Add Torch probe entries and Pi artifact sync

.env

@@ -67,6 +67,10 @@ TIME_SERIES_MIN_CONFIDENCE=0.4
 TIME_SERIES_MAX_ADJUSTMENT=0.08
 TIME_SERIES_LSTM_ENABLED=true
 TIME_SERIES_LSTM_MODEL_PATH=runtime/lstm_forecaster.json
+TIME_SERIES_PROBE_ENABLED=true
+TIME_SERIES_PROBE_MIN_EDGE_PERCENT=0.02
+TIME_SERIES_PROBE_MIN_PROBABILITY_UP=0.55
+TIME_SERIES_PROBE_SIZE_MULTIPLIER=0.40
 STOP_LOSS_PERCENT=0.04
 TAKE_PROFIT_PERCENT=0.035
 TRAILING_STOP_PERCENT=0.015

.env.example

@@ -67,6 +67,10 @@ TIME_SERIES_MIN_CONFIDENCE=0.4
 TIME_SERIES_MAX_ADJUSTMENT=0.08
 TIME_SERIES_LSTM_ENABLED=true
 TIME_SERIES_LSTM_MODEL_PATH=runtime/lstm_forecaster.json
+TIME_SERIES_PROBE_ENABLED=true
+TIME_SERIES_PROBE_MIN_EDGE_PERCENT=0.02
+TIME_SERIES_PROBE_MIN_PROBABILITY_UP=0.55
+TIME_SERIES_PROBE_SIZE_MULTIPLIER=0.40
 STOP_LOSS_PERCENT=0.04
 TAKE_PROFIT_PERCENT=0.035
 TRAILING_STOP_PERCENT=0.015

README.md

@@ -88,7 +88,13 @@ powershell -ExecutionPolicy Bypass -File tools\run_torch_retrain.ps1
 powershell -ExecutionPolicy Bypass -File tools\install_windows_torch_retrainer.ps1
 ```
 
-По умолчанию Windows-расписание переобучает PyTorch `LSTM/GRU` каждые 6 часов с `--limit 3000` на парах `BTCUSDT,ETHUSDT,SOLUSDT,LTCUSDT`. Параметры можно переопределить через env: `TORCH_RETRAIN_SYMBOLS`, `TORCH_RETRAIN_LIMIT`, `TORCH_RETRAIN_LOOKBACKS`, `TORCH_RETRAIN_ARCHITECTURES`, `TORCH_RETRAIN_HIDDEN_SIZES`, `TORCH_RETRAIN_LAYERS`, `TORCH_RETRAIN_DROPOUTS`, `TORCH_RETRAIN_HORIZON`, `TORCH_RETRAIN_HORIZONS`, `TORCH_RETRAIN_CONTEXT_SYMBOLS`, `TORCH_RETRAIN_FEATURES`, `TORCH_RETRAIN_EPOCHS`, `TORCH_RETRAIN_PATIENCE`, `TORCH_RETRAIN_INTERVAL`, `TORCH_RETRAIN_ENV`.
+По умолчанию Windows-расписание переобучает PyTorch `LSTM/GRU` каждые 6 часов с `--limit 3000` на парах `BTCUSDT,ETHUSDT,SOLUSDT,LTCUSDT`. Параметры можно переопределить через env: `TORCH_RETRAIN_SYMBOLS`, `TORCH_RETRAIN_LIMIT`, `TORCH_RETRAIN_LOOKBACKS`, `TORCH_RETRAIN_ARCHITECTURES`, `TORCH_RETRAIN_HIDDEN_SIZES`, `TORCH_RETRAIN_LAYERS`, `TORCH_RETRAIN_DROPOUTS`, `TORCH_RETRAIN_HORIZON`, `TORCH_RETRAIN_HORIZONS`, `TORCH_RETRAIN_CONTEXT_SYMBOLS`, `TORCH_RETRAIN_FEATURES`, `TORCH_RETRAIN_SEED`, `TORCH_RETRAIN_EPOCHS`, `TORCH_RETRAIN_PATIENCE`, `TORCH_RETRAIN_INTERVAL`, `TORCH_RETRAIN_ENV`.
+
+Если retrain запускается с `-DeployToPi`, после успешного guard он синхронизирует `runtime/lstm_forecaster.json`, `runtime/torch_retrain_guard.json` и `runtime/torch_threshold_calibration.json` на Raspberry Pi через SSH-ключ и перезапускает сервис `tradebot`. Отдельный запуск sync:
+
+```powershell
+powershell -ExecutionPolicy Bypass -File tools\sync_torch_artifacts_to_pi.ps1 -RemoteHost 192.168.0.185 -RemoteUser sevenhill -RemoteRoot /mnt/data/tradebot
+```
 
 Внутри recurrent модели используются exportable attention pooling и LayerNorm перед forecast-head; Raspberry Pi по-прежнему исполняет модель из JSON без PyTorch runtime.
 
@@ -165,6 +171,10 @@ TIME_SERIES_MIN_CONFIDENCE=0.4
 TIME_SERIES_MAX_ADJUSTMENT=0.08
 TIME_SERIES_LSTM_ENABLED=true
 TIME_SERIES_LSTM_MODEL_PATH=runtime/lstm_forecaster.json
+TIME_SERIES_PROBE_ENABLED=true
+TIME_SERIES_PROBE_MIN_EDGE_PERCENT=0.02
+TIME_SERIES_PROBE_MIN_PROBABILITY_UP=0.55
+TIME_SERIES_PROBE_SIZE_MULTIPLIER=0.40
 STOP_LOSS_PERCENT=0.04
 TAKE_PROFIT_PERCENT=0.035
 TRAILING_STOP_PERCENT=0.015

crypto_spot_bot/config.py

@@ -118,6 +118,10 @@ class Settings:
     time_series_max_adjustment: float
     time_series_lstm_enabled: bool
     time_series_lstm_model_path: Path
+    time_series_probe_enabled: bool
+    time_series_probe_min_edge_percent: float
+    time_series_probe_min_probability_up: float
+    time_series_probe_size_multiplier: float
     stop_loss_percent: float
     take_profit_percent: float
     trailing_stop_percent: float
@@ -266,6 +270,10 @@ def load_settings(env_file: str | Path | None = None) -> Settings:
         time_series_max_adjustment=_float_env("TIME_SERIES_MAX_ADJUSTMENT", 0.08),
         time_series_lstm_enabled=_bool_env("TIME_SERIES_LSTM_ENABLED", True),
         time_series_lstm_model_path=Path(os.getenv("TIME_SERIES_LSTM_MODEL_PATH", "runtime/lstm_forecaster.json")),
+        time_series_probe_enabled=_bool_env("TIME_SERIES_PROBE_ENABLED", True),
+        time_series_probe_min_edge_percent=_float_env("TIME_SERIES_PROBE_MIN_EDGE_PERCENT", 0.02),
+        time_series_probe_min_probability_up=_float_env("TIME_SERIES_PROBE_MIN_PROBABILITY_UP", 0.55),
+        time_series_probe_size_multiplier=_float_env("TIME_SERIES_PROBE_SIZE_MULTIPLIER", 0.40),
         stop_loss_percent=_float_env("STOP_LOSS_PERCENT", 0.04),
         take_profit_percent=_float_env("TAKE_PROFIT_PERCENT", 0.035),
         trailing_stop_percent=_float_env("TRAILING_STOP_PERCENT", 0.015),

crypto_spot_bot/dashboard.py

@@ -261,6 +261,10 @@ def _safe_config(settings: Settings) -> dict[str, Any]:
         "time_series_max_adjustment": settings.time_series_max_adjustment,
         "time_series_lstm_enabled": settings.time_series_lstm_enabled,
         "time_series_lstm_model_path": str(settings.time_series_lstm_model_path),
+        "time_series_probe_enabled": settings.time_series_probe_enabled,
+        "time_series_probe_min_edge_percent": settings.time_series_probe_min_edge_percent,
+        "time_series_probe_min_probability_up": settings.time_series_probe_min_probability_up,
+        "time_series_probe_size_multiplier": settings.time_series_probe_size_multiplier,
         "time_series_model_artifact": _time_series_model_artifact(settings),
         "stop_loss_percent": settings.stop_loss_percent,
         "take_profit_percent": settings.take_profit_percent,
@@ -678,7 +682,8 @@ HTML = r"""
             ['Horizon', String(artifact.target_horizon ?? '')],
             ['Min edge', `${num(config?.time_series_min_edge_percent, 3)}%`],
             ['Min P(up)', `${num((config?.time_series_min_probability_up || 0) * 100, 1)}%`],
-            ['Min confidence', num(config?.time_series_min_confidence, 3)]
+            ['Min confidence', num(config?.time_series_min_confidence, 3)],
+            ['Probe entry', config?.time_series_probe_enabled ? `${num(config?.time_series_probe_min_edge_percent, 3)}% / P ${num((config?.time_series_probe_min_probability_up || 0) * 100, 1)}% / size ${num((config?.time_series_probe_size_multiplier || 0) * 100, 0)}%` : 'off']
           ]))}
         </div>
         ${positionsPanel()}
@@ -699,6 +704,9 @@ HTML = r"""
       const quality = market.quality || {};
       const signal = latestSignals[symbol] || {};
