feat(monitoring): multi-model dashboard v2.1 — tabs, per-model records, voice playback + MinIO dual-write

Problem: the dashboard was Jev-centric; NLU/arbiter/fallback DeepSeek, STT
providers and the audio-enhancer were barely visible, and stored texts/voices
had no real access path.

Bot (additive; reply path untouched):
- nlu.result now records latency_ms + the DeepSeek usage tokens
- matching.arbitration/fallback.result fill the model + latency_ms columns
  (payload unchanged; SQL coalesces column/payload so old rows still count)
- storage.py: MinIO dual-write layer — every voice (raw + denoised) and user
  attachment is mirrored fire-and-forget into bucket bot-media; the blocking
  minio SDK runs via asyncio.to_thread (senior-engineer review) so the event
  loop is never stalled; empty MINIO_* env = layer off; bucket auto-created
- requirements: minio>=7.2

Backend (admin-gated, read-only):
- GET /bot-metrics/models — one record per model (jev, deepseek-nlu,
  deepseek-arbiter, deepseek-fallback, audio-enhancer + dynamic per-provider
  STT) with calls/ok-rate/p50/p95/tokens/last-seen + version-drift vs the pin
- GET /bot-metrics/models/{id}/daily — per-model daily calls/fails/tokens/p50
- GET /bot-metrics/stages — every stage tagged with its Persian pipeline
  section (صوت/درک پیام/تطبیق/ابهام و انتخاب/پیش‌نویس)
- /traces now carries input_kind + a 120-char text excerpt (consensus →
  input.text → first STT transcript)
- media serving: POST /media-url mints a short-lived HMAC URL (audio/a tags
  cannot send Authorization); GET /media streams from MinIO bot-media with
  the read-only ./bot/data mount as fallback for pre-MinIO files; hard ref
  validation (voices|attachments only, no .., extension whitelist)
- router exempted from the global Bearer dependency (files.py pattern) —
  every endpoint keeps its own require_role('admin')

Frontend /bot-monitor (RTL, recharts):
- four tabs: نمای کلی / مدل‌ها (records table + per-model expandable daily
  charts: calls/fails, tokens, p50) / بخش‌ها (sections grouped) / پیام‌ها
- message drawer rebuilt: inline <audio controls> for raw + denoised voice,
  download links, every STT transcript + consensus side-by-side, user
  attachments, then the event timeline
- terminology: «ترس» → «پرونده‌ی پیام» with tooltips + a one-line legend

Grafana: bot-observability gains a «کارکرد مدل‌ها» table (stage→model
mapping for legacy rows); the explorer gains a message text column.

Seed: real (tiny) ogg files written + mirrored to MinIO, NLU usage tokens,
column-level model/latency on matching events.

Verified locally: /models returns all 7 records incl. per-STT and NLU tokens;
media 200 via signed URL (MinIO) and 401 without; ../ and .py rejected (400);
disk fallback serves a legacy file; pm-role 403 on every new endpoint;
bucket auto-created with 14 mirrored objects; tsc + vite build clean;
Grafana re-provisions 24 panels.

bot/tools/seed_observability_demo.py

@@ -82,8 +82,19 @@ async def one_trace(s, chat_id: int, t0: datetime, kind: str) -> None:
     m = 0.0
     # ---- input
     if kind == "voice":
+        # a real (tiny, silent) ogg so the media player/download path has bytes
+        day = t0.strftime("%Y%m%d")
+        vdir = Path("data/voices") / day
+        vdir.mkdir(parents=True, exist_ok=True)
+        vpath = vdir / f"{tid}_{rng.randrange(1000, 99999)}.ogg"
+        vpath.write_bytes(bytes.fromhex("4f6767530002000000000000000000000001") + b"\x00" * 3000)
         await ev("input.voice", minutes=m, payload={
-            "path": f"data/voices/demo/{tid}.ogg", "size": 21400, "mime": "audio/ogg"})
+            "path": vpath.as_posix(), "size": vpath.stat().st_size, "mime": "audio/ogg"})
+        try:  # second copy in MinIO exactly like the live bot does
+            from app import storage
+            await storage.mirror_to_minio(storage.media_ref(vpath) or "", vpath, "audio/ogg")
+        except Exception:
+            pass
         # audio enhancement (new in 787824a)
         ok_enh = rng.random() < 0.85
         await ev("audio.enhance.result", minutes=(m := m + 0.1), ok=ok_enh,
@@ -111,7 +122,9 @@ async def one_trace(s, chat_id: int, t0: datetime, kind: str) -> None:
     mentions = _mentions(rng.randint(3, 6))
     await ev("nlu.result", minutes=(m := m + 0.9), latency=rng.randrange(1500, 3600),
              model="deepseek-chat", payload={
-                 "intent": "register_quote", "consensus_text": payload_text})
+                 "intent": "register_quote", "consensus_text": payload_text,
+                 "usage": {"input_tokens": rng.randint(600, 2200),
+                           "output_tokens": rng.randint(150, 900)}})
     await ev("entities.extracted", minutes=(m := m + 0.02), payload={"entity_mentions": mentions})
 
     # ---- Jev scoring + arbitration/fallback (two-stage, 787824a)