Add FastAPI backend for energy trading system

Implements FastAPI backend with ML model support for energy trading,
including price prediction models and RL-based battery trading policy.
Features dashboard, trading, backtest, and settings API routes with
WebSocket support for real-time updates.

backend/app/ml/utils/config.py

@@ -0,0 +1,16 @@
+from dataclasses import dataclass
+from typing import List, Dict, Any
+
+
+@dataclass
+class MLConfig:
+    enable_gpu: bool = False
+    n_jobs: int = 4
+    verbose: bool = True
+
+    @classmethod
+    def from_dict(cls, config_dict: Dict[str, Any]) -> "MLConfig":
+        return cls(**{k: v for k, v in config_dict.items() if k in cls.__annotations__})
+
+
+__all__ = ["MLConfig"]