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ui fixes

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This commit is contained in:
Dobromir Popov
2025-07-29 19:02:44 +03:00
parent ac4068c168
commit 0b5fa07498
4 changed files with 143 additions and 56 deletions
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16
data/ui_state.json
View File

@ -9,15 +9,21 @@
"training_enabled": true "training_enabled": true
}, },
"cob_rl": { "cob_rl": {
"inference_enabled": true, "inference_enabled": false,
"training_enabled": true "training_enabled": true
}, },
"decision_fusion": { "decision_fusion": {
"inference_enabled": false, "inference_enabled": false,
"training_enabled": false "training_enabled": true
},
"transformer": {
"inference_enabled": false,
"training_enabled": true
},
"dqn_agent": {
"inference_enabled": false,
"training_enabled": true
} }
}, },
"timestamp": "2025-07-29T15:55:43.690404" "timestamp": "2025-07-29T18:37:29.759605"
} }

96
web/clean_dashboard.py
View File

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

32
web/component_manager.py
View File

@ -140,7 +140,8 @@ class DashboardComponentManager:
# Create table headers # Create table headers
headers = html.Thead([ headers = html.Thead([
html.Tr([ html.Tr([
html.Th("Time", className="small"), html.Th("Entry Time", className="small"),
html.Th("Exit Time", className="small"),
html.Th("Side", className="small"), html.Th("Side", className="small"),
html.Th("Size", className="small"), html.Th("Size", className="small"),
html.Th("Entry", className="small"), html.Th("Entry", className="small"),
@ -158,6 +159,7 @@ class DashboardComponentManager:
if hasattr(trade, 'entry_time'): if hasattr(trade, 'entry_time'):
# This is a trade object # This is a trade object
entry_time = getattr(trade, 'entry_time', 'Unknown') entry_time = getattr(trade, 'entry_time', 'Unknown')
exit_time = getattr(trade, 'exit_time', 'Unknown')
side = getattr(trade, 'side', 'UNKNOWN') side = getattr(trade, 'side', 'UNKNOWN')
size = getattr(trade, 'size', 0) size = getattr(trade, 'size', 0)
entry_price = getattr(trade, 'entry_price', 0) entry_price = getattr(trade, 'entry_price', 0)
@ -168,6 +170,7 @@ class DashboardComponentManager:
else: else:
# This is a dictionary format # This is a dictionary format
entry_time = trade.get('entry_time', 'Unknown') entry_time = trade.get('entry_time', 'Unknown')
exit_time = trade.get('exit_time', 'Unknown')
side = trade.get('side', 'UNKNOWN') side = trade.get('side', 'UNKNOWN')
size = trade.get('quantity', trade.get('size', 0)) # Try 'quantity' first, then 'size' size = trade.get('quantity', trade.get('size', 0)) # Try 'quantity' first, then 'size'
entry_price = trade.get('entry_price', 0) entry_price = trade.get('entry_price', 0)
@ -176,11 +179,17 @@ class DashboardComponentManager:
fees = trade.get('fees', 0) fees = trade.get('fees', 0)
hold_time_seconds = trade.get('hold_time_seconds', 0.0) hold_time_seconds = trade.get('hold_time_seconds', 0.0)
# Format time # Format entry time
if isinstance(entry_time, datetime): if isinstance(entry_time, datetime):
time_str = entry_time.strftime('%H:%M:%S') entry_time_str = entry_time.strftime('%H:%M:%S')
else: else:
time_str = str(entry_time) entry_time_str = str(entry_time)
# Format exit time
if isinstance(exit_time, datetime):
exit_time_str = exit_time.strftime('%H:%M:%S')
else:
exit_time_str = str(exit_time)
# Determine P&L color # Determine P&L color
pnl_class = "text-success" if pnl >= 0 else "text-danger" pnl_class = "text-success" if pnl >= 0 else "text-danger"
@ -197,7 +206,8 @@ class DashboardComponentManager:
net_pnl = pnl - fees net_pnl = pnl - fees
row = html.Tr([ row = html.Tr([
html.Td(time_str, className="small"), html.Td(entry_time_str, className="small"),
html.Td(exit_time_str, className="small"),
html.Td(side, className=f"small {side_class}"), html.Td(side, className=f"small {side_class}"),
html.Td(f"${position_size_usd:.2f}", className="small"), # Show size in USD html.Td(f"${position_size_usd:.2f}", className="small"), # Show size in USD
html.Td(f"${entry_price:.2f}", className="small"), html.Td(f"${entry_price:.2f}", className="small"),
@ -714,11 +724,11 @@ class DashboardComponentManager:
"""Format training metrics for display - Enhanced with loaded models""" """Format training metrics for display - Enhanced with loaded models"""
try: try:
# DEBUG: Log what we're receiving # DEBUG: Log what we're receiving
logger.debug(f"format_training_metrics received: {type(metrics_data)}") logger.info(f"format_training_metrics received: {type(metrics_data)}")
if metrics_data: if metrics_data:
logger.debug(f"Metrics keys: {list(metrics_data.keys()) if isinstance(metrics_data, dict) else 'Not a dict'}") logger.info(f"Metrics keys: {list(metrics_data.keys()) if isinstance(metrics_data, dict) else 'Not a dict'}")
if isinstance(metrics_data, dict) and 'loaded_models' in metrics_data: if isinstance(metrics_data, dict) and 'loaded_models' in metrics_data:
logger.debug(f"Loaded models: {list(metrics_data['loaded_models'].keys())}") logger.info(f"Loaded models: {list(metrics_data['loaded_models'].keys())}")
if not metrics_data or 'error' in metrics_data: if not metrics_data or 'error' in metrics_data:
logger.warning(f"No training data or error in metrics_data: {metrics_data}") logger.warning(f"No training data or error in metrics_data: {metrics_data}")
@ -772,6 +782,7 @@ class DashboardComponentManager:
checkpoint_status = "LOADED" if model_info.get('checkpoint_loaded', False) else "FRESH" checkpoint_status = "LOADED" if model_info.get('checkpoint_loaded', False) else "FRESH"
# Model card # Model card
logger.info(f"Creating model card for {model_name} with toggles: inference={model_info.get('inference_enabled', True)}, training={model_info.get('training_enabled', True)}")
model_card = html.Div([ model_card = html.Div([
# Header with model name and toggle # Header with model name and toggle
html.Div([ html.Div([
@ -1043,10 +1054,15 @@ class DashboardComponentManager:
html.Span(f"{enhanced_stats['recent_validation_score']:.3f}", className="text-primary small fw-bold") html.Span(f"{enhanced_stats['recent_validation_score']:.3f}", className="text-primary small fw-bold")
], className="mb-1")) ], className="mb-1"))
logger.info(f"format_training_metrics returning {len(content)} components")
for i, component in enumerate(content[:3]): # Log first 3 components
logger.info(f" Component {i}: {type(component)}")
return content return content
except Exception as e: except Exception as e:
logger.error(f"Error formatting training metrics: {e}") logger.error(f"Error formatting training metrics: {e}")
import traceback
logger.error(f"Traceback: {traceback.format_exc()}")
return [html.P(f"Error: {str(e)}", className="text-danger small")] return [html.P(f"Error: {str(e)}", className="text-danger small")]
def _format_cnn_pivot_prediction(self, model_info): def _format_cnn_pivot_prediction(self, model_info):

