Lovable Prompt Creator - AI Prompt Generator

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## APPLICATION OVERVIEW
The AI-Based Scam Message & Fake News Detection System is a web application designed to help users identify and classify suspicious messages, links, and news. By leveraging AI technology, it provides instant feedback on whether the content is a scam, fake news, or safe, empowering users to protect themselves from cyber threats.

## CORE FEATURES
- **Message and Link Analysis**: Users can paste messages or links for real-time analysis using the AI detection engine.
- **Classification Output**: The system outputs a classification result (Scam, Fake News, Safe) along with a risk level and confidence score.
- **Scam Category Detection**: Identifies specific categories of scams, such as Lottery/Prize Scam, OTP Fraud, and more.
- **AI Explanation**: Provides insights into the detection process, detailing the patterns that led to the classification.
- **Safety Tips**: Offers personalized safety suggestions based on the content analyzed.
- **Admin Dashboard**: Allows administrators to monitor reported scams, analyze trends, and manage user reports.

## DESIGN SPECIFICATIONS
- **Visual Style**: Minimalist design featuring a clean, simple interface with ample white space. The focus remains on readability and user interaction.
- **Color Mode**: Light theme with dark text on light backgrounds to ensure clarity and ease of reading.
- **Layout**: 
  - **Home Page**: Title, short description, input area for messages/links, analyze button, and output display section including results and tips.
  - **History Page**: Displays previously scanned messages with snippets, results, risk levels, and reporting options.
- **Typography**: Use modern sans-serif fonts like Inter or Roboto for headings and body text, ensuring a clear hierarchy with larger sizes for titles and ample line spacing for readability.

## TECHNICAL REQUIREMENTS
- **Framework**: React with TypeScript for building a robust and type-safe frontend.
- **Styling**: Tailwind CSS for responsive design and quick styling.
- **UI Components**: Utilize shadcn/ui for reusable UI elements that maintain consistency throughout the application.
- **State Management**: Use React Query or Context API for managing application state and data fetching.

## IMPLEMENTATION STEPS
1. **Set up the Project Structure**: Initialize a new React project with TypeScript and Tailwind CSS.
2. **Create the AI Detection Engine**: Integrate a free NLP model from HuggingFace to classify text inputs.
3. **Build the Frontend Components**:
   - Design the Home Page with input and output components.
   - Create the History Page to display previous analyses.
4. **Implement Backend Logic**: Use Node.js/Express or Python FastAPI to handle requests between the frontend and the AI engine.
5. **Set Up Database**: Choose SQLite or a JSON storage solution to log user scans and history.
6. **Develop the Admin Dashboard**: Create a backend interface for administrators to view, filter, and export scam reports.
7. **Testing and Validation**: Include sample test cases to validate the AI output and overall application functionality.
8. **Deployment**: Prepare the application for deployment with a clear README and instructions for running the project.

## USER EXPERIENCE
The user journey begins on the Home Page, where users can easily paste a suspicious message or link into the input area and click the Analyze button. The results are displayed promptly, showing the classification, risk level, confidence score, and safety tips. Users can view their scan history on a dedicated page, where they can flag messages as suspicious, ensuring a comprehensive and user-friendly experience.

This comprehensive prompt outlines a detailed plan for creating a full-stack web application that meets the specified requirements while maintaining a user-friendly and minimalist design.
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