# Enhanced Multi-Modal Trading System Configuration

# Trading Symbols (extendable/configurable)
symbols:
  - "ETH/USDT"
  - "BTC/USDT"

# Timeframes for multi-timeframe analysis
timeframes:
  - "1m"
  - "5m" 
  - "15m"
  - "1h"
  - "4h"
  - "1d"

# Data Provider Settings
data:
  provider: "binance"
  cache_enabled: true
  cache_dir: "cache"
  historical_limit: 1000
  real_time_enabled: true
  websocket_reconnect: true
  feature_engineering:
    technical_indicators: true
    market_regime_detection: true
    volatility_analysis: true

# Enhanced CNN Configuration
cnn:
  window_size: 20
  features: ["open", "high", "low", "close", "volume"]
  timeframes: ["1m", "5m", "15m", "1h", "4h", "1d"]
  hidden_layers: [64, 128, 256]
  dropout: 0.2
  learning_rate: 0.001
  batch_size: 32
  epochs: 100
  confidence_threshold: 0.6
  early_stopping_patience: 10
  model_dir: "models/enhanced_cnn"
  # Timeframe-specific model weights
  timeframe_importance:
    "1m": 0.05   # Noise filtering
    "5m": 0.10   # Short-term momentum  
    "15m": 0.15  # Entry/exit timing
    "1h": 0.25   # Medium-term trend
    "4h": 0.25   # Stronger trend confirmation
    "1d": 0.20   # Long-term direction

# Enhanced RL Agent Configuration  
rl:
  state_size: 100  # Will be calculated dynamically based on features
  action_space: 3  # BUY, HOLD, SELL
  hidden_size: 256
  epsilon: 1.0
  epsilon_decay: 0.995
  epsilon_min: 0.01
  learning_rate: 0.0001
  gamma: 0.99
  memory_size: 10000
  batch_size: 64
  target_update_freq: 1000
  buffer_size: 10000
  model_dir: "models/enhanced_rl"
  # Market regime adaptation
  market_regime_weights:
    trending: 1.2    # Higher confidence in trending markets
    ranging: 0.8     # Lower confidence in ranging markets
    volatile: 0.6    # Much lower confidence in volatile markets
  # Prioritized experience replay
  replay_alpha: 0.6  # Priority exponent
  replay_beta: 0.4   # Importance sampling exponent

# Enhanced Orchestrator Settings
orchestrator:
  # Model weights for decision combination
  cnn_weight: 0.7      # Weight for CNN predictions
  rl_weight: 0.3       # Weight for RL decisions
  confidence_threshold: 0.6  # Increased for enhanced system
  decision_frequency: 30     # Seconds between decisions (faster)
  
  # Multi-symbol coordination
  symbol_correlation_matrix:
    "ETH/USDT-BTC/USDT": 0.85  # ETH-BTC correlation
    
  # Perfect move marking
  perfect_move_threshold: 0.02  # 2% price change to mark as significant
  perfect_move_buffer_size: 10000
  
  # RL evaluation settings
  evaluation_delay: 3600  # Evaluate actions after 1 hour
  reward_calculation:
    success_multiplier: 10    # Reward for correct predictions
    failure_penalty: 5        # Penalty for wrong predictions
    confidence_scaling: true   # Scale rewards by confidence

# Training Configuration
training:
  learning_rate: 0.001
  batch_size: 32
  epochs: 100
  validation_split: 0.2
  early_stopping_patience: 10
  
  # CNN specific
  cnn_training_interval: 21600  # Train every 6 hours
  min_perfect_moves: 200        # Minimum moves before training
  
  # RL specific  
  rl_training_interval: 3600    # Train every hour
  min_experiences: 100          # Minimum experiences before training
  training_steps_per_cycle: 10  # Training steps per cycle

# Trading Execution
trading:
  max_position_size: 0.05    # Maximum position size (5% of balance)
  stop_loss: 0.02           # 2% stop loss
  take_profit: 0.05         # 5% take profit
  trading_fee: 0.0002       # 0.02% trading fee
  min_trade_interval: 30    # Minimum seconds between trades (faster)
  
  # Risk management
  max_daily_trades: 20      # Maximum trades per day
  max_concurrent_positions: 2  # Max positions across symbols
  position_sizing:
    confidence_scaling: true  # Scale position by confidence
    base_size: 0.02          # 2% base position
    max_size: 0.05           # 5% maximum position

# Memory Management
memory:
  total_limit_gb: 8.0       # Total system memory limit
  model_limit_gb: 2.0       # Per-model memory limit
  cleanup_interval: 1800    # Memory cleanup every 30 minutes
  
# Web Dashboard
web:
  host: "127.0.0.1"
  port: 8050
  debug: false
  update_interval: 1000  # Milliseconds
  chart_history: 100     # Number of candles to show
  
  # Enhanced dashboard features
  show_timeframe_analysis: true
  show_confidence_scores: true
  show_perfect_moves: true
  show_rl_metrics: true

# Logging
logging:
  level: "INFO"
  format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
  file: "logs/enhanced_trading.log"
  max_size: 10485760  # 10MB
  backup_count: 5
  
  # Component-specific logging
  orchestrator_level: "INFO"
  cnn_level: "INFO"
  rl_level: "INFO"
  training_level: "INFO"

# Model Directories
model_dir: "models"
data_dir: "data"
cache_dir: "cache"
logs_dir: "logs"

# GPU/Performance
gpu:
  enabled: true
  memory_fraction: 0.8  # Use 80% of GPU memory
  allow_growth: true    # Allow dynamic memory allocation
  
# Monitoring and Alerting
monitoring:
  tensorboard_enabled: true
  tensorboard_log_dir: "logs/tensorboard"
  metrics_interval: 300     # Log metrics every 5 minutes
  performance_alerts: true
  
  # Performance thresholds
  min_confidence_threshold: 0.3
  max_memory_usage: 0.9     # 90% of available memory
  max_decision_latency: 10  # 10 seconds max per decision

# Backtesting (for future implementation)
backtesting:
  start_date: "2024-01-01"
  end_date: "2024-12-31"
  initial_balance: 10000
  commission: 0.0002
  slippage: 0.0001