feat: add AdversarialFilterConfig for Phase B post-hoc filter layer

app/question_gen/adversarial_config.py

@@ -0,0 +1,59 @@
+"""Phase B 对抗过滤层配置 — filter 层配置（非 strategy 属性）。
+
+设计: research-wiki/designs/2026-07-14-adversarial-question-gen-phaseB-design.md §8
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import TYPE_CHECKING
+
+import yaml
+
+if TYPE_CHECKING:
+    from pathlib import Path
+
+
+@dataclass(frozen=True)
+class AdversarialFilterConfig:
+    """后置对抗过滤配置。
+
+    属性:
+        filter_task_types: 被过滤的题型（仅这些走 agent 门），默认仅 AR。
+        adversarial_max_rounds: 补生成迭代上限。
+        adversarial_agent_max_steps: agent 试答步数上限。
+        difficulty_warn_threshold: 批次 agent 正确率告警阈值。
+    """
+
+    filter_task_types: tuple[str, ...] = ("Action Recognition",)
+    adversarial_max_rounds: int = 5
+    adversarial_agent_max_steps: int = 40
+    difficulty_warn_threshold: float = 0.85
+
+
+def load_adversarial_config(config_path: Path) -> AdversarialFilterConfig:
+    """从 YAML 的 adversarial_filter 区段加载配置，缺段/缺键用默认值。
+
+    参数:
+        config_path: YAML 配置文件路径。
+
+    返回:
+        AdversarialFilterConfig 实例。
+    """
+    with open(config_path, encoding="utf-8") as f:
+        raw = yaml.safe_load(f) or {}
+    section = raw.get("adversarial_filter", {}) or {}
+    default = AdversarialFilterConfig()
+    types = section.get("filter_task_types")
+    return AdversarialFilterConfig(
+        filter_task_types=tuple(types) if types else default.filter_task_types,
+        adversarial_max_rounds=int(
+            section.get("adversarial_max_rounds", default.adversarial_max_rounds)
+        ),
+        adversarial_agent_max_steps=int(
+            section.get("adversarial_agent_max_steps", default.adversarial_agent_max_steps)
+        ),
+        difficulty_warn_threshold=float(
+            section.get("difficulty_warn_threshold", default.difficulty_warn_threshold)
+        ),
+    )

config/question_gen_ar30.yaml

@@ -12,3 +12,10 @@ question_gen_v2:
   candidate_pool_size: 24     # grounded selector 首轮候选干扰项数 N
   selector_delta_low: 0.05    # 干扰项视觉分与正解的最小差（区间上界）
   selector_delta_high: 0.35   # 干扰项视觉分与正解的最大差（区间下界）
+
+# Phase B 后置对抗过滤层配置（filter 层，非 strategy 属性）
+adversarial_filter:
+  filter_task_types: [Action Recognition]   # 仅这些题型走 agent 门（路径隔离开关）
+  adversarial_max_rounds: 5                  # 补生成迭代上限
+  adversarial_agent_max_steps: 40            # agent 试答步数上限
+  difficulty_warn_threshold: 0.85            # 批次 agent 正确率告警阈值

tests/unit/test_adversarial_config.py

@@ -0,0 +1,38 @@
+"""AdversarialFilterConfig 默认值 + YAML 加载。"""
+
+from app.question_gen.adversarial_config import (
+    AdversarialFilterConfig,
+    load_adversarial_config,
+)
+
+
+def test_defaults():
+    cfg = AdversarialFilterConfig()
+    assert cfg.filter_task_types == ("Action Recognition",)
+    assert cfg.adversarial_max_rounds == 5
+    assert cfg.adversarial_agent_max_steps == 40
+    assert cfg.difficulty_warn_threshold == 0.85
+
+
+def test_load_from_yaml(tmp_path):
+    p = tmp_path / "c.yaml"
+    p.write_text(
+        "adversarial_filter:\n"
+        "  filter_task_types: [Action Recognition, Object Recognition]\n"
+        "  adversarial_max_rounds: 3\n"
+        "  adversarial_agent_max_steps: 20\n"
+        "  difficulty_warn_threshold: 0.7\n",
+        encoding="utf-8",
+    )
+    cfg = load_adversarial_config(p)
+    assert cfg.filter_task_types == ("Action Recognition", "Object Recognition")
+    assert cfg.adversarial_max_rounds == 3
+    assert cfg.adversarial_agent_max_steps == 20
+    assert cfg.difficulty_warn_threshold == 0.7
+
+
+def test_load_missing_section_uses_defaults(tmp_path):
+    p = tmp_path / "c.yaml"
+    p.write_text("question_gen_v2:\n  per_type: 3\n", encoding="utf-8")
+    cfg = load_adversarial_config(p)
+    assert cfg == AdversarialFilterConfig()