feat/ 导出开发容器内的数据用于评估

api/app/features/evaluation/gating_service.py

@@ -0,0 +1,92 @@
+"""平台门禁：均分提升 + 受保护 session 无明显退步。"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Any
+
+from app.core.config import settings
+from app.features.evaluation.models import EvalCase, EvalRun
+
+
+@dataclass
+class GateResult:
+    passed: bool
+    mean_baseline_composite: float
+    mean_candidate_composite: float
+    mean_delta: float
+    protected_regressions: list[dict[str, Any]]
+    per_case: list[dict[str, Any]]
+
+
+def compute_gate(
+    *,
+    cases: list[EvalCase],
+    runs: list[EvalRun],
+    regression_threshold: float | None = None,
+) -> GateResult:
+    thr = (
+        regression_threshold
+        if regression_threshold is not None
+        else settings.eval_gate_protected_regression_threshold
+    )
+    by_case: dict[str, dict[str, EvalRun]] = {}
+    for r in runs:
+        if r.status != "completed":
+            continue
+        by_case.setdefault(r.case_id, {})[r.side] = r
+
+    per_case: list[dict[str, Any]] = []
+    base_scores: list[float] = []
+    cand_scores: list[float] = []
+    protected_regs: list[dict[str, Any]] = []
+
+    case_map = {c.id: c for c in cases}
+    for cid, sides in by_case.items():
+        b = sides.get("baseline")
+        c_run = sides.get("candidate")
+        if not b or not c_run:
+            continue
+        if b.composite_score is None or c_run.composite_score is None:
+            continue
+        bs = float(b.composite_score)
+        cs = float(c_run.composite_score)
+        delta = cs - bs
+        base_scores.append(bs)
+        cand_scores.append(cs)
+        ec = case_map.get(cid)
+        protected = bool(ec and ec.is_protected)
+        row = {
+            "case_id": cid,
+            "title": ec.title if ec else None,
+            "baseline_composite": bs,
+            "candidate_composite": cs,
+            "delta": delta,
+            "protected": protected,
+        }
+        per_case.append(row)
+        if protected and delta < -thr:
+            protected_regs.append(
+                {
+                    "case_id": cid,
+                    "title": ec.title if ec else None,
+                    "delta": delta,
+                    "threshold": thr,
+                }
+            )
+
+    mean_b = sum(base_scores) / len(base_scores) if base_scores else 0.0
+    mean_c = sum(cand_scores) / len(cand_scores) if cand_scores else 0.0
+    mean_delta = mean_c - mean_b
+    passed = (
+        mean_c > mean_b + 1e-6 and len(protected_regs) == 0 and len(base_scores) > 0
+    )
+
+    return GateResult(
+        passed=passed,
+        mean_baseline_composite=mean_b,
+        mean_candidate_composite=mean_c,
+        mean_delta=mean_delta,
+        protected_regressions=protected_regs,
+        per_case=per_case,
+    )