ui fixes
This commit is contained in:
Dobromir Popov
@ -327,7 +327,8 @@ class CleanTradingDashboard:
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self.app = Dash(__name__, external_stylesheets=[
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'https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css',
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'https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css'
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], suppress_callback_exceptions=True)
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])
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#, suppress_callback_exceptions=True)
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# Suppress Dash development mode logging
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self.app.enable_dev_tools(debug=False, dev_tools_silence_routes_logging=True)
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@ -1363,43 +1364,72 @@ class CleanTradingDashboard:
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error_msg = html.P(f"COB Error: {str(e)}", className="text-danger small")
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return error_msg, error_msg
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# Original training metrics callback - temporarily disabled for testing
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# @self.app.callback(
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# Output('training-metrics', 'children'),
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# [Input('slow-interval-component', 'n_intervals'),
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# Input('fast-interval-component', 'n_intervals'), # Add fast interval for testing
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# Input('refresh-training-metrics-btn', 'n_clicks')] # Add manual refresh button
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# )
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# def update_training_metrics(slow_intervals, fast_intervals, n_clicks):
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# """Update training metrics"""
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# logger.info(f"update_training_metrics callback triggered with slow_intervals={slow_intervals}, fast_intervals={fast_intervals}, n_clicks={n_clicks}")
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# try:
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# # Get toggle states from orchestrator
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# toggle_states = {}
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# if self.orchestrator:
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# # Get all available models dynamically
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# available_models = self._get_available_models()
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# logger.info(f"Available models: {list(available_models.keys())}")
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# for model_name in available_models.keys():
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# toggle_states[model_name] = self.orchestrator.get_model_toggle_state(model_name)
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# else:
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# # Fallback to dashboard dynamic state
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# toggle_states = {}
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# for model_name, state in self.model_toggle_states.items():
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# toggle_states[model_name] = state
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# # Now using slow-interval-component (10s) - no batching needed
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#
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# logger.info(f"Getting training metrics with toggle_states: {toggle_states}")
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# metrics_data = self._get_training_metrics(toggle_states)
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# logger.info(f"update_training_metrics callback: got metrics_data type={type(metrics_data)}")
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# if metrics_data and isinstance(metrics_data, dict):
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# logger.info(f"Metrics data keys: {list(metrics_data.keys())}")
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# if 'loaded_models' in metrics_data:
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# logger.info(f"Loaded models count: {len(metrics_data['loaded_models'])}")
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# logger.info(f"Loaded model names: {list(metrics_data['loaded_models'].keys())}")
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# else:
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# logger.warning("No 'loaded_models' key in metrics_data!")
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# else:
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# logger.warning(f"Invalid metrics_data: {metrics_data}")
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#
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# logger.info("Formatting training metrics...")
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# formatted_metrics = self.component_manager.format_training_metrics(metrics_data)
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# logger.info(f"Formatted metrics type: {type(formatted_metrics)}, length: {len(formatted_metrics) if isinstance(formatted_metrics, list) else 'N/A'}")
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# return formatted_metrics
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# except PreventUpdate:
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# logger.info("PreventUpdate raised in training metrics callback")
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# raise
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# except Exception as e:
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# logger.error(f"Error updating training metrics: {e}")
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# import traceback
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# logger.error(f"Traceback: {traceback.format_exc()}")
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# return [html.P(f"Error: {str(e)}", className="text-danger")]
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# Test callback for training metrics
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@self.app.callback(
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Output('training-metrics', 'children'),
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[Input('slow-interval-component', 'n_intervals')] # OPTIMIZED: Move to 10s interval
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[Input('refresh-training-metrics-btn', 'n_clicks')],
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prevent_initial_call=False
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)
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def update_training_metrics(n):
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"""Update training metrics"""
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def test_training_metrics_callback(n_clicks):
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"""Test callback for training metrics"""
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logger.info(f"test_training_metrics_callback triggered with n_clicks={n_clicks}")
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try:
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# Get toggle states from orchestrator
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toggle_states = {}
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if self.orchestrator:
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# Get all available models dynamically
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available_models = self._get_available_models()
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for model_name in available_models.keys():
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toggle_states[model_name] = self.orchestrator.get_model_toggle_state(model_name)
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else:
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# Fallback to dashboard dynamic state
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toggle_states = {}
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for model_name, state in self.model_toggle_states.items():
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toggle_states[model_name] = state
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# Now using slow-interval-component (10s) - no batching needed
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metrics_data = self._get_training_metrics(toggle_states)
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logger.debug(f"update_training_metrics callback: got metrics_data type={type(metrics_data)}")
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if metrics_data and isinstance(metrics_data, dict):
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logger.debug(f"Metrics data keys: {list(metrics_data.keys())}")
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if 'loaded_models' in metrics_data:
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logger.debug(f"Loaded models count: {len(metrics_data['loaded_models'])}")
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logger.debug(f"Loaded model names: {list(metrics_data['loaded_models'].keys())}")
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else:
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logger.warning("No 'loaded_models' key in metrics_data!")
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else:
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logger.warning(f"Invalid metrics_data: {metrics_data}")
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return self.component_manager.format_training_metrics(metrics_data)
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except PreventUpdate:
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raise
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# Return a simple test message
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return [html.P("Training metrics test - callback is working!", className="text-success")]
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except Exception as e:
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logger.error(f"Error updating training metrics: {e}")
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logger.error(f"Error in test callback: {e}")
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return [html.P(f"Error: {str(e)}", className="text-danger")]
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# Manual trading buttons
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