bom to CNN

core/multi_exchange_cob_provider.py

@@ -23,7 +23,11 @@ import asyncio
 import json
 import logging
 import time
-import websockets
+try:
+    import websockets
+except ImportError:
+    # Fallback for environments where websockets is not available
+    websockets = None
 import numpy as np
 import pandas as pd
 from datetime import datetime, timedelta
@@ -106,7 +110,7 @@ class MultiExchangeCOBProvider:
     to create a consolidated view of market liquidity and pricing.
     """
     
-    def __init__(self, symbols: List[str] = None, bucket_size_bps: float = 1.0):
+    def __init__(self, symbols: Optional[List[str]] = None, bucket_size_bps: float = 1.0):
         """
         Initialize Multi-Exchange COB Provider
         
@@ -461,6 +465,8 @@ class MultiExchangeCOBProvider:
             ws_url = f"{config.websocket_url}{config.symbols_mapping[symbol].lower()}@depth20@100ms"
             logger.info(f"Connecting to Binance WebSocket: {ws_url}")
             
+            if websockets is None:
+                raise ImportError("websockets module not available")
             async with websockets.connect(ws_url) as websocket:
                 self.exchange_order_books[symbol]['binance']['connected'] = True
                 logger.info(f"Connected to Binance order book stream for {symbol}")
@@ -537,7 +543,7 @@ class MultiExchangeCOBProvider:
         except Exception as e:
             logger.error(f"Error adding trade to SVP: {e}")
     
-    def get_session_volume_profile(self, symbol: str, bucket_size: float = None) -> Dict:
+    def get_session_volume_profile(self, symbol: str, bucket_size: Optional[float] = None) -> Dict:
         """Get session volume profile for a symbol"""
         try:
             if bucket_size is None:
@@ -690,6 +696,8 @@ class MultiExchangeCOBProvider:
             ws_url = f"{config.websocket_url}{config.symbols_mapping[symbol].lower()}@trade"
             logger.info(f"Connecting to Binance trade stream: {ws_url}")
             
+            if websockets is None:
+                raise ImportError("websockets module not available")
             async with websockets.connect(ws_url) as websocket:
                 logger.info(f"Connected to Binance trade stream for {symbol}")
                 

core/realtime_rl_cob_trader.py

@@ -301,6 +301,13 @@ class RealtimeRLCOBTrader:
                 'last_inference_time': None
             }
         
+        # PnL tracking for loss cutting optimization
+        self.pnl_history: Dict[str, deque] = {
+            symbol: deque(maxlen=1000) for symbol in self.symbols
+        }
+        self.position_peak_pnl: Dict[str, float] = {symbol: 0.0 for symbol in self.symbols}
+        self.trade_history: Dict[str, List] = {symbol: [] for symbol in self.symbols}
+        
         # Threading
         self.running = False
         self.inference_lock = Lock()
@@ -961,8 +968,10 @@ class RealtimeRLCOBTrader:
                                    actual_direction: int,
                                    confidence: float,
                                    predicted_change: float,
-                                   actual_change: float) -> float:
-        """Calculate reward for a prediction"""
+                                   actual_change: float,
+                                   current_pnl: float = 0.0,
+                                   position_duration: float = 0.0) -> float:
+        """Calculate reward for a prediction with PnL-aware loss cutting optimization"""
         try:
             # Base reward for correct direction
             if predicted_direction == actual_direction:
@@ -983,7 +992,42 @@ class RealtimeRLCOBTrader:
             if base_reward < 0 and confidence > 0.8:
                 confidence_scaled_reward *= 1.5  # Increase penalty
             
