## Fixed Issues: - ✅ Resolved blank page caused by problematic chart component imports - ✅ Removed broken chart components that had library compatibility issues - ✅ Created SimpleChart component using HTML5 Canvas that works reliably - ✅ Cleaned up test pages and unused components ## Working Features: - ✅ Trading page loads correctly without blank screen - ✅ Professional candlestick chart with grid lines and price labels - ✅ Clean trading interface with all panels visible - ✅ No more loading errors or component failures ## Technical Implementation: - Used native HTML5 Canvas API for chart rendering - Proper TypeScript types and error handling - Responsive design that works in Docker environment - No external library dependencies to cause conflicts The trading dashboard is now stable and functional.
🚀 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.
✨ 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
🖼️ 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)
# 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
docker-compose up --build
# Access the dashboard
open http://localhost:3000
Option B: Node.js Development
# 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
# 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 builddocker-compose.yml- Development setupdocker-compose.prod.yml- Production deployment.dockerignore- Optimized build context
🎯 Usage Examples
Quick Multi-Timeframe Analysis
-
Select Trading Style Preset:
- 🕒 Scalping: 5m, 15m, 1h
- 📊 Day Trading: 1h, 4h, 1d
- 📈 Swing: 4h, 1d, 1w
- 🎯 Position: 1d, 1w, 1m
-
Click Any Coin for instant analysis across all selected timeframes
-
View Results with consensus, divergences, and individual timeframe setups
API Usage
# 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
│ ├── 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
# Test enhanced screenshot service
node test-enhanced-screenshot.js
# Test with curl
./test-simple-screenshot.js
# Test Docker setup
docker-compose up --build
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
🎯 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
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature - Commit changes:
git commit -m 'Add amazing feature' - Push to branch:
git push origin feature/amazing-feature - Open a Pull Request
📜 License
This project is licensed under the MIT License - see the 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!