       const minEdge = state.data.config?.time_series_min_edge_percent ?? 0;
+      const probeEnabled = Boolean(state.data.config?.time_series_probe_enabled);
+      const probeEdge = state.data.config?.time_series_probe_min_edge_percent ?? 0;
+      const probeProbability = state.data.config?.time_series_probe_min_probability_up ?? 0;
       const minConfidence = state.data.config?.time_series_min_confidence ?? 0;
       const diagnostics = parseDiagnostics(signal);
       const failed = Object.entries(diagnostics.checks || {}).filter(([, ok]) => !ok).map(([key]) => key);
@@ -716,6 +724,7 @@ HTML = r"""
             ['Model', modelName(forecast.model)],
             ['Edge', `${signed(forecast.expected_return_percent, 4)}% / min ${num(minEdge, 3)}%`],
             ['P(up)', num((forecast.probability_up || 0) * 100, 2) + '%'],
+            ['Probe', probeEnabled ? `${num(probeEdge, 3)}% / P ${num(probeProbability * 100, 1)}% / ${diagnostics.edge_mode || 'n/a'}` : 'off'],
             ['Confidence', `${num(signal.confidence, 4)} / min ${num(minConfidence, 2)}`],
             ['Q10/Q50/Q90', `${signed(forecast.quantile_10_percent, 2)} / ${signed(forecast.quantile_50_percent, 2)} / ${signed(forecast.quantile_90_percent, 2)}`],
             ['Blocked', forecast.block_entry ? 'yes' : 'no']

crypto_spot_bot/strategy.py

@@ -633,6 +633,34 @@ def _torch_forecast_entry_signal(
     skill = _safe_float(forecast.get("skill"), 0.0)
     min_edge = max(0.0, settings.time_series_min_edge_percent)
     min_probability = _torch_min_probability(settings)
+    probe_min_edge = max(0.0, min(settings.time_series_probe_min_edge_percent, min_edge))
+    probe_min_probability = round(
+        _clamp(settings.time_series_probe_min_probability_up, min_probability, 0.85),
+        4,
+    )
+    full_edge_ok = expected_return >= min_edge
+    probe_edge_ok = bool(
+        settings.time_series_probe_enabled
+        and not full_edge_ok
+        and expected_return >= probe_min_edge
+        and probability_up >= probe_min_probability
+    )
+    edge_mode = "full" if full_edge_ok else ("probe" if probe_edge_ok else "blocked")
+    if probe_edge_ok and position_notional > 0:
+        probe_multiplier = _clamp(settings.time_series_probe_size_multiplier, 0.05, 1.0)
+        position_notional = round(
+            min(
+                settings.max_position_usdt,
+                max(settings.min_position_usdt, position_notional * probe_multiplier),
+            ),
+            2,
+        )
+        sizing = {
+            **sizing,
+            "notional_usdt": position_notional,
+            "probe_size_multiplier": round(probe_multiplier, 4),
+            "edge_mode": "probe",
+        }
     confidence = _torch_forecast_confidence(settings, forecast)
     spread_ok = ticker.spread_percent <= settings.max_spread_percent
     liquidity_ok = ticker.turnover_24h >= settings.min_24h_turnover_usdt
@@ -641,7 +669,7 @@ def _torch_forecast_entry_signal(
         "torch_model_ok": model_ok,
         "forecast_usable": bool(forecast.get("usable", False)),
         "forecast_not_blocked": not bool(forecast.get("block_entry", False)),
-        "expected_edge_ok": expected_return >= min_edge,
+        "expected_edge_ok": full_edge_ok or probe_edge_ok,
         "probability_ok": probability_up >= min_probability,
         "skill_ok": skill > 0.0,
         "confidence_ok": confidence >= settings.time_series_min_confidence,
@@ -659,6 +687,10 @@ def _torch_forecast_entry_signal(
         "atr_trailing_multiplier": _clamp(settings.atr_trailing_multiplier, 0.5, 10.0),
         "expected_return_percent": expected_return,
         "min_edge_percent": min_edge,
+        "probe_enabled": settings.time_series_probe_enabled,
+        "probe_min_edge_percent": probe_min_edge,
+        "probe_min_probability_up": probe_min_probability,
+        "edge_mode": edge_mode,
         "probability_up": probability_up,
         "min_probability_up": min_probability,
         "min_confidence": settings.time_series_min_confidence,
@@ -679,7 +711,8 @@ def _torch_forecast_entry_signal(
             (
                 "torch_forecast: PyTorch edge confirmed; "
                 f"model={forecast.get('model')}, p_up={probability_up:.3f}, "
-                f"expected={expected_return:.4f}%, size={position_notional:.2f} USDT"
+                f"expected={expected_return:.4f}%, edge_mode={edge_mode}, "
+                f"size={position_notional:.2f} USDT"
             ),
             diagnostics,
         )

runtime/torch_guard_candidate.json

@@ -1,7 +1,7 @@
 {
   "artifact": {
     "version": 4,
-    "created_at": "2026-06-23T19:07:54.434411+00:00",
+    "created_at": "2026-06-24T18:25:26.346861+00:00",
     "feature_count": 55,
     "target_horizon": 3,
     "target_horizons": [
@@ -16,28 +16,28 @@
         "model": "torch_gru",
         "lookback": 64,
         "hidden_size": 96,
-        "skill": 0.15903346077183758,
+        "skill": 0.17771573949336475,
-        "directional_accuracy": 0.725
+        "directional_accuracy": 0.7166666666666667
       },
       "ETHUSDT": {
-        "model": "torch_gru",
+        "model": "torch_lstm",
         "lookback": 64,
         "hidden_size": 64,
-        "skill": 0.09273757527902074,
+        "skill": 0.08854869730624494,
         "directional_accuracy": 0.6916666666666667
       },
       "SOLUSDT": {
-        "model": "torch_gru",
+        "model": "torch_lstm",
         "lookback": 64,
-        "hidden_size": 96,
+        "hidden_size": 64,
-        "skill": 0.03400498728351002,
+        "skill": 0.022567259691807694,
-        "directional_accuracy": 0.6416666666666667
+        "directional_accuracy": 0.6166666666666667
       },
       "LTCUSDT": {
-        "model": "torch_gru",
+        "model": "torch_lstm",
         "lookback": 64,
-        "hidden_size": 96,
+        "hidden_size": 64,
-        "skill": 0.11954702418314447,
+        "skill": 0.106450769315762,
         "directional_accuracy": 0.6583333333333333
       }
     }
@@ -50,142 +50,75 @@
   },
   "recommended": {
     "edge": 0.1,
-    "probability": 0.6,
+    "probability": 0.59,
-    "confidence": 0.68,
+    "confidence": 0.72,
-    "trades": 16,
+    "trades": 1,
-    "wins": 9,
+    "wins": 1,
-    "win_rate": 0.5625,
+    "win_rate": 1.0,
-    "total_net_percent": 7.917141995065847,
+    "total_net_percent": 0.09543520096249036,
-    "average_net_percent": 0.4948213746916154,
+    "average_net_percent": 0.09543520096249036,
-    "max_drawdown_percent": 1.812991648733242,
