Schema (W0): - Add garments, garment_wears, outfits tables with Drizzle migrations - Drizzle migrations 0001 (garments/wears) and 0002 (outfits) auto-apply on deploy - RLS policies in drizzle/manual/06-wardrobe-rls.sql (apply via superuser in prod) API (W1–W9): - POST /api/garments/upload — direct upload to R2 garments/ prefix with sharp thumbnail - POST /api/garments/tag — vision tagging via LiteLLM, defensive parse, category validated - GET/POST /api/garments — list with composable filters, create - GET/PATCH/DELETE /api/garments/[id] — detail, edit, delete - POST /api/garments/[id]/wear — log worn date - GET /api/garments/outgrowth — pure SQL, explicit size ordering (no lexicographic sort) - GET /api/garments/packing — active garments grouped by category - GET /api/garments/outfit — Open-Meteo weather + deterministic outfit pairing, no LLM - GET/POST /api/garments/outfits + DELETE [id] — saved outfits Pages: - /wardrobe — grid with status/category/size/season filters + outgrowth nudge - /wardrobe/add — 3-step capture→vision→form, size required, batch-friendly - /wardrobe/[id] — detail/edit/status lifecycle + wear history - /wardrobe/packing — packing checklist by category - /wardrobe/outfit — weather-aware suggestions with shown basis - /wardrobe/saved-outfits — view/delete saved combinations Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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|---|---|---|
| .. | ||
| manual | ||
| meta | ||
| 0000_baseline_prod_2026_05_19.sql | ||
| 0001_wardrobe_tables.sql | ||
| 0002_outfits_table.sql | ||
| README.md | ||
Tia — Database Migrations
This folder is source code and is committed to git. It is consumed by the
deploy pipeline (pnpm db:migrate, run on container start — see Dockerfile).
Baseline reset — 2026-05-19
The project's first 16 migrations (0000–0015) plus a manual/ folder were
hand-rolled SQL applied directly via the Dokploy database terminal. They were
never run through Drizzle's migrator, so:
- prod had no
__drizzle_migrationstracking table; - the
drizzle/folder was gitignored, so migration SQL never reached the server; schema.tshad drifted well behind the real production schema.
To fix this we performed a Path A baseline reset:
pg_dumpbackup of prod taken and stored off-server.drizzle-kit pullintrospected the live prod schema (35 tables).src/db/schema/*.tswas rewritten to match prod exactly.- Legacy migrations were archived to
_archived_pre_baseline_2026-05-19/(also retained in git history). - A single fresh baseline —
0000_baseline_prod_2026_05_19.sql— was generated and verified column-for-column against the introspected prod schema. - Prod's
drizzle.__drizzle_migrationstable was created and seeded with one row marking0000_baseline_prod_2026_05_19as already applied, so the migrator treats prod as up-to-date and runs nothing on the next deploy.
Normal workflow from here
# 1. Edit src/db/schema/*.ts
# 2. Generate a migration from the diff:
pnpm db:generate # writes drizzle/000N_<name>.sql
# 3. Review the generated SQL by eye.
# 4. Apply locally against the dev DB:
pnpm db:migrate
# 5. Commit schema + migration together, then push.
# Dokploy redeploys; the migrator applies it in prod on container start.
Hard rules
- Never edit a migration file after it has been pushed. Fix-forward with a new migration instead.
- Never run schema-changing SQL directly against prod. It becomes drift.
- The
drizzle/folder must stay out of.gitignore.
RLS policies
Five log tables (feeds, diapers_logs, sleeps, vaccinations, growth)
plus children / family_members carry row-level-security policies in prod.
These are not modelled in the pgTable definitions and are managed
separately in the database. Drizzle migrations will not recreate them — keep
that in mind if you ever rebuild the DB from scratch.