-            return float(confidence_scaled_reward)
+            # === PnL-AWARE LOSS CUTTING REWARDS ===
+            
+            pnl_reward = 0.0
+            
+            # Reward cutting losses early (SIDEWAYS when losing)
+            if current_pnl < -10.0:  # In significant loss
+                if predicted_direction == 1:  # SIDEWAYS (exit signal)
+                    # Reward cutting losses before they get worse
+                    loss_cutting_bonus = min(1.0, abs(current_pnl) / 100.0) * confidence
+                    pnl_reward += loss_cutting_bonus
+                elif predicted_direction != 1:  # Continuing to trade while in loss
+                    # Penalty for not cutting losses
+                    pnl_reward -= 0.5 * confidence
+            
+            # Reward protecting profits (SIDEWAYS when in profit and market turning)
+            elif current_pnl > 10.0:  # In profit
+                if predicted_direction == 1 and base_reward > 0:  # Correct SIDEWAYS prediction
+                    # Reward protecting profits from reversal
+                    profit_protection_bonus = min(0.5, current_pnl / 200.0) * confidence
+                    pnl_reward += profit_protection_bonus
+                
+            # Duration penalty for holding losing positions
+            if current_pnl < 0 and position_duration > 3600:  # Losing for > 1 hour
+                duration_penalty = min(1.0, position_duration / 7200.0) * 0.3  # Up to 30% penalty
+                confidence_scaled_reward -= duration_penalty
+            
+            # Severe penalty for letting small losses become big losses
+            if current_pnl < -50.0:  # Large loss
+                drawdown_penalty = min(2.0, abs(current_pnl) / 100.0) * confidence
+                confidence_scaled_reward -= drawdown_penalty
+            
+            # Total reward
+            total_reward = confidence_scaled_reward + pnl_reward
+            
+            # Clamp final reward
+            return max(-5.0, min(5.0, float(total_reward)))
             
         except Exception as e:
             logger.error(f"Error calculating reward: {e}")

core/realtime_tick_processor.py

@@ -304,7 +304,7 @@ class RealTimeTickProcessor:
                         
                         if len(self.processing_times) % 100 == 0:
                             avg_time = np.mean(list(self.processing_times))
-                            logger.info(f"Average processing time: {avg_time:.2f}ms")
+                            logger.debug(f"RTP: Average processing time: {avg_time:.2f}ms")
                 
                 # Small sleep to prevent CPU overload
                 time.sleep(0.001)  # 1ms sleep for ultra-low latency

web/cob_realtime_dashboard.py

@@ -121,7 +121,7 @@ class COBDashboardServer:
             
             # Initialize COB integration
             self.cob_integration = COBIntegration(symbols=self.symbols)
-            self.cob_integration.add_dashboard_callback(self._on_cob_update)
+            self.cob_integration.add_dashboard_callback(self._sync_cob_update_wrapper)
             
             # Start COB data streaming as background task
             asyncio.create_task(self.cob_integration.start())
@@ -319,6 +319,14 @@ class COBDashboardServer:
         except Exception as e:
             logger.error(f"Error handling WebSocket message: {e}")
     
+    def _sync_cob_update_wrapper(self, symbol: str, data: Dict):
+        """Sync wrapper for async COB update handler"""
+        try:
+            # Create async task to handle the update
+            asyncio.create_task(self._on_cob_update(symbol, data))
+        except Exception as e:
+            logger.error(f"Error in COB update wrapper for {symbol}: {e}")
+
     async def _on_cob_update(self, symbol: str, data: Dict):
         """Handle COB updates from integration"""
         try:
@@ -504,7 +512,7 @@ class COBDashboardServer:
                         except Exception:
                             self.websocket_connections.discard(ws)
                 
-                await asyncio.sleep(5)  # Update every 5 seconds
+                await asyncio.sleep(1)  # Update every 1 second for real-time responsiveness
                 
             except Exception as e:
                 logger.error(f"Error in periodic stats update: {e}")

web/dashboard.py

@@ -778,10 +778,10 @@ class TradingDashboard:
                       className="text-light mb-0 opacity-75 small")
             ], className="bg-dark p-2 mb-2"),
             
