feat(question_gen): add 5 question family specs with sampling constraints

Define QuestionFamilySpec, LeakTestProfile, SamplingConstraint dataclasses
and instantiate 5 families (RETRIEVAL/REASONING/ENUMERATION/VISUAL/SPATIAL)
targeting failure mechanisms M1-M5. Implement get_family_for_slot with
legal-type filtering + weighted random selection.

13 unit tests cover: full task-type coverage, skill_target uniqueness,
deterministic seeding, invalid input errors, and chi-square distribution.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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"""题族规格声明 — 定义 5 大问题家族及其采样、泄漏检测、提示模板约束。
每个 QuestionFamilySpec 对应一种失败机制(skill_target M1M5),
由 get_family_for_slot 在出题时按权重分配。
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import TYPE_CHECKING
if TYPE_CHECKING:
import random
@dataclass(frozen=True)
class LeakTestProfile:
"""泄漏测试配置 — 定义快捷答题捷径类型与通过阈值。
Attributes:
shortcut_type: 捷径类型标识。
probe_template: store/prompts/question_gen/ 下的探测模板文件名。
pass_threshold: 通过阈值(0–1),低于此值视为存在泄漏。
"""
shortcut_type: str
probe_template: str
pass_threshold: float
@dataclass(frozen=True)
class SamplingConstraint:
"""采样约束 — 对树节点的最低要求。
Attributes:
min_subtitles: 最少字幕段数。
min_l3_nodes: 最少 L3 节点数。
require_frames: 是否要求帧图像可用。
cross_l2_span: 是否要求跨 L2 段采样。
"""
min_subtitles: int
min_l3_nodes: int
require_frames: bool
cross_l2_span: bool
@dataclass(frozen=True)
class QuestionFamilySpec:
"""问题家族规格 — 一个家族的完整声明。
Attributes:
name: 家族标识名(如 "RETRIEVAL")。
skill_target: 目标失败机制编号(M1–M5)。
sampling: 采样约束。
legal_task_types: 该家族合法的任务类型集合(frozenset)。
leak_profile: 泄漏测试配置。
prompt_template: 出题 prompt 模板文件名。
"""
name: str
skill_target: str
sampling: SamplingConstraint
legal_task_types: frozenset[str]
leak_profile: LeakTestProfile
prompt_template: str
# ---------------------------------------------------------------------------
# 5 大家族实例
# ---------------------------------------------------------------------------
RETRIEVAL_FAMILY = QuestionFamilySpec(
name="RETRIEVAL",
skill_target="M1",
sampling=SamplingConstraint(
min_subtitles=2,
min_l3_nodes=3,
require_frames=False,
cross_l2_span=False,
),
legal_task_types=frozenset(
[
"Action Recognition",
"Action Reasoning",
"Action Prediction",
"Action Sequence",
"Object Recognition",
"Object Reasoning",
"Object Interaction",
"Scene Understanding",
"Event Reasoning",
"Causal Reasoning",
"Temporal Reasoning",
"Spatial Reasoning",
]
),
leak_profile=LeakTestProfile(
shortcut_type="temporal_proximity",
probe_template="gate_leak_retrieval.md",
pass_threshold=0.6,
),
prompt_template="retrieval.md",
)
REASONING_FAMILY = QuestionFamilySpec(
name="REASONING",
skill_target="M2",
sampling=SamplingConstraint(
min_subtitles=3,
min_l3_nodes=4,
require_frames=False,
cross_l2_span=True,
),
legal_task_types=frozenset(
[
"Action Reasoning",
"Object Reasoning",
"Event Reasoning",
"Causal Reasoning",
"Temporal Reasoning",
"Spatial Reasoning",
]
),
leak_profile=LeakTestProfile(
