Files
trading_bot_v3/README.md
mindesbunister 71694ca660 📚 COMPREHENSIVE KNOWLEDGE DOCUMENTATION
ADVANCED SYSTEM KNOWLEDGE:
- Superior parallel screenshot system (60% performance gain)
- AI learning system architecture and decision flow
- Orphaned order cleanup integration patterns
- Critical technical fixes and troubleshooting guide
- Database schema best practices
- Memory leak prevention strategies

- AI learning system patterns and functions
- Error handling best practices for trading systems
- Integration patterns for position monitoring
- Performance optimization rules
- UI/UX consistency requirements
- Critical anti-patterns to avoid

- Added links to new knowledge base documents
- Comprehensive documentation structure
- Development guides and best practices
- Performance optimizations summary

- 60% screenshot performance improvement techniques
- AI learning system that adapts trading decisions
- Container stability and crash prevention
- Frontend-backend consistency requirements
- Integration strategies for existing infrastructure

This documentation preserves critical insights from complex debugging sessions and provides patterns for future development.
2025-07-26 15:12:57 +02:00

405 lines
14 KiB
Markdown
Raw Permalink Blame History

# 🚀 AI-Powered Trading Bot Dashboard v3
A professional-grade Next.js trading dashboard with AI-powered chart analysis, dual-session screenshot capture, and multi-timeframe analysis. Built for institutional-quality trading insights with cost-effective OpenAI integration.
![Trading Bot Dashboard](https://img.shields.io/badge/Status-Production%20Ready-brightgreen)
![Next.js](https://img.shields.io/badge/Next.js-15-black)
![TypeScript](https://img.shields.io/badge/TypeScript-5-blue)
![Docker](https://img.shields.io/badge/Docker-Optimized-blue)
![OpenAI](https://img.shields.io/badge/OpenAI-GPT--4o%20mini-orange)
## ✨ Key Features
### 🤖 **AI-Powered Analysis**
- **Professional Trading Assistant** - Behaves like a top proprietary desk trader
- **Multi-Layout Analysis** - AI + DIY TradingView layouts for comprehensive insights
- **Cost-Effective** - Using GPT-4o mini (~$0.006 per analysis)
- **Timeframe Risk Assessment** - Automatic leverage and position sizing recommendations
- **Cross-Layout Consensus** - Compare insights from multiple chart layouts
### 📊 **Multi-Timeframe Analysis**
- **Quick Presets**: Scalping (5m,15m,1h), Day Trading (1h,4h,1d), Swing (4h,1d,1w), Position (1d,1w,1m)
- **1-8 Timeframes** simultaneously for broader market outlook
- **Consensus Detection** - Identify when multiple timeframes agree
- **Individual Analysis** - Detailed breakdown for each timeframe
### 🎯 **Professional Trading Setups**
- **Precise Entry Levels** with ±buffers and technical rationale
- **Smart Stop Losses** with exact reasoning (above VWAP, failed breakout zones)
- **Enhanced Take Profits** with RSI/OBV expectations for TP1/TP2
- **Risk/Reward Ratios** with specific R:R calculations
- **Confirmation Triggers** - Exact signals to wait for before entry
### 🤖 **Automated Trading Features**
- **Multi-Timeframe Automation** - Select 1-8 timeframes for comprehensive strategy coverage
- **Trading Style Presets** - Scalping (5m,15m,1h), Day Trading (1h,4h,1d), Swing (4h,1d)
- **Automatic Position Sizing** - Balance-based calculations with leverage recommendations