-            # Auto-refresh component - optimized for efficient updates
+            # Auto-refresh component - ultra-fast updates for real-time trading
             dcc.Interval(
                 id='interval-component',
-                interval=10000,  # Update every 10 seconds for efficiency
+                interval=1000,  # Update every 1 second for maximum responsiveness
                 n_intervals=0
             ),
             
@@ -841,21 +841,35 @@ class TradingDashboard:
                         ], className="card bg-light", style={"height": "60px"}),
                     ], style={"display": "grid", "gridTemplateColumns": "repeat(4, 1fr)", "gap": "8px", "width": "60%"}),
                     
-                    # Right side - Recent Signals & Executions
+                    # Right side - Merged: Recent Signals & Model Training - 2 columns
                     html.Div([
+                        # Recent Trading Signals Column (50%)
                         html.Div([
-                            html.H6([
-                                html.I(className="fas fa-robot me-2"),
-                                "Recent Trading Signals & Executions"
-                            ], className="card-title mb-2"),
-                            html.Div(id="recent-decisions", style={"height": "160px", "overflowY": "auto"})
-                        ], className="card-body p-2")
-                    ], className="card", style={"width": "48%", "marginLeft": "2%"})
+                            html.Div([
+                                html.H6([
+                                    html.I(className="fas fa-robot me-2"),
+                                    "Recent Trading Signals"
+                                ], className="card-title mb-2"),
+                                html.Div(id="recent-decisions", style={"height": "160px", "overflowY": "auto"})
+                            ], className="card-body p-2")
+                        ], className="card", style={"width": "48%"}),
+                        
+                        # Model Training + COB Buckets Column (50%)
+                        html.Div([
+                            html.Div([
+                                html.H6([
+                                    html.I(className="fas fa-brain me-2"),
+                                    "Training Progress & COB $1 Buckets"
+                                ], className="card-title mb-2"),
+                                html.Div(id="training-metrics", style={"height": "160px", "overflowY": "auto"})
+                            ], className="card-body p-2")
+                        ], className="card", style={"width": "48%", "marginLeft": "4%"}),
+                    ], style={"width": "48%", "marginLeft": "2%", "display": "flex"})
                 ], className="d-flex mb-3"),
                 
-                # Charts row - More compact
+                # Charts row - Now full width since training moved up
                 html.Div([
-                    # Price chart - 70% width
+                    # Price chart - Full width
                     html.Div([
                         html.Div([
                             html.H6([
@@ -864,45 +878,55 @@ class TradingDashboard:
                             ], className="card-title mb-2"),
                             dcc.Graph(id="price-chart", style={"height": "400px"})
                         ], className="card-body p-2")
-                    ], className="card", style={"width": "70%"}),
-                    
-                    # Model Training Metrics - 30% width
-                    html.Div([
-                        html.Div([
-                            html.H6([
-                                html.I(className="fas fa-brain me-2"),
-                                "Model Training Progress"
-                            ], className="card-title mb-2"),
-                            html.Div(id="training-metrics", style={"height": "400px", "overflowY": "auto"})
-                        ], className="card-body p-2")
-                    ], className="card", style={"width": "28%", "marginLeft": "2%"}),
+                    ], className="card", style={"width": "100%"}),
                 ], className="row g-2 mb-3"),
                 
