Two changes:
1. foods catalog grows organically. Switch the canonical seed from the
noisy USDA dump (2462 rows of "'s, classic chicken noodle soup")
to the Sonnet-curated cut (229 clean rows). search_food() is now
exact + case-insensitive — Mealie's parser already canonicalizes
food names household-side, so cauldron just needs to look them up
verbatim. On miss, the /list view calls forge.fetch_food_info() to
ask Sonnet for {density_g_per_ml, default_unit_class, common_size_g,
category}, persists the row with source='claude', and the household's
actual kitchen catalog builds itself out as Abby uses it.
Killer case verified end-to-end: "2 cups + 50g + 1.25 lb rice"
collapses to a single "2.25 lb rice" line on the shopping list once
rice has a density row.
2. Game system stripped from /plan. Scoreboard panel, streak banner,
"first to lock takes the week" / "🏆 you locked this one in" copy
all gone. award_pick_points calls in /api/plan/generate +
/api/plan/regenerate stopped firing. household_scoreboard /
household_streak DB methods kept as dead code; cauldron_pick_points
table left in place — non-destructive, easy to revive later if
gamification comes back. Goal: get the base flow (pick → plan →
list) working for Abby first, layer features on after.
Phase A foundation. Cobb 2026-04-29: 'go big or go home' on density-table
aggregator — this commit lands the schema + seed data so the aggregator
engine has something to look up against in step 2.
DB:
- migration 010: cauldron_foods (canonical_name PK, density_g_per_ml,
default_unit_class enum mass/volume/count/mixed, common_size_g,
category, usda_fdc_id, source enum)
- migration 011: cauldron_food_mapping (per-household Mealie food_id →
cauldron canonical food_id, used by aggregator + foods-dedupe later)
Seed data:
- scripts/build_foods_seed.py — extractor that walks USDA SR Legacy
foodPortions, derives density g/ml from cup/tbsp/tsp/fl-oz/ml/etc
measurements (handles SR Legacy's quirk of putting unit in 'modifier'
with measureUnit.name='undetermined'), filters out babyfood / branded
/ fast-food / alcoholic-beverage clutter, normalizes names, categorizes
via longest-keyword-wins
- cauldron/data/foods_seed_usda.json — 2,462 foods with density values
derived from USDA. 636KB, ships in the image.
- cauldron/data/README.md — regen instructions + known issues / iteration
plan (next pass: claude-curated cleanup → ~500-800 high-relevance entries
+ count-based foods like egg/onion that USDA doesn't cover)
Loader (cauldron/foods.py):
- load_seed_if_empty(db) called on app startup right after migrate().
Idempotent — won't reload if table is non-empty.
- reload_seed(db) for forced reloads (INSERT IGNORE).
- search_food(db, name) helper for the aggregator + UI.
Categories present in seed:
produce-vegetable: 300, spice: 256, dairy: 207, condiment: 197,
legume: 189, meat: 166, beverage: 153, baking: 129, produce-fruit: 128,
oil-fat: 126, nut-seed: 115, grain: 89, other: 407
The 407 'other' bucket and the verbose USDA names ('mayonnaise, reduced
fat, with olive oil') will get cleaned up via clawdforge in step 3.
For now the aggregator can already do the math against this seed; the
unit-conversion engine is the next commit.
