remove emojis from console
This commit is contained in:
Dobromir Popov
@@ -196,14 +196,14 @@ class AnnotationDashboard:
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for attempt in range(max_retries):
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try:
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if attempt > 0:
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logger.info(f"🔄 Retry attempt {attempt + 1}/{max_retries} for model loading...")
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logger.info(f" Retry attempt {attempt + 1}/{max_retries} for model loading...")
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time.sleep(retry_delay)
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else:
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logger.info("🔄 Starting async model loading...")
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logger.info(" Starting async model loading...")
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# Check if TradingOrchestrator is available
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if not TradingOrchestrator:
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logger.error("❌ TradingOrchestrator class not available")
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logger.error(" TradingOrchestrator class not available")
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self.models_loading = False
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self.available_models = []
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return
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@@ -214,48 +214,48 @@ class AnnotationDashboard:
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data_provider=self.data_provider,
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enhanced_rl_training=True
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)
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logger.info(" ✅ Orchestrator created")
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logger.info(" Orchestrator created")
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# Initialize ML models
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logger.info(" Initializing ML models...")
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self.orchestrator._initialize_ml_models()
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logger.info(" ✅ ML models initialized")
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logger.info(" ML models initialized")
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# Update training adapter with orchestrator
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self.training_adapter.orchestrator = self.orchestrator
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logger.info(" ✅ Training adapter updated")
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logger.info(" Training adapter updated")
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# Get available models from orchestrator
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available = []
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if hasattr(self.orchestrator, 'rl_agent') and self.orchestrator.rl_agent:
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available.append('DQN')
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logger.info(" ✅ DQN model available")
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logger.info(" DQN model available")
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if hasattr(self.orchestrator, 'cnn_model') and self.orchestrator.cnn_model:
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available.append('CNN')
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logger.info(" ✅ CNN model available")
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logger.info(" CNN model available")
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if hasattr(self.orchestrator, 'transformer_model') and self.orchestrator.transformer_model:
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available.append('Transformer')
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logger.info(" ✅ Transformer model available")
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logger.info(" Transformer model available")
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self.available_models = available
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if available:
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logger.info(f"✅ Models loaded successfully: {', '.join(available)}")
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logger.info(f" Models loaded successfully: {', '.join(available)}")
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else:
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logger.warning("⚠️ No models were initialized (this might be normal if models aren't configured)")
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logger.warning(" No models were initialized (this might be normal if models aren't configured)")
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self.models_loading = False
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logger.info("✅ Async model loading complete")
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logger.info(" Async model loading complete")
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return # Success - exit retry loop
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except Exception as e:
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logger.error(f"❌ Error loading models (attempt {attempt + 1}/{max_retries}): {e}")
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logger.error(f" Error loading models (attempt {attempt + 1}/{max_retries}): {e}")
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import traceback
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logger.error(f"Traceback:\n{traceback.format_exc()}")
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if attempt == max_retries - 1:
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# Final attempt failed
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logger.error(f"❌ Model loading failed after {max_retries} attempts")
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logger.error(f" Model loading failed after {max_retries} attempts")
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self.models_loading = False
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self.available_models = []
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else:
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@@ -264,7 +264,7 @@ class AnnotationDashboard:
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# Start loading in background thread
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thread = threading.Thread(target=load_models, daemon=True, name="ModelLoader")
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thread.start()
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logger.info(f"🚀 Model loading started in background thread (ID: {thread.ident}, Name: {thread.name})")
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logger.info(f" Model loading started in background thread (ID: {thread.ident}, Name: {thread.name})")
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logger.info(" UI remains responsive while models load...")