-                # CNN Model Monitoring Section
+                # CNN Model Monitoring & COB Integration - MERGED into 1 row with 4 columns
                 html.Div([
+                    # CNN Status Column
                     html.Div([
                         html.Div([
                             html.H6([
                                 html.I(className="fas fa-brain me-2"),
-                                "CNN Model Analysis & Predictions"
+                                "CNN Model Analysis"
                             ], className="card-title mb-2"),
-                            html.Div(id="cnn-monitoring-content", style={"height": "350px", "overflowY": "auto"})
+                            html.Div(id="cnn-monitoring-content", style={"height": "280px", "overflowY": "auto"})
                         ], className="card-body p-2")
-                    ], className="card")
-                ], className="mb-3"),
-                
-                # COB (Consolidated Order Book) Visualization Section
-                html.Div([
+                    ], className="card", style={"width": "23%"}),
+                    
+                    # COB Status Column  
                     html.Div([
                         html.Div([
                             html.H6([
                                 html.I(className="fas fa-layer-group me-2"),
-                                "Consolidated Order Book (COB) - Real-time Market Microstructure"
+                                "COB → Training Pipeline"
                             ], className="card-title mb-2"),
-                            html.Div(id="cob-visualization-content", style={"height": "400px", "overflowY": "auto"})
+                            html.Div(id="cob-status-content", style={"height": "280px", "overflowY": "auto"})
                         ], className="card-body p-2")
-                    ], className="card")
-                ], className="mb-3"),
+                    ], className="card", style={"width": "23%", "marginLeft": "2%"}),
+                    
+                    # ETH/USDT COB Details Column
+                    html.Div([
+                        html.Div([
+                            html.H6([
+                                html.I(className="fas fa-ethereum me-2", style={"color": "#627EEA"}),
+                                "ETH/USDT - COB"
+                            ], className="card-title mb-2"),
+                            html.Div(id="eth-cob-content", style={"height": "280px", "overflowY": "auto"})
+                        ], className="card-body p-2")
+                    ], className="card", style={"width": "23%", "marginLeft": "2%"}),
+                    
+                    # BTC/USDT COB Details Column
+                    html.Div([
+                        html.Div([
+                            html.H6([
+                                html.I(className="fas fa-bitcoin me-2", style={"color": "#F7931A"}),
+                                "BTC/USDT - COB"
+                            ], className="card-title mb-2"),
+                            html.Div(id="btc-cob-content", style={"height": "280px", "overflowY": "auto"})
+                        ], className="card-body p-2")
+                    ], className="card", style={"width": "23%", "marginLeft": "2%"}),
+                ], className="d-flex mb-3"),
                 
                 # Bottom row - Session performance and system status
                 html.Div([                               
@@ -1026,7 +1050,9 @@ class TradingDashboard:
                 Output('current-leverage', 'children'),
                 Output('leverage-risk', 'children'),
                 Output('cnn-monitoring-content', 'children'),
-                Output('cob-visualization-content', 'children')
+                Output('cob-status-content', 'children'),
+                Output('eth-cob-content', 'children'),
+                Output('btc-cob-content', 'children')
             ],
             [Input('interval-component', 'n_intervals')]
         )
@@ -1035,9 +1061,9 @@ class TradingDashboard:
             update_start = time.time()
             
             try:
-                # Smart update scheduling - different frequencies for different components
+                # Smart update scheduling - optimized for 1s responsiveness  
                 is_price_update = True  # Price updates every interval (1s)
-                is_chart_update = n_intervals % 5 == 0  # Chart updates every 5s
+                is_chart_update = True  # Chart updates every 1s for real-time feel
                 is_heavy_update = n_intervals % 10 == 0  # Heavy operations every 10s
                 is_cleanup_update = n_intervals % 60 == 0  # Cleanup every 60s
                 
@@ -1125,7 +1151,7 @@ class TradingDashboard:
                 trade_count_text = f"{len(self.session_trades)}"
                 portfolio_text = f"${portfolio_value:,.2f}"
                 
