feat: thread and persist sub_pattern into accepted questions

2026-07-14 13:45:31 -04:00
parent 25f2a845ff
commit ae0a718f67
4 changed files with 98 additions and 25 deletions
@@ -251,6 +251,7 @@ def _to_generated_question(
    family: str,
    options: tuple[str, ...] | None = None,
    answer: str | None = None,
+    sub_pattern: str | None = None,
 ) -> GeneratedQuestion:
    """将 CandidateQuestion 转换为 GeneratedQuestion。

@@ -259,6 +260,7 @@ def _to_generated_question(
        family: 问题家族名称（如 "RETRIEVAL"）。
        options: 洗牌后的选项元组（若为 None 则使用 candidate 原始选项）。
        answer: 重映射后的答案字母（若为 None 则使用 candidate 原始答案）。
+        sub_pattern: 出题子模式标识（AR 特化策略使用，None 表示无）。

    返回:
        GeneratedQuestion 实例（difficulty_steps 初始为 None）。
@@ -275,6 +277,7 @@ def _to_generated_question(
        family=family,
        skill_target=candidate.skill_target,
        difficulty_steps=None,
+        sub_pattern=sub_pattern,
    )


@@ -531,6 +534,7 @@ async def _process_one_slot(
                family=strategy.strategy_name,
                options=pp.options,
                answer=pp.answer,
+                sub_pattern=sub_pattern.name if sub_pattern else None,
            )
            # 将题目 embedding 加入池（flatten 确保 1D）
            embed_pool.append(embed_fn(candidate.question).flatten())
@@ -48,6 +48,7 @@ class GeneratedQuestion:
        family: 问题家族名称（如 "RETRIEVAL"，v2 出题管线使用，None 表示未指定）。
        skill_target: 目标技能标识（v2 出题管线使用，None 表示未指定）。
        difficulty_steps: 推理步数估计（v2 出题管线使用，None 表示未指定）。
+        sub_pattern: 出题子模式标识（AR 特化策略使用，None 表示无）。
    """

    question_id: str
@@ -61,6 +62,7 @@ class GeneratedQuestion:
    family: str | None = field(default=None)
    skill_target: str | None = field(default=None)
    difficulty_steps: int | None = field(default=None)
+    sub_pattern: str | None = field(default=None)


