🥗 Calory AI: Intelligence System

Advanced Health-Tech Architecture with AI-Powered Nutritional Analysis & Automated Workflows

Calory AI is an intelligent, full-stack health platform designed to automate the complex process of nutritional tracking. By integrating Google Gemini AI for natural language meal analysis and n8n for backend workflow orchestration, the system provides a "zero-effort" tracking experience, synchronized in real-time via a Firebase cloud foundation.

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🏗️ System Architecture & Logic

The platform is built on a serverless, event-driven stack designed for high performance, real-time responsiveness, and intelligent data processing.

1. The Automation Engine (n8n)

• Workflow Orchestration: Custom n8n nodes act as the system's "central nervous system," routing data between the User Interface and the AI processing layers without manual server intervention.
• AI Integration: Seamlessly routes user meal descriptions to the Gemini AI API to extract precise caloric and macronutrient data from unstructured text.

2. Cloud Infrastructure (Firebase)

• Real-Time Data Layer: Leverages Firestore for sub-second synchronization of user logs, personal metrics, and health trends.
• Authentication Engine: Secure user entry and personalized session management handled through dedicated authentication workflows.
• Scalable Hosting: Optimized delivery via Firebase Hosting for global accessibility.

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✨ Feature Modules

• Smart Onboarding Engine: Multi-step collection of personal metrics (onboarding__personal_metrics.html) and activity levels to calculate personalized BMR and TDEE targets.
• AI Meal Analysis: Advanced text-to-data engine (ai_meal_analysis.html) that allows users to log meals naturally—the AI handles the math.
• Visual Intelligence Dashboard: A unified, high-fidelity view of daily progress, caloric targets, and historical health trends (history_&_trends_view.html).
• Premium Ecosystem: Integrated Pro-Upgrade logic (pro_upgrade_modal.html) showcasing a scalable monetization architecture.

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🛠️ Technical Stack

• Frontend: HTML5, CSS3 (Modern Glassmorphism UI), JavaScript (ES6+).
• AI Engine: Google Gemini AI (Generative Language Models).
• Automation: n8n (Workflow Automation Tool).
• Backend & Cloud: Firebase (Firestore, Auth, Hosting).

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📁 Technical Directory Structure

├── public/              # Core Application Interface
│   ├── index.html       # Landing Page
│   ├── onboarding/      # Goal Selection & Metric Collection
│   └── dashboard/       # Real-time Analysis & History Views
├── js/                  # Logic Layer (Firebase Config & AI Logic)
├── n8n-workflows/       # Exported JSON Automation Nodes
├── firebase.json        # Cloud Deployment Configuration
└── README.md            # Comprehensive Documentation

Professional Context This project serves as a key demonstration of AI-Driven Software Engineering. It showcases the ability to manage complex cloud integrations, automated backend logic, and real-time data synchronization in a modern health-tech context.

👨‍💻 Developed By Ghulam Rasool Shirzai Portfolio | LinkedIn