feat: Enhance project and scenario creation with monitoring metrics

- Added monitoring metrics for project creation success and error handling in `ProjectRepository`.
- Implemented similar monitoring for scenario creation in `ScenarioRepository`.
- Refactored `run_monte_carlo` function in `simulation.py` to include timing and success/error metrics.
- Introduced new CSS styles for headers, alerts, and navigation buttons in `main.css` and `projects.css`.
- Created a new JavaScript file for navigation logic to handle chevron buttons.
- Updated HTML templates to include new navigation buttons and improved styling for buttons.
- Added tests for reporting service and routes to ensure proper functionality and access control.
- Removed unused imports and optimized existing test files for better clarity and performance.

monitoring/__init__.py

@@ -1,7 +1,14 @@
 from __future__ import annotations
 
-from fastapi import APIRouter, Response
+from datetime import datetime, timedelta
+from typing import Optional
+
+from fastapi import APIRouter, Depends, HTTPException, Query, Response
 from prometheus_client import CONTENT_TYPE_LATEST, generate_latest
+from sqlalchemy.orm import Session
+
+from config.database import get_db
+from services.metrics import MetricsService
 
 
 router = APIRouter(prefix="/metrics", tags=["monitoring"])
@@ -11,3 +18,99 @@ router = APIRouter(prefix="/metrics", tags=["monitoring"])
 async def metrics_endpoint() -> Response:
     payload = generate_latest()
     return Response(content=payload, media_type=CONTENT_TYPE_LATEST)
+
+
+@router.get("/performance", summary="Get performance metrics")
+async def get_performance_metrics(
+    metric_name: Optional[str] = Query(
+        None, description="Filter by metric name"),
+    hours: int = Query(24, description="Hours back to look"),
+    db: Session = Depends(get_db),
+) -> dict:
+    """Get aggregated performance metrics."""
+    service = MetricsService(db)
+    start_time = datetime.utcnow() - timedelta(hours=hours)
+
+    if metric_name:
+        metrics = service.get_metrics(
+            metric_name=metric_name, start_time=start_time)
+        aggregated = service.get_aggregated_metrics(
+            metric_name, start_time=start_time)
+        return {
+            "metric_name": metric_name,
+            "period_hours": hours,
+            "aggregated": aggregated,
+            "recent_samples": [
+                {
+                    "timestamp": m.timestamp.isoformat(),
+                    "value": m.value,
+                    "labels": m.labels,
+                    "endpoint": m.endpoint,
+                    "method": m.method,
+                    "status_code": m.status_code,
+                    "duration_seconds": m.duration_seconds,
+                }
+                for m in metrics[:50]  # Last 50 samples
+            ],
+        }
+
+    # Return summary for all metrics
+    all_metrics = service.get_metrics(start_time=start_time, limit=1000)
+    metric_types = {}
+    for m in all_metrics:
+        if m.metric_name not in metric_types:
+            metric_types[m.metric_name] = []
+        metric_types[m.metric_name].append(m.value)
+
+    summary = {}
+    for name, values in metric_types.items():
+        summary[name] = {
+            "count": len(values),
+            "avg": sum(values) / len(values) if values else 0,
+            "min": min(values) if values else 0,
+            "max": max(values) if values else 0,
+        }
+
+    return {
+        "period_hours": hours,
+        "summary": summary,
+    }
+
+
+@router.get("/health", summary="Detailed health check with metrics")
+async def detailed_health(db: Session = Depends(get_db)) -> dict:
+    """Get detailed health status with recent metrics."""
+    service = MetricsService(db)
+    last_hour = datetime.utcnow() - timedelta(hours=1)
+
+    # Get request metrics from last hour
+    request_metrics = service.get_metrics(
+        metric_name="http_request", start_time=last_hour
+    )
+
+    if request_metrics:
+        durations = []
+        error_count = 0
+        for m in request_metrics:
+            if m.duration_seconds is not None:
+                durations.append(m.duration_seconds)
+            if m.status_code is not None and m.status_code >= 400:
+                error_count += 1
+        total_requests = len(request_metrics)
+
+        avg_duration = sum(durations) / len(durations) if durations else 0
+        error_rate = error_count / total_requests if total_requests > 0 else 0
+    else:
+        avg_duration = 0
+        error_rate = 0
+        total_requests = 0
+
+    return {
+        "status": "ok",
+        "timestamp": datetime.utcnow().isoformat(),
+        "metrics": {
+            "requests_last_hour": total_requests,
+            "avg_response_time_seconds": avg_duration,
+            "error_rate": error_rate,
+        },
+    }