🥗 AI Nutrition Analyzer & Daily Diet Tracker

A Flask-based web application that analyzes food nutrition using the USDA FoodData Central API. Users can search for food items, view detailed nutritional information, save meals to a daily tracker, monitor nutrition intake, and receive AI-inspired dietary recommendations.

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📌 Features

• 🔍 Search food items using the USDA FoodData Central API
• 🔥 View calories and nutritional information
• 💪 Display protein, fat, carbohydrates, fiber, and sugar
• 🍽️ Add meals to a daily nutrition tracker
• 📊 Dashboard with nutrition summary and charts
• 🤖 AI-inspired health recommendations based on daily intake
• 💾 SQLite database for storing meal history
• 🌐 Responsive web interface built with Flask

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🛠️ Technologies Used

Frontend

• HTML5
• CSS3
• JavaScript
• Chart.js

Backend

• Python
• Flask

Database

• SQLite

API

• USDA FoodData Central API

Python Libraries

• Flask
• Requests
• python-dotenv

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📁 Project Structure

Nutrition-Analyzer/
│
├── app.py
├── config.py
├── requirements.txt
├── README.md
├── .env
├── database.db
│
├── models/
│   └── database.py
│
├── services/
│   └── usda_api.py
│
├── utils/
│   └── recommendation.py
│
├── templates/
│   ├── index.html
│   ├── tracker.html
│   └── dashboard.html
│
└── static/
    ├── style.css
    ├── script.js
    └── images/

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⚙️ Installation

1. Clone the repository

git clone https://github.com/your-username/Nutrition-Analyzer.git

2. Open the project

cd Nutrition-Analyzer

3. Create a virtual environment

python -m venv venv

4. Activate the virtual environment

Windows

venv\Scripts\activate

5. Install dependencies

pip install -r requirements.txt

6. Create a .env file

USDA_API_KEY=YOUR_API_KEY

7. Run the application

python app.py

Open your browser and visit:

http://127.0.0.1:5000

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📷 Application Modules

• Home Page
• Food Search
• Nutrition Analysis
• Daily Meal Tracker
• Nutrition Dashboard
• AI Health Recommendations

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📊 Database

The application automatically creates an SQLite database (database.db) to store:

• Food Name
• Meal Type
• Calories
• Protein
• Fat
• Carbohydrates
• Fiber
• Sugar
• Quantity
• Date & Time

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🤖 AI Recommendation Logic

The application analyzes the user's daily nutritional intake and provides health recommendations such as:

• High calorie alerts
• Low protein suggestions
• High fat warnings
• High carbohydrate alerts
• Fiber improvement tips
• Sugar intake warnings

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🎯 Future Enhancements

• User authentication
• Weekly and monthly nutrition reports
• PDF report generation
• Food image integration
• BMI calculator
• Water intake tracker
• Personalized nutrition goals

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👩‍💻 Developed By

Samriddhi Gupta

AI/ML Internship Final Project

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📄 License

This project is developed for educational and internship purposes.