55
web/layout_manager.py
View File

@ -17,11 +17,32 @@ class DashboardLayoutManager:
def create_main_layout(self): def create_main_layout(self):
"""Create the main dashboard layout""" """Create the main dashboard layout"""
return html.Div([ try:
self._create_header(), print("Creating main layout...")
self._create_interval_component(), header = self._create_header()
self._create_main_content() print("Header created")
], className="container-fluid") interval_component = self._create_interval_component()
print("Interval component created")
main_content = self._create_main_content()
print("Main content created")
layout = html.Div([
header,
interval_component,
main_content
], className="container-fluid")
print("Main layout created successfully")
return layout
except Exception as e:
print(f"Error creating main layout: {e}")
import traceback
traceback.print_exc()
# Return a simple error layout
return html.Div([
html.H1("Dashboard Error", className="text-danger"),
html.P(f"Error creating layout: {str(e)}", className="text-danger")
])
def _create_header(self): def _create_header(self):
"""Create the dashboard header""" """Create the dashboard header"""
@ -52,7 +73,15 @@ class DashboardLayoutManager:
dcc.Interval( dcc.Interval(
id='slow-interval-component', id='slow-interval-component',
interval=10000, # Update every 10 seconds (0.1 Hz) - OPTIMIZED interval=10000, # Update every 10 seconds (0.1 Hz) - OPTIMIZED
n_intervals=0 n_intervals=0,
disabled=False
),
# Fast interval for testing (5 seconds)
dcc.Interval(
id='fast-interval-component',
interval=5000, # Update every 5 seconds for testing
n_intervals=0,
disabled=False
), ),
# WebSocket-based updates for high-frequency data (no interval needed) # WebSocket-based updates for high-frequency data (no interval needed)
html.Div(id='websocket-updates-container', style={'display': 'none'}) html.Div(id='websocket-updates-container', style={'display': 'none'})
@ -357,10 +386,16 @@ class DashboardLayoutManager:
html.Div([ html.Div([
html.Div([ html.Div([
html.Div([ html.Div([
html.H6([ html.Div([
html.I(className="fas fa-brain me-2"), html.H6([
"Models & Training Progress", html.I(className="fas fa-brain me-2"),
], className="card-title mb-2"), "Models & Training Progress",
], className="card-title mb-2"),
html.Button([
html.I(className="fas fa-sync-alt me-1"),
"Refresh"
], id="refresh-training-metrics-btn", className="btn btn-sm btn-outline-primary")
], className="d-flex justify-content-between align-items-center mb-2"),
html.Div( html.Div(
id="training-metrics", id="training-metrics",
style={"height": "300px", "overflowY": "auto"}, style={"height": "300px", "overflowY": "auto"},