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