Hardcore Blackout

A sophisticated Chrome extension that helps you take control of your social media experience through advanced content filtering and rating, powered by local AI processing with Ollama.

Features

🎯 Smart Content Rating

• Real-time content analysis using Ollama AI models
• 0-100 rating scale with visual indicators
• Content classification with icons (💬 Personal, 💼 Business, 💻 Tech, etc.)
• Comprehensive rating components:
  • Content Quality (40%)
  • Emotional Impact (30%)
  • User Preferences (30%)

🛡️ Content Filtering

• Platform-specific content detection (Twitter, Facebook, Reddit, LinkedIn)
• Customizable filtering thresholds
• Visual feedback through color-coded ratings
• Quick actions: Hide/Block content
• Automatic content dimming or hiding based on quality scores

🔒 Privacy First

• All processing happens locally using Ollama
• No data sent to external servers
• Complete control over AI model selection
• Your social media content never leaves your device

📊 Feed Analytics

• Track content quality trends over time
• Identify top authors and content types
• Export analytics data (CSV/JSON)
• LinkedIn-specific feed analysis

⚡ Performance

• Efficient post detection and processing
• Smart caching system with 24-hour expiration
• Minimal impact on browsing experience
• Real-time processing counter

🎨 Modern UI

• Clean, intuitive interface
• Dark mode support
• Material Design components
• Responsive overlays and popups
• Welcome screen with feature overview

Tech Stack

• Frontend: React 18, TypeScript, Material-UI
• Styling: TailwindCSS, PostCSS
• AI: Ollama (local LLM server)
• Build: Webpack 5, Babel
• Storage: Chrome Storage API, SQL.js for analytics

Prerequisites

Before you begin, ensure you have the following:

1. Node.js and npm

   • Download and install from nodejs.org
   • Required version: 16.x or higher

2. Ollama

   • Download and install from ollama.ai
   • Run Ollama locally: ollama serve
   • Pull a model (e.g., ollama pull llama3.2 or ollama pull gemma3:4b)

3. Git

   • For cloning the repository

Installation

1. Clone the repository

git clone https://github.com/yourusername/chrome-extension-hardcode-blackout.git
cd chrome-extension-hardcode-blackout

2. Install dependencies

npm install

3. Build the extension

npm run build

4. Load in Chrome

1. Open Chrome and navigate to chrome://extensions/
2. Enable "Developer mode" (toggle in top right)
3. Click "Load unpacked"
4. Select the dist directory from the project

5. Start Ollama

Make sure Ollama is running on your system:

ollama serve

Development

Available Scripts

# Development build with watch mode
npm run dev

# Production build
npm run build
npm run prod

# Type checking
npm run type-check

# Linting
npm run lint
npm run lint:fix

# Testing
npm test
npm run test:watch
npm run test:coverage

Project Structure

src/
├── background/          # Background service worker
│   ├── index.ts        # Main background script
│   ├── ollama-service.ts # Ollama API integration
│   └── database-service.ts # Analytics database
├── content/            # Content scripts
│   ├── content-script.ts # Main content script
│   └── feed-analyzer.ts  # LinkedIn feed analytics
├── ui/                 # React UI components
│   ├── popup/          # Extension popup
│   └── options/        # Options page
└── utils/              # Shared utilities and types

Development Workflow

1. Start Ollama: Ensure Ollama is running locally
2. Run dev build: npm run dev for automatic rebuilding
3. Reload extension: Click refresh in chrome://extensions/ after changes
4. Debug: Use Chrome DevTools for debugging

Configuration

Ollama Setup

1. Install Ollama models:

   # Recommended models
   ollama pull llama3.2      # Fast, balanced
   ollama pull gemma3:4b     # Google's Gemma
   ollama pull mistral       # Mistral AI
   ollama pull phi3          # Microsoft Phi-3

2. Configure in extension:

   • Click the extension icon
   • Go to Settings
   • Select your preferred Ollama model
   • Adjust inference settings (temperature, max tokens)

Content Filtering Settings

• Auto-Hide Threshold: Posts below this score are hidden (default: 20)
• Dim Threshold: Posts below this score are dimmed (default: 40)
• Highlight Threshold: Posts above this score are highlighted (default: 80)

Usage

Basic Usage

1. Initial Setup:

   • Install the extension
   • Ensure Ollama is running
   • Visit the options page for initial configuration

2. Browsing Social Media:

   • Navigate to supported platforms (Twitter, Facebook, Reddit, LinkedIn)
   • Posts are automatically analyzed and rated
   • Look for the rating overlay in the top-right of each post

3. Understanding Ratings:

   • 🔴 0-20: Very Poor (auto-hidden)
   • 🟠 20-40: Poor (dimmed)
   • 🟡 40-60: Fair (slightly dimmed)
   • 🟢 60-80: Good (normal display)
   • 🟢 80-100: Excellent (may be highlighted)

4. Content Classification Icons:

   • 💬 Personal/Social
   • 💼 Business
   • 💻 Technology
   • 💰 Finance
   • 📰 News
   • 🎬 Entertainment
   • 📚 Education
   • 📢 Promotion/Ads
   • 🏛️ Politics
   • 📄 Other

Advanced Features

• Feed Analytics (LinkedIn only):

  • View content quality trends
  • Track top authors
  • Export data for analysis

• Quick Actions:

  • Hide: Temporarily hide a post
  • Block: Permanently block similar content

Troubleshooting

Common Issues

1. "Ollama Not Available" error:

   • Ensure Ollama is running: ollama serve
   • Check if it's accessible at http://localhost:11434
   • Try clicking "Check Ollama Status" in settings

2. No ratings appearing:

   • Check the extension console for errors
   • Verify Ollama has a model loaded
   • Ensure you're on a supported platform

3. Performance issues:

   • Try a smaller Ollama model (e.g., phi3)
   • Adjust max tokens in settings
   • Clear cached ratings in Chrome storage

Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

Development Process

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Privacy & Security

• Local Processing: All AI inference happens on your device via Ollama
• No External APIs: No content is sent to external services
• Data Storage: Only ratings and analytics are stored locally
• Open Source: Full code transparency

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Ollama for local LLM inference
• Material-UI for UI components
• The open-source community for inspiration and support

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Note: This extension requires Ollama to be installed and running on your local machine. It does not include any AI models - you must download them separately through Ollama.