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/api/websocket.py

@@ -0,0 +1,62 @@
+from fastapi import WebSocket
+from typing import List
+from app.utils.logger import get_logger
+
+logger = get_logger(__name__)
+
+
+class ConnectionManager:
+    def __init__(self):
+        self.active_connections: List[WebSocket] = []
+
+    async def connect(self, websocket: WebSocket):
+        await websocket.accept()
+        self.active_connections.append(websocket)
+        logger.info(f"WebSocket connected. Total connections: {len(self.active_connections)}")
+
+    def disconnect(self, websocket: WebSocket):
+        if websocket in self.active_connections:
+            self.active_connections.remove(websocket)
+            logger.info(f"WebSocket disconnected. Total connections: {len(self.active_connections)}")
+
+    async def broadcast(self, event_type: str, data: dict):
+        message = {"event_type": event_type, "data": data, "timestamp": None}
+        disconnected = []
+
+        for connection in self.active_connections:
+            try:
+                await connection.send_json(message)
+            except Exception:
+                disconnected.append(connection)
+
+        for conn in disconnected:
+            self.disconnect(conn)
+
+    async def broadcast_price_update(self, region: str, price_data: dict):
+        await self.broadcast("price_update", {"region": region, "price_data": price_data})
+
+    async def broadcast_battery_update(self, battery_id: str, battery_state: dict):
+        await self.broadcast("battery_update", {"battery_id": battery_id, "battery_state": battery_state})
+
+    async def broadcast_trade(self, trade: dict):
+        await self.broadcast("trade_executed", trade)
+
+    async def broadcast_alert(self, alert: dict):
+        await self.broadcast("alert_triggered", alert)
+
+    async def broadcast_backtest_progress(self, backtest_id: str, progress: float, status: str):
+        await self.broadcast(
+            "backtest_progress",
+            {"backtest_id": backtest_id, "progress": progress, "status": status},
+        )
+
+    async def broadcast_model_training_progress(
+        self, model_id: str, progress: float, epoch: int = None, metrics: dict = None
+    ):
+        await self.broadcast(
+            "model_training_progress",
+            {"model_id": model_id, "progress": progress, "epoch": epoch, "metrics": metrics},
+        )
+
+
+manager = ConnectionManager()