@dataclass(frozen=True)
@@ -0,0 +1,73 @@
+"""GeneratedQuestion.sub_pattern 字段 + _to_generated_question 透传。"""
+
+from app.question_gen.generator_v2 import CandidateQuestion
+from app.question_gen.pipeline_v2 import _to_generated_question
+from core.types import GeneratedQuestion
+
+
+def _candidate() -> CandidateQuestion:
+    return CandidateQuestion(
+        question_id="v1_Action Recognition_0001",
+        video_id="v1",
+        task_type="Action Recognition",
+        skill_target="M1_AR",
+        question="厨师最终采用了哪种烹饪方式？",
+        options=("A. 蒸", "B. 炒", "C. 煮", "D. 炸"),
+        answer="A",
+        source_nodes=("n1", "n2"),
+        difficulty="hard",
+    )
+
+
+def test_generated_question_has_sub_pattern_default_none():
+    q = GeneratedQuestion(
+        question_id="q1", video_id="v1", task_type="Action Recognition",
+        question="?", options=("A. x",), answer="A",
+        source_nodes=("n1",), difficulty="easy",
+    )
+    assert q.sub_pattern is None
+
+
+def test_to_generated_question_threads_sub_pattern():
+    q = _to_generated_question(
+        _candidate(), family="ACTION_RECOGNITION",
+        sub_pattern="premature_evidence_anchoring",
+    )
+    assert q.sub_pattern == "premature_evidence_anchoring"
+
+
+def test_to_generated_question_sub_pattern_defaults_none():
+    q = _to_generated_question(_candidate(), family="RETRIEVAL")
+    assert q.sub_pattern is None
+
+
+def test_question_to_entry_includes_sub_pattern():
+    from tools.generate_questions import _question_to_entry
+    q = GeneratedQuestion(
+        question_id="v1_Action Recognition_0001", video_id="v1",
+        task_type="Action Recognition", question="?",
+        options=("A. 蒸", "B. 炒", "C. 煮", "D. 炸"), answer="A",
+        source_nodes=("n1",), difficulty="hard",
+        family="ACTION_RECOGNITION", skill_target="M1_AR",
+        sub_pattern="temporal_reasoning_failure",
+    )
+    entry = _question_to_entry(q)
+    assert entry["sub_pattern"] == "temporal_reasoning_failure"
+    assert entry["question_id"] == "v1_Action Recognition_0001"
+    assert entry["options"] == ["A. 蒸", "B. 炒", "C. 煮", "D. 炸"]
+
+
+def test_append_to_json_writes_sub_pattern(tmp_path):
+    from tools.generate_questions import _append_to_json
+    q = GeneratedQuestion(
+        question_id="v1_Action Recognition_0001", video_id="v1",
+        task_type="Action Recognition", question="?",
+        options=("A. 蒸", "B. 炒", "C. 煮", "D. 炸"), answer="A",
+        source_nodes=("n1",), difficulty="hard",
+        family="ACTION_RECOGNITION", skill_target="M1_AR",
+        sub_pattern="temporal_reasoning_failure",
+    )
+    _append_to_json(tmp_path, q)
+    import json
+    data = json.loads((tmp_path / "v1.json").read_text(encoding="utf-8"))
+    assert data[0]["sub_pattern"] == "temporal_reasoning_failure"
@@ -323,6 +323,23 @@ def _build_embed_provider():
 # ---------------------------------------------------------------------------


+def _question_to_entry(question: GeneratedQuestion) -> dict:
+    """将题目序列化为 JSON entry（_append_to_json 与 _on_accept 共用）。"""
+    return {
+        "question_id": question.question_id,
+        "video_id": question.video_id,
+        "task_type": question.task_type,
+        "question": question.question,
+        "options": list(question.options),
+        "answer": question.answer,
+        "source_nodes": list(question.source_nodes),
+        "difficulty": question.difficulty,
+        "family": question.family,
+        "skill_target": question.skill_target,
+        "sub_pattern": question.sub_pattern,
+    }
+
+
 def _append_to_json(output_dir: Path, question: GeneratedQuestion) -> None:
    """将生成的题目追加到对应 video_id 的 JSON 文件。

@@ -341,17 +358,7 @@ def _append_to_json(output_dir: Path, question: GeneratedQuestion) -> None:
            logger.warning("读取 {} 失败，覆盖写入", json_path)
            existing = []

-    entry = {
-        "question_id": question.question_id,
-        "task_type": question.task_type,
-        "question": question.question,
-        "options": list(question.options),
-        "answer": question.answer,
-        "source_nodes": list(question.source_nodes),
-        "difficulty": question.difficulty,
-        "family": question.family,
-        "skill_target": question.skill_target,
-    }
+    entry = _question_to_entry(question)
    existing.append(entry)

    # 原子写入
@@ -1120,20 +1127,7 @@ async def _run_generate_v2(args: argparse.Namespace) -> None:
            except (json.JSONDecodeError, OSError):
                existing = []

-        existing.append(
-            {
-                "question_id": q.question_id,
-                "video_id": q.video_id,
-                "task_type": q.task_type,
-                "question": q.question,
-                "options": list(q.options),
-                "answer": q.answer,
-                "source_nodes": list(q.source_nodes),
-                "difficulty": q.difficulty,
-                "family": q.family,
-                "skill_target": q.skill_target,
-            }
-        )
+        existing.append(_question_to_entry(q))

        tmp_path = output_path.with_suffix(".tmp")
        tmp_path.write_text(