refactor(engine): extract build_run_summary pure seam

Single-run summary口径 (pass_rate / judged_pass_rate / avg_latency /
connectivity split) was inlined in run(), reachable only by driving a
whole async run, and report.py recomputed judged_pass_rate independently.
Extract build_run_summary — a pure function parallel to aggregate_runs
(cross-run) and combine_case_outcome (case-level). run() now collects
material and delegates; judged_pass_rate is stored in RunSummary so the
report reads it instead of recomputing.

backend/agenteval/evaluation/engine.py

@@ -15,6 +15,7 @@ from agenteval.channels.factory import ChannelFactory
 from agenteval.config import get_settings
 from agenteval.evaluation.judgement import CaseOutcome, RuleOutcome, combine_case_outcome
 from agenteval.evaluation.rules import RuleResult, get_rule
+from agenteval.evaluation.run_summary import build_run_summary
 from agenteval.model_gateway import ModelGateway
 from agenteval.models import (
     Case,
@@ -130,9 +131,7 @@ class EvalEngine:
 
         try:
             total_cases = len(self.scenario.cases)
-            passed_cases = 0
-            failed_cases = 0
-            case_outcomes: dict[str, dict[str, bool]] = {}
+            case_outcomes: dict[str, CaseOutcome] = {}
 
             for idx, case in enumerate(self.scenario.cases, start=1):
                 self._check_cancel()
@@ -151,11 +150,7 @@ class EvalEngine:
                         case,
                         progress_callback,
                     )
-                case_outcomes[case.id] = {"passed": outcome.passed, "connectivity": outcome.connectivity}
-                if outcome.passed:
-                    passed_cases += 1
-                else:
-                    failed_cases += 1
+                case_outcomes[case.id] = outcome
                 await self._emit(
                     progress_callback,
                     "case_end",
@@ -170,34 +165,18 @@ class EvalEngine:
                 )
 
             results = self.run_repo.get_results(run.id)
-            total_rules = len(results)
-            passed_rules = sum(1 for r in results if r.passed)
-
             turns = self.run_repo.get_turns(run.id)
-            latencies = [t.latency_ms for t in turns if t.latency_ms is not None]
-            avg_latency_ms = round(sum(latencies) / len(latencies), 1) if latencies else None
-
-            summary = {
-                "total_cases": total_cases,
-                "passed_cases": passed_cases,
-                "failed_cases": failed_cases,
-                "total_rules": total_rules,
-                "passed_rules": passed_rules,
-                # 通过率是用例级口径（CONTEXT.md）；规则级数字保留在 passed_rules/total_rules
-                "pass_rate": round(passed_cases / total_cases, 4) if total_cases else 0.0,
-                # 平均时延（毫秒），供活动周期报告的时延轴聚合；无回复轮不计入
-                "avg_latency_ms": avg_latency_ms,
-                # 逐用例权威判定（judgement.py 算一次），报告/对比/渲染层只读不重算
-                "case_outcomes": case_outcomes,
-            }
-            # Surface fatal case-level errors (e.g. dynamic generation failures)
-            # so the report / DB record shows *why* a run produced no results.
-            if self._case_errors:
-                summary["case_errors"] = self._case_errors
-            if self._resolved_models:
-                summary["model_configs"] = {
-                    purpose.value: config.snapshot() for purpose, config in self._resolved_models.items()
-                }
+            summary = build_run_summary(
+                case_outcomes=case_outcomes,
+                latencies=[t.latency_ms for t in turns if t.latency_ms is not None],
+                rule_passes=[r.passed for r in results],
+                case_errors=self._case_errors or None,
+                model_configs=(
+                    {purpose.value: config.snapshot() for purpose, config in self._resolved_models.items()}
+                    if self._resolved_models
+                    else None
+                ),
+            )
             run.status = RunStatus.COMPLETED
             run.completed_at = utc_now()
             run.summary = summary
@@ -206,7 +185,7 @@ class EvalEngine:
                 "run_completed",
                 {
                     "status": "completed",
-                    "summary": summary,
+                    "summary": summary.model_dump(),
                 },
             )
         except CancelledError:

