ui fixes
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@@ -116,6 +116,8 @@ class TrainingSession:
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error: Optional[str] = None
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gpu_utilization: Optional[float] = None # GPU utilization percentage
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cpu_utilization: Optional[float] = None # CPU utilization percentage
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annotation_count: Optional[int] = None # Number of annotations used
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timeframe: Optional[str] = None # Primary timeframe (e.g., '1m', '5m')
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class RealTrainingAdapter:
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@@ -208,13 +210,17 @@ class RealTrainingAdapter:
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logger.info(f"Available models for training: {available}")
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return available
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def start_training(self, model_name: str, test_cases: List[Dict]) -> str:
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def start_training(self, model_name: str, test_cases: List[Dict],
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annotation_count: Optional[int] = None,
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timeframe: Optional[str] = None) -> str:
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"""
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Start REAL training session with test cases
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Args:
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model_name: Name of model to train (CNN, DQN, Transformer, COB, Extrema)
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test_cases: List of test cases from annotations
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annotation_count: Number of annotations used (optional)
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timeframe: Primary timeframe for training (optional, e.g., '1m', '5m')
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Returns:
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training_id: Unique ID for this training session
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@@ -224,6 +230,10 @@ class RealTrainingAdapter:
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training_id = str(uuid.uuid4())
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# Use annotation_count if provided, otherwise use test_cases count
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if annotation_count is None:
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annotation_count = len(test_cases)
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# Create training session
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session = TrainingSession(
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training_id=training_id,
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@@ -233,7 +243,9 @@ class RealTrainingAdapter:
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current_epoch=0,
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total_epochs=10, # Reasonable for annotation-based training
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current_loss=0.0,
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start_time=time.time()
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start_time=time.time(),
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annotation_count=annotation_count,
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timeframe=timeframe
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)
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self.training_sessions[training_id] = session
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@@ -2358,7 +2370,9 @@ class RealTrainingAdapter:
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'current_epoch': session.current_epoch,
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'total_epochs': session.total_epochs,
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'current_loss': session.current_loss,
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'start_time': session.start_time
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'start_time': session.start_time,
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'annotation_count': session.annotation_count,
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'timeframe': session.timeframe
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}
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return None
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@@ -46,29 +46,6 @@
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"exit_state": {}
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}
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},
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{
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"annotation_id": "91847a37-6315-4546-b5a0-573118311322",
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"symbol": "ETH/USDT",
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"timeframe": "1s",
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"entry": {
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"timestamp": "2025-10-25 13:08:04",
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"price": 3940.24,
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"index": 25
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},
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"exit": {
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"timestamp": "2025-10-25 13:15:12",
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"price": 3942.59,
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"index": 57
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},
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"direction": "LONG",
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"profit_loss_pct": 0.05964103709419639,
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"notes": "",
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"created_at": "2025-10-25T16:17:02.931920",
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"market_context": {
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"entry_state": {},
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"exit_state": {}
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}
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},
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{
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"annotation_id": "479eb310-c963-4837-b712-70e5a42afb53",
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"symbol": "ETH/USDT",
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@@ -137,10 +114,33 @@
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"entry_state": {},
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"exit_state": {}
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}
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},
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{
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"annotation_id": "46cc0e20-0bfb-498c-9358-71b52a003d0f",
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"symbol": "ETH/USDT",
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"timeframe": "1s",
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"entry": {
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"timestamp": "2025-11-22 12:50",
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"price": 2712.11,
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"index": 26
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},
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"exit": {
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"timestamp": "2025-11-22 12:53:06",
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"price": 2721.44,
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"index": 45
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},
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"direction": "LONG",
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"profit_loss_pct": 0.3440125953593301,
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"notes": "",
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"created_at": "2025-11-22T15:19:00.480166",
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"market_context": {
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"entry_state": {},
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"exit_state": {}
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}
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}
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],
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"metadata": {
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"total_annotations": 6,
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"last_updated": "2025-11-12T13:11:31.267456"
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"last_updated": "2025-11-22T15:19:15.521679"
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}
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}
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@@ -626,8 +626,7 @@ class AnnotationDashboard:
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if not self.orchestrator:
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logger.info("Initializing TradingOrchestrator...")
