design with a functioning AI HR agent with a RAG system. The responses, however, could be better. I've introduced some new elements to the architecture to perform better document processing and chunking, as well as re-ranker model to sort the semantic retrieval results by relevance: The ugly Docling IBM's Docling is an open-source document processing tool and easily one of the most effective ones I've tested. It can convert various file formats (e.g., PDF, docx, HTML) into clean, structured formats like Markdown and JSON. By integrating AI models and OCR, it doesn't just extract text, but also preserve the original layout's integrity. Through its hierarchical and hybrid chunking methods, Docling intelligently groups content