feat: add standalone AI/Tech regime-change monitor tab

A new /regime tab scoring how far the AI/Tech bull regime has deteriorated
toward a re-rating as a single 0-100 index with per-signal breakdown and a
7/30-day trend. Intentionally decoupled: nothing reads its output to gate or
score trades — the daily-pipeline membership is scheduling only.

- regime_monitor_service: price sub-scores (P1-P6 via Alpaca, like
  market_regime), VIX + HY credit spreads via a small FRED helper, weighted
  aggregation over available signals (missing source -> n/a, dropped from the
  denominator), one snapshot row/day, and a ~90-day history backfill by
  replaying the already-fetched series as-of each past day.
- F1/F3 fundamentals proposed by the configured grounded LLM (reuses
  sentiment_provider_service config resolution), with a manual override + lock.
- regime_snapshots table (migration 011); endpoints on the existing market
  router; admin-editable weights/threshold; standalone /regime page.

Data needs: prices via Alpaca, VIX/credit via FRED (optional key — signals show
n/a without it). No LLM needed for history.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

app/models/__init__.py

@@ -10,6 +10,7 @@ from app.models.watchlist import WatchlistEntry
 from app.models.settings import SystemSetting, IngestionProgress
 from app.models.alert import AlertLog
 from app.models.paper_trade import PaperTrade
+from app.models.regime_snapshot import RegimeSnapshot
 
 __all__ = [
     "Ticker",
@@ -26,4 +27,5 @@ __all__ = [
     "IngestionProgress",
     "AlertLog",
     "PaperTrade",
+    "RegimeSnapshot",
 ]

app/models/regime_snapshot.py

@@ -0,0 +1,26 @@
+from datetime import date as date_type
+from datetime import datetime
+
+from sqlalchemy import Date, DateTime, Float, String, Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.database import Base
+
+
+class RegimeSnapshot(Base):
+    """Daily snapshot of the AI/Tech regime-change index.
+
+    One row per calendar date (unique). ``breakdown_json`` holds the full
+    per-signal breakdown plus the raw inputs, so reads need no recomputation and
+    the 7/30-day trend is just a query over ``total_score``. Decoupled from the
+    rest of the platform: nothing reads this to gate or score trades.
+    """
+
+    __tablename__ = "regime_snapshots"
+
+    id: Mapped[int] = mapped_column(primary_key=True)
+    date: Mapped[date_type] = mapped_column(Date, nullable=False, unique=True, index=True)
+    total_score: Mapped[float] = mapped_column(Float, nullable=False)
+    band: Mapped[str] = mapped_column(String(20), nullable=False)
+    breakdown_json: Mapped[str] = mapped_column(Text, nullable=False)
+    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)