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self.orchestrator = TradingOrchestrator(
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data_provider=self.data_provider,
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config=self.config
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data_provider=self.data_provider
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)
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self.training_adapter.orchestrator = self.orchestrator
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logger.info("TradingOrchestrator initialized")
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@@ -1709,6 +1708,9 @@ class AnnotationDashboard:
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# CRITICAL: Get current symbol to filter annotations
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current_symbol = data.get('symbol', 'ETH/USDT')
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# Get primary timeframe for display (optional)
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timeframe = data.get('timeframe', '1m')
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# If no specific annotations provided, use all for current symbol
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if not annotation_ids:
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annotations = self.annotation_manager.get_annotations(symbol=current_symbol)
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@@ -1737,12 +1739,14 @@ class AnnotationDashboard:
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}
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})
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logger.info(f"Starting REAL training with {len(test_cases)} test cases for model {model_name}")
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logger.info(f"Starting REAL training with {len(test_cases)} test cases ({len(annotation_ids)} annotations) for model {model_name} on {timeframe}")
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# Start REAL training (NO SIMULATION!)
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training_id = self.training_adapter.start_training(
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model_name=model_name,
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test_cases=test_cases
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test_cases=test_cases,
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annotation_count=len(annotation_ids),
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timeframe=timeframe
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)
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return jsonify({
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@@ -10,6 +10,7 @@
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/* Chart Panel */
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.chart-panel {
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height: calc(100vh - 150px);
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transition: all 0.3s ease;
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}
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.chart-panel .card-body {
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@@ -17,6 +18,29 @@
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overflow: hidden;
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}
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/* Maximized Chart View */
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.chart-maximized {
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width: 100% !important;
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max-width: 100% !important;
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flex: 0 0 100% !important;
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transition: all 0.3s ease;
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}
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.chart-panel-maximized {
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height: calc(100vh - 80px) !important;
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position: fixed;
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top: 60px;
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left: 0;
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right: 0;
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z-index: 1040;
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margin: 0 !important;
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border-radius: 0 !important;
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}
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.chart-panel-maximized .card-body {
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height: calc(100% - 60px);
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}
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#chart-container {
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height: 100%;
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overflow-y: auto;
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@@ -236,11 +260,32 @@
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padding: 1rem;
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}
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/* Maximized View - Larger Charts */
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.chart-panel-maximized .chart-plot {
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height: 400px;
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}
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@media (min-width: 1400px) {
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.chart-panel-maximized .chart-plot {
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height: 450px;
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}
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}
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@media (min-width: 1920px) {
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.chart-panel-maximized .chart-plot {
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height: 500px;
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}
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}
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/* Responsive Adjustments */
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@media (max-width: 1200px) {
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.chart-plot {
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height: 250px;
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}
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.chart-panel-maximized .chart-plot {
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height: 350px;
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}
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}
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@media (max-width: 768px) {
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@@ -101,6 +101,23 @@
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if (typeof checkActiveTraining === 'function') {
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checkActiveTraining();
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}
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// Keyboard shortcuts for chart maximization
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document.addEventListener('keydown', function(e) {
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// ESC key to exit maximized mode
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if (e.key === 'Escape') {
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const chartArea = document.querySelector('.chart-maximized');
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if (chartArea) {
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document.getElementById('maximize-btn').click();
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}
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}
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// F key to toggle maximize (when not typing in input)
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if (e.key === 'f' && !e.ctrlKey && !e.metaKey &&
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!['INPUT', 'TEXTAREA', 'SELECT'].includes(document.activeElement.tagName)) {
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document.getElementById('maximize-btn').click();
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}
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});
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// Setup keyboard shortcuts
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setupKeyboardShortcuts();
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@@ -14,6 +14,9 @@
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<button type="button" class="btn btn-outline-light" id="reset-zoom-btn" title="Reset Zoom">
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<i class="fas fa-expand"></i>
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</button>
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<button type="button" class="btn btn-outline-light" id="maximize-btn" title="Maximize Chart Area">
