⚖️ The Other Side

🎯 Breaking the Echo Chamber

Our mission is to present people with a place to test the validity of their beliefs and expose themselves to new ideas from reliable sources advocating for all sides of a topic. By leveraging advanced AI and a curated knowledge base, we aim to foster meaningful dialogue and deeper understanding across different viewpoints.

💡 Overview

The Other Side is a website and Chrome extension that revolutionizes how people engage with online content and controversial topics. Using a specialized RAG (Retrieval-Augmented Generation) model trained on peer-reviewed research papers and reputable sources, we provide users with:

• Real-time fact-checking and source verification
• Balanced perspectives on complex topics
• Access to academic research in digestible formats
• Interactive debate features with AI-powered moderation

Our platform helps break echo chambers by exposing users to well-researched, diverse viewpoints while maintaining high standards of intellectual rigor.

✨ Key Features

• Interactive Debates: Engage in educational discussions with real-time fact-checking and source verification
• Webpage Analysis: Challenge and verify information on any webpage with our Chrome extension
• Source Library: Access a comprehensive database of peer-reviewed research and credible sources

🎨 Design Philosophy

Our platform is built on three core principles:

1. Transparency: All data sources are openly available and verifiable
2. Accessibility: Complex topics are presented in understandable formats
3. Neutrality: Balanced presentation of different viewpoints with clear source attribution

🛠️ Technologies Used

Frontend

• React 19: Core framework for building our user interface
• Framer Motion: Advanced animations and transitions

Backend

• Flask: Python-based REST API
• MongoDB: Document storage for user data and cached sources
• Google OAuth: Secure user authentication
• GCP (Google Cloud Platform): Cloud infrastructure and scaling
• Vertex AI: Large language model deployment and RAG implementation

AI/ML Stack

• Custom RAG Pipeline: Built with Vertex AI

⬇️ Installation Instructions

1. Clone the repository and navigate to the frontend directory:

   cd frontend-new/

2. Install the necessary Node.js dependencies:

   npm install

3. Build the frontend application:

   npm run build

4. Navigate to the backend directory:

   cd ../backend

5. Install the required Python dependencies:

   pip install -r requirements.txt

6. Start the backend application:

   python app.py
   

🎯 Future Enhancements

• Improved Data Curation: Disagreements on some topics may stem from deeper systemic divides (e.g. religion, ethnicity), there are less research papers, not only on the subject as a whole, but for each side as well.
• Knowledge Base Expansion: Add more topics and sources while maintaining quality standards
• Open Source Model: Release model weights and training pipeline for community verification
• Multimodal Integration: Support for images, videos, and audio in discussions
• Community Features: Peer review system for user contributions
• API Access: Public API for researchers and developers

🤝 Contributing

We welcome contributions from the community! To contribute:

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Open a pull request