backend/agenteval/evaluation/report.py

@@ -103,8 +103,10 @@ def generate_report(run_id: str, session=None) -> dict[str, Any]:
     passed_cases = summary.passed_cases
     connectivity_count = sum(1 for c in cases if c["connectivity"])
     judged_total = total_cases - connectivity_count
-    # 连通用例按引擎口径计通过，判定型通过数 = 总通过数 - 连通用例数
-    judged_pass_rate = round((passed_cases - connectivity_count) / judged_total, 4) if judged_total > 0 else None
+    # 判定型通过率由 build_run_summary 入库，读路径只读；老 run 缺字段时按同一口径回退近似
+    judged_pass_rate = summary.judged_pass_rate
+    if judged_pass_rate is None and judged_total > 0:
+        judged_pass_rate = round((passed_cases - connectivity_count) / judged_total, 4)
 
     return {
         "run_id": run.id,

backend/agenteval/evaluation/run_summary.py

@@ -0,0 +1,53 @@
+"""Single-run summary aggregation — the pure落点 for one run's口径.
+
+Parallel to ``metrics.aggregate_runs`` (cross-run) and
+``judgement.combine_case_outcome`` (case-level): given the authoritative
+per-case outcomes plus raw latency/rule material, compute the run's
+summary口径 once. No IO — the engine collects material and calls this; DB
+writes and event emits stay in the caller. See CONTEXT.md (通过率) / ADR-0002.
+"""
+
+from typing import Any, Optional, Sequence
+
+from agenteval.evaluation.judgement import CaseOutcome
+from agenteval.models import CaseOutcomeSummary, RunSummary
+
+
+def build_run_summary(
+    *,
+    case_outcomes: dict[str, CaseOutcome],
+    latencies: Sequence[float],
+    rule_passes: Sequence[bool],
+    case_errors: Optional[list[dict[str, str]]] = None,
+    model_configs: Optional[dict[str, Any]] = None,
+) -> RunSummary:
+    """Compute a run's summary口径 from its authoritative case outcomes."""
+    total_cases = len(case_outcomes)
+    passed_cases = sum(1 for o in case_outcomes.values() if o.passed)
+    connectivity_count = sum(1 for o in case_outcomes.values() if o.connectivity)
+
+    pass_rate = round(passed_cases / total_cases, 4) if total_cases else 0.0
+    # 连通用例按引擎口径计通过，判定型通过数 = 总通过数 - 连通用例数
+    judged_total = total_cases - connectivity_count
+    judged_pass_rate = (
+        round((passed_cases - connectivity_count) / judged_total, 4) if judged_total > 0 else None
+    )
+
+    avg_latency_ms = round(sum(latencies) / len(latencies), 1) if latencies else None
+
+    return RunSummary(
+        total_cases=total_cases,
+        passed_cases=passed_cases,
+        failed_cases=total_cases - passed_cases,
+        total_rules=len(rule_passes),
+        passed_rules=sum(1 for p in rule_passes if p),
+        pass_rate=pass_rate,
+        judged_pass_rate=judged_pass_rate,
+        avg_latency_ms=avg_latency_ms,
+        case_outcomes={
+            case_id: CaseOutcomeSummary(passed=o.passed, connectivity=o.connectivity)
+            for case_id, o in case_outcomes.items()
+        },
+        case_errors=case_errors or [],
+        model_configs=model_configs or {},
+    )

backend/agenteval/models.py

@@ -187,6 +187,8 @@ class RunSummary(BaseModel):
     passed_rules: int = 0
     # 用例级通过率，含执行失败（ADR-0002）；失败/取消的 run 无此值
     pass_rate: Optional[float] = None
+    # 判定型通过率：连通用例从分子分母双双剔除；无判定型用例时为空
+    judged_pass_rate: Optional[float] = None
     avg_latency_ms: Optional[float] = None
     case_outcomes: dict[str, CaseOutcomeSummary] = Field(default_factory=dict)
     case_errors: list[dict[str, str]] = Field(default_factory=list)

