02a6b6df7e
- db.init_db gains guarded ALTER TABLE additions for listings.year / seller_type / extras (schema.sql v1 untouched; PRAGMA-checked idempotent) - rubric: extras_from_text() returns matched EXTRAS labels (table order) - importer: normalize computes year (existing helper), seller_type ONLY from a real state-item signal (dealer/private, else NULL), extras JSON; upsert rewrites the new columns on both paths - verified on live DB: import idempotent, counts stay 640/560/80, year backfilled on 599 rows, extras on 45, seller_type 0 (no state signal)
Bike-Tinder
A private, Tinder-style web app for browsing the motorcycle market: swipe real listings (like / nope / maybe), see everything on one editable list, and let the deck learn your taste. Built for Glenn; runs on the Rotarran, published to the tailnet only.
Status: v0.1 — design phase. No code yet; this repo currently holds the design docs. Build begins once the docs are approved.
How it works
[single-source crawler] → [nightly importer] → [app DB] → [API + PWA deck] → Glenn's thumb
↓
[swipe history] → [ranking]
- Crawl — Kijiji (NS + NB; decided 2026-11-10 — see
docs/SOURCES.md) is swept nightly by the existing hunt crawler; a script-only importer folds the results in. No LLM involved, zero token cost. - Import — the importer upserts the source's catalog into the app database: new listings appear, changes update, vanished listings retire after repeated misses (never a blocked page, never a guess).
- Deck — a Tinder-like PWA: card stack, drag to swipe, big buttons. Like / Nope / Maybe. "It's a match" moment when you like something.
- List & edit — every entry in one table; re-file any call later (a nope can become a like).
- Ranking — cold start uses the hunt's rubric score; a cheap, fully explainable swipe-boost lands first (v1.x), then a small learned model (Phase 3, retrained nightly) orders the deck by your taste. "Because you liked X" chips, never a black box.
Docs
docs/SOURCES.md— the v1 source decision (candidates, evidence, choice)docs/DESIGN.md— architecture, components, data flow, deploymentdocs/DATA-MODEL.md— database schema + sync semanticsdocs/RANKING.md— cold-start + learned ranking designdocs/UI-SPEC.md— screens, gestures, Tinder-fidelity goalsdocs/PLAN.md— phases, acceptance criteria, status
Branches
main— stable trunk (docs + verified code); the default branch.dev— active development; build work lands here first.release— deployable cuts; the Rotarran stack tracks this branch.
Deployment (planned)
A small podman compose stack on the Rotarran under /var/mnt/DATA/podman-stacks/bike-tinder/, its own systemd user unit (Delegate=yes), SQLite database. The stack ships its own Tailscale node (sidecar container — no host-tailnet coupling) and serves the app privately at https://biketinder.tailf35a34.ts.net. Single user; reachable only from Glenn's own devices.
Crew
- Glenn — owner; the thumb that swipes.
- Alex — resident agent; architecture, orchestration, docs.
- Torres — engineer; builds and maintains this repo.