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👨‍⚕️ AI Nutritionist App

An AI-powered Health Management application built with Streamlit and Google Gemini API that helps users analyze food images to estimate calories and classify food items.

🚀 Features

  • 📷 Upload food images (JPG, JPEG, PNG)
  • 🤖 Analyze food items using Google Gemini multimodal model
  • 🔢 Estimate total calories with detailed breakdown
  • 🍎 Classify food into categories (fruits, vegetables, protein, grains, desserts, etc.)
  • 💡 Option to provide additional context (e.g., portion size)

🛠️ Tech Stack


📂 Project Structure

AI_Nutritionist_App/
    │── app.py # Main Streamlit app
    │── .env # Environment variables
    |    (contains GOOGLE_API_KEY)
    │── requirements.txt # Python dependencies
    │── README.md # Project documentation

⚙️ Installation & Setup

  1. Clone the repository

    git clone https://github.com/22MH1A42G1/AI_Nutritionist_App.git
    cd AI_Nutritionist_App
  2. Create a virtual environment (optional but recommended)

    python -m venv venv
    source venv/bin/activate   # For Linux/Mac
    source venv\Scripts\activate # For Windows
  3. Install dependencies

    pip install -r requirements.txt
  4. Set up environment variables

  • Create a .env file in the root folder and add your Google Gemini API key:
    GOOGLE_API_KEY=your_api_key_here
  1. Run the app
    python -m streamlit run app.py

📌 Usage

  • Open the app in your browser (default: http://localhost:8501).

  • Choose a task:

    1. Calorie Estimation → Get calorie breakdown of detected food items.

    2. Food Classification → Classify food into categories.

  • Upload a food image.

  • (Optional) Provide additional notes (e.g., portion size).

  • Click Analyze → Get AI-powered insights.

🧩 Example Output

Input: Uploaded image of rice, chicken curry, and salad.

Output:

  1. Rice (1 cup) - 200 calories
  2. Chicken Curry - 350 calories
  3. Salad - 80 calories

Total: 630 calories

✅ To-Do / Future Enhancements

  • 📊 Daily calorie tracker (using st.session_state)

  • 🥗 Personalized health recommendations

  • 📅 Meal logging & nutrition history

  • ⚡ Deploy to Streamlit Cloud / Hugging Face Spaces


👨‍💻 Author

Developed by Indana Aditya

🌐 LinkedIn

💻 GitHub

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An AI-powered Health Management application built with Streamlit and Google Gemini API that helps users analyze food images to estimate calories and classify food items.

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