RAG
Meet Elysia: A New Open-Source Python Framework Redefining Agentic RAG Systems with Decision Trees and Smarter Data Handling
If you’ve ever tried to build a agentic RAG system that actually works well, you know the pain. You feed it some documents, cross your fingers, and hope it doesn’t hallucinate when someone asks it a simple question. Most of the time, you get back irrelevant chunks of text that barely answer what was asked….
Creating an AI-Powered Tutor Using Vector Database and Groq for Retrieval-Augmented Generation (RAG): Step by Step Guide
Currently, three trending topics in the implementation of AI are LLMs, RAG, and Databases. These enable us to create systems that are suitable and specific to our use. This AI-powered system, combining a vector database and AI-generated responses, has applications across various industries. In customer support, AI chatbots retrieve knowledge base answers dynamically. The legal…
Beyond RAG: Building a Knowledge Management System That Enhances Rather Than Replaces Thought
I’ve been thinking a lot lately about where Zettelgarden fits into the long history of how humans manage and interact with knowledge. From Socrates worrying that writing would destroy memory, to today’s debates about AI-generated content, we’ve always struggled with how much of our thinking we should outsource to tools. While building Zettelgarden, I’ve had…