Hold fix

README.md

@@ -119,6 +119,12 @@ Safer learning defaults (already enabled by default):
 python adaptive_bot.py --interval 15m --min-model-samples-for-signal 50 --pause-on-negative-expectancy
 ```
 
+Auto-expire the safety pause after 3 hours (default) so the bot can retry entries:
+
+```bash
+python adaptive_bot.py --interval 15m --pause-cooldown-minutes 180
+```
+
 Enable periodic ML progress updates to Telegram (good for phone monitoring):
 
 ```bash
@@ -227,6 +233,7 @@ Environment variables used by the container:
 - `BOT_PAUSE_EXPECTANCY_LOOKBACK` (default `30`)
 - `BOT_PAUSE_EXPECTANCY_THRESHOLD_USD` (default `-1.0`)
 - `BOT_PAUSE_MAX_DRAWDOWN_PCT` (default `12.0`)
+- `BOT_PAUSE_COOLDOWN_MINUTES` (default `180`, set `0` to disable auto-expiry)
 - `ALLOW_LIVE_TRADING` (set to `1/true/yes` to manually approve live trading)
 - `BOT_LIVE_STARTUP_TEST` (set non-empty to add `--live-startup-test`)
 - `BOT_LIVE_STARTUP_TEST_COIN` (default `BTC`)

adaptive_bot.py

@@ -535,6 +535,7 @@ class AdaptiveHyperliquidBot:
         pause_expectancy_lookback: int,
         pause_expectancy_threshold_usd: float,
         pause_max_drawdown_pct: float,
+        pause_cooldown_minutes: float,
         telegram_ml_report_hours: float,
         telegram_ml_report_min_trades: int,
         health_host: str,
@@ -567,6 +568,9 @@ class AdaptiveHyperliquidBot:
         self.pause_expectancy_lookback = int(max(10, pause_expectancy_lookback))
         self.pause_expectancy_threshold_usd = float(pause_expectancy_threshold_usd)
         self.pause_max_drawdown_pct = float(max(0.0, pause_max_drawdown_pct))
+        self.pause_cooldown_minutes = float(max(0.0, pause_cooldown_minutes))
+        self._safety_pause_started_ts: Optional[float] = None
+        self._safety_pause_wait_recovery: bool = False
         self.telegram_ml_report_hours = float(max(0.0, telegram_ml_report_hours))
         self.telegram_ml_report_min_trades = int(max(0, telegram_ml_report_min_trades))
         self.health_host = health_host
@@ -626,6 +630,16 @@ class AdaptiveHyperliquidBot:
     def status_payload(self) -> Dict[str, Any]:
         metrics = self.learning.global_metrics()
         approval = self._live_approval_status_details()
+        safety_pause = {
+            "enabled": self.pause_on_negative_expectancy,
+            "lookback": self.pause_expectancy_lookback,
+            "expectancy_threshold_usd": self.pause_expectancy_threshold_usd,
+            "max_drawdown_pct": self.pause_max_drawdown_pct,
+            "cooldown_minutes": self.pause_cooldown_minutes,
+            "active": self._safety_pause_started_ts is not None,
+            "active_since_ts": self._safety_pause_started_ts,
+            "wait_recovery": self._safety_pause_wait_recovery,
+        }
         return {
             "service": "hyperliquid-adaptive-bot",
             "status": "ok" if self._running else "stopping",
@@ -656,6 +670,7 @@ class AdaptiveHyperliquidBot:
             },
             "model_samples": self.learning.model_samples,
             "min_model_samples_for_signal": self.min_model_samples_for_signal,
+            "safety_pause": safety_pause,
         }
 
     def status_overview_payload(self) -> Dict[str, Any]:
@@ -785,23 +800,64 @@ class AdaptiveHyperliquidBot:
 
