# Configuration file for the agentic AI trading system
data_source:
  type: 'csv'
  path: 'data/market_data.csv'

trading:
  symbol: 'AAPL'
  timeframe: '1m'
  capital: 100000

risk:
  max_position: 100
  max_drawdown: 0.05

execution:
  broker_api: 'paper'  # Options: 'paper', 'alpaca_paper', 'alpaca_live'
  order_size: 10
  delay_ms: 100
  success_rate: 0.95

# Alpaca configuration
alpaca:
  api_key: ''  # Set via environment variable ALPACA_API_KEY
  secret_key: ''  # Set via environment variable ALPACA_SECRET_KEY
  paper_trading: true  # Use paper trading by default
  base_url: 'https://paper-api.alpaca.markets'  # Paper trading URL
  live_url: 'https://api.alpaca.markets'  # Live trading URL
  data_url: 'https://data.alpaca.markets'  # Market data URL
  websocket_url: 'wss://stream.data.alpaca.markets/v2/iex'  # WebSocket URL
  account_type: 'paper'  # 'paper' or 'live'

# Synthetic data generation settings
synthetic_data:
  base_price: 150.0
  volatility: 0.02
  trend: 0.001
  noise_level: 0.005
  generate_data: true
  data_path: 'data/synthetic_market_data.csv'

# Logging configuration
logging:
  log_level: 'INFO'
  log_dir: 'logs'
  enable_console: true
  enable_file: true
  max_file_size_mb: 10
  backup_count: 5

# FinRL configuration
finrl:
  algorithm: 'PPO'  # PPO, A2C, DDPG, TD3
  learning_rate: 0.0003
  batch_size: 64
  buffer_size: 1000000
  learning_starts: 100
  gamma: 0.99
  tau: 0.005
  train_freq: 1
  gradient_steps: 1
  target_update_interval: 1
  exploration_fraction: 0.1
  exploration_initial_eps: 1.0
  exploration_final_eps: 0.05
  max_grad_norm: 10.0
  verbose: 1
  tensorboard_log: 'logs/finrl_tensorboard'
  training:
    total_timesteps: 100000
    eval_freq: 10000
    save_best_model: true
    model_save_path: 'models/finrl_best/'
  inference:
    use_trained_model: false
    model_path: 'models/finrl_best/best_model'