FactFlux

An intelligent multi-agent system for fact-checking social media posts using Agno framework and Bright Data tools.

🚀 Features

• Multi-Platform Support: TikTok, Instagram, Twitter/X, Facebook, YouTube, LinkedIn
• Intelligent Tool Selection: Automatically chooses optimal scraping methods
• Comprehensive Analysis: Content extraction, claim identification, cross-referencing, verdict synthesis
• Authoritative Sources: Verifies against news sites, fact-checkers, official sources
• Confidence Scoring: Evidence-based verdicts with transparency

Demo

Click to watch FactFlux in action

📋 Prerequisites

• Python 3.8+
• Valid API keys for:
  • Google's Gemini
  • Bright Data

🛠️ Installation

1. Clone the repository

   git clone https://github.com/MeirKaD/FactFlux.git
   cd FactFlux

2. Create virtual environment

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

3. Install dependencies

   pip install -r requirements.txt

4. Configure environment variables

   cp .env.example .env
   # Edit .env with your API keys

🔧 Configuration

Create a .env file with your API keys:

GOOGLE_API_KEY=your_google_gemini_api_key_here
BRIGHT_DATA_API_KEY=your_bright_data_api_key_here

🎯 Usage

Playground Mode (Recommended)

python playground_fact_check.py

Access the playground through the following URL :

https://app.agno.com/playground/teams?endpoint=localhost%253A7777

🏗️ Architecture

Agent Team Structure

1. Content Extractor Agent

   • Extracts post data using optimal Bright Data tools
   • Handles multiple platforms automatically

2. Claim Identifier Agent

   • Identifies verifiable factual claims
   • Separates facts from opinions/satire

3. Cross-Reference Agent

   • Verifies claims against authoritative sources
   • Performs reverse media searches

4. Verdict Agent

   • Synthesizes evidence and delivers final verdict
   • Provides confidence scores and reasoning

Workflow Process

URL Input → Content Extraction → Claim Identification → Cross-Reference → Final Verdict

🛡️ Supported Platforms

• ✅ TikTok
• ✅ Instagram
• ✅ Twitter/X
• ✅ Facebook
• ✅ YouTube
• ✅ LinkedIn

🚨 Error Handling

The system includes comprehensive error handling for:

• Invalid URLs
• Network failures
• API rate limits
• Malformed social media posts
• Missing content

🤝 Contributing

1. Fork the repository
2. Create a 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

📝 License

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

🆘 Support

• Check the logs for detailed error information
• Ensure all API keys are valid and have sufficient credits
• Verify the social media URL is publicly accessible
• Review the supported platforms list

🔄 Updates

• Check for Agno framework updates: pip install -U agno
• Monitor Bright Data API changes
• Keep model versions updated in configuration

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Note: This system is designed for educational and research purposes. Always respect platform terms of service and rate limits.