fix: solve vLLM->BLM misrecognition via glossary postprocessing

The bench and CLI kept emitting BLM for vLLM. Three layers:

1. rules.py: add default rule BLM -> vLLM (word-boundary, case-insensitive) so the default post_mode=rules path restores it everywhere.

2. benchmark/runner.py: the bench never ran postprocessing - it measured raw engine text, so entity retention (66.7%) never reflected rules/glossary. _transcribe_clip now builds Segments and runs run_postprocess(settings, glossary) before metrics; manifest top-level glossary {pattern: replacement} is supported and recorded in run_config (post_mode/glossary).

3. glossary plumbing: CLI transcribe gains --glossary KEY=VALUE (repeatable, parsed + validated); BatchPipeline.run accepts glossary= and passes it to run_postprocess; the in-proc worker forwards job.options.glossary or post_correction.

Notebook: transcribe cells pass --glossary BLM=vLLM, bench manifest carries glossary, postprocess section documents rules/glossary/hotword.

+ 9 unit tests (BLM rule, boundary/case behavior, bench postprocess + glossary entity retention). 147 tests pass, ruff clean.

tests/unit/test_benchmark.py

@@ -0,0 +1,143 @@
+"""벤치마크 단위 테스트 — 후처리 적용 + glossary 지원.
+
+벤치 지표는 원시 전사가 아니라 후처리(rules/glossary)를 거친 결과를 측정해야
+한다 (vLLM→BLM 같은 오인식 복원 포함).
+"""
+
+from __future__ import annotations
+
+from luke_scribe.benchmark.runner import _run_model, _transcribe_clip
+from luke_scribe.config import Settings
+from luke_scribe.engine.base import TranscriptionOptions
+
+REF_TEXT = "오늘은 vLLM 서버를 Kubernetes 클러스터에 배포합니다"
+ENTITIES = [
+    {"canonical": "vLLM", "surface": "vLLM", "start_char": 4, "end_char": 8},
+    {"canonical": "Kubernetes", "surface": "Kubernetes", "start_char": 13, "end_char": 23},
+]
+
+
+class _FakeOwner:
+    """세그먼트 dict를 반환하는 가짜 owner (dict 계약 사용)."""
+
+    def __init__(self, texts: list[str]) -> None:
+        self._texts = texts
+
+    def transcribe(self, req):  # noqa: ANN001
+        segs = [
+            {
+                "index": i,
+                "start": i * 2.0,
+                "end": i * 2.0 + 2.0,
+                "text": t,
+                "avg_logprob": -0.2,
+                "no_speech_prob": 0.01,
+            }
+            for i, t in enumerate(self._texts)
+        ]
+        return {
+            "segments": iter(segs),
+            "device": "cpu",
+            "compute_type": "int8",
+            "attempted_profiles": [{}],
+            "info": {"language": "ko"},
+        }
+
+
+class TestTranscribeClipPostprocess:
+    def test_rules_fix_blm_to_vllm(self):
+        owner = _FakeOwner(["오늘은 BLM 서버를 Kubernetes 클러스터에 배포합니다"])
+        settings = Settings(_env_file=None, post_mode="rules", post_enabled=True)
+        clip = {"audio_path": "x.mp3", "duration_sec": 10.0}
+        out = _transcribe_clip(owner, TranscriptionOptions(), clip, settings, None)
+        assert "vLLM" in out["text"]
+        assert "BLM" not in out["text"]
+
+    def test_glossary_applied(self):
+        owner = _FakeOwner(["브이엘엘엠 서버"])
+        settings = Settings(_env_file=None, post_mode="glossary", post_enabled=True)
+        clip = {"audio_path": "x.mp3", "duration_sec": 10.0}
+        out = _transcribe_clip(
+            owner, TranscriptionOptions(), clip, settings, {"브이엘엘엠": "vLLM"}
+        )
+        assert "vLLM" in out["text"]
+
+    def test_postprocess_disabled_keeps_raw(self):
+        owner = _FakeOwner(["오늘은 BLM 서버"])
+        settings = Settings(_env_file=None, post_mode="rules", post_enabled=False)
+        clip = {"audio_path": "x.mp3", "duration_sec": 10.0}
+        out = _transcribe_clip(owner, TranscriptionOptions(), clip, settings, None)
+        assert "BLM" in out["text"]
+
+
+class TestRunModelPostprocess:
+    def _report(self) -> dict:
+        return {"run_config": {"hotword_set": []}}
+
+    def _clip(self, ref_path: str) -> dict:
+        return {
+            "id": "c1",
+            "audio_path": "x.mp3",
+            "reference_path": ref_path,
+            "duration_sec": 10.0,
+            "entities": ENTITIES,
+        }
+
+    def test_entity_retention_full_with_rules(self, tmp_path):
+        ref = tmp_path / "ref.txt"
+        ref.write_text(REF_TEXT, encoding="utf-8")
+        owner = _FakeOwner(["오늘은 BLM 서버를 Kubernetes 클러스터에 배포합니다"])
+        settings = Settings(_env_file=None, post_mode="rules", post_enabled=True)
+        agg = _run_model(
+            owner,
+            [self._clip(str(ref))],
+            "large-v3-turbo",
+            "cpu",
+            "int8",
+            1,
+            [],
+            self._report(),
+            settings,
+            None,
+        )
+        assert agg["summary"]["entity_retention"] == 1.0
+        assert agg["summary"]["failure_rate"] == 0.0
+
+    def test_glossary_raises_entity_retention(self, tmp_path):
+        ref = tmp_path / "ref.txt"
+        ref.write_text(REF_TEXT, encoding="utf-8")
+        owner = _FakeOwner(["오늘은 BLM 서버를 Kubernetes 클러스터에 배포합니다"])
+        settings = Settings(_env_file=None, post_mode="glossary", post_enabled=True)
+        agg = _run_model(
+            owner,
+            [self._clip(str(ref))],
+            "large-v3-turbo",
+            "cpu",
+            "int8",
+            1,
+            [],
+            self._report(),
+            settings,
+            {"BLM": "vLLM"},
+        )
+        assert agg["summary"]["entity_retention"] == 1.0
+
+    def test_raw_text_fails_entity_retention_without_postprocess(self, tmp_path):
+        # 후처리 없이 raw 전사("BLM")를 측정하면 vLLM 엔티티가 보존되지 않는다
+        ref = tmp_path / "ref.txt"
+        ref.write_text(REF_TEXT, encoding="utf-8")
+        owner = _FakeOwner(["오늘은 BLM 서버를 Kubernetes 클러스터에 배포합니다"])
+        settings = Settings(_env_file=None, post_mode="none", post_enabled=False)
+        agg = _run_model(
+            owner,
+            [self._clip(str(ref))],
+            "large-v3-turbo",
+            "cpu",
+            "int8",
+            1,
+            [],
+            self._report(),
+            settings,
+            None,
+        )
+        assert agg["summary"]["entity_retention"] < 1.0