+    "max_drawdown_percent": 0.0,
-    "profit_factor": 3.629214989861449,
+    "profit_factor": 999.0,
-    "score": 0.5816887551556058
+    "score": 0.04938446142797822
   },
   "full_replay": {
-    "trades": 5,
+    "trades": 1,
-    "wins": 5,
+    "wins": 1,
     "win_rate": 1.0,
-    "total_net_percent": 9.5746,
+    "total_net_percent": 0.0113,
-    "avg_net_percent": 1.9149,
+    "avg_net_percent": 0.0113,
     "max_drawdown_percent": 0.0,
     "profit_factor": 999.0,
     "trades_detail": [
       {
         "symbol": "ETHUSDT",
-        "entry_timestamp": 1779940800000,
+        "entry_timestamp": 1780462800000,
-        "exit_timestamp": 1779962400000,
+        "exit_timestamp": 1780470000000,
-        "net_percent": 0.1545,
+        "net_percent": 0.0113,
         "reason": "forecast_weak_profit_lock",
-        "held_bars": 6,
+        "held_bars": 2,
-        "entry_probability": 0.6018,
+        "entry_probability": 0.5905,
-        "entry_expected_percent": 0.3155
+        "entry_expected_percent": 0.3024
-      },
-      {
-        "symbol": "ETHUSDT",
-        "entry_timestamp": 1780300800000,
-        "exit_timestamp": 1780336800000,
-        "net_percent": 0.1707,
-        "reason": "forecast_weak_profit_lock",
-        "held_bars": 10,
-        "entry_probability": 0.6164,
-        "entry_expected_percent": 0.3215
-      },
-      {
-        "symbol": "ETHUSDT",
-        "entry_timestamp": 1781154000000,
-        "exit_timestamp": 1781157600000,
-        "net_percent": 0.1476,
-        "reason": "forecast_weak_profit_lock",
-        "held_bars": 1,
-        "entry_probability": 0.6009,
-        "entry_expected_percent": 0.3352
-      },
-      {
-        "symbol": "ETHUSDT",
-        "entry_timestamp": 1781161200000,
-        "exit_timestamp": 1781164800000,
-        "net_percent": 0.0713,
-        "reason": "forecast_weak_profit_lock",
-        "held_bars": 1,
-        "entry_probability": 0.6004,
-        "entry_expected_percent": 0.3017
-      },
-      {
-        "symbol": "ETHUSDT",
-        "entry_timestamp": 1781445600000,
-        "exit_timestamp": 1781532000000,
-        "net_percent": 9.0305,
-        "reason": "max_hold",
-        "held_bars": 24,
-        "entry_probability": 0.6014,
-        "entry_expected_percent": 0.2946
       }
     ]
   },
   "walk_forward": {
     "summary": {
-      "trades": 15,
+      "trades": 0,
-      "wins": 8,
+      "wins": 0,
-      "win_rate": 0.5333,
+      "win_rate": 0.0,
-      "total_net_percent": 7.1747,
+      "total_net_percent": 0,
-      "avg_net_percent": 0.4783,
+      "avg_net_percent": 0.0,
-      "max_drawdown_percent": 1.3024,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.471,
+      "profit_factor": 0.0,
-      "status": "ok"
+      "status": "warn"
     },
     "folds": [
-      {
-        "fold": 1,
-        "train_records": 720,
-        "test_records": 720,
-        "thresholds": {
-          "edge": 0.1,
-          "probability": 0.6,
-          "confidence": 0.72,
-          "trades": 2,
-          "wins": 1,
-          "win_rate": 0.5,
-          "total_net_percent": -0.10348384852443271,
-          "average_net_percent": -0.051741924262216354,
-          "max_drawdown_percent": 0.5106090484004788,
-          "profit_factor": 0.7973325211360753,
-          "score": -0.014117837267286302
-        },
-        "test": {
-          "trades": 4,
-          "wins": 2,
-          "win_rate": 0.5,
-          "total_net_percent": 0.0557,
-          "avg_net_percent": 0.0139,
-          "max_drawdown_percent": 1.3024,
-          "profit_factor": 1.0428
-        }
-      },
       {
         "fold": 2,
         "train_records": 1440,
         "test_records": 720,
         "thresholds": {
           "edge": 0.1,
-          "probability": 0.55,
+          "probability": 0.59,
           "confidence": 0.72,
-          "trades": 13,
+          "trades": 1,
-          "wins": 8,
+          "wins": 1,
-          "win_rate": 0.6153846153846154,
+          "win_rate": 1.0,
-          "total_net_percent": 2.3573472403187523,
+          "total_net_percent": 0.09543520096249036,
-          "average_net_percent": 0.1813344031014425,
+          "average_net_percent": 0.09543520096249036,
-          "max_drawdown_percent": 1.812991648733242,
+          "max_drawdown_percent": 0.0,
-          "profit_factor": 2.0042930935847436,
+          "profit_factor": 999.0,
-          "score": 0.18692024685961114
+          "score": 0.05733739484151908
         },
         "test": {
-          "trades": 11,
+          "trades": 0,
-          "wins": 6,
+          "wins": 0,
-          "win_rate": 0.5455,
+          "win_rate": 0.0,
-          "total_net_percent": 7.119,
+          "total_net_percent": 0,
-          "avg_net_percent": 0.6472,
+          "avg_net_percent": 0.0,
-          "max_drawdown_percent": 1.0894,
+          "max_drawdown_percent": 0.0,
-          "profit_factor": 5.4462
+          "profit_factor": 0.0
         }
       },
       {
@@ -194,16 +127,16 @@
         "test_records": 720,
         "thresholds": {
           "edge": 0.1,
-          "probability": 0.62,
+          "probability": 0.59,
           "confidence": 0.72,
-          "trades": 9,
+          "trades": 1,
-          "wins": 3,
+          "wins": 1,
-          "win_rate": 0.3333333333333333,
+          "win_rate": 1.0,
-          "total_net_percent": 7.33207561878414,
+          "total_net_percent": 0.09543520096249036,
-          "average_net_percent": 0.8146750687537934,
+          "average_net_percent": 0.09543520096249036,
-          "max_drawdown_percent": 1.4887951136316468,
+          "max_drawdown_percent": 0.0,
-          "profit_factor": 3.9118496582300852,
+          "profit_factor": 999.0,
-          "score": 0.8933256829599393
+          "score": 0.05733739484151908
         },
         "test": {
           "trades": 0,
@@ -220,266 +153,252 @@
   "probability_calibration": {
     "samples": 2880,
     "buckets": [
+      {
+        "bucket": "0.25-0.30",
+        "samples": 25,
+        "avg_probability": 0.2947,
+        "actual_win_rate": 0.12,
+        "avg_future_net_percent": -0.6611
+      },
       {
         "bucket": "0.30-0.35",
-        "samples": 38,
+        "samples": 87,
-        "avg_probability": 0.336,
+        "avg_probability": 0.3257,
-        "actual_win_rate": 0.1053,
+        "actual_win_rate": 0.1379,
-        "avg_future_net_percent": -0.6575
+        "avg_future_net_percent": -0.5883
       },
       {
         "bucket": "0.35-0.40",
