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- SPEC.md: project specification and goals - ARCHITECTURE.md: system design and component descriptions - database-schema.md: PostgreSQL schema with all tables - implementation-plan.md: 12-phase implementation guide - RUNNING.md: deployment and troubleshooting guide - ORIENTATION.md: context compaction recovery guide - README.md: project overview and quick start Family profile: 2 adults, 2 children. Mushroom avoidance for 3/4. Approval workflow: email proposals, one denial swaps meal. Tech stack: FastAPI, PostgreSQL, React, Playwright, SendGrid.
4.5 KiB
4.5 KiB
Meal Planner System
Goal
Self-hosted meal planning system that sources ingredients from Lucky California sales, generates weekly meal plans, sends approval requests to you and your wife via email, and creates actionable shopping lists.
Architecture
┌─────────────────────────────────────────────────────────┐
│ MealPlanner App │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Scraper │ │ Recipe │ │ Meal │ │ Notif. │ │
│ │ Service │ │ Engine │ │ Planner │ │ Service │ │
│ └────┬─────┘ └────┬─────┘ └────┬─────┘ └────┬─────┘ │
│ │ │ │ │ │
│ ┌────┴─────────────┴─────────────┴─────────────┴────┐ │
│ │ PostgreSQL Database │ │
│ └───────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────┘
│ │ │
▼ ▼ ▼
Lucky California SendGrid Email Web UI (React)
(scraper) / Twilio WA (local + reverse proxy)
Tech Stack
- Backend: Python/FastAPI
- Database: PostgreSQL
- Frontend: React + Tailwind CSS
- Scraping: Playwright for Lucky California
- Email: SendGrid
- Image Gen: AI (on-demand fallback only)
- Hosting: Docker Compose + reverse proxy
Project Structure
mealplanner/
├── docker-compose.yml
├── backend/
│ ├── app/
│ │ ├── main.py
│ │ ├── scraper/
│ │ │ ├── lucky_ca.py
│ │ │ └── recipe_scraper.py
│ │ ├── models/
│ │ ├── api/
│ │ └── services/
│ └── requirements.txt
└── frontend/
├── src/
└── package.json
Tasks
Phase 1: Foundation
- Set up Docker Compose with PostgreSQL, backend, frontend services
- Create PostgreSQL schema (recipes, meal_plans, family_profiles, home_items, feedback)
- Build FastAPI skeleton with basic CRUD endpoints
- Set up reverse proxy (nginx or Caddy) for local + remote access
Phase 2: Scraping
- Build Lucky California scraper (weekly ad + product catalog)
- Scrape recipe images from public recipe sites (NYT, AllRecipes, etc.) as primary image source
- Store scraped data in PostgreSQL
Phase 3: Recipe & Meal Engine
- Recipe database with ingredient tags, dietary info, cuisine types
- Meal planner that selects meals based on: family profile (mushroom avoidance), budget, seasonal ingredients, variety
- "Never suggest" and rating feedback loop to train preferences
- Incorporate home pantry items as constraints
Phase 4: Notifications & Approval
- SendGrid email integration for weekly meal approval
- Approval workflow: meal proposed → email to both → one deny = swap meal
- Email contains: meal name, image, ingredients, cooking time
- Store approval/denial history for learning
Phase 5: Shopping List & UI
- Generate weekly shopping list grouped by Lucky California aisle/sales
- React web UI for family members to: view meals, approve/deny, adjust home pantry items, view recipes
- Print-friendly recipe view
- Feedback mechanism ("Never suggest this", "Loved it", etc.)
Phase 6: Polish
- AI image generation as fallback when scraped images unavailable
- Meal variety analysis (sauce/ingredient rhythm detection)
- Budget tracking and optimization
Done When
- Family receives email each week with proposed meals
- Shopping list reflects actual Lucky California sales and in-season items
- Home pantry items influence meal suggestions
- Web UI accessible to non-technical family members
- System learns from feedback over time