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<i class="fas fa-arrows-alt"></i>
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</button>
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<button type="button" class="btn btn-outline-light" id="fullscreen-btn" title="Fullscreen">
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<i class="fas fa-expand-arrows-alt"></i>
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</button>
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@@ -110,6 +113,41 @@
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}
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});
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document.getElementById('maximize-btn').addEventListener('click', function () {
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const mainRow = document.querySelector('.row.mt-3');
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const leftSidebar = mainRow.querySelector('.col-md-2:first-child');
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const chartArea = mainRow.querySelector('.col-md-8');
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const rightSidebar = mainRow.querySelector('.col-md-2:last-child');
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const chartPanel = document.querySelector('.chart-panel');
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const maximizeIcon = this.querySelector('i');
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// Toggle maximize state
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if (chartArea.classList.contains('chart-maximized')) {
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// Restore normal view
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leftSidebar.style.display = '';
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rightSidebar.style.display = '';
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chartArea.classList.remove('chart-maximized');
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chartPanel.classList.remove('chart-panel-maximized');
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maximizeIcon.className = 'fas fa-arrows-alt';
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this.title = 'Maximize Chart Area';
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} else {
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// Maximize chart area
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leftSidebar.style.display = 'none';
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rightSidebar.style.display = 'none';
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chartArea.classList.add('chart-maximized');
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chartPanel.classList.add('chart-panel-maximized');
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maximizeIcon.className = 'fas fa-compress-arrows-alt';
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this.title = 'Restore Normal View';
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}
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// Update chart layouts after transition
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setTimeout(() => {
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if (window.appState && window.appState.chartManager) {
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window.appState.chartManager.updateChartLayout();
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}
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}, 350);
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});
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document.getElementById('fullscreen-btn').addEventListener('click', function () {
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const chartContainer = document.getElementById('chart-container');
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if (chartContainer.requestFullscreen) {
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@@ -40,9 +40,13 @@
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role="progressbar" style="width: 0%"></div>
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</div>
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<div class="small">
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<div>Epoch: <span id="training-epoch">0</span>/<span id="training-total-epochs">0</span></div>
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<div>Loss: <span id="training-loss">--</span></div>
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<div>GPU: <span id="training-gpu-util">--</span>% | CPU: <span id="training-cpu-util">--</span>%</div>
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<div>Annotations: <span id="training-annotation-count" class="fw-bold text-primary">--</span></div>
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<div>Timeframe: <span id="training-timeframe" class="fw-bold text-info">--</span></div>
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<div class="mt-1 pt-1 border-top">
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<div>Epoch: <span id="training-epoch">0</span>/<span id="training-total-epochs">0</span></div>
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<div>Loss: <span id="training-loss">--</span></div>
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<div>GPU: <span id="training-gpu-util">--</span>% | CPU: <span id="training-cpu-util">--</span>%</div>
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</div>
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</div>
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</div>
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</div>
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@@ -193,6 +197,15 @@
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// Resume tracking
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activeTrainingId = data.session.training_id;
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showTrainingStatus();
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// Populate annotation count and timeframe if available
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if (data.session.annotation_count) {
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document.getElementById('training-annotation-count').textContent = data.session.annotation_count;
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}
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if (data.session.timeframe) {
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document.getElementById('training-timeframe').textContent = data.session.timeframe.toUpperCase();
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}
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pollTrainingProgress(activeTrainingId);
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} else {
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console.log('No active training session');
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@@ -408,10 +421,17 @@
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// Show training status
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showTrainingStatus();
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// Get primary timeframe for training
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const primaryTimeframe = document.getElementById('primary-timeframe-select').value;
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// Reset progress
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document.getElementById('training-progress-bar').style.width = '0%';
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document.getElementById('training-epoch').textContent = '0';
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document.getElementById('training-loss').textContent = '--';
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// Set annotation count and timeframe
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document.getElementById('training-annotation-count').textContent = annotationIds.length;
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document.getElementById('training-timeframe').textContent = primaryTimeframe.toUpperCase();
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// Start training request
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fetch('/api/train-model', {
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@@ -420,7 +440,8 @@
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body: JSON.stringify({
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model_name: modelName,
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annotation_ids: annotationIds,
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symbol: appState.currentSymbol // CRITICAL: Filter by current symbol
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symbol: appState.currentSymbol, // CRITICAL: Filter by current symbol
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timeframe: primaryTimeframe // Primary timeframe for display
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})
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})
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.then(response => response.json())
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