I Built RAG From Scratch in Python to Understand It. Here's What I Learned.

Short summary

Author deconstructed LangChain's RAG abstraction by rebuilding a production pipeline in 500 lines of plain Python, making every layer inspectable and testable. The build log reveals critical design decisions: sliding-window chunking with 100-character overlap, whitespace normalization, and modular single-responsibility architecture. Essential technical learning for anyone building RAG-powered AI products.

• •Author rebuilt LangChain's RAG system from scratch to understand hidden complexity and trust production outputs
• •Critical insight: chunking with overlap and whitespace normalization prevent information loss at chunk boundaries
• •Modular six-module design (loaders→chunker→store→pipeline→llm) makes each layer testable and swappable

Generated with AI, which can make mistakes.