fix(dashboard): trends per-company lines instead of meaningless average

backend/app/routers/dashboard.py

@@ -166,50 +166,52 @@ async def get_health_heatmap(
 
 @router.get("/trends", response_model=ApiResponse[list[dict]])
 async def get_health_trends(
-    company_id: str | None = Query(default=None, description="指定企业 ID，不传则汇总"),
+    company_id: str | None = Query(default=None, description="指定企业 ID，不传则返回全部企业"),
     months: int = Query(default=6, ge=1, le=24, description="趋势月数"),
     db: AsyncSession = Depends(get_db),
     user: User = Depends(get_current_user),
 ):
-    """获取健康度趋势对比数据 — 按月汇总评分变化。
+    """获取健康度趋势数据 — 按企业分组，每家企业一条折线。
 
-    返回格式：[{ period, avg_score, company_count, dimension_avgs: { dimension: avg } }]
+    返回格式：[{ company_id, company_name, data: [{ period, score }] }]
     """
     query = (
-        select(HealthScore)
+        select(HealthScore, Company.name.label("company_name"))
         .join(Company, HealthScore.company_id == Company.id)
         .where(Company.tenant_id == user.tenant_id)
     )
     if company_id:
         query = query.where(HealthScore.company_id == company_id)
 
-    query = query.order_by(HealthScore.calculated_at.desc()).limit(months * 50)
+    query = query.order_by(HealthScore.calculated_at.asc()).limit(months * 100)
     result = await db.execute(query)
-    scores = result.scalars().all()
 
-    # 按月分组
-    monthly: dict[str, list[HealthScore]] = {}
-    for s in scores:
-        period = s.calculated_at.strftime("%Y-%m")
-        monthly.setdefault(period, []).append(s)
+    # 按企业分组
+    by_company: dict[str, dict[str, list]] = {}
+    for row in result.all():
+        score = row[0]
+        cname = row[1]
+        cid = str(score.company_id)
+        if cid not in by_company:
+            by_company[cid] = {"company_name": cname, "scores": []}
+        by_company[cid]["scores"].append(score)
 
     trends = []
-    for period in sorted(monthly.keys()):
-        month_scores = monthly[period]
-        count = len(month_scores)
-        avg_total = sum(s.total_score for s in month_scores) / count if count else 0
-
-        dim_avgs = {}
-        for dim_key in _DIMENSION_KEYS:
-            vals = [getattr(s, dim_key) for s in month_scores if getattr(s, dim_key) is not None]
-            if vals:
-                dim_avgs[dim_key] = round(sum(vals) / len(vals), 1)
+    for cid, info in by_company.items():
+        # 每月取最新一条
+        monthly: dict[str, float] = {}
+        for s in info["scores"]:
+            period = s.calculated_at.strftime("%Y-%m")
+            monthly[period] = s.total_score
 
+        data_points = [
+            {"period": p, "score": round(v, 1)}
+            for p, v in sorted(monthly.items())
+        ]
         trends.append({
-            "period": period,
-            "avg_score": round(avg_total, 1),
-            "company_count": count,
-            "dimension_avgs": dim_avgs,
+            "company_id": cid,
+            "company_name": info["company_name"],
+            "data": data_points,
         })
 
     return success(data=trends)