An AI-powered symptom screening application that uses Gemini to provide dynamic medical questionnaires and recommendations.

• Dynamic Question Generation: Uses Google's Gemini AI to generate contextual follow-up questions based on user responses
• Body Area Selection: Interactive body selector for targeted symptom assessment
• Intelligent Diagnosis: AI-powered analysis providing diagnosis confidence levels and recommendations
• Appointment Booking: Integration with family doctor scheduling
• Clinic Finder: Locate nearby medical facilities

Frontend:

• React + TypeScript
• Vite
• Tailwind CSS
• shadcn/ui components

Backend:

• Flask (Python)
• SQLAlchemy + Alembic
• Google Gemini AI
• CORS enabled for frontend integration

• Node.js (v16 or higher)
• Python 3.8+
• Pipenv (for Python dependency management)

1. Navigate to the server directory:

   cd server

2. Install Python dependencies:

   pipenv install
   pipenv shell

3. Set up environment variables: Create a .env file in the server directory:

   # Required for production
   GEMINI_API_KEY=your_gemini_api_key_here
   DATABASE_URL=sqlite:///./symptify.db
   
   # Optional: Use mock responses for development
   USE_GPT_MOCK=1

4. Run database migrations:

   alembic upgrade head

5. Start the Flask server:

   python -m app.main

   The server will run on http://localhost:5001

1. Navigate to the client directory:

   cd client

2. Install dependencies:

   npm install

3. Create environment file: Create a .env file in the client directory:

   VITE_API_URL=http://localhost:5001

4. Start the development server:

   npm run dev

   The client will run on http://localhost:5173

For development without a Gemini API key, set USE_GPT_MOCK=1 in your server .env file. This will use predefined mock responses instead of calling the Gemini API.

• POST /api/questions/generate

  • Generate next question or final diagnosis
  • Body: { "answers": {}, "body_location": "head" }
  • Returns: Question object or diagnosis result

• GET /api/questions/status

  • Get API status and available conditions

1. Select Body Areas: Choose areas of discomfort using the interactive body selector
2. Answer Questions: Respond to AI-generated questions tailored to your symptoms
3. Receive Diagnosis: Get AI analysis with confidence level and recommendations
4. Take Action: Follow self-care advice or book medical appointments

The frontend maps detailed body regions to general categories:

• head, neck → head
• chest → chest
• abdomen, pelvis → abdomen
• back → back
• *arm*, *hand* → arms
• *thigh*, *shin*, *foot* → legs

interface GeminiQuestion {
  question: string;
  question_id: string;
  type: "yes/no" | "multiple_choice";
  options: string[];
  is_final: boolean;
  question_number: number;
  total_questions: number;
}

interface GeminiDiagnosis {
  diagnosis: string;
  confidence: "high" | "medium" | "low";
  recommendation: "self_care" | "see_doctor";
  advice: string;
}

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Ensure TypeScript compilation passes: tsc --strict
5. Test the end-to-end flow
6. Submit a pull request

MIT License