docs: rEADME

README.md

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-# hd-gwei-sensei
+# 🥷 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:
+
+```bash
+npm install -g gwei-sensei
+```
+
+Or add it to your project:
+
+```bash
+npm install gwei-sensei
+```
+
+## 🚀 Usage
+
+### CLI Usage
+
+```bash
+# 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
+
+```typescript
+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
+
+```bash
+# 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](LICENSE) file for details.
+
+## 💬 Support
+
+For support, questions, or feedback, please [open an issue](https://github.com/yourusername/gwei-sensei/issues) on our GitHub repository.