     def _entry_pause_reason(self) -> Optional[str]:
         if not self.pause_on_negative_expectancy:
+            self._safety_pause_started_ts = None
+            self._safety_pause_wait_recovery = False
             return None
         pnl = [float(t.get("pnl_usd", 0.0)) for t in self.learning.closed_trades]
         if len(pnl) < self.pause_expectancy_lookback:
+            self._safety_pause_started_ts = None
+            self._safety_pause_wait_recovery = False
             return None
         exp_recent = float(np.mean(pnl[-self.pause_expectancy_lookback:]))
         if exp_recent >= self.pause_expectancy_threshold_usd:
+            if self._safety_pause_wait_recovery:
+                logger.info("Safety pause re-armed after expectancy recovered (expectancy_%d=%+.3f).", self.pause_expectancy_lookback, exp_recent)
+            self._safety_pause_started_ts = None
+            self._safety_pause_wait_recovery = False
             return None
 
         max_dd = self.learning.ml_progress_metrics().get("max_drawdown_pct")
         max_dd_val = float(max_dd) if max_dd is not None else 0.0
         if max_dd_val < self.pause_max_drawdown_pct:
+            if self._safety_pause_wait_recovery:
+                logger.info("Safety pause re-armed after drawdown recovered (max_dd=%.2f%%).", max_dd_val)
+            self._safety_pause_started_ts = None
+            self._safety_pause_wait_recovery = False
             return None
-        return (
+
+        if self._safety_pause_wait_recovery:
+            return None
+
+        reason = (
             f"safety_pause expectancy_{self.pause_expectancy_lookback}={exp_recent:+.3f} "
             f"< {self.pause_expectancy_threshold_usd:+.3f} and max_dd={max_dd_val:.2f}%"
         )
 
+        if self.pause_cooldown_minutes <= 0:
+            return reason
+
+        now_ts = time.time()
+        if self._safety_pause_started_ts is None:
+            self._safety_pause_started_ts = now_ts
+
+        cooldown_seconds = self.pause_cooldown_minutes * 60.0
+        elapsed_seconds = now_ts - self._safety_pause_started_ts
+        if elapsed_seconds >= cooldown_seconds:
+            self._safety_pause_started_ts = None
+            self._safety_pause_wait_recovery = True
+            logger.warning(
+                "Safety pause cooldown expired after %.1f minutes; allowing entries until metrics recover.",
+                self.pause_cooldown_minutes,
+            )
+            return None
+
+        remaining_seconds = int(max(0.0, cooldown_seconds - elapsed_seconds))
+        remaining_minutes = remaining_seconds // 60
+        remaining_remainder = remaining_seconds % 60
+        return (
+            f"{reason} (cooldown {remaining_minutes:02d}m{remaining_remainder:02d}s remaining)"
+        )
+
     def _live_approval_granted(self) -> bool:
         return self._live_approval_status_details()["granted"]
 
@@ -1423,6 +1479,12 @@ def build_arg_parser() -> argparse.ArgumentParser:
         default=float(os.environ.get("BOT_PAUSE_MAX_DRAWDOWN_PCT", "12.0")),
         help="Pause only when max drawdown is also at/above this percentage",
     )
+    p.add_argument(
+        "--pause-cooldown-minutes",
+        type=float,
+        default=float(os.environ.get("BOT_PAUSE_COOLDOWN_MINUTES", "180")),
+        help="Minutes to keep safety pause active before auto-resuming entries until metrics recover (0 disables auto-expiry)",
+    )
     p.add_argument(
         "--telegram-ml-report-hours",
         type=float,
@@ -1466,6 +1528,7 @@ def main() -> None:
         pause_expectancy_lookback=args.pause_expectancy_lookback,
         pause_expectancy_threshold_usd=args.pause_expectancy_threshold_usd,
         pause_max_drawdown_pct=args.pause_max_drawdown_pct,
+        pause_cooldown_minutes=args.pause_cooldown_minutes,
         telegram_ml_report_hours=args.telegram_ml_report_hours,
         telegram_ml_report_min_trades=args.telegram_ml_report_min_trades,
         health_host=args.health_host,