MediMate is an AI-powered Flask web application that helps users find the right medical specialists based on their symptoms and health concerns. Using Google's Gemini AI, it provides personalized specialist recommendations and helpful medical guidance.
- Intelligent Specialist Matching : AI-powered recommendations for appropriate medical specialists
- Symptom Analysis : Analyzes user-described symptoms to suggest relevant specialties
- Educational Information : Provides brief, helpful information about medical conditions
- Safety-First Approach : Always emphasizes the importance of professional medical consultation
- REST API : Simple JSON-based API for chat interactions
- Health Check Endpoint : Monitor application status
- Cardiologist (Heart conditions)
- Dermatologist (Skin conditions)
- Neurologist (Nervous system)
- Orthopedist (Bone and joint issues)
- Gastroenterologist (Digestive system)
- Pulmonologist (Respiratory system)
- Endocrinologist (Hormonal disorders)
- Rheumatologist (Autoimmune conditions)
- Psychiatrist (Mental health)
- Gynecologist (Women's health)
- Urologist (Urinary system)
- Ophthalmologist (Eye care)
- ENT Specialist (Ear, Nose, Throat)
- And many more.....
- Python 3.8 or higher
- Google Gemini API key
- pip (Python Package Installer)
-
Clone the repository
git clone <your-repository-url> cd medimate
-
Create a virtual environment
python -m venv venv # On Windows venv\Scripts\activate # On macOS/Linux source venv/bin/activate
-
Install dependencies
pip install -r requirements.txt
-
Set up environment variables (Recommended)
Create a
.envfile in the root directory:GEMINI_API_KEY=your_actual_api_key_here FLASK_ENV=development FLASK_DEBUG=True
-
Configure API Key
Option 1: Update the API key directly in
app.py(not recommended for production)API_KEY = "your_actual_api_key_here"
Option 2: Use environment variables (recommended)
API_KEY = os.getenv('GEMINI_API_KEY')
-
Start the Flask server
python app.py
-
Access the application
- Open your browser and go to:
http://localhost:5000 - The API will be available at:
http://localhost:5000/chat - Health check endpoint:
http://localhost:5000/health
- Open your browser and go to:
medimate/
│
├── app.py # Main Flask application
├── requirements.txt # Python dependencies
├── README.md # Project documentation
├── .env # Environment variables (create this)
├── .gitignore # Git ignore file
│
└── templates/ # HTML templates (you need to create this)
└── index.html # Frontend interface
Send a message to MediMate and get specialist recommendations.
Request:
{
"message": "I have been experiencing chest pain and shortness of breath"
}Response:
{
"response": "I understand your concern about chest pain and shortness of breath. Based on these symptoms, I recommend consulting with a **Cardiologist** as your primary specialist...",
"timestamp": "2024-05-30T10:30:00.000000"
}Check if the application is running properly.
Response:
{
"status": "healthy",
"service": "MediMate"
}Create a templates/index.html file for the web interface:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>MediMate - Medical Specialist Finder</title>
<style>
body { font-family: Arial, sans-serif; margin: 40px; }
.container { max-width: 800px; margin: 0 auto; }
.chat-box { border: 1px solid #ddd; height: 400px; overflow-y: scroll; padding: 20px; margin: 20px 0; }
.input-group { display: flex; gap: 10px; }
#messageInput { flex: 1; padding: 10px; }
#sendButton { padding: 10px 20px; background: #007bff; color: white; border: none; cursor: pointer; }
</style>
</head>
<body>
<div class="container">
<h1>🏥 MediMate - Medical Specialist Finder</h1>
<p>Describe your symptoms and get recommendations for the right medical specialist.</p>
<div id="chatBox" class="chat-box"></div>
<div class="input-group">
<input type="text" id="messageInput" placeholder="Describe your symptoms..." />
<button id="sendButton">Send</button>
</div>
</div>
<script>
// Add your JavaScript for chat functionality here
</script>
</body>
</html>- Not a Medical Diagnosis Tool: MediMate provides specialist recommendations only
- Emergency Situations: For urgent symptoms, seek immediate medical attention
- Professional Consultation: Always consult with qualified healthcare professionals
- Educational Purpose: Information provided is for educational purposes only
You can modify the AI response behavior in app.py:
generation_config=genai.types.GenerationConfig(
max_output_tokens=600, # Adjust response length
temperature=0.7 # Adjust creativity (0.0-1.0)
)The application handles various error scenarios:
- Invalid API keys
- Rate limiting
- Content safety filters
- Network issues
python app.pyFor production deployment, consider:
- Using a WSGI server like Gunicorn
- Setting up proper environment variables
- Implementing rate limiting
- Adding authentication if needed
- Using HTTPS
Example with Gunicorn:
pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:5000 app:app- Fork the repository
- Create a feature branch
- Make your changes
- Test thoroughly
- Submit a pull request
This project is licensed under the MIT License - see the LICENSE file for details.
-
API Key Error
- Verify your Gemini API key is correct
- Check if the API key has proper permissions
- Ensure you haven't exceeded rate limits
-
Import Errors
- Make sure all dependencies are installed:
pip install -r requirements.txt - Verify you're using the correct Python version
- Make sure all dependencies are installed:
-
Template Not Found
- Create the
templates/directory - Add the
index.htmlfile in the templates folder
- Create the
-
Port Already in Use
- Change the port in
app.py:app.run(port=5001) - Or kill the process using the port
- Change the port in
If you encounter issues:
- Check the troubleshooting section above
- Review the error messages in the console
- Ensure all prerequisites are met
- Verify your API key is working
Remember: MediMate is a tool to help you find the right medical professional. It does not replace professional medical advice, diagnosis, or treatment.