Lovable Prompt Creator - AI Prompt Generator

## APPLICATION OVERVIEW
This application is a web-based tool designed for vocal mood detection, allowing users to upload audio samples and receive instant feedback on the mood conveyed within the audio. The application aims to provide a premium and interactive experience while maintaining a minimalist aesthetic.

## CORE FEATURES
1. **Audio Upload**: Users can easily upload audio samples in various formats (e.g., MP3, WAV) for analysis.
2. **Mood Detection Engine**: Utilizes advanced algorithms to analyze vocal characteristics and determine the mood of the audio sample (e.g., happy, sad, angry).
3. **Visualization Dashboard**: Displays mood predictions in a unique and engaging format, such as dynamic graphs or emotive icons, to enhance user understanding.
4. **User Feedback Loop**: Users can provide feedback on the accuracy of mood predictions to improve model performance over time.
5. **History Log**: Allows users to view past audio uploads and their corresponding mood analyses, enhancing user engagement and retention.
6. **Settings Panel**: Users can adjust preferences for mood detection sensitivity and notification settings.

## DESIGN SPECIFICATIONS
- **Visual Style**: Minimalist with a clean, simple design that emphasizes functionality. The layout should have ample white space to ensure clarity and focus on content.
- **Color Mode**: Light theme featuring dark text on light backgrounds, promoting readability and a premium feel.
- **Layout**: 
  - **Home Page**: Centralized audio upload feature with a prominent call-to-action button, flanked by brief descriptions of the app's purpose.
  - **Results Page**: Dynamic visualization of mood detection results, utilizing a grid layout for mood icons and feedback options.
  - **History Page**: Clean list view of past uploads with mood results, allowing easy access to historical data.
- **Typography**: Use modern sans-serif fonts such as "Roboto" or "Helvetica Neue" for body text and headings, ensuring a clear hierarchy with larger font sizes for titles and appropriate spacing for readability.

## TECHNICAL REQUIREMENTS
- **Framework**: React with TypeScript for a robust and scalable web application.
- **Styling**: Tailwind CSS for responsive design and streamlined styling capabilities.
- **UI Components**: Utilize shadcn/ui for pre-built components that align with the minimalist design aesthetic.
- **State Management**: Use React Context or a state management library like Redux if necessary for managing global state across the application.

## IMPLEMENTATION STEPS
1. **Project Setup**: Initialize a new React project with TypeScript and install Tailwind CSS and shadcn/ui.
2. **Create Core Components**: Develop the audio upload component, mood detection engine, and visualization dashboard.
3. **Implement Mood Detection Logic**: Integrate machine learning models or third-party APIs for mood analysis based on vocal characteristics.
4. **Design Layout**: Structure the main pages (Home, Results, History) following the specified layout and apply Tailwind CSS for styling.
5. **Connect State Management**: Set up state management for user data, uploaded audio, and mood results.
6. **Testing**: Conduct thorough testing of the application for functionality, performance, and user experience.
7. **Deployment**: Deploy the application on a cloud platform, ensuring accessibility and scalability.

## USER EXPERIENCE
Users will interact with the application by navigating to the home page to upload audio files. Upon submission, they will be redirected to the results page, where mood predictions are visualized in an engaging format. Users can provide feedback on the results, which will be recorded in their history log for future reference. The settings panel allows customization of their experience, making the tool both intuitive and user-friendly. The overall interaction flow should feel seamless and responsive, enhancing the user experience.