feat: Integrated Dashboard v2.0 with LLM-driven Mock Backend

- Promoted prototype dashboard to main app
- Added /api/market-data endpoint
- Implemented market_simulator.py for realistic OHLCV generation
- Updated MoomooClient to serve simulated scenarios
- Wired frontend to backend API

data/connectors/moomoo_client.py

@@ -265,7 +265,27 @@ class MoomooClient(DataConnector):
             interval = params.get("interval", "1d") if params else "1d"
             limit = params.get("limit", 100) if params else 100
             
-            # Generate mock OHLCV data
+            # Try to load LLM-generated scenario first
+            scenario_file = f"data/mock_scenarios/{symbol}_rally.json"
+            try:
+                import os
+                if os.path.exists(scenario_file):
+                    with open(scenario_file, 'r') as f:
+                        data = json.load(f)
+                        # Filter/slice data if needed
+                        return {
+                            "code": 0,
+                            "msg": "success",
+                            "data": {
+                                "symbol": symbol,
+                                "interval": interval,
+                                "list": data[:limit]
+                            }
+                        }
+            except Exception as e:
+                logger.warning(f"Failed to load mock scenario: {e}")
+
+            # Fallback to algorithmic generation
             data = []
             base_price = random.uniform(100, 200)
             for i in range(limit):