https://github.com/zuyux/vlinks
Decentralized AI-Driven Video Aggregation Platform
https://github.com/zuyux/vlinks
dapp link-share nextjs scraping vercel video
Last synced: about 2 months ago
JSON representation
Decentralized AI-Driven Video Aggregation Platform
- Host: GitHub
- URL: https://github.com/zuyux/vlinks
- Owner: zuyux
- Created: 2024-08-04T19:49:08.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-01-13T03:54:34.000Z (5 months ago)
- Last Synced: 2025-02-11T12:36:54.154Z (4 months ago)
- Topics: dapp, link-share, nextjs, scraping, vercel, video
- Language: TypeScript
- Homepage: https://ox-zyx.vercel.app/
- Size: 291 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Vlinks
Vlinks centralize access to audiovisual content available on various video platforms. It allows users to download this content to mobile and portable devices for personal use, simplifying the process of keeping up with multiple streams from different platforms. Vlinks also addresses the issue of algorithmic censorship by ensuring a fair redistribution of content, promoting diverse perspectives, and enhancing critical thinking among users.
## Features
- **Centralized Access**: Access all your favorite video content from various platforms in one place.
- **Download Capabilities**: Download videos to your mobile or portable devices for offline use.
- **Anti-Censorship**: Equitable redistribution of content to avoid algorithmic biases and information bubbles.
- **AI-Powered Recommendations**: Advanced algorithms to promote critical thinking and expose users to a variety of perspectives.
- **Quality Content Promotion**: Enhanced visibility for high-quality content creators using sophisticated ranking algorithms.
- **Decentralized Infrastructure**: Leveraging blockchain technology to ensure transparency and resistance to censorship.
- **Automated Tagging**: Utilizes AI for automated tagging of videos to improve searchability and recommendations.
- **Next.js**: Built with Next.js for a robust and scalable web application.
## Technology Stack
- **Front-End**: Next.js, React.js
- **Back-End**: Node.js, Express.js
- **AI & Machine Learning**: TensorFlow
- **Blockchain**: Ethereum, IPFS
- **Data Pipelines**: Apache Kafka, Apache Airflow
- **DevOps**: Docker, Kubernetes
- **Database**: PostgreSQL, MongoDB
## Key Components
1. **Content Diversification**: Optimized multi-objective algorithms to balance content relevance and diversity.
2. **Trust-Based Models**: Recommendations based on user preferences and the trustworthiness of content sources.
3. **Anti-Bias Algorithms**: Techniques like counterfactual inference and fairness-aware learning to mitigate algorithmic biases.
4. **Quality-Based Ranking**: Prioritizing content quality over immediate popularity using NLP and other metrics.
5. **Long-Tail Recommendation**: Promoting less popular but high-quality content through adjusted collaborative filtering.
6. **Explainable AI**: Enhancing user trust by explaining the rationale behind content recommendations.
7. **Decentralized Infrastructure**: Ensuring content availability and censorship resistance with blockchain and IPFS.
8. **Robust Data Pipelines and MLOps**: Efficient data ingestion, processing, and continuous model updates using tools like Apache Kafka and Airflow.
## Getting Started
### Prerequisites
- Node.js
- npm or Yarn
- Docker (for running services in containers)
### Installation
1. **Clone the repository**:
```bash
git clone https://github.com/zuyux/vlinks.git
cd ox
```
2. **Install dependencies**:
```bash
npm install
```
3. **Run the development server**:
```bash
npm run dev
```
4. **Open your browser** and navigate to `http://localhost:3000`.
### Deployment
OX can be deployed using various cloud providers or container orchestration platforms like Kubernetes. For a simple deployment, you can use Vercel:
1. **Install Vercel CLI**:
```bash
npm install -g vercel
```
2. **Deploy**:
```bash
vercel
```
## Contributing
We welcome contributions from the community. Please read our [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct and the process for submitting pull requests.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.