🥷 gwei-sensei

A machine learning-powered tool for predicting optimal transaction fees and scheduling deployments across multiple blockchain networks. Despite the playful 'gwei' reference in the name (a nod to Ethereum's gas unit), gwei-sensei supports both EVM and non-EVM chains where transaction fee optimization is crucial. It helps developers minimize costs and optimize deployment timing using historical fee data and advanced prediction models.

🎯 Features

• Fee Prediction: ML-based forecasting of transaction fees across chains
• Deployment Scheduling: Optimal timing suggestions for contract/program deployments
• Multi-Chain Support: Extensive support for various blockchain networks
• Flexible Usage: Available as bot- Historical Analysis: Uses historical fee data for accurate predictions

🌐 Supported Networks

gwei-sensei supports fee optimization for the following blockchain networks:

EVM Compatible Networks

• Ethereum Mainnet
• Polygon PoS
• BNB Smart Chain
• Arbitrum One
• Optimism
• Avalanche C-Chain
• Base
• zkSync Era
• Linea

Non-EVM Networks

• Solana (prioritization fees)
• Cosmos Hub (gas fees)
• Sui (gas fees)
• Aptos (gas fees)
• Near Protocol (gas fees)
• Polkadot (transaction fees)
• Cardano (transaction fees)
• Tezos (gas fees)

Each network has its own fee model and optimization strategies. gwei-sensei automatically adjusts its predictions and recommendations based on the specific characteristics of each chain.

📦 Installation

Install gwei-sensei globally using npm:

npm install -g gwei-sensei

Or add it to your project:

npm install gwei-sensei

🚀 Usage

CLI Usage

# Get the next optimal deployment window
gwei-sensei predict-window

# Get current fee recommendation
gwei-sensei suggest-fee --network ethereum

# Schedule a deployment for optimal gas price
gwei-sensei schedule-deploy --max-gas 100 --deadline "2024-01-01"

Code Integration

import { GweiSensei } from 'gwei-sensei';

// Initialize the predictor
const sensei = new GweiSensei();

// Get next optimal deployment window
const window = await sensei.predictOptimalWindow({
maxGas: 100,
deadline: new Date('2024-01-01'),
});

// Schedule a deployment
const schedule = await sensei.scheduleDeployment({
contract: './MyContract.sol',
maxGas: 100,
deadline: new Date('2024-01-01'),
});

🛠 Development

# Clone the repository
git clone https://github.com/yourusername/gwei-sensei.git
cd gwei-sensei

# Install dependencies
npm install

# Build the project
npm run build

# Run tests
npm test

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repository
2. Create your 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

For support, questions, or feedback, please open an issue on our GitHub repository.