-        "samples": 418,
+        "samples": 276,
-        "avg_probability": 0.3839,
+        "avg_probability": 0.3787,
-        "actual_win_rate": 0.2225,
+        "actual_win_rate": 0.221,
-        "avg_future_net_percent": -0.6359
+        "avg_future_net_percent": -0.5378
       },
       {
         "bucket": "0.40-0.45",
-        "samples": 1065,
+        "samples": 1720,
-        "avg_probability": 0.427,
+        "avg_probability": 0.4263,
-        "actual_win_rate": 0.2873,
+        "actual_win_rate": 0.3203,
-        "avg_future_net_percent": -0.4036
+        "avg_future_net_percent": -0.3469
       },
       {
         "bucket": "0.45-0.50",
-        "samples": 911,
+        "samples": 629,
-        "avg_probability": 0.4746,
+        "avg_probability": 0.4701,
-        "actual_win_rate": 0.3271,
+        "actual_win_rate": 0.31,
-        "avg_future_net_percent": -0.3061
+        "avg_future_net_percent": -0.4239
       },
       {
         "bucket": "0.50-0.55",
-        "samples": 290,
+        "samples": 111,
-        "avg_probability": 0.5188,
+        "avg_probability": 0.5223,
-        "actual_win_rate": 0.3966,
+        "actual_win_rate": 0.4414,
-        "avg_future_net_percent": -0.0583
+        "avg_future_net_percent": 0.252
       },
       {
         "bucket": "0.55-0.60",
-        "samples": 104,
+        "samples": 32,
-        "avg_probability": 0.5758,
+        "avg_probability": 0.5658,
-        "actual_win_rate": 0.4327,
+        "actual_win_rate": 0.375,
-        "avg_future_net_percent": 0.0173
+        "avg_future_net_percent": -0.2001
-      },
-      {
-        "bucket": "0.60-0.65",
-        "samples": 42,
-        "avg_probability": 0.6138,
-        "actual_win_rate": 0.4762,
-        "avg_future_net_percent": -0.0041
-      },
-      {
-        "bucket": "0.65-0.70",
-        "samples": 6,
-        "avg_probability": 0.6679,
-        "actual_win_rate": 0.3333,
-        "avg_future_net_percent": 0.6587
-      },
-      {
-        "bucket": "0.70-0.75",
-        "samples": 6,
-        "avg_probability": 0.7103,
-        "actual_win_rate": 0.8333,
-        "avg_future_net_percent": 2.1268
       }
     ]
   },
   "top_results": [
     {
       "edge": 0.1,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.72,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.1,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.68,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
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-      "profit_factor": 3.9118496582300852,
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-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.1,
-      "probability": 0.62,
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       "confidence": 0.64,
-      "trades": 9,
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-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.1,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.6,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.1,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.56,
-      "trades": 9,
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+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.1,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.5,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
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+      "total_net_percent": 0.09543520096249036,
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+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
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+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.08,
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+      "probability": 0.59,
       "confidence": 0.72,
-      "trades": 9,
+      "trades": 1,
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+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.08,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.68,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.08,
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+      "probability": 0.59,
       "confidence": 0.64,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.08,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.6,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.08,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.56,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.08,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.5,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.06,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.72,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.06,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.68,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     },
     {
       "edge": 0.06,
-      "probability": 0.62,
+      "probability": 0.59,
       "confidence": 0.64,
-      "trades": 9,
+      "trades": 1,
-      "wins": 3,
+      "wins": 1,
-      "win_rate": 0.3333333333333333,
+      "win_rate": 1.0,
-      "total_net_percent": 7.33207561878414,
+      "total_net_percent": 0.09543520096249036,
-      "average_net_percent": 0.8146750687537934,
+      "average_net_percent": 0.09543520096249036,
-      "max_drawdown_percent": 1.4887951136316468,
+      "max_drawdown_percent": 0.0,
-      "profit_factor": 3.9118496582300852,
+      "profit_factor": 999.0,
-      "score": 0.689656915771491
+      "score": 0.04938446142797822
     }
   ]
 }

runtime/torch_retrain_guard.json

@@ -1,95 +1,59 @@
 {
-  "accepted": true,
+  "accepted": false,
-  "reason": "candidate_passed_guard",
+  "reason": "candidate_has_too_few_full_replay_trades",
   "current": {
-    "score": 0.0,
+    "score": 3.097468,
-    "recommended": {},
-    "full_replay": {},
-    "walk_forward_summary": {}
-  },
-  "candidate": {
-    "score": 3.499028,
     "recommended": {
       "edge": 0.1,
-      "probability": 0.52,
+      "probability": 0.6,
-      "confidence": 0.72,
+      "confidence": 0.68,
-      "trades": 30,
+      "trades": 16,
-      "wins": 17,
+      "wins": 9,
-      "win_rate": 0.5666666666666667,
+      "win_rate": 0.5625,
-      "total_net_percent": 12.82679871911413,
+      "total_net_percent": 7.917141995065847,
-      "average_net_percent": 0.42755995730380436,
+      "average_net_percent": 0.4948213746916154,
       "max_drawdown_percent": 1.812991648733242,
-      "profit_factor": 3.2963631842987433,
+      "profit_factor": 3.629214989861449,
-      "score": 0.5882388552951857
+      "score": 0.5816887551556058
     },
