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adminandClaude Sonnet 4.6
ac2b575f6b
- Flip matching direction: iterate ingredients, search grocery items
(previously: iterate grocery items → false positives from partial word
overlap, e.g. Pampers Wipes matched Ginger Fresh via the word "Fresh")
- Score = partial_token_sort_ratio × (ingredient_sig / grocery_sig_words)
— precision term penalises long branded products where the ingredient
word appears incidentally ("Vermicelli, Garlic & Olive Oil" now scores
lower than a pure olive oil SKU)
- 100% recall guard: every significant ingredient word must appear in the
grocery name (eliminates cross-category noise completely)
- Stop-word list strips generic qualifiers so "boneless skinless" in an
ingredient name doesn't block "Chicken Thighs Boneless" in the grocery
- ON CONFLICT DO NOTHING preserves manual matches on re-run
Benchmark on today's Lucky CA weekly ad (10,965 items):
Before: ~25% correct (Pampers→Ginger, Red Wine→Bell Pepper, etc.)
After: ~80% correct; remaining misses are data gaps (Lucky has no
standalone garlic or olive oil in this week's ad)
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
Meal Planner
Self-hosted meal planning system that integrates with Lucky California grocery store, sends weekly meal proposals via email to family members, generates shopping lists, and learns from feedback.
Background
This project was born out of frustration with meal kit services (Blue Apron → EveryPlate → HungryRoot → Sunbasket) that:
- Escalate costs to 3x ingredient markup
- Fall into repetitive meal rhythms
- Force users to log into apps to manage selections
- Don't integrate with home pantry items
Features
- Grocery Integration: Scrapes Lucky California weekly ads and sales
- Family Approval Workflow: Email proposals with approve/deny; one denial swaps the meal
- Shopping List Generation: Weekly list grouped by store aisles, highlighting sales
- Pantry Integration: Specify home items to incorporate into suggestions
- Web UI: Modern interface for the whole family
- Learning: Feedback-based meal recommendations
- Recipe Images: Scraped from public recipe sites, AI fallback available
Architecture
- Backend: Python/FastAPI
- Database: PostgreSQL
- Frontend: React + Tailwind CSS
- Email: SendGrid
- Hosting: Docker Compose with nginx reverse proxy
Documentation
Quick Start
# Clone and start
docker-compose up -d
# View logs
docker-compose logs -f
# Stop
docker-compose down
Family Profile
Household: 2 adults, 2 children
- One adult likes mushrooms, one child OK with them
- Three family members do NOT like mushrooms
- No allergies
- Calorie, budget, and health conscious eating
Approval Workflow
- System generates 7-day meal plan based on sales, dietary constraints, budget, variety
- Email sent to both adults with meal previews
- One denial = meal swapped; no denials = auto-approved
- Shopping list generated after approval
Tech Stack
| Component | Technology |
|---|---|
| Backend | Python 3.11, FastAPI |
| Database | PostgreSQL 15 |
| Frontend | React 18, TypeScript, Tailwind |
| Scraping | Playwright, BeautifulSoup |
| SendGrid | |
| Hosting | Docker Compose, nginx |