feat(enrichment): alias-aware scoring — auto-confirm non-Latin-primary artists (#772)

* feat(enrichment): loose MusicBrainz search fallback (find aliased artists)

The MB text search used a strict field-phrase query
(`recording:"<title>" AND artist:"<artist>"`). A field phrase only matches
MusicBrainz's *primary* artist/title — it never searches ALIASES — so a
recording stored under a non-Latin primary name (大橋純子) whose romanized
form ("Junko Ohashi") is only an alias returns ZERO results, even though MB
has it. Whole swaths of a community library (e.g. romanized J-pop / city-pop
charts) were unsearchable.

- `build_recording_query(..., loose=True)` drops the field scoping + phrases
  for plain AND-ed term groups (`(telephone number) AND (junko ohashi)`),
  which searches the whole document incl. aliases.
- `_mb_search_recordings` runs the strict query first (unchanged, high
  precision) and only on an EMPTY result retries once with the loose query —
  so mainstream matches are untouched and the extra throttled request is spent
  only on a miss. Results are re-scored by rank_candidates, so recall goes up
  without lowering match quality (auto-accept still needs the per-field floors).

Verified live: "Junko Ohashi / Telephone Number" and "Anri / Windy Summer"
(both 0 under the strict query) now surface the real records; "AC/DC /
Highway to Hell" still hits strict at score 1.0 with no loose retry.

Follow-up (separate): alias-aware SCORING so these can auto-confirm, not just
appear as manual candidates.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* feat(enrichment): alias-aware scoring (auto-confirm non-Latin-primary artists)

Builds on the loose-search fallback: that surfaces a recording stored under a
Japanese primary name (大橋純子) via its romanized alias, but the SCORER still
compared the reference ("Junko Ohashi") against the primary only → artist
similarity 0 → below the auto floor, so it could only ever be a manual
candidate, never an auto-fill.

- mb_match: `cand_artist_sim` takes the best similarity over the candidate's
  primary name AND its `artist_aliases`; score_candidate + classify use it.
- server: `_mb_artist_aliases(id)` fetches an artist's aliases (one throttled
  lookup, process-cached — a one-artist discography costs ONE request) and
  `_alias_enrich` attaches them ONLY to promising near-misses (title agrees,
  primary artist doesn't) so a normal pass spends zero extra requests. Wired
  into both the auto-matcher (_enrich_one) and the manual search proxy.

Verified live: "Junko Ohashi / Telephone Number" → 大橋純子 candidate goes from
score 0.5 (loose-only) to 1.0 (auto-confirmable), ranked #1; "AC/DC / Highway
to Hell" unchanged at 1.0 with no alias lookup.

Stacks on #771 (feat/mb-loose-search-fallback).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(enrichment): keep live exclusion in the loose search fallback

The loose fallback dropped the strict path's -secondarytype:Live filter, so a
studio chart whose strict query missed could fall back to — and, since
score_candidate doesn't penalize live takes, auto-confirm — a live-only
recording. Apply the same live gate to the loose query (skipped only when the
source title is itself a live take).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: byrongamatos <xasiklas@gmail.com>

tests/test_mb_enrichment.py

@@ -134,6 +134,57 @@ def test_search_does_not_retry_when_strict_hits(server, monkeypatch):
     assert len(calls) == 1
 
 
+# ── alias-aware scoring (non-Latin-primary artists) ──────────────────────────
+
+_AID = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
+
+
+def test_artist_aliases_fetched_and_cached(server, monkeypatch):
+    calls = []
+
+    def fake(path, params):
+        calls.append(path)
+        return {"sort-name": "Ohashi, Junko",
+                "aliases": [{"name": "Junko Ohashi"}, {"name": "大橋 純子"}]}
+
+    monkeypatch.setattr(server, "_mb_http_get", fake)
+    names = server._mb_artist_aliases(_AID)
+    assert "Junko Ohashi" in names and "Ohashi, Junko" in names
+    server._mb_artist_aliases(_AID)          # cached → no second request
+    assert len(calls) == 1
+
+
+def test_artist_aliases_rejects_bad_id(server, monkeypatch):
+    def boom(path, params):
+        raise AssertionError("must not fetch for a non-UUID id")
+
+    monkeypatch.setattr(server, "_mb_http_get", boom)
+    assert server._mb_artist_aliases("not-a-uuid") == []
+
+
+def test_enrich_auto_matches_japanese_primary_via_alias(server, monkeypatch):
+    # A pack whose (romanized) artist MB stores under a Japanese primary name.
+    _put(server, "x.sloppak", title="Telephone Number", artist="Junko Ohashi")
+
+    def _routed(path, params):
+        if path.startswith("artist/"):                      # alias lookup
+            return {"sort-name": "Ohashi, Junko",
+                    "aliases": [{"name": "Junko Ohashi"}]}
+        q = params.get("query", "")
+        if q.startswith("recording:"):                      # strict phrase → nothing
+            return {"recordings": []}
+        return {"recordings": [mb_doc(rid="rec-jp", title="Telephone Number",
+                                      artist="大橋純子", artist_id=_AID)]}   # loose hit
+
+    monkeypatch.setattr(server, "_mb_http_get", _routed)
+    monkeypatch.setattr(server, "_enrich_network_enabled", lambda: True)
+    server._background_enrich()
+    row = server.meta_db.get_enrichment("x.sloppak")
+    # The romanized alias lifts the artist over the auto floor → auto-confirmed.
+    assert row["match_state"] == "matched"
+    assert row["mb_recording_id"] == "rec-jp"
+
+
 # ── offline safety (the pytest-never-hits-network contract) ──────────────────
 
 def test_offline_default_skips_matching(server, monkeypatch):

tests/test_mb_match.py

@@ -216,6 +216,27 @@ def test_build_recording_query_loose_keeps_live_for_live_charts():
     assert loose == "(highway to hell) AND (ac dc)"
 
 
+# ── alias-aware artist scoring ────────────────────────────────────────────────
+
+def test_cand_artist_sim_uses_aliases():
+    song = {"artist": "Junko Ohashi", "title": "Telephone Number"}
+    # primary is the Japanese name → romanized reference scores 0…
+    assert m.cand_artist_sim(song, {"artist": "大橋純子"}) == 0.0
+    # …but a romanized alias confirms it
+    assert m.cand_artist_sim(
+        song, {"artist": "大橋純子", "artist_aliases": ["Ohashi Junko", "Junko Ohashi"]}) == 1.0
+
+
+def test_alias_lifts_candidate_to_auto():
+    song = {"artist": "Junko Ohashi", "title": "Telephone Number"}
+    jp = {"artist": "大橋純子", "title": "Telephone Number"}
+    # Without the alias: title matches but the artist floor fails → never auto.
+    assert m.classify(song, jp, m.score_candidate(song, jp)) != "auto"
+    # With the romanized alias attached: artist clears the floor → auto.
+    jp_alias = dict(jp, artist_aliases=["Junko Ohashi"])
+    assert m.classify(song, jp_alias, m.score_candidate(song, jp_alias)) == "auto"
+
+
 # ── MusicBrainz response parsing ──────────────────────────────────────────────
 
 MB_DOC = {