fix: Remove fallback that breaks TP2-as-runner system
- Change tp2SizePercent fallback from || 100 to ?? 0 - Allows 0 value to pass through (means 'activate trailing stop, don't close') - Fixes bug where TP2 was closing 100% of remaining position - Now correctly leaves 25% runner after TP1 closes 75% - Applied to both execute and test endpoints
This commit is contained in:
mindesbunister
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REENTRY_SYSTEM_COMPLETE.md
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REENTRY_SYSTEM_COMPLETE.md
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# ✅ Re-Entry Analytics System - IMPLEMENTATION COMPLETE
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## 🎯 What Was Implemented
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A smart validation system that checks if manual Telegram trades make sense **before** executing them, using fresh TradingView market data and recent trade performance.
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## 📊 System Components
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### 1. Market Data Cache (`lib/trading/market-data-cache.ts`)
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- Singleton service storing TradingView metrics
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- 5-minute expiry on cached data
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- Tracks: ATR, ADX, RSI, volumeRatio, pricePosition, timeframe
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- Methods: `set()`, `get()`, `has()`, `getAvailableSymbols()`
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### 2. Market Data Webhook (`app/api/trading/market-data/route.ts`)
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- **POST**: Receives TradingView alert data every 1-5 minutes
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- **GET**: Debug endpoint to view current cache
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- Normalizes TradingView symbols to Drift format
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- Validates incoming data and stores in cache
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### 3. Re-Entry Check Endpoint (`app/api/analytics/reentry-check/route.ts`)
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- Validates manual trade requests from Telegram
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- Decision logic:
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1. Check for fresh TradingView data (<5min old)
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2. Fall back to historical data from last trade
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3. Score signal quality (0-100)
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4. Apply performance modifiers based on last 3 trades
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5. Return `should_enter` + detailed reasoning
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### 4. Auto-Caching (`app/api/trading/execute/route.ts`)
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- Every incoming trade signal auto-caches metrics
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- Ensures fresh data available for manual re-entries
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- No additional TradingView alerts needed for basic functionality
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### 5. Telegram Bot Integration (`telegram_command_bot.py`)
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- Pre-execution analytics check before manual trades
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- Parses `--force` flag to bypass validation
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- Shows data freshness and source in responses
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- Fail-open: Proceeds if analytics check fails
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## 🔄 User Flow
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### Scenario 1: Analytics Approves
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```
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User: "long sol"
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Bot checks analytics...
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✅ Analytics check passed (68/100)
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Data: tradingview_real (23s old)
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Proceeding with LONG SOL...
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✅ OPENED LONG SOL
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Entry: $162.45
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Size: $2100.00 @ 10x
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TP1: $162.97 TP2: $163.59 SL: $160.00
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```
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### Scenario 2: Analytics Blocks
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```
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User: "long sol"
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Bot checks analytics...
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🛑 Analytics suggest NOT entering LONG SOL
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Reason: Recent long trades losing (-2.4% avg)
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Score: 45/100
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Data: ✅ tradingview_real (23s old)
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Use `long sol --force` to override
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```
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### Scenario 3: User Overrides
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```
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User: "long sol --force"
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⚠️ Skipping analytics check...
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✅ OPENED LONG SOL (FORCED)
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Entry: $162.45
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Size: $2100.00 @ 10x
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...
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```
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## 📈 Scoring System
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**Base Score:** Signal quality (0-100) using ATR/ADX/RSI/Volume/PricePosition
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**Modifiers:**
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- **-20 points**: Last 3 trades lost money (avgPnL < -5%)
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- **+10 points**: Last 3 trades won (avgPnL > +5%, WR >= 66%)
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- **-5 points**: Using stale/historical data
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- **-10 points**: No market data available
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**Threshold:**
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- Minimum re-entry score: **55** (vs 60 for new signals)
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- Lower threshold acknowledges visual chart confirmation
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## 🚀 Next Steps to Deploy
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### 1. Build and Deploy
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```bash
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cd /home/icke/traderv4
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# Build updated Docker image
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docker compose build trading-bot
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# Restart trading bot
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docker compose up -d trading-bot
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# Restart Telegram bot
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docker compose restart telegram-bot
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# Check logs
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docker logs -f trading-bot-v4
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docker logs -f telegram-bot
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```
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### 2. Create TradingView Market Data Alerts
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**For each symbol (SOL, ETH, BTC), create:**
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**Alert Name:** "Market Data - SOL 5min"
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**Condition:**
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```
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ta.change(time("1"))
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```
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(Fires every bar close)
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**Alert Message:**
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```json
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{
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"action": "market_data",
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"symbol": "{{ticker}}",
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"timeframe": "{{interval}}",
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"atr": {{ta.atr(14)}},
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"adx": {{ta.dmi(14, 14)}},
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"rsi": {{ta.rsi(14)}},
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"volumeRatio": {{volume / ta.sma(volume, 20)}},
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"pricePosition": {{(close - ta.lowest(low, 100)) / (ta.highest(high, 100) - ta.lowest(low, 100)) * 100}},
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"currentPrice": {{close}}
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}
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```
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**Webhook URL:**
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```
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https://your-domain.com/api/trading/market-data
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```
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**Frequency:** Every 1-5 minutes
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### 3. Test the System
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```bash
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# Check market data cache
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curl http://localhost:3001/api/trading/market-data
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# Test via Telegram
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# Send: "long sol"
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# Expected: Analytics check runs, shows score and decision
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```
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## 📊 Benefits
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✅ **Prevents revenge trading** - Blocks entry after consecutive losses
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✅ **Data-driven decisions** - Uses fresh TradingView metrics + recent performance
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✅ **Not overly restrictive** - Lower threshold (55 vs 60) + force override available
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✅ **Transparent** - Shows exactly why trade was blocked/allowed
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✅ **Fail-open design** - If analytics fails, trade proceeds (not overly conservative)
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✅ **Auto-caching** - Works immediately with existing trade signals
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✅ **Optional enhancement** - Create dedicated alerts for 100% fresh data
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## 🎯 Success Metrics (After 2-4 Weeks)
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Track these to validate the system:
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1. **Block Rate:**
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- How many manual trades were blocked?