     "full_replay": {
-      "trades": 8,
+      "trades": 4,
-      "wins": 8,
+      "wins": 4,
       "win_rate": 1.0,
-      "total_net_percent": 21.0484,
+      "total_net_percent": 9.8223,
-      "avg_net_percent": 2.631,
+      "avg_net_percent": 2.4556,
       "max_drawdown_percent": 0.0,
       "profit_factor": 999.0,
       "trades_detail": [
-        {
-          "symbol": "ETHUSDT",
-          "entry_timestamp": 1779832800000,
-          "exit_timestamp": 1779868800000,
-          "net_percent": 0.5281,
-          "reason": "forecast_weak_profit_lock",
-          "held_bars": 10,
-          "entry_probability": 0.5747,
-          "entry_expected_percent": 0.3453
-        },
         {
           "symbol": "ETHUSDT",
           "entry_timestamp": 1779940800000,
-          "exit_timestamp": 1779984000000,
+          "exit_timestamp": 1779962400000,
-          "net_percent": 1.3185,
+          "net_percent": 0.1545,
           "reason": "forecast_weak_profit_lock",
-          "held_bars": 12,
+          "held_bars": 6,
-          "entry_probability": 0.6018,
+          "entry_probability": 0.6036,
-          "entry_expected_percent": 0.3155
+          "entry_expected_percent": 0.3223
         },
         {
           "symbol": "ETHUSDT",
           "entry_timestamp": 1780300800000,
-          "exit_timestamp": 1780347600000,
+          "exit_timestamp": 1780336800000,
-          "net_percent": 0.2591,
+          "net_percent": 0.1707,
           "reason": "forecast_weak_profit_lock",
-          "held_bars": 13,
+          "held_bars": 10,
-          "entry_probability": 0.6164,
+          "entry_probability": 0.6181,
-          "entry_expected_percent": 0.3215
+          "entry_expected_percent": 0.3255
         },
         {
           "symbol": "ETHUSDT",
-          "entry_timestamp": 1780768800000,
+          "entry_timestamp": 1781154000000,
-          "exit_timestamp": 1780855200000,
+          "exit_timestamp": 1781164800000,
-          "net_percent": 4.4581,
+          "net_percent": 0.4665,
-          "reason": "max_hold",
-          "held_bars": 24,
-          "entry_probability": 0.5632,
-          "entry_expected_percent": 0.5685
-        },
-        {
-          "symbol": "ETHUSDT",
-          "entry_timestamp": 1780862400000,
-          "exit_timestamp": 1780869600000,
-          "net_percent": 2.4609,
           "reason": "forecast_weak_profit_lock",
-          "held_bars": 2,
+          "held_bars": 3,
-          "entry_probability": 0.5368,
+          "entry_probability": 0.6017,
-          "entry_expected_percent": 0.4055
+          "entry_expected_percent": 0.3383
-        },
-        {
-          "symbol": "ETHUSDT",
-          "entry_timestamp": 1781139600000,
-          "exit_timestamp": 1781204400000,
-          "net_percent": 2.0707,
-          "reason": "forecast_weak_profit_lock",
-          "held_bars": 18,
-          "entry_probability": 0.5775,
-          "entry_expected_percent": 0.3013
         },
         {
           "symbol": "ETHUSDT",
@@ -98,29 +62,66 @@
           "net_percent": 9.0305,
           "reason": "max_hold",
           "held_bars": 24,
-          "entry_probability": 0.6014,
+          "entry_probability": 0.6028,
-          "entry_expected_percent": 0.2946
+          "entry_expected_percent": 0.2963
-        },
-        {
-          "symbol": "ETHUSDT",
-          "entry_timestamp": 1781892000000,
-          "exit_timestamp": 1781942400000,
-          "net_percent": 0.9224,
-          "reason": "forecast_weak_profit_lock",
-          "held_bars": 14,
-          "entry_probability": 0.5966,
-          "entry_expected_percent": 0.2647
         }
       ]
     },
     "walk_forward_summary": {
-      "trades": 16,
+      "trades": 12,
-      "wins": 8,
+      "wins": 6,
       "win_rate": 0.5,
-      "total_net_percent": 6.8682,
+      "total_net_percent": 8.0551,
-      "avg_net_percent": 0.4293,
+      "avg_net_percent": 0.6713,
-      "max_drawdown_percent": 1.3024,
+      "max_drawdown_percent": 1.1326,
-      "profit_factor": 3.1396,
+      "profit_factor": 4.7976,
+      "status": "ok"
+    }
+  },
+  "candidate": {
+    "score": 0.323872,
+    "recommended": {
+      "edge": 0.1,
+      "probability": 0.59,
+      "confidence": 0.72,
+      "trades": 1,
+      "wins": 1,
+      "win_rate": 1.0,
+      "total_net_percent": 0.09543520096249036,
+      "average_net_percent": 0.09543520096249036,
+      "max_drawdown_percent": 0.0,
+      "profit_factor": 999.0,
+      "score": 0.04938446142797822
+    },
+    "full_replay": {
+      "trades": 1,
+      "wins": 1,
+      "win_rate": 1.0,
+      "total_net_percent": 0.0113,
+      "avg_net_percent": 0.0113,
+      "max_drawdown_percent": 0.0,
+      "profit_factor": 999.0,
+      "trades_detail": [
+        {
+          "symbol": "ETHUSDT",
+          "entry_timestamp": 1780462800000,
+          "exit_timestamp": 1780470000000,
+          "net_percent": 0.0113,
+          "reason": "forecast_weak_profit_lock",
+          "held_bars": 2,
+          "entry_probability": 0.5905,
+          "entry_expected_percent": 0.3024
+        }
+      ]
+    },
+    "walk_forward_summary": {
+      "trades": 0,
+      "wins": 0,
+      "win_rate": 0.0,
+      "total_net_percent": 0,
+      "avg_net_percent": 0.0,
+      "max_drawdown_percent": 0.0,
+      "profit_factor": 0.0,
       "status": "warn"
     }
   }

tests/conftest.py

@@ -83,6 +83,10 @@ def make_settings():
             time_series_max_adjustment=0.08,
             time_series_lstm_enabled=True,
             time_series_lstm_model_path=tmp_path / "lstm_forecaster.json",
+            time_series_probe_enabled=True,
+            time_series_probe_min_edge_percent=0.02,
+            time_series_probe_min_probability_up=0.55,
+            time_series_probe_size_multiplier=0.40,
             stop_loss_percent=0.02,
             take_profit_percent=0.035,
             trailing_stop_percent=0.015,

tests/test_dashboard.py

@@ -39,6 +39,10 @@ def test_safe_config_summarizes_torch_forecast_artifact(make_settings, tmp_path)
 
     config = _safe_config(settings)
 
+    assert config["time_series_probe_enabled"] is True
+    assert config["time_series_probe_min_edge_percent"] == 0.02
+    assert config["time_series_probe_min_probability_up"] == 0.55
+    assert config["time_series_probe_size_multiplier"] == 0.40
     assert config["time_series_model_artifact"] == {
         "available": True,
         "type": "pytorch_recurrent_forecaster",

tests/test_strategy.py

