Ami - Family Healthcare Assistant 🏥🤖

Ami is a full-stack AI-powered family healthcare assistant built to provide personalized health advice, seamless daily interaction, and multi-user support via face recognition.

🌟 Key Features

• Face Recognition Login: Built-in OpenCV facial recognition to automatically identify family members and fetch their specific medical history.
• AI Brain: Powered by Google's Gemini for conversational health assistance, empathetic responses, and emotion detection.
• Live Widgets: Real-time integrations with WeatherAPI and NewsAPI to give context to daily conversations.
• Persistent Conversation Memory: Learns frequent topics and tracks the history of individual members automatically.
• Voice Support: Integrated speech-to-text and text-to-speech for accessible communication.

🏗️ System Architecture

graph TD
    subgraph Frontend [React + Vite Frontend]
        UI[User Interface]
        Webcam[React Webcam]
        Audio[Audio/Voice Interface]
    end
    subgraph Backend [FastAPI Backend]
        API[FastAPI Router]
        Auth[Face Recognition Module]
        Memory[Conversation Memory Manager]
        Gemini[Gemini AI Handler]
    end
    subgraph External Services
        MySQL[(MySQL Database)]
        Google[Google Gemini API]
        Weather[WeatherAPI]
        News[NewsAPI]
    end
    UI <-->|JSON/REST| API
    Webcam -->|Image Bytes (UploadFile)| Auth
    
    API <--> Memory
    Memory <--> MySQL
    Auth <--> MySQL
    
    API <--> Gemini
    Gemini <--> Google
    API --> Weather
    API --> News

🔄 Face Recognition Workflow

sequenceDiagram
    participant User
    participant Frontend
    participant FastAPI
    participant OpenCV
    participant MySQL
    User->>Frontend: Steps in front of camera
    Frontend->>FastAPI: POST /recognize (Image Bytes)
    FastAPI->>OpenCV: Extract features (Grayscale -> Haarcascade -> LBP Histogram)
    FastAPI->>MySQL: Fetch stored member encodings
    MySQL-->>FastAPI: Return encoded face features
    FastAPI->>FastAPI: Calculate Euclidean distance
    FastAPI-->>Frontend: Return Authentication Success (Member Data)
    Frontend-->>User: "Welcome back!" & Load Healthcare Profile

💻 Technology Stack

Frontend

• Framework: React 18 with Vite
• Styling: Tailwind CSS
• Icons & UI: Lucide React, modern component styling
• Hardware Integrations: react-webcam

Backend

• Framework: FastAPI (Python)
• AI / ML: OpenCV Haarcascade, Google Generative AI (gemini-pro/vision)
• Database: MySQL with Python Connector Pooling
• Audio Processing: Google Text-to-Speech (gTTS), SpeechRecognition, PyDub

🚀 Getting Started

1. Database Configuration

1. Create a MySQL database named healthcare.
2. Run the backend/database.sql script to set up the necessary members and families tables.

2. Configure Environment Variables

Inside the backend/ folder, create a .env file containing the following:

DB_HOST=localhost
DB_USER=root
DB_PASSWORD=your_mysql_password
DB_NAME=healthcare
DB_PORT=3306
GOOGLE_API_KEY=your_gemini_api_key
WEATHER_API_KEY=your_weatherapi_key
NEWS_API_KEY=your_newsapi_key

3. Start the Backend Server

Open your terminal and run:

cd backend
python -m venv venv
venv\Scripts\activate   # (or source venv/bin/activate on Mac/Linux)
pip install -r requirements.txt
python app.py

4. Start the Frontend App

Open a second terminal window and run:

cd frontend
npm install
npm run dev

Your app should now be running locally at http://localhost:5173!