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Building a RAG Pipeline for Semantic Code Search
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This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend What I Built DemurrageDesk is a local RAG assistant for working with shipping line and terminal documents. I built it around a problem I could easily imagine a friend working in logistics dealing with: finding…
# Building a Resilient Local RAG Backend Engine 🎃 Hacktoberfest 2026 Submission For the Hacktoberfest 2026 DEV Challenge, I built a zero-dependency, local-first Retrieval-Augmented Generation (RAG) backend engine designed to run open-weight models completely offline. 🚀 What I Built An asynchronous…
This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend What I Built Darvin is a terminal + FastAPI RAG chat where you give it the path to a PDF (or upload via API), and it answers questions only from that PDF, with citations. Who I built it for: My friend is preparing for…
An immigration lawyer in Warsaw was spending hours a day on the same questions. Which documents do I need for a karta pobytu? How long does it take? Her site was a brochure: it brought no leads from Google, and every first message was answered by hand. We rebuilt the site and put a consultant…
The support ticket was one line long: "Your assistant says our docs don't mention refunds. We have an entire page called Refunds." I checked. The page was there. It was chunked, embedded, and sitting in Postgres with the right tenant_id . I ran the exact retrieval query the bot runs, by hand, in…
I've been shipping software for 28 years, 21 of them as a consultant working across over 100 different engagements. Past a certain point, a resume stops being a record and becomes a burdensome editing problem. Two pages can barely hold a half-dozen engagements, selected by hand for someone to read…
"Should we fine-tune a model on our documents?" It's one of the most common questions I hear from teams starting with AI, and the answer is usually no. The short answer Use RAG (retrieval-augmented generation) when your AI needs to answer from your own, changing information: documents, policies…
Imagine asking your AI assistant about last quarter's compliance report and getting a precise answer, sourced directly from your internal documents, without that data ever leaking to a public model. This is no longer science fiction—it's RAG (Retrieval-Augmented Generation) in production. Over my…
Imagine um assistente de IA capaz de responder perguntas sobre contratos, políticas internas e manuais da sua empresa — com a precisão de quem leu cada documento e a discrição de quem nunca vaza informação confidencial. Esse cenário deixou de ser ficção. Ao longo de duas décadas lidando com…