Policy-Locked Triage for Messy Citizen Text: A Municipal-Style Routing PoC with SFT and Preference Alignment

How I stabilized noisy 311-style requests with supervised training and reviewer preferences in Python TL;DR This write-up is an experimental account of how I built a small routing proof of concept for synthetic municipal-style service requests. The goal was not to ship a city-wide system. From my perspective, the interesting part is the training story: start with labeled text, fit a transparent classifier, then inject reviewer-style preferences so the policy moves toward routes that match operational nuance. The repository is public, fully synthetic, and designed to run on a laptop without calling a hosted large language model. If you are looking for a polished civic product, this is not it. If you are looking for a clean, inspectable playground that mirrors how I think about aligning lightweight agents before any serious conversation about production, this article walks through the motivation, design, code, and limitations in depth. Introduction I have spent a fair amount of time thin