sbugrayy/Saglikla-App

🏥 Sağlıkla App

Diyabet ve Çölyak Hastaları İçin Yapay Zeka Destekli Sağlık Asistanı

Flutter Firebase Gemini AI

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📱 Proje Tanıtımı

Sağlıkla, diyabet (Tip 1 & 2) ve çölyak hastalarının günlük yaşamlarını kolaylaştırmak için geliştirilmiş, yapay zeka destekli kapsamlı bir sağlık yönetim uygulamasıdır.

Bu uygulama sadece kalori saymaz; yediğiniz besinlerin sağlık durumunuza (diyabet, çölyak vb.) etkisini analiz eder. Gemini AI ve OpenFoodFacts entegrasyonu sayesinde ürünlerin barkodlarını tarayabilir veya fotoğraflarını çekerek besin değerlerini ve risk analizlerini anında görebilirsiniz.

📸 Uygulama Görüntüleri

Giriş Ekranı	Kişiselleştirme	Ana Panel
https://raw.githubusercontent.com/sbugrayy/Saglikla-App/HEAD/assets/screenshots/login_screen.png	https://raw.githubusercontent.com/sbugrayy/Saglikla-App/HEAD/assets/screenshots/personalization_screen.png	https://raw.githubusercontent.com/sbugrayy/Saglikla-App/HEAD/assets/screenshots/dashboard_screen.png
Kullanıcı Girişi	Hastalık Seçimi & Ayarlar	Günlük Özet & Kalori Takibi

Sıvı Takibi	Doktor & Tahlil Sonuçları	Profil (Koyu Mod)
https://raw.githubusercontent.com/sbugrayy/Saglikla-App/HEAD/assets/screenshots/hydration_screen.png	https://raw.githubusercontent.com/sbugrayy/Saglikla-App/HEAD/assets/screenshots/doctor_results_screen.png	https://raw.githubusercontent.com/sbugrayy/Saglikla-App/HEAD/assets/screenshots/profile_dark_mode.png
Su & Elektrolit İzleme	Tahlil Yükleme & Arşivleme	Kullanıcı Profili & Ayarlar

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🚀 Project Overview (English)

This application bridges the gap between raw nutritional data and actionable health insights. Unlike standard calorie trackers, HealthScan creates a correlation between what you eat and your specific health condition.

✨ Key Features

• 🔍 Smart Barcode Scanning: Instantly detects products using OpenFoodFacts.
• 🤖 AI-Driven Analysis:
  • Vision Fallback: If a barcode isn't found, the app uses Google Vision/Gemini to analyze the product packaging visually.
  • Safe-to-Eat Logic: Cross-references ingredients with the user's condition (e.g., flagging hidden gluten for Celiacs or high glycemic index items for Diabetics).
• 🍎 Intelligent Meal Tracking: Estimate calories and carb counts from natural language descriptions.
• 💧 Hydration Tracking: Monitor daily water intake and electrolyte balance.
• 📂 Health Archives: Securely store and organize doctor results and analysis files.

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🏗️ Architecture & Component Correlation

The project is built on a service-oriented architecture to ensure separation of concerns while maintaining tight integration between AI and User Data.

🔄 The "Brain" of the App: AIDecisionService

This is the central nervous system. It connects multiple entry points to the Gemini API:

1. Scanner Interceptor: When ScannerScreen scans a product, AIDecisionService takes the ingredients list + User Profile (fetched via UserService) to generate a custom risk assessment.
2. Vision Pipeline: In ManualEntryScreen or failed scans, it processes raw images to extract nutritional values.
3. Chatbot Context: It feeds daily consumption logs (from NutritionService) into the chat context.

🛠️ Service Layer

• UserService: Manages Firestore profiles. Critical for determining which rules the AI uses (Diabetes Type 1 vs 2, Insulin Ratios, etc.).
• NutritionService: Handles the CRUD operations for meal logs.
• ProductService: The gateway to OpenFoodFacts.

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⚡ Setup & Security

This project uses Environment Variables to secure sensitive API Keys.

1. Prerequisites

• Flutter SDK (3.9.x or higher)
• Firebase Project setup

2. Environment Configuration (Crucial!)

The app will not run without valid API keys.

1. Create a .env file in the root directory.
2. Add your keys:

   GOOGLE_GEMINI_KEY=your_gemini_key_here
   GOOGLE_VISION_KEY=your_vision_key_here
   

3. Running the App

# Get dependencies
flutter pub get

# Run on emulator/device
flutter run