mirror of
https://github.com/NicolasBohn/NexQuant.git
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feat: Full system integration - RL + Protections + Backtesting + CLI
Connect all Predix components into unified trading system: INTEGRATION (ALL 295 TESTS PASS): - RL Trading connected with Protection Manager - RL Trading connected with Backtesting Engine - CLI command 'rdagent rl_trading' added (train/backtest/live modes) - Graceful fallback for users without stable-baselines3 OPEN SOURCE COMPATIBILITY: - System works WITHOUT stable-baselines3 (momentum fallback) - System works WITHOUT local models/prompts (uses standard) - Clear warning messages when optional deps missing - GitHub users get FULLY WORKING system CLOSED SOURCE PROTECTION: - models/local/, prompts/local/, .env stay local only - .gitignore properly configured - Our alpha (best models/prompts) remains private DOCUMENTATION: - QWEN.md: Open/closed source strategy - QWEN.md: Development guidelines for AI assistant - QWEN.md: Open source compatibility principle - README.md: RL Trading CLI commands and examples - requirements/rl.txt: Optional RL dependencies Modified files: - rdagent/app/cli.py: Added rl_trading command - rdagent/components/backtesting/backtest_engine.py: RL backtest support - rdagent/components/coder/rl/costeer.py: Protection Manager integration - rdagent/components/coder/rl/__init__.py: Conditional imports + fallback - rdagent/components/coder/rl/fallback.py: NEW - Simple momentum fallback - requirements.txt: Optional RL deps commented - requirements/rl.txt: NEW - Full RL dependencies - test/integration/test_all_features.py: 7 new integration tests - QWEN.md: Open source strategy + development guidelines - README.md: RL Trading documentation 295 tests pass: 67 integration + 89 RL + 139 backtesting
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TPTBusiness
@@ -158,7 +158,7 @@ class RLCoSTEER(CoSTEER):
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class RLCosteer:
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"""
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RL-based trading controller.
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RL-based trading controller with protection manager integration.
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Takes market data, technical indicators, and portfolio state,
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then uses a trained RL model to decide position sizing.
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@@ -175,6 +175,8 @@ class RLCosteer:
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Maximum position size (0 to 1)
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risk_limit : float
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Maximum drawdown before forcing position close
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enable_protections : bool
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Enable trading protection manager (default: True)
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Examples
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--------
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@@ -190,12 +192,14 @@ class RLCosteer:
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window_size: int = 60,
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max_position: float = 1.0,
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risk_limit: float = 0.15,
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enable_protections: bool = True,
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) -> None:
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self.model_path = model_path
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self.algorithm = algorithm.upper()
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self.window_size = window_size
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self.max_position = max_position
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self.risk_limit = risk_limit
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self.enable_protections = enable_protections
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# State
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self.is_active = False
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@@ -203,12 +207,32 @@ class RLCosteer:
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self.current_position: float = 0.0
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self.peak_equity: float = 0.0
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self.trade_history: List[Dict[str, Any]] = []
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self.equity_history: List[float] = []
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# Protection Manager
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self.protection_manager: Optional[Any] = None
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if enable_protections:
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try:
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from rdagent.components.backtesting.protections.protection_manager import (
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ProtectionManager,
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)
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self.protection_manager = ProtectionManager()
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self.protection_manager.create_default_protections()
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except ImportError:
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import warnings
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warnings.warn(
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"Protection manager not available. Trading protections disabled."
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)
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self.protection_manager = None
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# Market data (set during initialize)
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self.prices: np.ndarray = np.array([])
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self.indicators: Optional[np.ndarray] = None
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self.initial_equity: float = 0.0
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self.current_step: int = 0
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self.timestamps_history: List[datetime] = []
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# Load model if path provided
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if model_path is not None and model_path.exists():
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@@ -243,9 +267,11 @@ class RLCosteer:
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current_equity: float,
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cash: float,
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position: float,
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returns_history: Optional[List[float]] = None,
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timestamps: Optional[List[datetime]] = None,
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) -> float:
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"""
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Get trading action from RL model.
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Get trading action from RL model with protection checks.
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Parameters
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----------
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@@ -255,21 +281,47 @@ class RLCosteer:
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Available cash
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position : float
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Current position size
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returns_history : list, optional
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Historical returns for protection checks
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timestamps : list, optional
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Historical timestamps for protection checks
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Returns
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-------
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float
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Target position (-1 to 1)
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"""
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if not self.is_active or self.model is None:
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return 0.0 # Hold if not active
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# Check protections first (if enabled and available)
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if self.protection_manager and returns_history and len(returns_history) > 0:
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peak_equity = max(self.equity_history + [current_equity]) if self.equity_history else current_equity
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# Build observation
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protection_result = self.protection_manager.check_all(
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returns=returns_history,
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timestamps=timestamps or self.timestamps_history[-len(returns_history):] if timestamps is None else [],
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current_equity=current_equity,
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peak_equity=peak_equity,
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)
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if protection_result.should_block:
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# Protection triggered - force close position
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return 0.0
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# If not active or no model, hold
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if not self.is_active or self.model is None:
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return 0.0
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# Build observation for RL model
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observation = self._build_observation(current_equity, cash, position)
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# Get action from model
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prediction = self.model.predict(observation)
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target_position = float(np.asarray(prediction[0]).flatten()[0])
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try:
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prediction = self.model.predict(observation)
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target_position = float(np.asarray(prediction[0]).flatten()[0])
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except Exception as e:
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import warnings
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warnings.warn(f"RL model prediction failed: {e}. Returning hold.")
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return 0.0
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# Apply risk limits
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drawdown = (self.peak_equity - current_equity) / self.peak_equity if self.peak_equity > 0 else 0.0
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@@ -356,6 +408,8 @@ class RLCosteer:
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current_equity: float,
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cash: float,
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position: float,
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returns_history: Optional[List[float]] = None,
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timestamps: Optional[List[datetime]] = None,
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) -> Dict[str, Any]:
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"""
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Execute one trading step.
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@@ -368,14 +422,24 @@ class RLCosteer:
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Available cash
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position : float
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Current position size
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returns_history : list, optional
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Historical returns for protection checks
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timestamps : list, optional
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Historical timestamps for protection checks
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Returns
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-------
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dict
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Step information including action taken
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"""
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# Get action
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target_position = self.get_action(current_equity, cash, position)
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# Get action with protections
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target_position = self.get_action(
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current_equity=current_equity,
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cash=cash,
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position=position,
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returns_history=returns_history,
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timestamps=timestamps,
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)
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# Record trade
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trade = {
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@@ -388,6 +452,13 @@ class RLCosteer:
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}
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self.trade_history.append(trade)
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# Track equity and timestamps
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self.equity_history.append(current_equity)
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if timestamps:
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self.timestamps_history.extend(timestamps)
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else:
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self.timestamps_history.append(datetime.now())
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# Update peak equity
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if current_equity > self.peak_equity:
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self.peak_equity = current_equity
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