🚀 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

🤖 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)

# 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

# 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 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

# 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

# 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

# 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

<EFBFBD> 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.

<EFBFBD>📜 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.

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Built with ❤️ for professional traders who demand institutional-quality analysis at startup costs.

🚀 Ready to deploy and start trading with AI-powered insights!