feat(core/backend): pipeline continuity + threaded ffmpeg burn-in export + upload/save-timeline

Video pipeline (script→assets→storyboard→video→stitch):
- robust split_script_into_segments (4 non-empty scenes), scene-aware storyboard/video prompts
- link VideoSegment→ScriptSegment + storyboard-frame reference image (graceful text fallback)
- idempotent poll_video_segment (no double-charge on repeated polling)
- threaded export (no Celery worker needed) + poll-export endpoint
- run_export_job rewritten to filter_complex: per-clip trim, xfade transitions,
  subtitle burn-in (Pillow PNG overlay; this ffmpeg lacks libass), BGM mix
- upload-video-segment / upload-bgm / save-timeline endpoints
- serializers embed asset preview URLs (beat assets pagination); Pillow added to requirements

Also includes prior uncommitted backend work: account preferences/sessions,
billing trend, product/asset endpoints, accounts 0002 migration.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

core/backend/apps/billing/urls.py

@@ -1,9 +1,10 @@
 from django.urls import path
 
-from .views import ledgers, recharge, summary
+from .views import ledgers, recharge, summary, trend
 
 urlpatterns = [
     path("summary/", summary, name="billing-summary"),
     path("ledgers/", ledgers, name="billing-ledgers"),
     path("recharge/", recharge, name="billing-recharge"),
+    path("trend/", trend, name="billing-trend"),
 ]

core/backend/apps/billing/views.py

@@ -1,17 +1,33 @@
+from datetime import timedelta
 from decimal import Decimal, InvalidOperation
 
 from django.db import transaction
 from django.db.models import Sum
+from django.db.models.functions import TruncDate
+from django.utils import timezone
 from rest_framework import status
 from rest_framework.decorators import api_view, permission_classes
 from rest_framework.permissions import IsAuthenticated
 from rest_framework.response import Response
 
+from apps.ai.models import AITask
 from apps.common.api import get_current_team
 
 from .models import CreditAccount, CreditLedger
 from .serializers import CreditAccountSerializer, CreditLedgerSerializer
 
+# AITask.task_type → 账户页「按阶段分布」的 4 个聚合桶
+_STAGE_BUCKET = {
+    AITask.Type.SCRIPT_GENERATION: "script",
+    AITask.Type.SCRIPT_OPTIMIZATION: "script",
+    AITask.Type.PRODUCT_IMAGE: "base",
+    AITask.Type.PERSON_IMAGE: "base",
+    AITask.Type.SCENE_IMAGE: "base",
+    AITask.Type.STORYBOARD: "storyboard",
+    AITask.Type.VIDEO_SEGMENT: "video",
+    AITask.Type.EXPORT: "video",
+}
+
 
 @api_view(["GET"])
 @permission_classes([IsAuthenticated])
@@ -78,3 +94,81 @@ def recharge(request):
         },
         status=status.HTTP_201_CREATED,
     )
+
+
+@api_view(["GET"])
+@permission_classes([IsAuthenticated])
+def trend(request):
+    """账户页消费分析:消费趋势(日/周/月可切)+ 本月按阶段/按项目分布。全部来自真实 CHARGE 流水。"""
+    team = get_current_team(request.user)
+    today = timezone.localdate()
+    rng = request.query_params.get("range", "day")
+    charges = CreditLedger.objects.filter(team=team, ledger_type=CreditLedger.Type.CHARGE)
+
+    def _daily_amounts(win_start):
+        rows = (
+            charges.filter(created_at__date__gte=win_start)
+            .annotate(day=TruncDate("created_at"))
+            .values("day")
+            .annotate(amount=Sum("amount"))
+        )
+        return {row["day"]: row["amount"] or Decimal("0") for row in rows}
+
+    # 按 range 选窗口与分桶:日=近 14 天 / 周=近 8 周 / 月=近 6 个自然月(缺口补 0)
+    series = []
+    if rng == "week":
+        monday = today - timedelta(days=today.weekday())
+        starts = [monday - timedelta(weeks=(7 - i)) for i in range(8)]
+        amt_by_day = _daily_amounts(starts[0])
+        for s in starts:
+            total = sum((amt_by_day.get(s + timedelta(days=k), Decimal("0")) for k in range(7)), Decimal("0"))
+            series.append({"date": s.isoformat(), "label": s.strftime("%m/%d"), "amount": str(total)})
+    elif rng == "month":
+        seq = []
+        y, m = today.year, today.month
+        for _ in range(6):
+            seq.append((y, m))
+            m -= 1
+            if m == 0:
+                m, y = 12, y - 1
+        seq.reverse()
+        amt_by_day = _daily_amounts(today.replace(year=seq[0][0], month=seq[0][1], day=1))
+        for yy, mm in seq:
+            total = sum((v for d, v in amt_by_day.items() if d.year == yy and d.month == mm), Decimal("0"))
+            series.append({"date": f"{yy}-{mm:02d}-01", "label": f"{mm}月", "amount": str(total)})
+    else:
+        start = today - timedelta(days=13)
+        amt_by_day = _daily_amounts(start)
+        for i in range(14):
+            d = start + timedelta(days=i)
+            series.append({"date": d.isoformat(), "label": d.strftime("%m/%d"), "amount": str(amt_by_day.get(d, Decimal("0")))})
+
+    daily = series
+    total_14d = sum((Decimal(s["amount"]) for s in series), Decimal("0"))
+    peak = max((Decimal(s["amount"]) for s in series), default=Decimal("0"))
+    avg = (total_14d / len(series)).quantize(Decimal("0.0001")) if series else Decimal("0")
+
+    # 本月按阶段分布(task.task_type → 4 桶)
+    month_start = today.replace(day=1)
+    month_charges = charges.filter(created_at__date__gte=month_start).select_related("task")
+    by_stage = {"script": Decimal("0"), "base": Decimal("0"), "storyboard": Decimal("0"), "video": Decimal("0")}
+    project_amounts: dict[str, Decimal] = {}
+    for row in month_charges:
+        task = row.task
+        bucket = _STAGE_BUCKET.get(task.task_type) if task else None
+        if bucket:
+            by_stage[bucket] += row.amount
+        pid = str(row.project_id) if row.project_id else None
+        if pid:
+            project_amounts[pid] = project_amounts.get(pid, Decimal("0")) + row.amount
+
+    return Response(
+        {
+            "daily": daily,
+            "total_14d": str(total_14d),
+            "avg": str(avg),
+            "peak": str(peak),
+            "by_stage": {k: str(v) for k, v in by_stage.items()},
+            "by_project": {k: str(v) for k, v in project_amounts.items()},
+        }
+    )