Tbh I had no idea this was even a thing until recently. I've been working with Rails for a while now and somehow never came across it. So let me explain it the way I understood it. You know how we normally do associations in Rails, User has many Posts, Post belongs to User. Two different models, two different tables. Simple. But what if a model needs to reference itself? Like same table, same mode
Fixed-length chunking requires no external services, yet semantic chunking absolutely needs an Embedding API — why? The core idea of semantic chunking is to split text at semantic boundaries. Determining whether "two pieces of text belong to the same topic" requires converting text into vectors and computing similarity — that's exactly what the Embedding API does. Dimension Fixed-Length / Recur
Why Does Switching Embedding Models Make Such a Huge Difference? In the first four articles, we built the RAG pipeline, tuned parameters, and mastered chunking strategies. But there's one question we haven't dived into: After your documents are chunked, how do they become vectors? This process is called Embedding. It transforms human-readable text into machine-computable vectors. The choice of E