- **Real-Time Balance Integration** - Live wallet display with percentage-based position sizing
- **Risk Management** - Timeframe-specific leverage and position size recommendations
- **Clean UI/UX** - Checkbox-based timeframe selection with visual feedback
### 🖼️ **Enhanced Screenshot Service**
- **Dual-Session Capture** - Parallel AI and DIY layout screenshots
- **Docker Optimized** - Full CPU utilization for faster processing
- **Robust Error Handling** - Individual layout failures don't break analysis
- **Production Ready** - Automated browser management and session persistence
### 🎨 **Beautiful UI/UX**
- **Modern Design** - Gradient backgrounds, smooth animations, responsive layouts
- **Quick Analysis** - One-click coin + timeframe combination analysis
- **Visual Indicators** - Clear selection states, progress indicators, success/failure states
- **Professional Display** - Bloomberg terminal-style result presentation
## 🚀 Quick Start
### Option A: Docker (Recommended)
```bash
# Clone the repository
git clone <your-repo-url> trading_bot_v3
cd trading_bot_v3
# Create environment file
cp .env.example .env.local
# Add your OpenAI API key to .env.local
# Start with Docker Compose v2
docker compose up --build
# Access the dashboard
open http://localhost:3000
```
### Option B: Node.js Development
```bash
# Clone and install dependencies
git clone <your-repo-url> trading_bot_v3
cd trading_bot_v3
npm install
# Configure environment
cp .env.example .env.local
# Add your OpenAI API key
# Start development server
npm run dev
# Access the dashboard
open http://localhost:3000
```
## ⚙️ Configuration
### Required Environment Variables
```env
# OpenAI API Key (Required for AI analysis)
OPENAI_API_KEY=your_openai_api_key_here
# TradingView Credentials (Optional - for automation)
TRADINGVIEW_USERNAME=your_username
TRADINGVIEW_PASSWORD=your_password
# Layout Configuration (Optional)
NEXT_PUBLIC_TRADINGVIEW_LAYOUTS=ai,diy
```
### Docker Configuration
The system includes optimized Docker configurations:
- **`Dockerfile`** - Production-optimized build
- **`docker-compose.yml`** - Development setup
- **`docker-compose.prod.yml`** - Production deployment
- **`.dockerignore`** - Optimized build context
## 🎯 Usage Examples
### Quick Multi-Timeframe Analysis
1. **Select Trading Style Preset**:
- 🕒 Scalping: 5m, 15m, 1h
- 📊 Day Trading: 1h, 4h, 1d
- 📈 Swing: 4h, 1d, 1w
- 🎯 Position: 1d, 1w, 1m
2. **Click Any Coin** for instant analysis across all selected timeframes
3. **View Results** with consensus, divergences, and individual timeframe setups
### Multi-Timeframe Automation (/automation-v2)
1. **Access Automation**: Navigate to `/automation-v2` for the latest automation interface
2. **Select Timeframes**: Use checkboxes to select 1-8 timeframes
- Individual selection: Click any timeframe checkbox
- Quick presets: Scalping, Day Trading, Swing Trading buttons
3. **Position Sizing**:
- View real-time wallet balance
- Select position percentage (1%, 5%, 10%, 25%, 50%)
- Automatic leverage calculations based on timeframe
4. **Execute**: Run automation across all selected timeframes simultaneously
### Docker Development Workflow
```bash
# Start development environment
npm run docker:dev # Runs on http://localhost:9001
# View logs for debugging
npm run docker:logs
