🏥 MediMind AI - Multimodal Health Assistant

🎬 Demo

Watch the demo GIF above to see MediMind AI in action!

A sophisticated health assistant powered by Google's Gemini 2.0 API that can analyze text, images, and audio to provide health-related insights and recommendations.

🌟 Features

• 📝 Text Analysis: Answer health questions and provide medical information
• 🖼️ Image Analysis: Analyze health-related images (rashes, medications, medical devices)
• 🎵 Audio Analysis: Process spoken health concerns and symptoms
• 🚨 Emergency Services: Quick access to emergency numbers and nearby hospital finder
• 🌍 Multilingual Support: Support for English, Hindi, and Spanish
• 📊 Session Management: Track interactions and export data
• 💡 Health Tips Database: Curated health advice by category
• ⚡ Rate Limiting: Built-in API rate limiting and error handling

🚀 Quick Start

Prerequisites

• Python 3.8 or higher
• Google Cloud Platform account with Vertex AI enabled and Places API
• Gemini 2.0 API access

Installation

1. Clone the repository

   git clone <repository-url>
   cd 'MediMind-AI-Multimodal-Health-Intelligence'

2. Install dependencies

   pip install -r requirements.txt

3. Set up credentials

   • Download your Google Cloud service account credentials JSON file
   • Place it in the project root as cred.json

4. Run the application

   Command Line Interface:

   # Interactive mode
   python main.py --interactive
   
   # Text analysis
   python main.py --text "What causes headaches?"
   
   # Image analysis
   python main.py --image rash.jpg --description "Red rash on arm"
   
   # Audio analysis
   python main.py --audio symptoms.wav --language hi

   Web Interface:

   streamlit run streamlit_app.py

   Demo:

   # Quick demo
   python examples/demo.py --quick
   
   # Full demo
   python examples/demo.py

📁 Project Structure

medi-mind-ai/
├── src/
│   ├── __init__.py
│   ├── config.py              # Configuration settings
│   ├── gemini_client.py       # Gemini API client
│   ├── health_assistant.py    # Main health assistant class
│   ├── emergency_hospital.py  # Emergency hospital finder
│   └── utils.py               # Utility functions
├── examples/
│   └── demo.py                # Demo script
├── main.py                    # Command-line interface
├── streamlit_app.py           # Web interface
├── requirements.txt           # Python dependencies
├── cred.json                  # Google Cloud credentials
└── README.md                  # This file

🔧 Configuration

VertexAI Credentials Setup

1. Create a Google Cloud Project

   • Go to Google Cloud Console
   • Create a new project or select an existing one

2. Enable APIs

   • Enable Vertex AI API
   • Enable Gemini API

3. Create Service Account

   • Go to IAM & Admin > Service Accounts
   • Create a new service account
   • Grant necessary permissions (Vertex AI User, etc.)

4. Download Credentials

   • Create and download a JSON key for the service account
   • Save as cred.json in the project root

Google Maps API Setup (For Emergency Hospital Finder)

To use the emergency hospital finder feature, you'll need a Google Maps API key:

1. Enable Google Maps APIs

   • Go to Google Cloud Console
   • Navigate to "APIs & Services" > "Library"
   • Search for and enable the following API:
     • Places API (for finding nearby hospitals)

2. Create API Key

   • Go to "APIs & Services" > "Credentials"
   • Click "Create Credentials" > "API Key"
   • Copy the generated API key

3. Usage

   • For Streamlit app: Enter the API key in the Emergency tab interface

📖 Usage Examples

Text Analysis

from src.health_assistant import HealthAssistant

assistant = HealthAssistant(project_id="your-project-id")
result = assistant.process_query(
    text_input="What are the symptoms of dehydration?", 
    language="en"
)
print(result['response'])

Image Analysis

result = assistant.process_query(
    image_path="rash.jpg", 
    description="Red rash on the arm"
)
print(result['response'])

Audio Analysis

result = assistant.process_query(
    audio_path="symptoms.wav", 
    language="hi"  # Hindi audio
)
print(result['response'])

Emergency Services Features

• Auto-location detection via IP address
• Manual location input with custom coordinates
• Nearby hospital search with customizable radius (1-10km)
• Detailed hospital information including:
  • Phone numbers (clickable in web interface)
  • Addresses
  • Ratings
  • Websites
  • Opening hours
• Emergency numbers prominently displayed
• Professional emergency UI with proper disclaimers

🌍 Multilingual Support

The assistant supports three languages:

Language	Code	Example Query
English	en	"What causes headaches?"
Hindi	hi	"मुझे सिरदर्द हो रहा है, क्या करूं?"
Spanish	es	"¿Qué debo hacer para un dolor de cabeza?"

📊 Session Management

The assistant provides session tracking and data export:

• Session tracking: Monitor interactions and usage patterns
• Data export: Export session data to JSON format
• Health tips: Access curated health advice by category

# Get session summary
summary = assistant.get_session_summary()
print(f"Total queries: {summary['total_queries']}")

# Save session data
result = assistant.save_session_to_file("session_data.json")
print(f"Session saved to: {result['filepath']}")

🛡️ Safety and Disclaimers

⚠️ IMPORTANT DISCLAIMER

This health assistant is for educational and informational purposes only. It is NOT a substitute for professional medical advice, diagnosis, or treatment.

Key Points:

• ❌ NOT for medical diagnosis or treatment
• ❌ NOT for emergency situations
• ❌ NOT a replacement for healthcare professionals
• ✅ FOR learning and information
• ✅ FOR general health awareness
• ✅ FOR educational purposes

Always consult qualified healthcare professionals for medical concerns.

🔒 Privacy & Security

• No data is stored permanently
• All processing happens through Google's secure APIs
• Credentials are handled locally
• Session data can be exported/deleted

Adding New Features

1. Update the appropriate module in src/
2. Update documentation
3. Test thoroughly
4. Streamlit app updates if necessary

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests (if applicable)
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Google Gemini 2.0 API
• GDE AI Sprint 2025 #AISprint
• Streamlit for the web interface
• The open-source community

📞 Support

For issues and questions:

1. Check the documentation
2. Review existing issues
3. Create a new issue with details

---

Remember: This is an educational tool. Always consult healthcare professionals for medical advice.