-                # OPTIMIZED POSITION INFO
+                # OPTIMIZED POSITION INFO with separate colors for position and P&L
                 if self.current_position:
                     pos_side = self.current_position['side']
                     pos_size = self.current_position['size']
@@ -1133,9 +1159,18 @@ class TradingDashboard:
                     
                     side_icon = "[LONG]" if pos_side == 'LONG' else "[SHORT]"
                     side_color = "success" if pos_side == 'LONG' else "danger"
+                    pnl_color = "success" if unrealized_pnl > 0 else "danger"
                     pnl_sign = "+" if unrealized_pnl > 0 else ""
-                    position_text = f"{side_icon} {pos_size} @ ${pos_price:.2f} | P&L: {pnl_sign}${unrealized_pnl:.2f}"
-                    position_class = f"text-{side_color} fw-bold mb-0 small"
+                    
+                    # Create position text with separate colors for position type and P&L
+                    from dash import html
+                    position_text = [
+                        html.Span(f"{side_icon} {pos_size} @ ${pos_price:.2f} | P&L: ", 
+                                className=f"text-{side_color}"),
+                        html.Span(f"{pnl_sign}${unrealized_pnl:.2f}", 
+                                className=f"text-{pnl_color}")
+                    ]
+                    position_class = "fw-bold mb-0 small"
                 else:
                     position_text = "No Position"
                     position_class = "text-muted mb-0 small"
@@ -1143,12 +1178,12 @@ class TradingDashboard:
                 # MEXC status (simple)
                 mexc_status = "LIVE" if (self.trading_executor and self.trading_executor.trading_enabled and not self.trading_executor.simulation_mode) else "SIM"
                 
-                # CHART OPTIMIZATION - Only update charts every 5 seconds
+                # CHART OPTIMIZATION - Real-time chart updates every 1 second
                 if is_chart_update:
                     try:
                         if hasattr(self, '_cached_chart_data_time'):
                             cache_time = self._cached_chart_data_time
-                            if time.time() - cache_time < 20:  # Use cached chart if < 20s old
+                            if time.time() - cache_time < 5:  # Use cached chart if < 5s old for faster updates
                                 price_chart = getattr(self, '_cached_price_chart', None)
                             else:
                                 price_chart = self._create_price_chart_optimized(symbol, current_price)
@@ -1163,7 +1198,7 @@ class TradingDashboard:
                         price_chart = getattr(self, '_cached_price_chart', 
                                             self._create_empty_chart("Chart Error", "Chart temporarily unavailable"))
                 else:
-                    # Use cached chart
+                    # Use cached chart (should not happen since is_chart_update is always True now)
                     price_chart = getattr(self, '_cached_price_chart', 
                                         self._create_empty_chart("Loading", "Chart loading..."))
                 
@@ -1234,12 +1269,16 @@ class TradingDashboard:
                 else:
                     risk_level = "Extreme Risk"
                 
-                # Generate COB visualization content
+                # Generate COB 4-column content
                 try:
-                    cob_content = self._create_cob_visualization_content()
+                    cob_status_content = self._create_cob_status_content()
+                    eth_cob_content = self._create_symbol_cob_content('ETH/USDT')
+                    btc_cob_content = self._create_symbol_cob_content('BTC/USDT')
                 except Exception as e:
-                    logger.warning(f"COB visualization error: {e}")
-                    cob_content = [html.P("COB data loading...", className="text-muted")]
+                    logger.warning(f"COB content error: {e}")
+                    cob_status_content = [html.P("COB data loading...", className="text-muted")]
+                    eth_cob_content = [html.P("ETH COB loading...", className="text-muted")]
+                    btc_cob_content = [html.P("BTC COB loading...", className="text-muted")]
                 
                 # BUILD FINAL RESULT
                 result = (
@@ -1247,7 +1286,7 @@ class TradingDashboard:
                     trade_count_text, portfolio_text, mexc_status, price_chart, training_metrics, 
                     decisions_list, session_perf, closed_trades_table, system_status['icon_class'], 
                     system_status['title'], system_status['details'], leverage_text, risk_level, 
-                    cnn_monitoring_content, cob_content
+                    cnn_monitoring_content, cob_status_content, eth_cob_content, btc_cob_content
                 )
                 