tests/unit/test_build_run_summary.py

@@ -0,0 +1,116 @@
+"""Unit tests for the pure single-run summary seam.
+
+build_run_summary is the single reusable落点 for one run's口径 (pass_rate /
+judged_pass_rate / avg_latency / connectivity split), parallel to
+metrics.aggregate_runs (cross-run) and judgement.combine_case_outcome
+(case-level). No IO — fed constructed material, asserted directly.
+"""
+
+from agenteval.evaluation.judgement import CaseOutcome
+from agenteval.evaluation.run_summary import build_run_summary
+
+
+def _outcomes(**kw: CaseOutcome) -> dict[str, CaseOutcome]:
+    return dict(kw)
+
+
+def test_all_judged_passing():
+    summary = build_run_summary(
+        case_outcomes=_outcomes(
+            a=CaseOutcome(passed=True, connectivity=False),
+            b=CaseOutcome(passed=True, connectivity=False),
+        ),
+        latencies=[100.0, 300.0],
+        rule_passes=[True, True, True],
+    )
+    assert summary.total_cases == 2
+    assert summary.passed_cases == 2
+    assert summary.failed_cases == 0
+    assert summary.pass_rate == 1.0
+    assert summary.judged_pass_rate == 1.0
+    assert summary.total_rules == 3
+    assert summary.passed_rules == 3
+    assert summary.avg_latency_ms == 200.0
+
+
+def test_mixed_pass_fail():
+    summary = build_run_summary(
+        case_outcomes=_outcomes(
+            a=CaseOutcome(passed=True, connectivity=False),
+            b=CaseOutcome(passed=False, connectivity=False),
+            c=CaseOutcome(passed=False, connectivity=False),
+        ),
+        latencies=[],
+        rule_passes=[True, False],
+    )
+    assert summary.total_cases == 3
+    assert summary.passed_cases == 1
+    assert summary.failed_cases == 2
+    assert summary.pass_rate == 0.3333
+    assert summary.judged_pass_rate == 0.3333
+    assert summary.passed_rules == 1
+    assert summary.total_rules == 2
+    assert summary.avg_latency_ms is None
+
+
+def test_connectivity_excluded_from_judged_rate():
+    # 连通用例计入总通过率，但从判定型口径的分子分母双双剔除（report.py 现口径）
+    summary = build_run_summary(
+        case_outcomes=_outcomes(
+            conn=CaseOutcome(passed=True, connectivity=True),
+            judged_pass=CaseOutcome(passed=True, connectivity=False),
+            judged_fail=CaseOutcome(passed=False, connectivity=False),
+        ),
+        latencies=[50.0],
+        rule_passes=[True, False],
+    )
+    assert summary.total_cases == 3
+    assert summary.passed_cases == 2  # conn + judged_pass
+    assert summary.pass_rate == 0.6667
+    # judged: 分母 = 3 - 1 连通 = 2；分子 = 2 通过 - 1 连通 = 1
+    assert summary.judged_pass_rate == 0.5
+
+
+def test_all_connectivity_yields_no_judged_rate():
+    summary = build_run_summary(
+        case_outcomes=_outcomes(
+            a=CaseOutcome(passed=True, connectivity=True),
+            b=CaseOutcome(passed=True, connectivity=True),
+        ),
+        latencies=[10.0],
+        rule_passes=[],
+    )
+    assert summary.pass_rate == 1.0
+    assert summary.judged_pass_rate is None  # judged_total == 0
+
+
+def test_empty_run():
+    summary = build_run_summary(case_outcomes={}, latencies=[], rule_passes=[])
+    assert summary.total_cases == 0
+    assert summary.pass_rate == 0.0
+    assert summary.judged_pass_rate is None
+    assert summary.avg_latency_ms is None
+
+
+def test_case_errors_and_model_configs_passed_through():
+    errors = [{"case_id": "x", "message": "boom"}]
+    configs = {"judge": {"model": "gpt-4o"}}
+    summary = build_run_summary(
+        case_outcomes=_outcomes(x=CaseOutcome(passed=False, connectivity=False)),
+        latencies=[],
+        rule_passes=[],
+        case_errors=errors,
+        model_configs=configs,
+    )
+    assert summary.case_errors == errors
+    assert summary.model_configs == configs
+
+
+def test_case_outcomes_persisted_as_verdict_snapshot():
+    summary = build_run_summary(
+        case_outcomes=_outcomes(a=CaseOutcome(passed=True, connectivity=True)),
+        latencies=[],
+        rule_passes=[],
+    )
+    assert summary.case_outcomes["a"].passed is True
+    assert summary.case_outcomes["a"].connectivity is True