https://github.com/turtir-ai/warpcrypto-trader
AI-Powered Multi-Cryptocurrency Analysis Platform with Advanced Trading Strategies - Powered by Turtir-AI
https://github.com/turtir-ai/warpcrypto-trader
ai bitcoin cryptocurrency ethereum machine-learning solana streamlit technical-analysis tensorflow trading-bot
Last synced: 3 months ago
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AI-Powered Multi-Cryptocurrency Analysis Platform with Advanced Trading Strategies - Powered by Turtir-AI
- Host: GitHub
- URL: https://github.com/turtir-ai/warpcrypto-trader
- Owner: turtir-ai
- License: mit
- Created: 2025-08-24T10:36:11.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-08-24T10:49:28.000Z (10 months ago)
- Last Synced: 2025-08-24T16:43:22.705Z (10 months ago)
- Topics: ai, bitcoin, cryptocurrency, ethereum, machine-learning, solana, streamlit, technical-analysis, tensorflow, trading-bot
- Language: Python
- Homepage: https://github.com/turtir-ai
- Size: 1.32 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🚀 WarpCrypto-Trader v2.0
[](https://www.python.org/)
[](https://streamlit.io/)
[](https://www.tensorflow.org/)
[](LICENSE)
[](https://github.com/turtir-ai)
## 🎯 Overview
**WarpCrypto-Trader** is an advanced AI-powered cryptocurrency analysis platform that provides real-time predictions, technical analysis, and trading strategy comparisons for Bitcoin, Ethereum, and Solana. Perfect for creating engaging content for social media platforms like X.com (Twitter)!
## ✨ Features
### 🤖 AI-Powered Predictions
- **LSTM/GRU Hybrid Models** - Advanced deep learning architecture for accurate price predictions
- **Multi-Horizon Forecasting** - 1-day, 3-day, and 7-day price predictions
- **AI Confidence Score** - Measures prediction consistency and reliability
- **Per-Crypto Models** - Separately trained models for BTC, ETH, and SOL
### 📊 Technical Analysis
- **Real-time Data** - Live cryptocurrency data from Yahoo Finance
- **25+ Technical Indicators** - RSI, MACD, Bollinger Bands, Moving Averages, and more
- **Interactive RSI Gauge** - Visual representation of market conditions
- **Dynamic Price Charts** - Candlestick charts with volume analysis
### 🏆 Strategy Leaderboard
- **Multiple Trading Strategies** - RSI, MACD, Bollinger Bands, and combined strategies
- **Backtesting Engine** - Historical performance analysis
- **Win Rate & Returns** - Comprehensive strategy metrics
- **Real-time Comparison** - Find the best strategy for current market conditions
### 🎨 Modern UI/UX
- **Glassmorphism Design** - Beautiful, transparent card layouts
- **Dynamic Color Themes** - Each cryptocurrency has its unique color scheme
- **Responsive Layout** - Works perfectly on all screen sizes
- **Dark Mode** - Eye-friendly interface for extended use
## 🛠️ Installation
### Prerequisites
- Python 3.10 or higher
- pip package manager
- Git
### Step 1: Clone the Repository
```bash
git clone https://github.com/turtir-ai/WarpCrypto-Trader.git
cd WarpCrypto-Trader
```
### Step 2: Install Dependencies
```bash
pip install -r requirements.txt
```
### Step 3: Train the Models (Optional)
Train models for all cryptocurrencies:
**Windows PowerShell:**
```powershell
.\train_all_models.ps1
```
**Linux/Mac:**
```bash
chmod +x train_all_models.sh
./train_all_models.sh
```
Or train individually:
```bash
python train_model_fixed.py --ticker BTC-USD
python train_model_fixed.py --ticker ETH-USD
python train_model_fixed.py --ticker SOL-USD
```
### Step 4: Launch the Application
```bash
streamlit run app_v2.py
```
The application will open in your browser at `http://localhost:8501`
## 📁 Project Structure
```
WarpCrypto-Trader/
│
├── app_v2.py # Main Streamlit application (English version)
├── data_processor.py # Data fetching and processing module
├── train_model_fixed.py # LSTM/GRU model training script
├── strategy_backtester.py # Trading strategy backtesting engine
│
├── train_all_models.ps1 # Windows batch training script
├── train_all_models.sh # Linux/Mac batch training script
│
├── models/ # Trained models directory (auto-created)
│ ├── btc_usd_predictor_improved.keras
│ ├── eth_usd_predictor_improved.keras
│ └── sol_usd_predictor_improved.keras
│
├── requirements.txt # Python dependencies
├── LICENSE # MIT License
└── README.md # This file
```
## 🎮 Usage Guide
### 1. Select Cryptocurrency
Use the sidebar dropdown to choose between Bitcoin, Ethereum, or Solana.
