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/config.py

@@ -0,0 +1,48 @@
+from pydantic_settings import BaseSettings, SettingsConfigDict
+from pathlib import Path
+from typing import List, Union
+
+
+class Settings(BaseSettings):
+    APP_NAME: str = "Energy Trading API"
+    APP_VERSION: str = "1.0.0"
+    DEBUG: bool = True
+
+    HOST: str = "0.0.0.0"
+    PORT: int = 8000
+
+    DATA_PATH: str = "~/energy-test-data/data/processed"
+    DATA_PATH_RESOLVED: Path = Path(DATA_PATH).expanduser()
+
+    CORS_ORIGINS: Union[str, List[str]] = [
+        "http://localhost:3000",
+        "http://localhost:5173",
+    ]
+
+    WS_HEARTBEAT_INTERVAL: int = 30
+
+    CELERY_BROKER_URL: str = "redis://localhost:6379/0"
+    CELERY_RESULT_BACKEND: str = "redis://localhost:6379/0"
+
+    MODELS_PATH: str = "models"
+    RESULTS_PATH: str = "results"
+
+    BATTERY_MIN_RESERVE: float = 0.10
+    BATTERY_MAX_CHARGE: float = 0.90
+
+    ARBITRAGE_MIN_SPREAD: float = 5.0
+    MINING_MARGIN_THRESHOLD: float = 5.0
+
+    ML_PREDICTION_HORIZONS: List[int] = [1, 5, 15, 60]
+    ML_FEATURE_LAGS: List[int] = [1, 5, 10, 15, 30, 60]
+
+    model_config = SettingsConfigDict(env_file=".env", case_sensitive=True, env_ignore_empty=True)
+
+    @property
+    def cors_origins_list(self) -> List[str]:
+        if isinstance(self.CORS_ORIGINS, str):
+            return [origin.strip() for origin in self.CORS_ORIGINS.split(",")]
+        return self.CORS_ORIGINS if isinstance(self.CORS_ORIGINS, list) else []
+
+
+settings = Settings()