TLDR Tech / Dev
Building a RAG Pipeline for Semantic Code Search: A Developer Diary and Field Notes
This field report breaks down the first stages of a production semantic code search pipeline, covering structure-aware chunking, chunk evaluation, and vectorization for large repositories. It explains why the system keeps all 4,096 embedding dimensions at one-bit precision for a 32-fold storage reduction, when 16-bit vectors are still needed, and how the design avoids storing source code on the server.
Read the full story