TruthTracker is an advanced fact-checking system that uses AI to analyze and verify Twitter content in real-time. It combines multiple search engines, AI analysis, and source credibility assessment to provide comprehensive fact-checking results.

• Real-time Tweet Analysis: Fetch and analyze tweets instantly
• Multi-Source Verification: Aggregate data from Google, DuckDuckGo, and Wikipedia
• AI-Powered Analysis: Advanced claim verification using Groq AI
• Source Credibility: Evaluate source reliability and relevance
• Comprehensive Reports: Detailed fact-checking results with evidence
• Engagement Analysis: Consider social context and virality
• Async Processing: Handle multiple requests efficiently

• Python 3.9+
• Twitter API Bearer Token
• Groq API Key
• FastAPI
• uvicorn

1. Clone the repository:

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

2. Create and activate virtual environment:

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

3. Install dependencies:

pip install -r requirements.txt

4. Create .env file:

GROQ_API_KEY=your_groq_api_key
TWITTER_BEARER_TOKEN=your_twitter_bearer_token
ENVIRONMENT=development
LOG_LEVEL=INFO

5. Run the application:

uvicorn app.main:app --reload

POST /api/v1/check/tweet

{
    "tweet_id": "1234567890",
    "background_check": false
}

POST /api/v1/check/text

{
    "text": "Your text to fact check",
    "background_check": false
}

GET /api/v1/check/{check_id}

{
    "check_id": "uuid",
    "status": "completed",
    "started_at": "2024-11-24T12:00:00Z",
    "completed_at": "2024-11-24T12:00:30Z",
    "results": {
        "responses": [
            "Fact Check Results",
            "Evidence Analysis",
            "Source Analysis"
        ],
        "analysis": {
            "verdict": "True/False/Partially True",
            "confidence": "high/medium/low",
            // ... more analysis details
        }
    }
}

fact_checker/
├── app/
│   ├── api/
│   │   ├── routes.py      # API endpoints
│   │   ├── models.py      # Pydantic models
│   │   └── dependencies.py
│   ├── core/
│   │   ├── twitter.py     # Twitter integration
│   │   ├── search.py      # Search tools
│   │   ├── analysis.py    # Groq analysis
│   │   └── workflow.py    # Fact-check workflow
│   ├── services/
│   │   └── fact_checker.py
│   └── utils/
│       └── logging.py
├── requirements.txt
├── .env.example
└── README.md

pytest tests/

# Install development dependencies
pip install -r requirements-dev.txt

# Run linter
flake8 app/

# Run type checker
mypy app/

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

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

• FastAPI for the web framework
• Groq for AI analysis
• Twitter API for data access
• All the contributors and supporters

For support and questions, please open an issue on GitHub.

Built with ❤️ and Python