Building a RAG Pipeline for Semantic Code Search
A new article on Hacker News explains how to construct a Retrieval‑Augmented Generation (RAG) pipeline for semantic code search. The guide walks readers through indexing code repositories, embedding functions, and querying with a language model to retrieve relevant snippets. It covers data preprocessing, vector store selection, and fine‑tuning the model for accurate code retrieval. The post offers code snippets and best‑practice tips for developers.