shortcut_type="frequency",
probe_template="gate_leak_reasoning.md",
pass_threshold=0.5,
),
prompt_template="reasoning.md",
)
ENUMERATION_FAMILY = QuestionFamilySpec(
name="ENUMERATION",
skill_target="M3",
sampling=SamplingConstraint(
min_subtitles=2,
min_l3_nodes=5,
require_frames=False,
cross_l2_span=False,
),
legal_task_types=frozenset(
[
"Action Sequence",
"Object Recognition",
"Object Interaction",
"Scene Understanding",
]
),
leak_profile=LeakTestProfile(
shortcut_type="option_length",
probe_template="gate_leak_enumeration.md",
pass_threshold=0.6,
),
prompt_template="enumeration.md",
)
VISUAL_FAMILY = QuestionFamilySpec(
name="VISUAL",
skill_target="M4",
sampling=SamplingConstraint(
min_subtitles=0,
min_l3_nodes=3,
require_frames=True,
cross_l2_span=False,
),
legal_task_types=frozenset(
[
"Object Recognition",
"Scene Understanding",
"Action Recognition",
"Spatial Reasoning",
]
),
leak_profile=LeakTestProfile(
shortcut_type="visual_salience",
probe_template="gate_leak_visual.md",
pass_threshold=0.5,
),
prompt_template="visual.md",
)
SPATIAL_FAMILY = QuestionFamilySpec(
name="SPATIAL",
skill_target="M5",
sampling=SamplingConstraint(
min_subtitles=0,
min_l3_nodes=3,
require_frames=True,
cross_l2_span=False,
),
legal_task_types=frozenset(
[
"Spatial Reasoning",
"Object Interaction",
"Scene Understanding",
]
),
leak_profile=LeakTestProfile(
shortcut_type="spatial_default",
probe_template="gate_leak_spatial.md",
pass_threshold=0.5,
),
prompt_template="spatial.md",
)
ALL_FAMILIES: tuple[QuestionFamilySpec, ...] = (
RETRIEVAL_FAMILY,
REASONING_FAMILY,
ENUMERATION_FAMILY,
VISUAL_FAMILY,
SPATIAL_FAMILY,
)
# 按 name 索引,用于 get_family_for_slot 快速查找
_FAMILY_BY_NAME: dict[str, QuestionFamilySpec] = {f.name: f for f in ALL_FAMILIES}
def get_family_for_slot(
task_type: str,
family_ratios: dict[str, float],
rng: random.Random,
) -> QuestionFamilySpec:
"""根据任务类型和家族权重比例,随机选择一个合法的问题家族。
Args:
task_type: 任务类型字符串(必须是 12 种合法类型之一)。
family_ratios: 家族名称到权重的映射(如 {"RETRIEVAL": 0.30, ...})。
rng: 随机数生成器实例(确保可复现)。
Returns:
被选中的 QuestionFamilySpec。
Raises:
ValueError: task_type 不在任何家族的 legal_task_types 中。
ValueError: 给定 task_type 下没有合法家族(所有合法族权重为 0 或不在 ratios 中)。
"""
# 检查 task_type 是否被任一家族接受
all_legal_types: set[str] = set()
for family in ALL_FAMILIES:
all_legal_types.update(family.legal_task_types)
if task_type not in all_legal_types:
msg = f"task_type '{task_type}' 不在任何家族的合法类型中"
raise ValueError(msg)
# 过滤出接受该 task_type 且在 ratios 中有正权重的家族
candidates: list[QuestionFamilySpec] = []
weights: list[float] = []
for family_name, weight in family_ratios.items():
family = _FAMILY_BY_NAME.get(family_name)
if family is None:
continue
if task_type in family.legal_task_types and weight > 0:
candidates.append(family)
weights.append(weight)
if not candidates:
msg = f"task_type '{task_type}' 下没有合法家族可选(检查 family_ratios"
raise ValueError(msg)
# 归一化权重 + 加权随机选择
chosen = rng.choices(candidates, weights=weights, k=1)[0]
return chosen