fix:批量修复了一些问题

src/llm/baseline.py

@@ -0,0 +1,113 @@
+"""极简基线预测:主客场场均进球估计(不调用 LLM,不产生费用)。
+
+用于与 LLM 预测做 eval 对比。这是最简单的统计基线,仅供研究参考,
+文档与 reasoning 均明确标注「非投注建议」。
+"""
+from __future__ import annotations
+
+import logging
+from datetime import datetime
+
+from sqlalchemy import case, func, select
+
+from src.db.base import AsyncSession, AsyncSessionLocal
+from src.db.models import Match
+
+logger = logging.getLogger(__name__)
+
+
+async def _avg_goals(
+    db: AsyncSession,
+    *,
+    team_id: int,
+    side: str,
+    league_id: int,
+    before: datetime | None,
+) -> float:
+    """某队在该联赛已完赛场次的场均进球(side=home/away)。"""
+    if side == "home":
+        goals_col = Match.home_goals
+        team_col = Match.home_team_id
+    else:
+        goals_col = Match.away_goals
+        team_col = Match.away_team_id
+
+    stmt = (
+        select(func.avg(goals_col).label("avg_goals"), func.count().label("cnt"))
+        .where(
+            Match.match_status == "finished",
+            team_col == team_id,
+            Match.league_id == league_id,
+            goals_col.is_not(None),
+        )
+    )
+    if before is not None:
+        stmt = stmt.where(Match.match_date < before)
+    row = (await db.execute(stmt)).one()
+    return float(row.avg_goals) if row.avg_goals is not None and row.cnt > 0 else 0.0
+
+
+async def predict_baseline(
+    match_id: int,
+    *,
+    backtest: bool = False,
+    cutoff_at: datetime | None = None,
+) -> dict:
+    """极简基线预测:主场场均进球 vs 客场场均进球。
+
+    返回与 PredictResult 兼容的字典:
+      provider=model="baseline", 不调用 LLM,latency_ms≈0。
+    """
+    async with AsyncSessionLocal() as db:
+        match = await db.get(Match, match_id)
+        if match is None:
+            raise ValueError(f"match {match_id} not found")
+
+        before = None
+        if backtest and match.match_dt:
+            from datetime import timedelta
+
+            before = match.match_dt - timedelta(days=1)
+        elif cutoff_at is not None:
+            before = cutoff_at
+
+        home_avg = await _avg_goals(
+            db, team_id=match.home_team_id, side="home",
+            league_id=match.league_id, before=before,
+        )
+        away_avg = await _avg_goals(
+            db, team_id=match.away_team_id, side="away",
+            league_id=match.league_id, before=before,
+        )
+
+    pred_home = max(0, min(10, round(home_avg)))
+    pred_away = max(0, min(10, round(away_avg)))
+    # 主场轻微加成(可选,这里保持极简不额外加权)
+    if pred_home > pred_away:
+        pred_1x2 = "1"
+    elif pred_home < pred_away:
+        pred_1x2 = "2"
+    else:
+        pred_1x2 = "X"
+
+    return {
+        "pred_home_goals": float(pred_home),
+        "pred_away_goals": float(pred_away),
+        "alt_pred_home_goals": None,
+        "alt_pred_away_goals": None,
+        "pred_1x2": pred_1x2,
+        "subjective_confidence": 0.5,
+        "prompt_tokens": 0,
+        "completion_tokens": 0,
+        "reasoning": (
+            f"基线估计(非投注建议): 主队主场场均进球 {home_avg:.2f} → 预测 {pred_home}; "
+            f"客队客场场均进球 {away_avg:.2f} → 预测 {pred_away}。"
+        ),
+        "provider": "baseline",
+        "model": "baseline",
+        "prompt_version": "baseline_v1",
+        "mode": "baseline",
+        "status": "success",
+        "latency_ms": 0,
+        "raw": {"home_avg": round(home_avg, 2), "away_avg": round(away_avg, 2)},
+    }