Building a Minimal RAG System from Scratch: PDF to Highlighted Answers in ~100 Lines of Python
By
angela shi
Toasted golden, schmeared with insight. Top of the rack.
Summary
A hands-on tutorial that builds the smallest functional RAG (Retrieval-Augmented Generation) system from scratch using about 100 lines of Python, without vector databases, frameworks, or agents. It runs on the "Attention Is All You Need" paper, demonstrating how to extract text from a PDF, retrieve relevant passages, and generate grounded answers with highlighted source lines. The article then walks through each code block and raises the natural questions each component introduces, serving as both a practical guide and a conceptual deep-dive into RAG fundamentals.
Key quotes
· 3 pulledThe fastest way to understand what RAG is is to build the smallest version that actually works, run it on a real document, and look closely at what just happened.
About a hundred lines of Python (no vector database, no framework, no agents) running on the Attention Is All You Need paper, returning a sourced answer with the exact source lines highlighted on the page.
Then we walk back through each block and ask the question it naturally raises. Each question is what a larger system would need to answer.
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