fix(question_gen): sample_anchor Codex 审查修正

- C1/C2: Temporal Reasoning ≥3 L2 + Object Reasoning ≥2 L2 下限检查
- I1: L2 题型子帧不足时 ValueError
- I2: L3 过滤无 frame_path 的节点
- I3/I4: distractor_texts 扩展到整棵树范围
- I5-I7: 测试补强 Information Synopsis/Temporal Reasoning/Object Reasoning
- M1: Spatial Reasoning 测试断言 spatial_layout

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

app/question_gen/synthesizer.py

@@ -12,7 +12,7 @@ from typing import TYPE_CHECKING
 if TYPE_CHECKING:
     import random
 
-    from app.tree.index import L1Node, L2Node, L3Node, TreeIndex
+    from app.tree.index import L2Node, L3Node, TreeIndex
 
 
 @dataclass(frozen=True)
@@ -170,27 +170,33 @@ def _sample_l3(
     异常:
         ValueError: 候选 L3 节点不足。
     """
-    # Phase 1: 收集所有 L3 候选
+    # Phase 1: 收集所有 L3 候选（必须有 frame_path）
     candidates: list[tuple[L3Node, L2Node]] = []
     for root in tree.roots:
         for l2 in root.children:
             for l3 in l2.children:
-                if l3.id not in used_node_ids:
+                if l3.id not in used_node_ids and l3.frame_path:
                     candidates.append((l3, l2))
 
     if not candidates:
-        raise ValueError(f"锚节点不足: {task_type} 无可用 L3 节点")
+        raise ValueError(f"锚节点不足: {task_type} 无可用 L3 节点（需具备 frame_path）")
 
     # Phase 2: 随机选取
     chosen_l3, parent_l2 = rng.choice(candidates)
 
-    # Phase 3: 构造上下文
+    # Phase 3: 构造上下文（frame_path 已在候选过滤中保证非 None）
     card_text = _serialize_l3_card(chosen_l3, spec.context_fields)
-    frame_paths = [chosen_l3.frame_path] if chosen_l3.frame_path else []
+    frame_paths = [chosen_l3.frame_path]  # type: ignore[list-item]
     subtitle = chosen_l3.subtitle or ""
 
-    # Phase 4: 干扰项——同 L2 下其他 L3 的 frame_summary
+    # Phase 4: 干扰项——整棵树中其他 L3 的 frame_summary
-    distractor_texts = [l3.card.frame_summary for l3 in parent_l2.children if l3.id != chosen_l3.id]
+    distractor_texts = [
+        l3.card.frame_summary
+        for root in tree.roots
+        for l2 in root.children
+        for l3 in l2.children
+        if l3.id != chosen_l3.id
+    ]
 
     return AnchorContext(
         node_id=chosen_l3.id,
@@ -227,17 +233,17 @@ def _sample_l2(
         ValueError: 候选 L2 节点不足。
     """
     # Phase 1: 收集所有 L2 候选
-    all_l2: list[tuple[L2Node, L1Node]] = []
+    all_l2: list[L2Node] = []
     for root in tree.roots:
         for l2 in root.children:
             if l2.id not in used_node_ids:
-                all_l2.append((l2, root))
+                all_l2.append(l2)
 
     if not all_l2:
         raise ValueError(f"锚节点不足: {task_type} 无可用 L2 节点")
 
     # Phase 2: 随机选取
-    chosen_l2, parent_l1 = rng.choice(all_l2)
+    chosen_l2 = rng.choice(all_l2)
 
     is_temporal_perception = task_type == "Temporal Perception"
 
@@ -252,8 +258,13 @@ def _sample_l2(
     else:
         # 普通 L2：随机采样 2-3 个 L3 帧
         children_with_frames = [l3 for l3 in chosen_l2.children if l3.frame_path]
+        if len(children_with_frames) < 2:
+            raise ValueError(
+                f"锚节点不足: {task_type} 需要 >=2 个子帧，"
+                f"但 {chosen_l2.id} 仅有 {len(children_with_frames)} 个可用帧"
+            )
         n_frames = min(rng.randint(2, 3), len(children_with_frames))
-        sampled = rng.sample(children_with_frames, n_frames) if n_frames > 0 else []
+        sampled = rng.sample(children_with_frames, n_frames)
         frame_paths = [l3.frame_path for l3 in sampled if l3.frame_path]
 
     # Phase 4: card_text
@@ -266,9 +277,12 @@ def _sample_l2(
     if chosen_l2.children and chosen_l2.children[0].subtitle:
         subtitle = chosen_l2.children[0].subtitle
 
-    # Phase 6: 干扰项——同 L1 下其他 L2 的 event_description
+    # Phase 6: 干扰项——整棵树中其他 L2 的 event_description
     distractor_texts = [
-        l2.card.event_description for l2 in parent_l1.children if l2.id != chosen_l2.id
+        l2.card.event_description
+        for root in tree.roots
+        for l2 in root.children
+        if l2.id != chosen_l2.id
     ]
 
     return AnchorContext(
@@ -290,7 +304,7 @@ def _sample_l1(
     """L1 层级锚节点采样（Temporal Reasoning / Information Synopsis）。
 