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- What % of blocked trades would have won/lost?
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2. **Override Analysis:**
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- Win rate of `--force` trades vs accepted trades
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- Are overrides improving or hurting performance?
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3. **Data Freshness:**
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- How often is fresh TradingView data available?
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- Impact on decision quality
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4. **Threshold Tuning:**
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- Should MIN_REENTRY_SCORE be adjusted?
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- Should penalties/bonuses be changed?
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## 📁 Files Created/Modified
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**New Files:**
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- ✅ `lib/trading/market-data-cache.ts` - Cache service (116 lines)
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- ✅ `app/api/trading/market-data/route.ts` - Webhook endpoint (155 lines)
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- ✅ `app/api/analytics/reentry-check/route.ts` - Validation logic (235 lines)
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- ✅ `docs/guides/REENTRY_ANALYTICS_QUICKSTART.md` - Setup guide
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**Modified Files:**
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- ✅ `app/api/trading/execute/route.ts` - Auto-cache metrics
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- ✅ `telegram_command_bot.py` - Pre-execution analytics check
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- ✅ `.github/copilot-instructions.md` - Documentation update
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**Total Lines Added:** ~1,500+ (including documentation)
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## 🔮 Future Enhancements (Phase 2+)
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1. **Time-Based Cooldown:** No re-entry within 10min of exit
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2. **Trend Reversal Detection:** Check if price crossed key moving averages
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3. **Volatility Spike Filter:** Block entry on ATR expansion
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4. **ML Model:** Train on override decisions to auto-adjust thresholds
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5. **Multi-Timeframe Analysis:** Compare 5min vs 1h signals
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## 📝 Commit Details
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**Commit:** `9b76734`
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**Message:**
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```
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feat: Implement re-entry analytics system with fresh TradingView data
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- Add market data cache service (5min expiry)
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- Create webhook endpoint for TradingView data updates
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- Add analytics validation for manual trades
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- Update Telegram bot with pre-execution checks
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- Support --force flag for overrides
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- Comprehensive setup documentation
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```
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**Files Changed:** 14 files, +1269 insertions, -687 deletions
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---
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## ✅ READY TO USE
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The system is fully implemented and ready for testing. Just deploy the code and optionally create TradingView market data alerts for 100% fresh data.
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**Test command:** Send `long sol` in Telegram to see analytics in action!
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@@ -481,8 +481,8 @@ export async function POST(request: NextRequest): Promise<NextResponse<ExecuteTr
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tp1Price,
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tp2Price,
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stopLossPrice,
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tp1SizePercent: config.takeProfit1SizePercent || 50,
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tp2SizePercent: config.takeProfit2SizePercent || 100,
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tp1SizePercent: config.takeProfit1SizePercent ?? 75,
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tp2SizePercent: config.takeProfit2SizePercent ?? 0, // 0 = activate trailing stop, don't close
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direction: body.direction,
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// Dual stop parameters
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useDualStops: config.useDualStops,
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@@ -258,8 +258,8 @@ export async function POST(request: NextRequest): Promise<NextResponse<TestTrade
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tp1Price,
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tp2Price,
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stopLossPrice,
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tp1SizePercent: config.takeProfit1SizePercent || 50,
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tp2SizePercent: config.takeProfit2SizePercent || 100,
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tp1SizePercent: config.takeProfit1SizePercent ?? 75,
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tp2SizePercent: config.takeProfit2SizePercent ?? 0, // 0 = activate trailing stop, don't close
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direction: direction,
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// Dual stop parameters
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useDualStops: config.useDualStops,
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