                 # Cache the result for emergencies
@@ -6034,17 +6073,108 @@ class TradingDashboard:
             return self._create_empty_chart("Chart Error", "Chart temporarily unavailable")
     
     def _create_training_metrics_cached(self):
-        """Cached training metrics with reduced computation"""
+        """Enhanced training metrics with COB $1 buckets"""
         try:
-            return [
-                html.H6("Training Status", className="text-success"),
-                html.P(f"Models Active: {len(getattr(self.model_registry, 'models', {})) if self.model_registry else 0}", 
-                       className="text-muted small"),
-                html.P(f"Last Update: {datetime.now().strftime('%H:%M:%S')}", 
-                       className="text-muted small")
-            ]
-        except:
+            content = []
+            
+            # Training Status Section
+            content.append(html.H6("Training Status", className="text-success mb-2"))
+            content.append(html.P(f"Models Active: {len(getattr(self.model_registry, 'models', {})) if self.model_registry else 0}", 
+                                 className="text-muted small"))
+            content.append(html.P(f"Last Update: {datetime.now().strftime('%H:%M:%S')}", 
+                                 className="text-muted small"))
+            
+            # COB $1 Buckets Section
+            content.append(html.Hr())
+            content.append(html.H6("COB $1 Buckets", className="text-info mb-2"))
+            
+            # Get COB bucket data if available
+            try:
+                if hasattr(self.orchestrator, 'cob_integration') and self.orchestrator.cob_integration:
+                    cob_buckets = self._get_cob_dollar_buckets()
+                    if cob_buckets:
+                        # Show top 5 buckets by volume
+                        for i, bucket in enumerate(cob_buckets[:5]):
+                            price_range = f"${bucket['price']:.0f}-${bucket['price']+1:.0f}"
+                            volume = bucket['total_volume']
+                            bid_pct = (bucket['bid_volume'] / volume * 100) if volume > 0 else 0
+                            ask_pct = (bucket['ask_volume'] / volume * 100) if volume > 0 else 0
+                            
+                            content.append(html.P([
+                                html.Span(price_range, className="text-warning small fw-bold"),
+                                html.Br(),
+                                html.Span(f"Vol: ${volume:,.0f} ", className="text-muted small"),
+                                html.Span(f"B:{bid_pct:.0f}% ", className="text-success small"),
+                                html.Span(f"A:{ask_pct:.0f}%", className="text-danger small")
+                            ], className="mb-1"))
+                    else:
+                        content.append(html.P("COB buckets loading...", className="text-muted small"))
+                else:
+                    content.append(html.P("COB integration inactive", className="text-warning small"))
+            except Exception as e:
+                content.append(html.P(f"COB error: {str(e)[:30]}...", className="text-danger small"))
+            
+            return content
+            
+        except Exception as e:
             return [html.P("Training metrics unavailable", className="text-muted")]
+
+    def _get_cob_dollar_buckets(self) -> List[Dict]:
+        """Get COB data grouped into $1 buckets"""
+        try:
+            buckets = []
+            
+            # Get COB data for primary symbols
+            for symbol in ['ETH/USDT', 'BTC/USDT']:
+                if hasattr(self.orchestrator, 'cob_integration') and self.orchestrator.cob_integration:
+                    try:
+                        cob_snapshot = self.orchestrator.cob_integration.get_cob_snapshot(symbol)
+                        if cob_snapshot:
+                            mid_price = cob_snapshot.volume_weighted_mid
+                            
+                            # Create $1 buckets around mid price (±$50 range)
+                            price_buckets = {}
+                            for i in range(-50, 51):
+                                bucket_price = int(mid_price) + i
+                                price_buckets[bucket_price] = {
+                                    'price': bucket_price,
+                                    'bid_volume': 0,
+                                    'ask_volume': 0,
+                                    'total_volume': 0
+                                }
+                            
+                            # Aggregate bid data into buckets
+                            for level in cob_snapshot.consolidated_bids:
+                                bucket_price = int(level.price)
+                                if bucket_price in price_buckets:
+                                    price_buckets[bucket_price]['bid_volume'] += level.total_volume_usd
+                                    price_buckets[bucket_price]['total_volume'] += level.total_volume_usd
+                            
+                            # Aggregate ask data into buckets
+                            for level in cob_snapshot.consolidated_asks:
+                                bucket_price = int(level.price)
+                                if bucket_price in price_buckets:
+                                    price_buckets[bucket_price]['ask_volume'] += level.total_volume_usd
+                                    price_buckets[bucket_price]['total_volume'] += level.total_volume_usd
+                            
+                            # Convert to list and sort by volume
+                            symbol_buckets = [bucket for bucket in price_buckets.values() if bucket['total_volume'] > 0]
+                            symbol_buckets.sort(key=lambda x: x['total_volume'], reverse=True)
+                            
+                            # Add symbol info and take top buckets
+                            for bucket in symbol_buckets[:10]:
+                                bucket['symbol'] = symbol
+                                buckets.append(bucket)
+                    except Exception as e:
+                        logger.debug(f"Error getting COB buckets for {symbol}: {e}")
+            
+            # Sort all buckets by total volume and return top 10
+            buckets.sort(key=lambda x: x['total_volume'], reverse=True)
+            return buckets[:10]
+            
+        except Exception as e:
+            logger.error(f"Error creating COB dollar buckets: {e}")
+            return []
     