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logger.info(" Will retry up to 3 times if loading fails")
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@@ -284,7 +284,7 @@ class AnnotationDashboard:
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)
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if success:
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logger.info("✅ ANNOTATE: Unified storage enabled for real-time data")
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logger.info(" ANNOTATE: Unified storage enabled for real-time data")
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# Get statistics
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stats = self.data_provider.get_unified_storage_stats()
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@@ -293,7 +293,7 @@ class AnnotationDashboard:
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logger.info(" Historical data access: <100ms")
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logger.info(" Annotation data: Available at any timestamp")
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else:
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logger.warning("⚠️ ANNOTATE: Unified storage not available, using cached data only")
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logger.warning(" ANNOTATE: Unified storage not available, using cached data only")
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except Exception as e:
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logger.warning(f"ANNOTATE: Could not enable unified storage: {e}")
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@@ -312,7 +312,7 @@ class AnnotationDashboard:
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# Wait for app to fully start
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time.sleep(5)
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logger.info("🔄 Starting one-time background data refresh (fetching only recent missing data)")
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logger.info(" Starting one-time background data refresh (fetching only recent missing data)")
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# Disable startup mode to fetch fresh data
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self.data_loader.disable_startup_mode()
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@@ -321,7 +321,7 @@ class AnnotationDashboard:
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logger.info("Using on-demand refresh for recent data")
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self.data_provider.refresh_data_on_demand()
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logger.info("✅ One-time background data refresh completed")
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logger.info(" One-time background data refresh completed")
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except Exception as e:
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logger.error(f"Error in background data refresh: {e}")
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@@ -488,9 +488,9 @@ class AnnotationDashboard:
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<h1 class="text-center">📝 ANNOTATE - Manual Trade Annotation UI</h1>
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<div class="alert alert-info">
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<h4>System Status</h4>
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<p>✅ Annotation Manager: Active</p>
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<p>⚠️ Data Provider: {'Available' if self.data_provider else 'Not Available (Standalone Mode)'}</p>
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<p>⚠️ Trading Orchestrator: {'Available' if self.orchestrator else 'Not Available (Standalone Mode)'}</p>
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<p> Annotation Manager: Active</p>
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<p> Data Provider: {'Available' if self.data_provider else 'Not Available (Standalone Mode)'}</p>
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<p> Trading Orchestrator: {'Available' if self.orchestrator else 'Not Available (Standalone Mode)'}</p>
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</div>
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<div class="row">
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<div class="col-md-6">
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@@ -537,7 +537,7 @@ class AnnotationDashboard:
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'error': {'code': 'INVALID_REQUEST', 'message': 'Missing timeframe or timestamps'}
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})
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logger.info(f"🔄 Recalculating pivots for {symbol} {timeframe} with {len(timestamps)} candles")
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logger.info(f" Recalculating pivots for {symbol} {timeframe} with {len(timestamps)} candles")
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# Convert to DataFrame
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df = pd.DataFrame({
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@@ -552,7 +552,7 @@ class AnnotationDashboard:
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# Recalculate pivot markers
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pivot_markers = self._get_pivot_markers_for_timeframe(symbol, timeframe, df)
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logger.info(f" ✅ Recalculated {len(pivot_markers)} pivot candles")
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logger.info(f" Recalculated {len(pivot_markers)} pivot candles")
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return jsonify({
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'success': True,
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@@ -614,7 +614,7 @@ class AnnotationDashboard:
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)
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if df is not None and not df.empty:
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logger.info(f" ✅ {timeframe}: {len(df)} candles ({df.index[0]} to {df.index[-1]})")
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logger.info(f" {timeframe}: {len(df)} candles ({df.index[0]} to {df.index[-1]})")
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# Get pivot points for this timeframe
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pivot_markers = self._get_pivot_markers_for_timeframe(symbol, timeframe, df)
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@@ -630,7 +630,7 @@ class AnnotationDashboard:
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'pivot_markers': pivot_markers # Optional: only present if pivots exist
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}
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else:
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logger.warning(f" ❌ {timeframe}: No data returned")
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logger.warning(f" {timeframe}: No data returned")
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# Get pivot bounds for the symbol
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pivot_bounds = None
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