# Access container shell for troubleshooting
npm run docker:exec
# Test volume mount sync (if files not updating)
echo "test-$(date)" > test-volume-mount.txt
docker compose -f docker-compose.dev.yml exec app cat test-volume-mount.txt
# Full rebuild if issues persist
docker compose -f docker-compose.dev.yml down
docker compose -f docker-compose.dev.yml up --build
```
### API Usage
```bash
# Test the enhanced screenshot API
curl -X POST http://localhost:3000/api/enhanced-screenshot \
-H "Content-Type: application/json" \
-d '{
"symbol": "BTCUSD",
"timeframe": "240",
"layouts": ["ai", "diy"],
"analyze": true
}'
# Run included test script
node test-enhanced-screenshot.js
```
### Professional Trading Analysis Output
```
💰 TRADING SETUP:
📍 Entry: $162.5 ±0.25
💡 Rejection from 15 EMA + VWAP confluence near intraday supply
🛑 Stop Loss: $160
💡 Above VWAP + failed breakout zone
🎯 TAKE PROFIT TARGETS:
🥉 TP1: $164
📋 Target based on resistance level observed in both layouts
📊 RSI: Should reach 60-65 zone
📈 OBV: Confirming upward momentum
🥈 TP2: $166
📋 Target aligns with upper resistance in AI layout
📊 RSI: Approaching 70+ overbought
📈 OBV: Making new highs with price
⚖️ Risk/Reward: 1:2.5
⏰ TIMEFRAME RISK ASSESSMENT:
📊 Risk Level: Medium (4H timeframe)
💼 Position Size: Larger position appropriate for swing trade
🎚️ Leverage: 3-5x recommended for 4H timeframe
```
## 🛠️ Tech Stack
- **Frontend**: Next.js 15, TypeScript, Tailwind CSS
- **AI**: OpenAI GPT-4o mini (cost-optimized)
- **Automation**: Puppeteer, Playwright
- **Database**: Prisma (optional)
- **Deployment**: Docker, Docker Compose
- **Testing**: Custom API test suites
## 📂 Project Structure
```
trading_bot_v3/
├── app/ # Next.js app router
│ ├── analysis/ # Multi-timeframe analysis page
│ ├── automation/ # Trading automation pages
│ │ ├── page.js # Original automation (legacy)
│ │ └── page-v2.js # Clean automation implementation
│ ├── automation-v2/ # NEW: Multi-timeframe automation
│ │ └── page.js # Full automation with timeframe support
│ ├── api/enhanced-screenshot/ # Screenshot & AI analysis API
│ ├── globals.css # Global styles
│ ├── layout.tsx # Root layout
│ └── page.tsx # Main dashboard
├── components/ # React components
│ ├── AIAnalysisPanel.tsx # Multi-timeframe analysis UI
│ ├── Dashboard.tsx # Main dashboard
│ └── ... # Other trading components
├── lib/ # Core services
│ ├── ai-analysis.ts # OpenAI integration
│ ├── enhanced-screenshot-simple.ts # Dual-session capture
│ ├── auto-trading.ts # Trading automation
│ └── ... # Other services
├── docker-compose.yml # Development setup
├── docker-compose.prod.yml # Production setup
├── Dockerfile # Optimized container
└── test-enhanced-screenshot.js # API testing
```
## 🧪 Testing
### Run Test Suite
```bash
# Test enhanced screenshot service
node test-enhanced-screenshot.js
# Test with curl
./test-simple-screenshot.js
# Test Docker setup
docker compose up --build
# Test automation features
curl -X POST http://localhost:9001/api/automation \
-H "Content-Type: application/json" \
-d '{
"symbol": "BTCUSD",
"timeframes": ["1h", "4h", "1d"],
"positionSize": 10
}'
```
### Expected Test Output
```
🚀 Testing Enhanced Screenshot Service with Dual Sessions (API)
✅ API endpoint available
🎯 SUCCESS: Both AI and DIY layouts captured successfully!
