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# AI-Powered Trading Bot Dashboard

This is a Next.js 15 App Router application with TypeScript, Tailwind CSS, and API routes. It's a production-ready trading bot with AI analysis, automated screenshot capture, and real-time trading execution via Drift Protocol and Jupiter DEX.

## Core Architecture

### Dual-Session Screenshot Automation
- **AI Layout**: `Z1TzpUrf` - RSI (top), EMAs, MACD (bottom)
- **DIY Layout**: `vWVvjLhP` - Stochastic RSI (top), VWAP, OBV (bottom)
- Parallel browser sessions for multi-layout capture in `lib/enhanced-screenshot.ts`
- TradingView automation with session persistence in `lib/tradingview-automation.ts`

### AI Analysis Pipeline  
- OpenAI GPT-4o mini for cost-effective chart analysis (~$0.006 per analysis)
- Multi-layout comparison and consensus detection
- Professional trading setups with exact entry/exit levels and risk management
- Layout-specific indicator analysis (RSI vs Stochastic RSI, MACD vs OBV)

### Trading Integration
- **Drift Protocol**: Perpetual futures trading via `@drift-labs/sdk`
- **Jupiter DEX**: Spot trading on Solana
- Position management and P&L tracking
- Real-time account balance and collateral monitoring

## Critical Development Patterns

### Docker Environment
Use Docker for consistency: `npm run docker:dev` (port 9001) or `npm run docker:up` (port 9000)
- Multi-stage builds with browser automation optimizations
- Session persistence via volume mounts
- Chromium path: `/usr/bin/chromium`

### API Route Structure
```typescript
// Enhanced screenshot with progress tracking
POST /api/enhanced-screenshot
{
  symbol: "SOLUSD", 
  timeframe: "240", 
  layouts: ["ai", "diy"],
  analyze: true
}

// Returns: { screenshots, analysis, sessionId }
```

### Progress Tracking System
- `lib/progress-tracker.ts` manages real-time analysis progress
- SessionId-based tracking for multi-step operations
- Steps: init → auth → navigation → loading → capture → analysis

### Timeframe Mapping
Critical: Always use minute values first to avoid TradingView confusion
```typescript
'4h': ['240', '240m', '4h', '4H'] // 240 minutes FIRST, not "4h"
'1h': ['60', '60m', '1h', '1H']   // 60 minutes FIRST
```

### Component Architecture
- `components/AIAnalysisPanel.tsx` - Multi-timeframe analysis interface
- `components/Dashboard.tsx` - Main trading dashboard with real Drift positions
- `components/AdvancedTradingPanel.tsx` - Drift Protocol trading interface
- Layout: `app/layout.js` with gradient styling and navigation

## Environment Variables
```bash
OPENAI_API_KEY=        # Required for AI analysis
TRADINGVIEW_EMAIL=     # Required for automation
TRADINGVIEW_PASSWORD=  # Required for automation
SOLANA_RPC_URL=        # Drift trading
DRIFT_PRIVATE_KEY=     # Drift trading (base58 encoded)
```

## Build & Development Commands
```bash
# Development (recommended)
npm run docker:dev         # Port 9001, hot reload
npm run docker:logs        # View container logs
npm run docker:exec        # Shell access

# Production deployment  
npm run docker:prod:up     # Port 9000, optimized build

# Testing automation
node test-enhanced-screenshot.js  # Test dual-session capture
./test-docker-comprehensive.sh    # Full system test
```

## Code Style Guidelines
- Use `"use client"` for client components with state/effects
- Tailwind with gradient backgrounds and glassmorphism effects
- TypeScript interfaces for all trading parameters and API responses
- Error handling with detailed logging for browser automation
- Session persistence to avoid TradingView captchas

## Key Integration Points
- Session data: `.tradingview-session/` (volume mounted)
- Screenshots: `screenshots/` directory
- Progress tracking: EventEmitter-based real-time updates
- Database: Prisma with SQLite (file:./prisma/dev.db)

Generate code that follows these patterns and integrates seamlessly with the existing trading infrastructure.