feat(api): 新增 trends 和 feedback 統計端點

- /stats/incidents/trends: 每日/週/月趨勢分析
- /stats/feedback/summary: 人類回饋摘要 (正/中/負比例 + 常見主題萃取)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

apps/api/src/api/v1/stats.py

@@ -383,3 +383,131 @@ async def get_affected_services(
         )
         for svc, stats in sorted_services
     ]
+
+
+@router.get(
+    "/incidents/trends",
+    response_model=IncidentTrends,
+    summary="事件趨勢分析",
+)
+async def get_incident_trends(
+    days: int = Query(30, ge=7, le=365, description="統計區間 (天)"),
+    period: str = Query("daily", description="週期: daily/weekly/monthly"),
+    db: AsyncSession = Depends(get_db),  # noqa: B008
+) -> IncidentTrends:
+    """
+    取得事件趨勢數據
+
+    支援週期:
+    - daily: 每日事件數
+    - weekly: 每週事件數
+    - monthly: 每月事件數
+    """
+    since = datetime.utcnow() - timedelta(days=days)
+
+    # 取得所有事件的建立時間
+    result = await db.execute(
+        select(IncidentRecord.created_at).where(
+            IncidentRecord.created_at >= since
+        )
+    )
+    timestamps = [row[0] for row in result.all()]
+
+    # 依週期聚合
+    counts: dict[str, int] = {}
+    for ts in timestamps:
+        if period == "daily":
+            key = ts.strftime("%Y-%m-%d")
+        elif period == "weekly":
+            # ISO 週數
+            key = ts.strftime("%Y-W%W")
+        else:  # monthly
+            key = ts.strftime("%Y-%m")
+        counts[key] = counts.get(key, 0) + 1
+
+    # 排序並轉換為 TrendPoint
+    sorted_data = sorted(counts.items(), key=lambda x: x[0])
+    trend_data = [TrendPoint(date=k, count=v) for k, v in sorted_data]
+
+    logger.info(
+        "stats_incident_trends",
+        period=period,
+        days=days,
+        data_points=len(trend_data),
+    )
+
+    return IncidentTrends(period=period, data=trend_data)
+
+
+@router.get(
+    "/feedback/summary",
+    response_model=FeedbackSummary,
+    summary="人類回饋摘要",
+)
+async def get_feedback_summary(
+    days: int = Query(30, ge=1, le=365, description="統計區間 (天)"),
+    db: AsyncSession = Depends(get_db),  # noqa: B008
+) -> FeedbackSummary:
+    """
+    取得人類回饋統計
+
+    從 Incident outcome 中萃取:
+    - 正面/中性/負面回饋比例
+    - 常見主題 (從 learning_notes 萃取)
+    """
+    since = datetime.utcnow() - timedelta(days=days)
+
+    # 取得有 outcome 的事件
+    result = await db.execute(
+        select(IncidentRecord.outcome).where(
+            IncidentRecord.created_at >= since,
+            IncidentRecord.outcome.isnot(None),
+        )
+    )
+    outcomes = [row[0] for row in result.all() if row[0]]
+
+    # 統計回饋分數
+    positive = 0
+    neutral = 0
+    negative = 0
+    themes: dict[str, int] = {}
+
+    for o in outcomes:
+        score = o.get("effectiveness_score") or o.get("feedback_score")
+        if score:
+            if score >= 4:
+                positive += 1
+            elif score == 3:
+                neutral += 1
+            else:
+                negative += 1
+
+        # 萃取主題 (從 learning_notes)
+        notes = o.get("learning_notes") or o.get("notes") or ""
+        if notes:
+            # 簡單關鍵字萃取 (未來可用 NLP)
+            for keyword in ["timeout", "memory", "network", "disk", "cpu", "connection"]:
+                if keyword.lower() in notes.lower():
+                    themes[keyword] = themes.get(keyword, 0) + 1
+
+    # 取前 5 個常見主題
+    sorted_themes = sorted(themes.items(), key=lambda x: x[1], reverse=True)[:5]
+    common_themes = [t[0] for t in sorted_themes]
+
+    total = positive + neutral + negative
+
+    logger.info(
+        "stats_feedback_summary",
+        total=total,
+        positive=positive,
+        negative=negative,
+        days=days,
+    )
+
+    return FeedbackSummary(
+        total_feedback=total,
+        positive_count=positive,
+        neutral_count=neutral,
+        negative_count=negative,
+        common_themes=common_themes,
+    )