@@ -284,6 +284,80 @@ def test_torch_forecast_blocks_without_valid_torch_model(make_settings, tmp_path
     assert signal.diagnostics["checks"]["torch_model_ok"] is False
 
 
+def test_torch_forecast_probe_buys_on_positive_high_probability(make_settings, tmp_path) -> None:
+    settings = make_settings(
+        tmp_path,
+        strategy_mode="torch_forecast",
+        time_series_min_edge_percent=0.10,
+        time_series_min_probability_up=0.52,
+        time_series_probe_enabled=True,
+        time_series_probe_min_edge_percent=0.02,
+        time_series_probe_min_probability_up=0.55,
+        time_series_probe_size_multiplier=0.40,
+        max_position_usdt=25,
+        stop_loss_percent=0.04,
+        risk_per_trade_percent=0.01,
+    )
+    strategy = SpotStrategy(settings)
+    ticker = Ticker("SOLUSDT", 65, 64.99, 65.01, 10_000_000, 1000, 1.0)
+
+    signal = strategy.entry_signal(
+        "SOLUSDT",
+        [],
+        ticker,
+        open_positions_for_symbol=0,
+        forecast={
+            "usable": True,
+            "model": "torch_gru",
+            "expected_return_percent": 0.04,
+            "probability_up": 0.57,
+            "skill": 0.05,
+            "block_entry": False,
+        },
+        account={"equity": 100.0},
+    )
+
+    assert signal.action == "BUY"
+    assert signal.diagnostics["edge_mode"] == "probe"
+    assert signal.diagnostics["checks"]["expected_edge_ok"] is True
+    assert signal.diagnostics["position_sizing"]["edge_mode"] == "probe"
+    assert settings.min_position_usdt <= signal.diagnostics["position_notional_usdt"] < settings.max_position_usdt
+
+
+def test_torch_forecast_probe_blocks_negative_expected_return(make_settings, tmp_path) -> None:
+    settings = make_settings(
+        tmp_path,
+        strategy_mode="torch_forecast",
+        time_series_min_edge_percent=0.10,
+        time_series_min_probability_up=0.52,
+        time_series_probe_enabled=True,
+        time_series_probe_min_edge_percent=0.02,
+        time_series_probe_min_probability_up=0.55,
+    )
+    strategy = SpotStrategy(settings)
+    ticker = Ticker("BTCUSDT", 59_000, 58_999, 59_001, 10_000_000, 1000, 1.0)
+
+    signal = strategy.entry_signal(
+        "BTCUSDT",
+        [],
+        ticker,
+        open_positions_for_symbol=0,
+        forecast={
+            "usable": True,
+            "model": "torch_gru",
+            "expected_return_percent": -0.03,
+            "probability_up": 0.60,
+            "skill": 0.16,
+            "block_entry": False,
+        },
+        account={"equity": 100.0},
+    )
+
+    assert signal.action == "HOLD"
+    assert signal.diagnostics["edge_mode"] == "blocked"
+    assert signal.diagnostics["checks"]["expected_edge_ok"] is False
+
+
 def test_torch_forecast_exits_when_forecast_turns_negative(make_settings, tmp_path) -> None:
     settings = make_settings(tmp_path, strategy_mode="torch_forecast", stop_loss_percent=0.04)
     strategy = SpotStrategy(settings)

tools/install_windows_torch_retrainer.ps1

@@ -8,7 +8,12 @@ param(
     [string]$Horizons = "",
     [string]$Features = "",
     [string]$ContextSymbols = "",
-    [int]$FirstRunMinutes = 0
+    [int]$FirstRunMinutes = 0,
+    [switch]$DeployToPi,
+    [string]$PiHost = "192.168.0.185",
+    [string]$PiUser = "sevenhill",
+    [string]$PiRoot = "/mnt/data/tradebot",
+    [string]$PiSshKeyPath = ""
 )
 
 $ErrorActionPreference = "Stop"
@@ -46,6 +51,21 @@ if ($Features) {
 if ($ContextSymbols) {
     $actionArgs += " -ContextSymbols `"$ContextSymbols`""
 }
+if ($DeployToPi) {
+    $actionArgs += " -DeployToPi"
+}
+if ($PiHost) {
+    $actionArgs += " -PiHost `"$PiHost`""
+}
+if ($PiUser) {
+    $actionArgs += " -PiUser `"$PiUser`""
+}
+if ($PiRoot) {
+    $actionArgs += " -PiRoot `"$PiRoot`""
+}
+if ($PiSshKeyPath) {
+    $actionArgs += " -PiSshKeyPath `"$PiSshKeyPath`""
+}
 $action = New-ScheduledTaskAction -Execute "powershell.exe" -Argument $actionArgs -WorkingDirectory $RepoRoot
 $trigger = New-ScheduledTaskTrigger `
     -Once `

tools/run_retrain_until_replay8.ps1

@@ -0,0 +1,114 @@
+[CmdletBinding()]
+param(
+    [int]$MinReplayTrades = 8,
+    [int]$MaxAttempts = 0,
+    [string]$Symbols = "BTCUSDT,ETHUSDT,SOLUSDT,LTCUSDT",
+    [int]$Limit = 3000,
+    [switch]$DeployToPi,
+    [string]$PiHost = "192.168.0.185",
+    [string]$PiUser = "sevenhill",
+    [string]$PiRoot = "/mnt/data/tradebot",
+    [string]$PiSshKeyPath = "",
+    [int]$SeedStart = 0
+)
+
+$ErrorActionPreference = "Stop"
+
+$RepoRoot = (Resolve-Path (Join-Path $PSScriptRoot "..")).Path
+$RuntimeDir = Join-Path $RepoRoot "runtime"
+$LoopLog = Join-Path $RuntimeDir "torch_retrain_until_replay8.log"
+$GuardReport = Join-Path $RuntimeDir "torch_retrain_guard.json"
+$Runner = Join-Path $RepoRoot "tools\run_torch_retrain.ps1"
+New-Item -ItemType Directory -Force -Path $RuntimeDir | Out-Null
+
+function Write-LoopLog {
+    param([string]$Message)
+    $timestamp = Get-Date -Format "yyyy-MM-dd HH:mm:ssK"
+    "[$timestamp] $Message" | Tee-Object -FilePath $LoopLog -Append
+}
+
+function ConvertTo-IntOrZero {
+    param($Value)
+    try {
+        if ($null -eq $Value) {
+            return 0
+        }
+        return [int]$Value
+    }
+    catch {
+        return 0
+    }
+}
+
+function Read-GuardSummary {
+    if (-not (Test-Path $GuardReport)) {
+        return [pscustomobject]@{
+            Accepted = $false
+            Reason = "guard_report_missing"
+            ReplayTrades = 0
+            WalkForwardTrades = 0
+        }
+    }
+    try {
+        $payload = Get-Content -Raw -LiteralPath $GuardReport | ConvertFrom-Json
+        return [pscustomobject]@{
+            Accepted = [bool]$payload.accepted
+            Reason = [string]$payload.reason
+            ReplayTrades = ConvertTo-IntOrZero $payload.candidate.full_replay.trades
+            WalkForwardTrades = ConvertTo-IntOrZero $payload.candidate.walk_forward_summary.trades
+        }
+    }
+    catch {
+        return [pscustomobject]@{
+            Accepted = $false
+            Reason = "guard_report_unreadable"
+            ReplayTrades = 0
+            WalkForwardTrades = 0
+        }
+    }
+}
+
+$attempt = 0
+while ($true) {
+    $attempt += 1
+    if ($SeedStart -gt 0) {
+        $attemptSeed = $SeedStart + $attempt - 1
+    }
+    else {
+        $attemptSeed = Get-Random -Minimum 1 -Maximum 2147483647
+    }
+    Write-LoopLog "Attempt $attempt started; seed=$attemptSeed; target full_replay.trades >= $MinReplayTrades."
