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
Step-by-Step: Migrating from Node.js 21 to Bun 1.2 for Your Backend APIs Why Migrate to Bun 1.2? Bun 1.2 is a modern JavaScript runtime built for speed, offering native TypeScript support, a built-in bundler, test runner, and package manager. Compared to Node.js 21, Bun delivers up to 3x faster startup times, lower memory usage, and seamless compatibility with most Node.js APIs. For b
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