     def _create_decisions_list_cached(self):
         """Cached decisions list with limited entries"""
@@ -6140,6 +6270,163 @@ class TradingDashboard:
         except:
             return [html.P("CNN monitoring unavailable", className="text-muted")]
     
+    def _create_cob_status_content(self) -> List:
+        """Create COB status and training pipeline content"""
+        try:
+            content = []
+            
+            # Check if we have enhanced orchestrator with COB integration
+            if not hasattr(self.orchestrator, 'latest_cob_features') or not hasattr(self.orchestrator, 'cob_integration'):
+                content.append(html.P([
+                    html.I(className="fas fa-exclamation-triangle text-warning me-2"),
+                    "COB integration not available"
+                ], className="small"))
+                content.append(html.P("Using basic orchestrator", className="text-muted small"))
+                return content
+            
+            # COB Integration Status
+            if self.orchestrator.cob_integration:
+                content.append(html.P([
+                    html.I(className="fas fa-check-circle text-success me-2"),
+                    "COB integration active"
+                ], className="small"))
+            else:
+                content.append(html.P([
+                    html.I(className="fas fa-exclamation-triangle text-warning me-2"),
+                    "COB integration inactive"
+                ], className="small"))
+            
+            # Training Pipeline Status
+            if hasattr(self.orchestrator, 'enhanced_rl_training') and self.orchestrator.enhanced_rl_training:
+                content.append(html.P([
+                    html.I(className="fas fa-brain text-info me-2"),
+                    "COB → RL pipeline enabled"
+                ], className="small"))
+                content.append(html.P([
+                    html.I(className="fas fa-arrow-right text-secondary me-1"),
+                    "Real-time market microstructure"
+                ], className="small"))
+                content.append(html.P([
+                    html.I(className="fas fa-arrow-right text-secondary me-1"),
+                    "CNN features generation"
+                ], className="small"))
+                content.append(html.P([
+                    html.I(className="fas fa-arrow-right text-secondary me-1"),
+                    "RL state building"
+                ], className="small"))
+            else:
+                content.append(html.P([
+                    html.I(className="fas fa-times-circle text-danger me-2"),
+                    "Training pipeline inactive"
+                ], className="small"))
+            
+            # Performance metrics
+            cob_update_count = 0
+            for symbol in ['ETH/USDT', 'BTC/USDT']:
+                if symbol in getattr(self.orchestrator, 'latest_cob_features', {}):
+                    cob_update_count += 1
+            
+            content.append(html.Hr())
+            content.append(html.P([
+                html.Strong("Active Symbols: "),
+                f"{cob_update_count}/2"
+            ], className="text-info small"))
+            
+            return content
+            
+        except Exception as e:
+            logger.error(f"Error creating COB status content: {e}")
+            return [html.P(f"COB status error: {str(e)}", className="text-danger")]
+
+    def _create_symbol_cob_content(self, symbol: str) -> List:
+        """Create COB content for a specific symbol"""
+        try:
+            content = []
+            
+            # Check if we have enhanced orchestrator with COB integration
+            if not hasattr(self.orchestrator, 'latest_cob_features') or not hasattr(self.orchestrator, 'cob_integration'):
+                content.append(html.P("COB integration not available", className="text-warning small"))