+
+    $runnerArgs = @(
+        "-NoProfile",
+        "-ExecutionPolicy", "Bypass",
+        "-File", $Runner,
+        "-Symbols", $Symbols,
+        "-Limit", $Limit.ToString(),
+        "-Seed", $attemptSeed.ToString()
+    )
+    if ($DeployToPi) {
+        $runnerArgs += "-DeployToPi"
+        if ($PiHost) { $runnerArgs += @("-PiHost", $PiHost) }
+        if ($PiUser) { $runnerArgs += @("-PiUser", $PiUser) }
+        if ($PiRoot) { $runnerArgs += @("-PiRoot", $PiRoot) }
+        if ($PiSshKeyPath) { $runnerArgs += @("-PiSshKeyPath", $PiSshKeyPath) }
+    }
+
+    & powershell.exe @runnerArgs 2>&1 | Tee-Object -FilePath $LoopLog -Append
+    $runnerExit = $LASTEXITCODE
+    $summary = Read-GuardSummary
+    Write-LoopLog "Attempt $attempt finished; runner_exit=$runnerExit accepted=$($summary.Accepted) reason=$($summary.Reason) full_replay.trades=$($summary.ReplayTrades) walk_forward.trades=$($summary.WalkForwardTrades)."
+
+    if ($summary.ReplayTrades -ge $MinReplayTrades) {
+        Write-LoopLog "Stop condition reached: full_replay.trades=$($summary.ReplayTrades) >= $MinReplayTrades."
+        exit 0
+    }
+
+    if ($MaxAttempts -gt 0 -and $attempt -ge $MaxAttempts) {
+        Write-LoopLog "MaxAttempts=$MaxAttempts reached before replay target."
+        exit 2
+    }
+
+    Start-Sleep -Seconds 10
+}

tools/run_torch_retrain.ps1

@@ -11,10 +11,17 @@ param(
     [string]$Horizons = "",
     [string]$Features = "",
     [string]$ContextSymbols = "",
+    [int]$Seed = 0,
     [int]$Epochs = 0,
     [int]$Patience = 0,
     [string]$Interval = "",
     [string]$EnvFile = "",
+    [switch]$DeployToPi,
+    [string]$PiHost = "",
+    [string]$PiUser = "",
+    [string]$PiRoot = "",
+    [string]$PiSshKeyPath = "",
+    [switch]$NoPiRestart,
     [switch]$SkipGuard
 )
 
@@ -52,6 +59,51 @@ function Resolve-Python {
     throw "Python was not found. Create .venv or install Python 3.12."
 }
 
+function Test-TorchArtifactFile {
+    param([string]$Path)
+    if (-not (Test-Path $Path)) {
+        return $false
+    }
+    try {
+        $payload = Get-Content -Raw -LiteralPath $Path | ConvertFrom-Json
+        return $payload.type -eq "pytorch_recurrent_forecaster" -and $null -ne $payload.symbols
+    }
+    catch {
+        return $false
+    }
+}
+
+function Sync-AcceptedArtifactsToPi {
+    if (-not ($DeployToPi -or $env:TORCH_RETRAIN_DEPLOY_TO_PI)) {
+        Write-RetrainLog "Pi artifact sync disabled."
+        return
+    }
+
+    $syncScript = Join-Path $RepoRoot "tools\sync_torch_artifacts_to_pi.ps1"
+    if (-not (Test-Path $syncScript)) {
+        throw "Pi sync script not found: $syncScript"
+    }
+
+    $syncArgs = @(
+        "-NoProfile",
+        "-ExecutionPolicy", "Bypass",
+        "-File", $syncScript,
+        "-RepoRoot", $RepoRoot
+    )
+    if ($PiHost) { $syncArgs += @("-RemoteHost", $PiHost) }
+    if ($PiUser) { $syncArgs += @("-RemoteUser", $PiUser) }
+    if ($PiRoot) { $syncArgs += @("-RemoteRoot", $PiRoot) }
+    if ($PiSshKeyPath) { $syncArgs += @("-SshKeyPath", $PiSshKeyPath) }
+    if ($NoPiRestart) { $syncArgs += "-NoRestart" }
+
+    Write-RetrainLog "Syncing accepted Torch artifacts to Raspberry Pi."
+    & powershell.exe @syncArgs 2>&1 | Tee-Object -FilePath $LogFile -Append
+    if ($LASTEXITCODE -ne 0) {
+        throw "Pi artifact sync failed with exit code $LASTEXITCODE."
+    }
+    Write-RetrainLog "Pi artifact sync completed."
+}
+
 if (-not $Symbols -and $env:TORCH_RETRAIN_SYMBOLS) { $Symbols = $env:TORCH_RETRAIN_SYMBOLS }
 if ($Limit -le 0) {
     $Limit = if ($env:TORCH_RETRAIN_LIMIT) { [int]$env:TORCH_RETRAIN_LIMIT } else { 3000 }
@@ -65,6 +117,7 @@ if ($Horizon -le 0 -and $env:TORCH_RETRAIN_HORIZON) { $Horizon = [int]$env:TORCH
 if (-not $Horizons -and $env:TORCH_RETRAIN_HORIZONS) { $Horizons = $env:TORCH_RETRAIN_HORIZONS }
 if (-not $Features -and $env:TORCH_RETRAIN_FEATURES) { $Features = $env:TORCH_RETRAIN_FEATURES }
 if (-not $ContextSymbols -and $env:TORCH_RETRAIN_CONTEXT_SYMBOLS) { $ContextSymbols = $env:TORCH_RETRAIN_CONTEXT_SYMBOLS }
+if ($Seed -le 0 -and $env:TORCH_RETRAIN_SEED) { $Seed = [int]$env:TORCH_RETRAIN_SEED }
 if ($Epochs -le 0) { $Epochs = if ($env:TORCH_RETRAIN_EPOCHS) { [int]$env:TORCH_RETRAIN_EPOCHS } else { 70 } }
 if ($Patience -le 0) { $Patience = if ($env:TORCH_RETRAIN_PATIENCE) { [int]$env:TORCH_RETRAIN_PATIENCE } else { 8 } }
 if (-not $Interval -and $env:TORCH_RETRAIN_INTERVAL) { $Interval = $env:TORCH_RETRAIN_INTERVAL }
@@ -110,19 +163,27 @@ try {
     if ($Horizons) { $trainerArgs += @("--horizons", $Horizons) }
     if ($Features) { $trainerArgs += @("--features", $Features) }
     if ($ContextSymbols) { $trainerArgs += @("--context-symbols", $ContextSymbols) }
+    if ($Seed -gt 0) { $trainerArgs += @("--seed", $Seed.ToString()) }
 
     Push-Location $RepoRoot
     $pushedLocation = $true
     Write-RetrainLog "Starting PyTorch recurrent retrain: $python $($trainerArgs -join ' ')"
     & $python @trainerArgs 2>&1 | Tee-Object -FilePath $LogFile -Append
-    if ($LASTEXITCODE -ne 0) {
+    $trainerExitCode = $LASTEXITCODE
-        throw "Trainer failed with exit code $LASTEXITCODE."