### 2. Train Models (First Time)
Click the "Train Model" button in the sidebar if the model hasn't been trained yet.
### 3. Customize Display
- **RSI Gauge Indicator** - Toggle the visual RSI gauge
- **Strategy Leaderboard** - Show/hide strategy comparison table
- **AI Confidence Score** - Display prediction reliability metric
### 4. Analyze Results
- Check current price and trend
- Review AI predictions for different time horizons
- Compare trading strategy performances
- Examine technical indicators
## 📹 Content Creation Tips
Perfect for creating engaging content on X.com (Twitter):
### Video Ideas
1. **"AI Predicts Crypto Prices!"** - Show AI predictions with confidence scores
2. **"Best Trading Strategy Revealed"** - Highlight the strategy leaderboard
3. **"Bitcoin vs Ethereum vs Solana"** - Quick comparison between cryptos
4. **"RSI Alert!"** - Focus on the RSI gauge when it's in extreme zones
### Recording Tips
- Use dark theme for better visuals
- Slow transitions between sections
- Highlight AI confidence scores
- Show strategy performance comparisons
- Zoom in on key metrics
## 🔧 Configuration
### Modify Cryptocurrencies
Edit the `CRYPTO_OPTIONS` dictionary in `app_v2.py`:
```python
CRYPTO_OPTIONS = {
'Bitcoin (BTC)': 'BTC-USD',
'Ethereum (ETH)': 'ETH-USD',
'Solana (SOL)': 'SOL-USD',
# Add more here
}
```
### Adjust Model Parameters
In `train_model_fixed.py`, modify:
```python
predictor = ImprovedCryptoPredictor(
ticker=ticker,
sequence_length=30, # Days of historical data
prediction_horizons=[1, 3, 7] # Prediction days
)
```
### Change Analysis Period
Default periods can be modified in the sidebar options.
## 📊 Technical Indicators
The platform calculates and displays:
- **Price Metrics**: Open, High, Low, Close, Volume
- **Moving Averages**: SMA (10, 30, 50, 200), EMA (12, 26)
- **Momentum**: RSI, MACD, Stochastic Oscillator
- **Volatility**: Bollinger Bands, ATR
- **Volume**: OBV, Volume Ratio
- **Custom**: Support/Resistance Levels, Trend Direction
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## 📝 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🙏 Acknowledgments
- **Yahoo Finance** - Real-time cryptocurrency data
- **Streamlit** - Amazing web app framework
- **TensorFlow** - Deep learning models
- **Plotly** - Interactive visualizations
- **TA-Lib** - Technical analysis indicators
## ⚡ Powered by Turtir-AI
This project is powered by **[Turtir-AI](https://github.com/turtir-ai)** - Advanced AI Solutions for Trading and Analysis.
## 📧 Contact
For questions, suggestions, or collaborations:
- Twitter: [@turtirai](https://x.com/turtirai)
- GitHub: [Turtir-AI](https://github.com/turtir-ai)
---
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