     Information Synopsis：使用目标 L1 下全部 L2 子节点。
-    Temporal Reasoning：使用 >=3 个 L2 子节点（不足 3 个则全部使用）。
+    Temporal Reasoning：严格要求 >=3 个 L2 子节点，不足则抛 ValueError。
     L2 按 time_range 升序排列，每个 L2 取一帧代表。
 
     参数:
@@ -304,7 +318,7 @@ def _sample_l1(
         AnchorContext 实例。
 
     异常:
-        ValueError: 候选 L1 节点不足。
+        ValueError: 候选 L1 节点不足，或 Temporal Reasoning 的 L2 子节点 <3。
     """
     # Phase 1: 收集可用 L1
     candidates = [r for r in tree.roots if r.id not in used_node_ids]
@@ -319,8 +333,13 @@ def _sample_l1(
         # 必须使用全部 L2
         selected_l2 = list(chosen_l1.children)
     else:
-        # Temporal Reasoning：>=3 个 L2（不足则全部）
+        # Temporal Reasoning：严格要求 >=3 个 L2
-        if len(chosen_l1.children) <= 3:
+        if len(chosen_l1.children) < 3:
+            raise ValueError(
+                f"锚节点不足: {task_type} 需要 >=3 个 L2 子节点，"
+                f"但 {chosen_l1.id} 仅有 {len(chosen_l1.children)} 个"
+            )
+        if len(chosen_l1.children) == 3:
             selected_l2 = list(chosen_l1.children)
         else:
             selected_l2 = rng.sample(chosen_l1.children, rng.randint(3, len(chosen_l1.children)))
@@ -385,8 +404,10 @@ def _sample_l1_l2(
             if l2.id not in used_node_ids:
                 all_l2.append(l2)
 
-    if not all_l2:
+    if len(all_l2) < 2:
-        raise ValueError(f"锚节点不足: {task_type} 无可用 L2 节点")
+        raise ValueError(
+            f"锚节点不足: {task_type} 需要 >=2 个 L2 节点，但仅有 {len(all_l2)} 个可用"
+        )
 
     # Phase 2: 随机选 2-3 个
     n_pick = min(rng.randint(2, 3), len(all_l2))

tests/unit/test_synthesizer.py

@@ -185,15 +185,15 @@ class TestSampleAnchor:
         """Information Synopsis 必须使用目标 L1 下所有 L2 子节点。"""
         tree, _vid = _load_test_tree()
         ctx = sample_anchor(tree, "Information Synopsis", set(), random.Random(42))
-        # 至少应有帧（每个 L2 取一帧代表）
+        # 找到被选中的 L1，验证 frame_paths 数量 == 该 L1 下全部 L2 数量
-        total_l2 = sum(len(r.children) for r in tree.roots)
+        chosen_l1 = next(r for r in tree.roots if r.id == ctx.node_id)
-        assert len(ctx.frame_paths) >= min(total_l2, 1)
+        assert len(ctx.frame_paths) == len(chosen_l1.children)
 
     def test_l1_type_l2_nodes_in_time_order(self) -> None:
-        """L1 题型（Temporal Reasoning）的 card_text 应有实质内容。"""
+        """Temporal Reasoning 应返回 >=3 帧且 card_text 有实质内容。"""
         tree, _vid = _load_test_tree()
         ctx = sample_anchor(tree, "Temporal Reasoning", set(), random.Random(42))
-        assert len(ctx.frame_paths) >= 1
+        assert len(ctx.frame_paths) >= 3
         assert len(ctx.card_text) > 20
 
     def test_used_node_ids_excluded(self) -> None:
@@ -219,12 +219,13 @@ class TestSampleAnchor:
         """Object Reasoning (L1-L2) 应选 2-3 个 L2 并按时间排序。"""
         tree, _vid = _load_test_tree()
         ctx = sample_anchor(tree, "Object Reasoning", set(), random.Random(42))
-        assert 1 <= len(ctx.frame_paths) <= 3
+        assert 2 <= len(ctx.frame_paths) <= 3
         assert len(ctx.card_text) > 10
 
     def test_spatial_reasoning_context_fields(self) -> None:
-        """Spatial Reasoning 的 card_text 应包含 spatial_layout 内容。"""
+        """Spatial Reasoning 的 card_text 应包含 spatial_layout 字段。"""
         tree, _vid = _load_test_tree()
         ctx = sample_anchor(tree, "Spatial Reasoning", set(), random.Random(42))
-        # context_fields 包含 spatial_layout，card_text 应含有该字段内容
+        # context_fields 包含 spatial_layout，card_text 必须出现该字段名
+        assert "spatial_layout" in ctx.card_text
         assert len(ctx.card_text) > 20