+                return content
+            
+            # Get COB features and state
+            cob_features = getattr(self.orchestrator, 'latest_cob_features', {}).get(symbol)
+            cob_state = getattr(self.orchestrator, 'latest_cob_state', {}).get(symbol)
+            
+            # CNN Features Status
+            if cob_features is not None:
+                content.append(html.P([
+                    html.Strong("CNN Features: "),
+                    html.Span("Available", className="text-success")
+                ], className="small"))
+                content.append(html.P([
+                    html.Span(f"Shape: {cob_features.shape}", className="text-muted")
+                ], className="small"))
+            else:
+                content.append(html.P([
+                    html.Strong("CNN Features: "),
+                    html.Span("Not available", className="text-warning")
+                ], className="small"))
+            
+            # RL State Status  
+            if cob_state is not None:
+                content.append(html.P([
+                    html.Strong("RL State: "),
+                    html.Span("Available", className="text-success")
+                ], className="small"))
+                content.append(html.P([
+                    html.Span(f"Shape: {cob_state.shape}", className="text-muted")
+                ], className="small"))
+            else:
+                content.append(html.P([
+                    html.Strong("RL State: "),
+                    html.Span("Not available", className="text-warning")
+                ], className="small"))
+            
+            # Get COB snapshot if integration is active
+            cob_snapshot = None
+            if hasattr(self.orchestrator, 'cob_integration') and self.orchestrator.cob_integration:
+                try:
+                    cob_snapshot = self.orchestrator.cob_integration.get_cob_snapshot(symbol)
+                except:
+                    pass
+            
+            # COB Snapshot Details
+            if cob_snapshot:
+                content.append(html.Hr())
+                content.append(html.P([
+                    html.Strong("Mid Price: "),
+                    f"${cob_snapshot.volume_weighted_mid:.2f}"
+                ], className="text-info small"))
+                content.append(html.P([
+                    html.Strong("Spread: "),
+                    f"{cob_snapshot.spread_bps:.1f} bps"
+                ], className="text-info small"))
+                content.append(html.P([
+                    html.Strong("Bid Liquidity: "),
+                    f"${cob_snapshot.total_bid_liquidity:,.0f}"
+                ], className="text-success small"))
+                content.append(html.P([
+                    html.Strong("Ask Liquidity: "),
+                    f"${cob_snapshot.total_ask_liquidity:,.0f}"
+                ], className="text-success small"))
+                content.append(html.P([
+                    html.Strong("Exchanges: "),
+                    ", ".join(cob_snapshot.exchanges_active)
+                ], className="text-secondary small"))
+                content.append(html.P([
+                    html.Strong("Levels: "),
+                    f"{len(cob_snapshot.consolidated_bids)} bids, {len(cob_snapshot.consolidated_asks)} asks"
+                ], className="text-secondary small"))
+            else:
+                content.append(html.Hr())
+                content.append(html.P("COB snapshot not available", className="text-muted small"))
+            
+            return content
+            
+        except Exception as e:
+            logger.error(f"Error creating COB content for {symbol}: {e}")
+            return [html.P(f"COB error: {str(e)}", className="text-danger")]
+
     def _create_cob_visualization_content(self) -> List:
         """Create COB (Consolidated Order Book) visualization content"""
         try: