Initial commit: CI Agent competitive-intelligence monitoring app

FastAPI + Celery + Next.js + Postgres/Redis app with company monitoring,
source collection, LLM-based change analysis, enrichment, and account
security (Turnstile, escalating lockout, email verification).

apps/api/app/services/analytics_service.py

@@ -0,0 +1,105 @@
+"""Dashboard analytics: aggregate counts across every company a user owns,
+scoped by joining through Company.user_id (none of the source tables carry
+user_id directly except Alert). Every bucketed dict is pre-seeded with every
+enum member at 0 so the frontend never has to guess which keys might be
+missing.
+"""
+
+from __future__ import annotations
+
+import uuid
+from datetime import UTC, datetime, timedelta
+
+from sqlalchemy import func, select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.models.alert import Alert
+from app.models.company import Company
+from app.models.detected_change import DetectedChange
+from app.models.enums import ChangeType, MonitoringRunStatus, SeverityLevel, SourceStatus
+from app.models.monitoring_run import MonitoringRun
+from app.models.source import Source
+from app.schemas.dashboard import DashboardAnalytics, RecentSignal, RunsByDayPoint
+
+
+async def get_dashboard_analytics(
+    db: AsyncSession, user_id: uuid.UUID, *, days: int = 30, recent_limit: int = 10
+) -> DashboardAnalytics:
+    since = datetime.now(UTC) - timedelta(days=days)
+
+    changes_by_type = {ct.value: 0 for ct in ChangeType}
+    changes_result = await db.execute(
+        select(DetectedChange.change_type, func.count())
+        .join(Company, DetectedChange.company_id == Company.id)
+        .where(Company.user_id == user_id, DetectedChange.created_at >= since)
+        .group_by(DetectedChange.change_type)
+    )
+    for change_type, count in changes_result.all():
+        changes_by_type[change_type.value] = count
+
+    alerts_by_severity = {s.value: 0 for s in SeverityLevel}
+    alerts_result = await db.execute(
+        select(Alert.severity, func.count())
+        .where(Alert.user_id == user_id, Alert.created_at >= since)
+        .group_by(Alert.severity)
+    )
+    for severity, count in alerts_result.all():
+        alerts_by_severity[severity.value] = count
+
+    sources_by_status = {s.value: 0 for s in SourceStatus}
+    sources_result = await db.execute(
+        select(Source.status, func.count())
+        .join(Company, Source.company_id == Company.id)
+        .where(Company.user_id == user_id)
+        .group_by(Source.status)
+    )
+    for source_status, count in sources_result.all():
+        sources_by_status[source_status.value] = count
+
+    runs_result = await db.execute(
+        select(MonitoringRun.created_at, MonitoringRun.status)
+        .join(Company, MonitoringRun.company_id == Company.id)
+        .where(Company.user_id == user_id, MonitoringRun.created_at >= since)
+    )
+    day_buckets: dict[str, dict[str, int]] = {}
+    for created_at, run_status in runs_result.all():
+        day = created_at.date().isoformat()
+        bucket = day_buckets.setdefault(day, {"successful": 0, "failed": 0, "other": 0})
+        if run_status == MonitoringRunStatus.SUCCESSFUL:
+            bucket["successful"] += 1
+        elif run_status == MonitoringRunStatus.FAILED:
+            bucket["failed"] += 1
+        else:
+            bucket["other"] += 1
+    runs_by_day = [
+        RunsByDayPoint(date=day, **counts) for day, counts in sorted(day_buckets.items())
+    ]
+
+    signals_result = await db.execute(
+        select(DetectedChange, Company.name)
+        .join(Company, DetectedChange.company_id == Company.id)
+        .where(Company.user_id == user_id)
+        .order_by(DetectedChange.created_at.desc())
+        .limit(recent_limit)
+    )
+    recent_signals = [
+        RecentSignal(
+            id=change.id,
+            company_id=change.company_id,
+            company_name=company_name,
+            change_type=change.change_type.value,
+            severity=change.severity.value,
+            confidence_score=change.confidence_score,
+            summary=change.summary,
+            created_at=change.created_at,
+        )
+        for change, company_name in signals_result.all()
+    ]
+
+    return DashboardAnalytics(
+        changes_by_type=changes_by_type,
+        alerts_by_severity=alerts_by_severity,
+        sources_by_status=sources_by_status,
+        runs_by_day=runs_by_day,
+        recent_signals=recent_signals,
+    )