better vyt/sell signal proecessing/display

ANNOTATE/core/real_training_adapter.py

@@ -316,7 +316,14 @@ class RealTrainingAdapter:
             return None
     
     def _create_pivot_training_batch(self, model_inputs: Dict, pivot_event, inference_ref) -> Optional[Dict]:
-        """Create training batch from inference inputs and pivot event"""
+        """
+        Create training batch from inference inputs and pivot event
+        
+        Strategy: Train to execute trades on L2 pivots that align with upper trend
+        - L2L (support) in UPTREND → BUY
+        - L2H (resistance) in DOWNTREND → SELL
+        - Misaligned pivots → HOLD (don't trade against trend)
+        """
         try:
             import torch
             
@@ -327,15 +334,29 @@ class RealTrainingAdapter:
             # Get device
             device = next(iter(batch.values())).device if batch else torch.device('cpu')
             
-            # Determine action from pivot type
-            # L2L, L3L, etc. -> BUY (support levels)
-            # L2H, L3H, etc. -> SELL (resistance levels)
-            if pivot_event.pivot_type.endswith('L'):
-                action = 1  # BUY
-            elif pivot_event.pivot_type.endswith('H'):
-                action = 2  # SELL
-            else:
-                action = 0  # HOLD
+            # Get trend direction from pivot event (if available)
+            trend_direction = getattr(pivot_event, 'trend_direction', 'sideways')
+            pivot_type = pivot_event.pivot_type
+            
+            # Determine action based on pivot type AND trend alignment
+            # Only trade when pivot aligns with trend
+            action = 0  # Default: HOLD
+            
+            if pivot_type in ['L2L', 'L3L']:  # Support levels (lows)
+                # BUY only if in UPTREND (buying at support in uptrend)
+                if trend_direction in ['up', 'uptrend', 'UPTREND']:
+                    action = 1  # BUY
+                    logger.info(f"Pivot training: BUY signal at {pivot_type} (aligned with {trend_direction})")
+                else:
+                    logger.debug(f"Pivot training: HOLD at {pivot_type} (not aligned with {trend_direction})")
+                    
+            elif pivot_type in ['L2H', 'L3H']:  # Resistance levels (highs)
+                # SELL only if in DOWNTREND (selling at resistance in downtrend)
+                if trend_direction in ['down', 'downtrend', 'DOWNTREND']:
+                    action = 2  # SELL
+                    logger.info(f"Pivot training: SELL signal at {pivot_type} (aligned with {trend_direction})")
+                else:
+                    logger.debug(f"Pivot training: HOLD at {pivot_type} (not aligned with {trend_direction})")
             
             batch['actions'] = torch.tensor([[action]], dtype=torch.long, device=device)
             
@@ -4824,7 +4845,7 @@ class RealTrainingAdapter:
         Execute trade based on signal, respecting position management rules
         
         Rules:
-        1. Only execute if confidence >= 0.6
+        1. Only execute if confidence >= 0.5 (lowered for more learning opportunities)
         2. Only open new position if no position is currently open
         3. Close position on opposite signal
         4. Track all executed trades for visualization
@@ -4836,8 +4857,8 @@ class RealTrainingAdapter:
         confidence = signal['confidence']
         timestamp = signal['timestamp']
         
-        # Rule 1: Confidence threshold
-        if confidence < 0.6:
+        # Rule 1: Confidence threshold (lowered to 0.5 for more learning opportunities)
+        if confidence < 0.5:
             return None  # Rejected: low confidence
         
         # Rule 2 & 3: Position management
@@ -4962,8 +4983,8 @@ class RealTrainingAdapter:
         confidence = signal['confidence']
         position = session.get('position')
         
-        if confidence < 0.6:
-            return f"Low confidence ({confidence:.2f} < 0.6)"
+        if confidence < 0.5:
+            return f"Low confidence ({confidence:.2f} < 0.5)"
         
         if action == 'HOLD':
             return "HOLD signal (no trade)"