ops(pipeline): 생성 LLM 홀드 게이트 held_stages — 맥미니 모델 확정까지 보류

맥북 LLM 백지화 + 맥미니 모델 재결정에 따라 DS 의 생성 LLM 소비를 일괄 보류.
held = classify/summarize/deep_summary(큐, claim 미발생·attempts 미소모) +
digest(04:00)/briefing(05:10) cron + study explanation/session_analysis/memo_card 컨슈머.
GPU 특화 스테이지·수집기·인터랙티브(ask/eid chat)는 무영향. 기본값 [] = 무동작.
/api/digest/regenerate 는 홀드 중 409 명시. 해제 = config held_stages 비우고 fastapi 재기동.
exec plan: ~/.claude/plans/ds-llm-hold-exec-20260611.md

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

tests/test_pipeline_hold.py

@@ -0,0 +1,168 @@
+"""생성 LLM 홀드 (pipeline.held_stages) — 컨슈머/워커 게이트 동작 테스트.
+
+홀드 시멘틱: held 스테이지는 claim 자체를 하지 않는다 (attempts 미소모, DB 무접촉).
+비-held 스테이지는 기존과 동일하게 처리된다.
+"""
+
+import pytest
+
+from core.config import Settings, settings
+from workers import digest_worker, queue_consumer
+
+
+def _fake_consumer_env(monkeypatch, held):
+    processed = []
+
+    async def fake_process(stage, worker):
+        processed.append(stage)
+
+    async def fake_reset(stages, threshold):
+        return None
+
+    monkeypatch.setattr(queue_consumer, "_process_stage", fake_process)
+    monkeypatch.setattr(queue_consumer, "reset_stale_items", fake_reset)
+    monkeypatch.setattr(
+        queue_consumer, "_load_workers",
+        lambda: {s: object() for s in queue_consumer.MAIN_QUEUE_STAGES + ["markdown"]},
+    )
+    monkeypatch.setattr(queue_consumer, "_hold_logged", False)
+    monkeypatch.setattr(settings, "pipeline_held_stages", held)
+    return processed
+
+
+def test_settings_default_empty():
+    """미설정 시 빈 리스트 = 무동작 (기존 동작 무회귀)."""
+    assert Settings().pipeline_held_stages == []
+
+
+@pytest.mark.asyncio
+async def test_consume_queue_skips_held_stages(monkeypatch):
+    processed = _fake_consumer_env(
+        monkeypatch, ["classify", "summarize", "deep_summary"]
+    )
+
+    await queue_consumer.consume_queue()
+
+    assert "classify" not in processed
+    assert "summarize" not in processed
+    assert "deep_summary" not in processed
+    # GPU/특화 스테이지는 계속 처리
+    for stage in ("extract", "embed", "chunk", "stt", "fulltext"):
+        assert stage in processed
+
+
+@pytest.mark.asyncio
+async def test_consume_queue_empty_hold_processes_all(monkeypatch):
+    processed = _fake_consumer_env(monkeypatch, [])
+
+    await queue_consumer.consume_queue()
+
+    assert processed == list(queue_consumer.MAIN_QUEUE_STAGES)
+
+
+@pytest.mark.asyncio
+async def test_markdown_consumer_not_held(monkeypatch):
+    """markdown 컨슈머는 홀드 비대상 (LLM 무관 — marker GPU 변환)."""
+    processed = _fake_consumer_env(
+        monkeypatch, ["classify", "summarize", "deep_summary", "digest"]
+    )
+
+    await queue_consumer.consume_markdown_queue()
+
+    assert processed == ["markdown"]
+
+
+@pytest.mark.asyncio
+async def test_digest_worker_held_returns_before_pipeline(monkeypatch):
+    called = {"pipeline": False}
+
+    async def fake_pipeline():
+        called["pipeline"] = True
+        return {}
+
+    monkeypatch.setattr(digest_worker, "run_digest_pipeline", fake_pipeline)
+    monkeypatch.setattr(settings, "pipeline_held_stages", ["digest"])
+
+    await digest_worker.run()
+
+    assert called["pipeline"] is False
+
+
+@pytest.mark.asyncio
+async def test_digest_worker_unheld_runs_pipeline(monkeypatch):
+    called = {"pipeline": False}
+
+    async def fake_pipeline():
+        called["pipeline"] = True
+        return {"clusters": 0}
+
+    monkeypatch.setattr(digest_worker, "run_digest_pipeline", fake_pipeline)
+    monkeypatch.setattr(settings, "pipeline_held_stages", [])
+
+    await digest_worker.run()
+
+    assert called["pipeline"] is True
+
+
+@pytest.mark.asyncio
+async def test_briefing_worker_held_returns_before_pipeline(monkeypatch):
+    from workers import briefing_worker
+
+    called = {"pipeline": False}
+
+    async def fake_pipeline(target_date):
+        called["pipeline"] = True
+        return {}
+
+    monkeypatch.setattr(briefing_worker, "run_briefing_pipeline", fake_pipeline)
+    monkeypatch.setattr(settings, "pipeline_held_stages", ["briefing"])
+
+    assert await briefing_worker.run() is None
+    assert called["pipeline"] is False
+
+
+@pytest.mark.asyncio
+async def test_study_explanation_consumer_held(monkeypatch):
+    from workers import study_queue_consumer
+
+    touched = []
+
+    async def fake_reset():
+        touched.append("reset")
+
+    monkeypatch.setattr(study_queue_consumer, "reset_stale_study_jobs", fake_reset)
+    monkeypatch.setattr(settings, "pipeline_held_stages", ["study_explanation"])
+
+    await study_queue_consumer.consume_study_queue()
+
+    assert touched == []
+
+
+@pytest.mark.asyncio
+async def test_study_consumers_held_no_db_touch(monkeypatch):
+    """held 시 stale reset 포함 DB 접근 0 — claim 미발생 실증."""
+    from workers import study_memo_card_jobs_consumer, study_session_queue_consumer
+
+    touched = []
+
+    async def fake_reset_session():
+        touched.append("session_reset")
+
+    async def fake_reset_card():
+        touched.append("card_reset")
+
+    monkeypatch.setattr(
+        study_session_queue_consumer, "reset_stale_session_jobs", fake_reset_session
+    )
+    monkeypatch.setattr(
+        study_memo_card_jobs_consumer, "reset_stale_card_jobs", fake_reset_card
+    )
+    monkeypatch.setattr(
+        settings, "pipeline_held_stages",
+        ["study_session_analysis", "study_memo_card"],
+    )
+
+    await study_session_queue_consumer.consume_study_session_queue()
+    await study_memo_card_jobs_consumer.consume_study_memo_card_queue()
+
+    assert touched == []