24219b611e9f8611b9470f4a9efc35799205ddf4
Backend (Go): - Project structure with chi router, pgxpool, goose migrations - JWT auth (access/refresh tokens) with Firebase token verification - NoopTokenVerifier for local dev without Firebase credentials - PostgreSQL user repository with atomic profile updates (transactions) - Mifflin-St Jeor calorie calculation based on profile data - REST API: POST /auth/login, /auth/refresh, /auth/logout, GET/PUT /profile, GET /health - Middleware: auth, CORS (localhost wildcard), logging, recovery, request_id - Unit tests (51 passing) and integration tests (testcontainers) - Docker Compose setup with postgres healthcheck and graceful shutdown Flutter client: - Riverpod state management with GoRouter navigation - Firebase Auth (email/password + Google sign-in with web popup support) - Platform-aware API URLs (web/Android/iOS) - Dio HTTP client with JWT auth interceptor and concurrent refresh handling - Secure token storage - Screens: Login, Register, Home (tabs: Menu, Recipes, Products, Profile) - Unit tests (17 passing) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Description
FoodAI — мобильное приложение, которое помогает пользователю управлять своим питанием: планировать меню, вести учёт калорий и контролировать запасы продуктов. Ключевая особенность — использование камеры телефона для распознавания продуктов, чеков и готовых блюд с автоматическим подсчётом калорий и подбором рецептов.
Languages
Dart
58.1%
Go
38.9%
PLpgSQL
2.6%
Makefile
0.2%
HTML
0.1%