Lovable Prompt Creator - AI Prompt Generator

## APPLICATION OVERVIEW
This project is a web application designed to function as an AI-Powered Symptom Triage and Referral Assistant specifically for rural healthcare settings. Its main purpose is to assist patients in assessing their symptoms through AI-driven analysis and facilitate timely referrals to appropriate healthcare facilities, ultimately bridging the gap in early diagnosis and care in rural areas.

## CORE FEATURES
1. **Symptom Input**: Users can enter their symptoms via text or voice input supported by the Web Speech API. The application will detect the language and translate it as needed.
2. **AI Symptom Assessment**: An NLP-powered engine extracts symptoms and assesses urgency levels (Low/Moderate/Critical) using machine learning models.
3. **Referral Recommendations**: Based on symptom urgency and geographic location, the application suggests appropriate healthcare facilities, such as Primary Health Centres (PHCs) or District Hospitals.
4. **Patient Advice Generation**: The application provides tailored advice to patients based on their symptoms and urgency level, ensuring clear communication.
5. **Community Health Worker (CHW) Dashboard**: A dedicated dashboard for CHWs to manage patient history and view urgency classifications, enhancing their ability to assist patients effectively.
6. **Ethical Guidelines Display**: Each output includes disclaimers about the nature of the service, ensuring users understand it is not a medical diagnosis.

## DESIGN SPECIFICATIONS
- **Visual Style**: Minimalist - Clean, simple design with plenty of white space. The layout focuses on usability and readability, featuring large buttons and clear iconography to cater to low-literacy users.
- **Color Mode**: Light theme with dark text on light backgrounds, using green, yellow, and red color codes to indicate urgency levels.
- **Layout**: A card-based layout for ease of use, with sections for symptom input, urgency display, referral recommendations, and advice generation.
- **Typography**: Use a sans-serif font for clarity, with headings in a slightly larger size to establish a clear hierarchy. Ensure sufficient spacing between text elements to enhance readability.

## TECHNICAL REQUIREMENTS
- **Framework**: React with TypeScript for a robust and type-safe frontend experience.
- **Styling**: Tailwind CSS for a responsive and easily customizable styling approach.
- **UI Components**: Utilize `shadcn/ui` for pre-built and accessible UI components.
- **State Management**: Use React's built-in state management (or Redux if needed) for managing application state across components.

## IMPLEMENTATION STEPS
1. **Week 1: Data & Model**
   - Download and preprocess the Kaggle symptom-disease dataset.
   - Train the Random Forest classifier for symptom classification.
   - Establish urgency mapping rules based on symptom severity.
   - Test the model for accuracy, targeting over 85%.
   
2. **Week 2: Backend API Development**
   - Set up FastAPI endpoints for triage, referral recommendations, and advice generation.
   - Integrate the Web Speech API for voice input functionality.
   - Implement language detection and translation for at least two regional languages.

3. **Week 3: Frontend Development**
   - Create a React UI with a symptom input form that supports both text and voice input.
   - Design the results screen to display urgency levels, referral suggestions, and advice clearly.
   - Develop a CHW dashboard for managing patient interactions and viewing history.

4. **Week 4: Integration & Testing**
   - Connect the frontend with the backend API.
   - Conduct end-to-end testing with simulated cases to ensure functionality.
   - Incorporate ethical disclaimers in the UI to inform users about the service's purpose.

5. **Final Steps: Demo Preparation**
   - Record demo scenarios showcasing the application in action.
   - Prepare a presentation slide deck covering architecture, impact, and ethical considerations.
   - Deploy the application on a low-cost VPS or Raspberry Pi for local clinic use.

## USER EXPERIENCE
Users will interact with the application by first selecting their symptoms through either voice or text input. The AI system will quickly analyze the input, classify the symptoms, and determine the urgency level. Based on this assessment, users will receive clear recommendations for the nearest healthcare facility and specific advice tailored to their symptoms. The CHW dashboard will allow community health workers to access patient histories and provide additional support, creating a seamless experience for both patients and healthcare providers.