📊 Test Summary: 100% success rate
🤖 Testing Multi-Timeframe Automation
✅ Timeframe selection working
✅ Position sizing calculations correct
✅ Balance integration successful
```
## 🎯 Features in Detail
### AI Analysis Capabilities
- **Market Sentiment Analysis** - BULLISH/BEARISH/NEUTRAL with confidence scores
- **Technical Indicator Analysis** - RSI, VWAP, OBV, MACD with specific action triggers
- **Entry/Exit Strategy** - Precise levels with technical rationale
- **Risk Management** - Position sizing based on timeframe and volatility
- **Alternative Scenarios** - Backup plans and invalidation levels
### Screenshot Service Features
- **Dual-Session Architecture** - Parallel AI and DIY layout capture
- **Smart Navigation** - Automatic symbol/timeframe selection
- **Error Recovery** - Robust handling of navigation failures
- **Performance Optimized** - Full CPU utilization, optimized for i7-4790K
- **Session Persistence** - Avoid repeated logins and captchas
### Multi-Timeframe Analysis
- **Cross-Timeframe Consensus** - Identify alignment across timeframes
- **Divergence Detection** - Spot conflicts between timeframes
- **Risk-Adjusted Positioning** - Different strategies for different timeframes
- **Comprehensive Outlook** - From scalping to position trading
## 📊 Performance & Costs
- **Analysis Speed**: ~30-60 seconds for dual-layout capture + AI analysis
- **AI Cost**: ~$0.006 per analysis (GPT-4o mini)
- **Screenshot Performance**: Optimized for multi-core CPUs
- **Memory Efficient**: Docker optimizations for production deployment
## 🔒 Security & Best Practices
- **Environment Variables** - Secure API key management
- **Input Validation** - Sanitized user inputs
- **Error Handling** - Graceful degradation
- **Rate Limiting** - Built-in delays between requests
- **Production Ready** - Docker security best practices
## 🤝 Contributing
1. Fork the repository
2. Create a feature branch: `git checkout -b feature/amazing-feature`
3. Commit changes: `git commit -m 'Add amazing feature'`
4. Push to branch: `git push origin feature/amazing-feature`
5. Open a Pull Request
## 📚 Documentation & Knowledge Base
This project includes comprehensive documentation covering all aspects of the system:
### 🎯 **Core Documentation**
- **`README.md`** - Main project overview and quick start guide
- **`ADVANCED_SYSTEM_KNOWLEDGE.md`** - Critical technical insights and troubleshooting
- **`.github/copilot-instructions.md`** - Development patterns and best practices
### 🧠 **AI & Learning System**
- **Complete AI Learning Architecture** - Pattern recognition and adaptive decision making
- **Smart Recommendation Engine** - Historical outcome analysis for trading decisions
- **Learning Report Generation** - 15-minute progress reports with confidence tracking
- **Threshold Optimization** - Automatic adjustment based on trading success rates
### 🔧 **Technical Analysis Documentation**
- **`TECHNICAL_ANALYSIS_BASICS.md`** - Complete guide to all indicators used
- **`TA_QUICK_REFERENCE.md`** - Quick reference for indicator interpretation
- **AI Analysis Integration** - TA fundamentals built into AI analysis prompts
### ⚡ **Performance Optimizations**
- **Superior Parallel Screenshot System** - 60% faster than sequential (71s vs 180s)
- **Orphaned Order Cleanup Integration** - Automatic cleanup when positions close
- **Container Stability Fixes** - Resolved memory leaks and crash issues
- **Database Schema Optimizations** - Proper Prisma validation and error handling
### 🛠️ **Development Guides**
- **Integration Patterns** - How to add features without breaking existing systems
- **Error Handling Best Practices** - Defensive programming for AI systems
- **Testing Protocols** - Isolated testing for critical components
- **Debugging Strategies** - Common issues and their solutions
## <20> Technical Analysis Documentation
This project includes comprehensive Technical Analysis (TA) documentation:
- **`TECHNICAL_ANALYSIS_BASICS.md`** - Complete guide to all indicators used
- **`TA_QUICK_REFERENCE.md`** - Quick reference for indicator interpretation
- **AI Analysis Integration** - TA fundamentals built into AI analysis prompts
### Indicators Covered:
- **RSI & Stochastic RSI** - Momentum oscillators
- **MACD** - Trend and momentum indicator
- **EMAs** - Exponential Moving Averages (9, 20, 50, 200)
- **VWAP** - Volume Weighted Average Price
- **OBV** - On-Balance Volume
- **Smart Money Concepts** - Institutional flow analysis
The AI analysis system uses established TA principles to provide accurate, educational trading insights based on proven technical analysis methodologies.
## <20>📜 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🙏 Acknowledgments
- OpenAI for providing cost-effective GPT-4o mini API
- TradingView for comprehensive charting platform
- Next.js team for excellent React framework
- Docker for containerization capabilities
## 📞 Support
For support, please open an issue in the GitHub repository or contact the development team.
---
**Built with ❤️ for professional traders who demand institutional-quality analysis at startup costs.**
🚀 **Ready to deploy and start trading with AI-powered insights!**