feat(question_gen): sample_anchor — 按题型层级采样锚节点

含 6 种层级分支：L3 单帧、L2 多帧、Temporal Perception 特例、
L1 全量/采样 L2、L1-L2 混合。时间排序 + used_node_ids 排除。

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

tests/unit/test_synthesizer.py

@@ -1,10 +1,20 @@
-"""synthesizer 模块单元测试 — AnchorContext + 题型映射常量。"""
+"""synthesizer 模块单元测试 — AnchorContext + 题型映射常量 + sample_anchor。"""
 
 from __future__ import annotations
 
 import dataclasses
+import random
+from pathlib import Path
 
-from app.question_gen.synthesizer import TASK_TYPE_LEVEL_MAP, AnchorContext, TaskTypeSpec
+import pytest
+
+from app.question_gen.synthesizer import (
+    TASK_TYPE_LEVEL_MAP,
+    AnchorContext,
+    TaskTypeSpec,
+    sample_anchor,
+)
+from app.tree.index import TreeIndex
 
 ALL_12_TYPES = [
     "Object Recognition",
@@ -132,3 +142,89 @@ class TestTaskTypeSpec:
             assert isinstance(spec.context_fields, tuple), (
                 f"{task_type} 的 context_fields 不是 tuple"
             )
+
+
+# ---------------------------------------------------------------------------
+# sample_anchor 测试
+# ---------------------------------------------------------------------------
+
+
+def _load_test_tree() -> tuple[TreeIndex, str]:
+    """加载真实测试树（store/videos/ 下第一棵）。"""
+    videos_dir = Path("store/videos")
+    first_vid = sorted(videos_dir.iterdir())[0]
+    tree = TreeIndex.load_json(str(first_vid / "tree.json"))
+    return tree, first_vid.name
+
+
+class TestSampleAnchor:
+    """sample_anchor 锚节点采样测试（基于真实树数据）。"""
+
+    def test_l3_type_returns_single_frame(self) -> None:
+        """L3 题型（Object Recognition）应返回恰好 1 帧。"""
+        tree, _vid = _load_test_tree()
+        ctx = sample_anchor(tree, "Object Recognition", set(), random.Random(42))
+        assert len(ctx.frame_paths) == 1
+        assert ctx.node_id.startswith("L") or "_L3_" in ctx.node_id
+        assert len(ctx.distractor_texts) > 0
+
+    def test_l2_type_returns_multiple_frames(self) -> None:
+        """L2 题型（Action Reasoning）应返回 2-3 帧。"""
+        tree, _vid = _load_test_tree()
+        ctx = sample_anchor(tree, "Action Reasoning", set(), random.Random(42))
+        assert 2 <= len(ctx.frame_paths) <= 3
+
+    def test_temporal_perception_zero_or_one_frame(self) -> None:
+        """Temporal Perception 特殊处理：0-1 帧，且 card_text 包含 time_range。"""
+        tree, _vid = _load_test_tree()
+        ctx = sample_anchor(tree, "Temporal Perception", set(), random.Random(42))
+        assert len(ctx.frame_paths) <= 1
+        assert "time_range" in ctx.card_text.lower() or "time" in ctx.card_text.lower()
+
+    def test_information_synopsis_uses_all_l2(self) -> None:
+        """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）
+        total_l2 = sum(len(r.children) for r in tree.roots)
+        assert len(ctx.frame_paths) >= min(total_l2, 1)
+
+    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。"""
+        tree, _vid = _load_test_tree()
+        ctx = sample_anchor(tree, "Temporal Reasoning", set(), random.Random(42))
+        assert len(ctx.frame_paths) >= 1
+        assert len(ctx.card_text) > 20
+
+    def test_used_node_ids_excluded(self) -> None:
+        """used_node_ids 中的节点不应被再次选中。"""
+        tree, _vid = _load_test_tree()
+        rng = random.Random(42)
+        ctx1 = sample_anchor(tree, "Object Recognition", set(), rng)
+        ctx2 = sample_anchor(tree, "Object Recognition", {ctx1.node_id}, random.Random(43))
+        assert ctx2.node_id != ctx1.node_id
+
+    def test_insufficient_nodes_raises(self) -> None:
+        """所有候选节点均被排除时应抛出 ValueError。"""
+        tree, _vid = _load_test_tree()
+        all_l3_ids: set[str] = set()
+        for root in tree.roots:
+            for l2 in root.children:
+                for l3 in l2.children:
+                    all_l3_ids.add(l3.id)
+        with pytest.raises(ValueError, match="锚节点不足"):
+            sample_anchor(tree, "Object Recognition", all_l3_ids, random.Random(42))
+
+    def test_object_reasoning_l1_l2_type(self) -> None:
+        """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 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。"""
+        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
+        assert len(ctx.card_text) > 20