A powerful tool for monitoring Twitter users through Nitter instances, featuring AI-powered translation, analysis, and smart notification system.
- Intelligent content categorization with emojis:
- 💰 Cryptocurrency related
- 🚀 Space exploration
- 🤖 Artificial Intelligence
- 💊 Important policies/announcements
- 🀄 Other significant content
- DeepSeek API integration for accurate translation
- Smart content summarization and key points extraction
- Uses steel-browser (browserless/chrome) for stable web scraping
- Automatic instance health monitoring and switching
- Screenshot capture for tweet preservation
- Monitor influential figures' real-time opinions
- Track cryptocurrency market sentiment
- Proactive information gathering instead of passive subscription
- Quick translation and key information extraction
- 📈 Cryptocurrency market monitoring
- 🗣️ Public figure statement tracking
- 📰 Breaking news early detection
- 💡 Tech trend analysis
- 📊 Market sentiment analysis
- 🔄 Monitor Twitter users through multiple Nitter instances
- 🌐 Automatic instance switching and health monitoring
- 📷 Automatic screenshot capture of tweets
- 🔔 Support multiple push channels (ServerChan, PushDeer)
- 🤖 AI-powered translation and analysis
- 🖼️ Built-in image server for screenshot viewing
- 🐳 Docker support for easy deployment
- Clone the repository:
git clone https://github.com/yourusername/twitter-monitor.git
cd twitter-monitor- Copy and configure environment file:
cp .env.example .env
# Edit .env with your settings- Start with Docker Compose:
docker-compose -f docker-compose-demo.yaml up -dKey environment variables in .env:
TWITTER_USERS: List of users to monitor (format:alias:username,alias2:username2)CHECK_INTERVAL: Check interval in secondsDEEPSEEK_KEY: Your DeepSeek API key for translationPUSH_KEY/SC_KEY: Push notification keys
The demo setup includes:
- Twitter monitor service
- Browserless Chrome for web scraping
- Persistent storage for archives and screenshots
- Image server for viewing screenshots
Supported push channels:
- ServerChan
- PushDeer
/archives: Tweet archives/data/screenshots: Tweet screenshots/logs: Application logs
- Create virtual environment:
python -m venv .venv
source .venv/bin/activate # Linux/Mac
# or
.venv\Scripts\activate # Windows- Install dependencies:
pip install -r requirements.txt- Run tests:
python -m pytest tests/MIT License
Contributions are welcome! Please feel free to submit a Pull Request.