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76516abd62 feat: metric/imperial unit preference (#81)
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- Settings: add unit_system key (metric | imperial, default metric)
- Recipe LLM prompts: inject unit instruction into L3 and L4 prompts
  so generated recipes use the user's preferred units throughout
- Frontend: new utils/units.ts converter (mirrors Python units.py)
- Inventory list: display quantities converted to preferred units
- Settings view: metric/imperial toggle with save button
- Settings store: load/save unit_system alongside cooking_equipment

Closes #81
2026-04-15 23:04:29 -07:00
9371df1c95 feat: recipe engine Phase 3 — StyleAdapter, LLM levels 3-4, user settings
Task 13: StyleAdapter with 5 cuisine templates (Italian, Latin, East Asian,
Eastern European, Mediterranean). Each template includes weighted method_bias
(sums to 1.0), element-filtered aromatics/depth/structure helpers, and
seasoning/finishing-fat vectors. StyleTemplate is a fully immutable frozen
dataclass with tuple fields.

Task 14: LLMRecipeGenerator for Levels 3 and 4. Level 3 builds a structured
element-scaffold prompt; Level 4 generates a minimal wildcard prompt (<1500
chars). Allergy hard-exclusion wired through RecipeRequest.allergies into
both prompt builders and the generate() call path. Parsed LLM response
(title, ingredients, directions, notes) fully propagated to RecipeSuggestion.

Task 15: User settings key-value store. Migration 012 adds user_settings
table. Store.get_setting / set_setting with upsert. GET/PUT /settings/{key}
endpoints with Pydantic SettingBody, key allowlist, get_session dependency.
RecipeEngine reads cooking_equipment from settings when hard_day_mode=True.

55 tests passing.
2026-03-31 14:15:18 -07:00