+    if ($trainerExitCode -ne 0) {
+        if (Test-TorchArtifactFile $CandidateFile) {
+            Write-RetrainLog "WARNING: Trainer exited with code $trainerExitCode after writing a valid candidate artifact; continuing to guard."
+        }
+        else {
+            throw "Trainer failed with exit code $trainerExitCode."
+        }
     }
     Write-RetrainLog "Finished PyTorch recurrent retrain candidate: $CandidateFile"
 
     if ($SkipGuard -or -not (Test-Path $ModelFile)) {
         Move-Item -Force -LiteralPath $CandidateFile -Destination $ModelFile
         Write-RetrainLog "Accepted candidate without guard. Active artifact: $ModelFile"
+        Sync-AcceptedArtifactsToPi
         exit 0
     }
 
@@ -162,7 +223,12 @@ try {
     if ($LASTEXITCODE -ne 0) {
         throw "Retrain guard failed with exit code $LASTEXITCODE."
     }
+    if (Test-Path $CandidateCalibration) {
+        Copy-Item -Force -LiteralPath $CandidateCalibration -Destination (Join-Path $RuntimeDir "torch_threshold_calibration.json")
+        Write-RetrainLog "Updated active threshold calibration: $(Join-Path $RuntimeDir "torch_threshold_calibration.json")"
+    }
     Write-RetrainLog "Candidate accepted by guard. Active artifact: $ModelFile"
+    Sync-AcceptedArtifactsToPi
 }
 catch {
     Write-RetrainLog "ERROR: $($_.Exception.Message)"

tools/sync_torch_artifacts_to_pi.ps1

@@ -0,0 +1,95 @@
+[CmdletBinding()]
+param(
+    [string]$RepoRoot = "",
+    [string]$RemoteHost = "",
+    [string]$RemoteUser = "",
+    [string]$RemoteRoot = "",
+    [string]$SshKeyPath = "",
+    [string]$ServiceName = "tradebot",
+    [switch]$NoRestart,
+    [switch]$DryRun
+)
+
+$ErrorActionPreference = "Stop"
+
+if (-not $RepoRoot) { $RepoRoot = (Resolve-Path (Join-Path $PSScriptRoot "..")).Path }
+if (-not $RemoteHost -and $env:TORCH_DEPLOY_PI_HOST) { $RemoteHost = $env:TORCH_DEPLOY_PI_HOST }
+if (-not $RemoteUser -and $env:TORCH_DEPLOY_PI_USER) { $RemoteUser = $env:TORCH_DEPLOY_PI_USER }
+if (-not $RemoteRoot -and $env:TORCH_DEPLOY_PI_ROOT) { $RemoteRoot = $env:TORCH_DEPLOY_PI_ROOT }
+if (-not $SshKeyPath -and $env:TORCH_DEPLOY_PI_SSH_KEY) { $SshKeyPath = $env:TORCH_DEPLOY_PI_SSH_KEY }
+if (-not $RemoteHost) { $RemoteHost = "192.168.0.185" }
+if (-not $RemoteUser) { $RemoteUser = "sevenhill" }
+if (-not $RemoteRoot) { $RemoteRoot = "/mnt/data/tradebot" }
+
+$RuntimeDir = Join-Path $RepoRoot "runtime"
+$artifactNames = @(
+    "lstm_forecaster.json",
+    "torch_retrain_guard.json",
+    "torch_threshold_calibration.json"
+)
+$localFiles = @()
+foreach ($name in $artifactNames) {
+    $path = Join-Path $RuntimeDir $name
+    if (Test-Path $path) {
+        $localFiles += (Resolve-Path $path).Path
+    }
+}
+if ($localFiles.Count -eq 0) {
+    throw "No Torch artifacts found in $RuntimeDir."
+}
+
+function ConvertTo-RemoteSingleQuoted {
+    param([string]$Value)
+    return "'" + ($Value -replace "'", "'\''") + "'"
+}
+
+function Invoke-LoggedCommand {
+    param(
+        [string]$Exe,
+        [string[]]$Arguments
+    )
+    $rendered = @($Exe) + $Arguments
+    Write-Host ($rendered -join " ")
+    if ($DryRun) {
+        return
+    }
+    & $Exe @Arguments
+    if ($LASTEXITCODE -ne 0) {
+        throw "$Exe failed with exit code $LASTEXITCODE."
+    }
+}
+
+$ssh = (Get-Command "ssh.exe" -ErrorAction SilentlyContinue)
+if (-not $ssh) { $ssh = Get-Command "ssh" -ErrorAction Stop }
+$scp = (Get-Command "scp.exe" -ErrorAction SilentlyContinue)
+if (-not $scp) { $scp = Get-Command "scp" -ErrorAction Stop }
+
+$commonSshArgs = @("-o", "BatchMode=yes", "-o", "StrictHostKeyChecking=accept-new", "-o", "ConnectTimeout=15")
+if ($SshKeyPath) {
+    $expandedKey = $ExecutionContext.SessionState.Path.GetUnresolvedProviderPathFromPSPath($SshKeyPath)
+    $commonSshArgs += @("-i", $expandedKey)
+}
+
+$remote = "${RemoteUser}@${RemoteHost}"
+$remoteRuntime = "$RemoteRoot/runtime"
+$remoteIncoming = "$remoteRuntime/.incoming-torch"
+$mkdirCommand = "mkdir -p $(ConvertTo-RemoteSingleQuoted $remoteIncoming) $(ConvertTo-RemoteSingleQuoted $remoteRuntime)"
+Invoke-LoggedCommand $ssh.Source (@($commonSshArgs + @($remote, $mkdirCommand)))
+
+$destination = "${remote}:$remoteIncoming/"
+Invoke-LoggedCommand $scp.Source (@($commonSshArgs + $localFiles + @($destination)))
+
+$moveParts = @()
+foreach ($path in $localFiles) {
+    $name = Split-Path $path -Leaf
+    $moveParts += "mv -f $(ConvertTo-RemoteSingleQuoted "$remoteIncoming/$name") $(ConvertTo-RemoteSingleQuoted "$remoteRuntime/$name")"
+}
+$moveCommand = $moveParts -join " && "
+Invoke-LoggedCommand $ssh.Source (@($commonSshArgs + @($remote, $moveCommand)))
+
+if (-not $NoRestart) {
+    $restartCommand = "cd $(ConvertTo-RemoteSingleQuoted $RemoteRoot) && docker compose restart $(ConvertTo-RemoteSingleQuoted $ServiceName)"
+    Invoke-LoggedCommand $ssh.Source (@($commonSshArgs + @($remote, $restartCommand)))
+}
+
+Write-Host "Synced Torch artifacts to ${remote}:$remoteRuntime"