refactor: Sprint 3 - 引入 UnitOfWork + Repository 架构

新增:
- src/db/unit_of_work.py: UnitOfWork 事务封装
- src/db/repositories.py: Match/Team/League/Prediction Repository

重构:
- 删除 src/data/match_lookup.py(由 Repository 替代)
- 数据源(bzzoiro/understat/injuries)不再自行 commit
- API 路由(ingest)改用 UnitOfWork
- LLM 服务(predict/orchestrator/eval/backtest)改用 UnitOfWork

事务边界统一由调用方控制,数据层不再自行决定 commit。

src/llm/eval.py

@@ -5,23 +5,22 @@ import logging
 
 from sqlalchemy import select
 
-from src.db.base import AsyncSessionLocal
 from src.db.models import Prediction
+from src.db.unit_of_work import get_uow
 
 logger = logging.getLogger(__name__)
 
 
 async def settle_prediction(prediction_id: int, home_goals: int, away_goals: int) -> Prediction:
     """回填实际结果。"""
-    async with AsyncSessionLocal() as db:
-        pred = await db.get(Prediction, prediction_id)
+    async with get_uow() as uow:
+        pred = await uow.session.get(Prediction, prediction_id)
         if pred is None:
             raise ValueError(f"prediction {prediction_id} not found")
         pred.actual_home_goals = home_goals
         pred.actual_away_goals = away_goals
         pred.settled = True
-        await db.commit()
-        await db.refresh(pred)
+        await uow.commit()
         return pred
 
 
@@ -36,12 +35,12 @@ def _actual_1x2(home: int, away: int) -> str:
 
 async def get_eval_summary() -> dict:
     """按 provider × 模型聚合评估。"""
-    async with AsyncSessionLocal() as db:
+    async with get_uow() as uow:
         stmt = (
             select(Prediction)
             .where(Prediction.settled == True)
         )
-        result = await db.execute(stmt)
+        result = await uow.session.execute(stmt)
         rows = list(result.scalars().all())
 
         from collections import defaultdict
@@ -76,6 +75,6 @@ async def get_eval_summary() -> dict:
                 "total": b["total"],
                 "accuracy_1x2": round(acc, 1),
                 "avg_score_rmse": round(avg_err, 2) if avg_err is not None else None,
-                "avg_confidence": round(avg_conf, 2) if avg_conf is not None else None,
+                "avg_subjective_confidence": round(avg_conf, 2) if avg_conf is not None else None,
             })
         return {"summary": summary}