X Thread Analyzer (XRAT10)

An intelligent web application that analyzes X (formerly Twitter) threads for sentiment analysis, bot detection, and engagement metrics.

Features

• Real-time thread monitoring and analysis
• Advanced sentiment analysis using VADER
• Lightweight bot detection
• Engagement-optimized responses
• Web interface for manual analysis
• Historical analysis storage
• Automated engagement strategies

Prerequisites

• Python 3.8+
• X Developer Account with API access
• SQLite3

Installation

1. Clone the repository:

git clone https://github.com/yourusername/XRAT10.git
cd XRAT10

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Set up environment variables:

cp .env.example .env

Edit .env with your X API credentials and other configuration settings.

Environment Variables

The following environment variables are required:

• X_API_KEY: Your X API Key
• X_API_SECRET: Your X API Secret
• X_ACCESS_TOKEN: Your X Access Token
• X_ACCESS_TOKEN_SECRET: Your X Access Token Secret
• X_BEARER_TOKEN: Your X Bearer Token
• CLIENT_ID: Your OAuth 2.0 Client ID
• CLIENT_SECRET: Your OAuth 2.0 Client Secret
• SECRET_KEY: A secure secret key for the application
• DEBUG: Set to False in production
• DATABASE_URL: Your database URL (default: SQLite)

For development, copy .env.example to .env and fill in your values. For production deployment (e.g., Vercel), set these in your deployment platform's environment variables.

Project Structure

XRAT10/
├── app/
│   ├── api/
│   │   └── endpoints/
│   ├── core/
│   │   ├── config.py
│   │   └── security.py
│   ├── db/
│   │   └── models.py
│   ├── services/
│   │   ├── sentiment.py
│   │   └── bot_detection.py
│   ├── static/
│   │   ├── css/
│   │   └── js/
│   └── templates/
├── tests/
├── .env.example
├── .gitignore
├── README.md
└── requirements.txt

Usage

1. Start the application:

uvicorn app.main:app --reload

2. Access the web interface at http://localhost:8000

3. Enter a tweet ID to analyze or wait for mentions to trigger automatic analysis

API Endpoints

• GET /: Home page
• POST /analyze: Analyze a specific thread
• GET /past_analyses: View historical analyses
• GET /api/v1/stats: Get analysis statistics (API)

Deployment

Local Development

Follow the installation instructions above.

Production (Vercel)

1. Fork/clone this repository
2. Import to Vercel
3. Set up environment variables in Vercel project settings
4. Deploy!

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

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

Acknowledgments

• VADER Sentiment Analysis
• FastAPI framework
• X API