show each model's prediction (last inference) and store T model checkpoint
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@ -677,15 +677,31 @@ class DashboardComponentManager:
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# Model metrics
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html.Div([
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# Last prediction
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# Last prediction with enhanced details
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html.Div([
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html.Span("Last: ", className="text-muted small"),
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html.Span(f"{pred_action}",
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className=f"small fw-bold {'text-success' if pred_action == 'BUY' else 'text-danger' if pred_action == 'SELL' else 'text-muted'}"),
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className=f"small fw-bold {'text-success' if pred_action == 'BUY' else 'text-danger' if pred_action == 'SELL' else 'text-warning' if 'PREDICTION' in pred_action else 'text-info'}"),
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html.Span(f" ({pred_confidence:.1f}%)", className="text-muted small"),
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html.Span(f" @ {pred_time}", className="text-muted small")
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], className="mb-1"),
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# Additional prediction details if available
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*([
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html.Div([
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html.Span("Price: ", className="text-muted small"),
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html.Span(f"${last_prediction.get('predicted_price', 0):.2f}", className="text-warning small fw-bold")
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], className="mb-1")
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] if last_prediction.get('predicted_price', 0) > 0 else []),
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*([
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html.Div([
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html.Span("Change: ", className="text-muted small"),
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html.Span(f"{last_prediction.get('price_change', 0):+.2f}%",
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className=f"small fw-bold {'text-success' if last_prediction.get('price_change', 0) > 0 else 'text-danger'}")
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], className="mb-1")
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] if last_prediction.get('price_change', 0) != 0 else []),
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# Timing information (NEW)
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html.Div([
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html.Span("Timing: ", className="text-muted small"),
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