feat: add orderbook shadow training pipeline

crypto_spot_bot/dashboard.py

@@ -20,6 +20,7 @@ from crypto_spot_bot.learning import TradeLearner
 from crypto_spot_bot.market_data import MarketData
 from crypto_spot_bot.patterns import PatternAnalyzer
 from crypto_spot_bot.reconciliation import reconciliation_snapshot
+from crypto_spot_bot.shadow import shadow_gate_snapshot
 from crypto_spot_bot.storage import Storage
 from crypto_spot_bot.strategy import SpotStrategy
 from crypto_spot_bot.time_series import TimeSeriesForecaster
@@ -47,7 +48,23 @@ def create_app(settings: Settings | None = None) -> FastAPI:
     pattern_analyzer = PatternAnalyzer()
     learner = TradeLearner(settings, storage)
     forecaster = TimeSeriesForecaster(settings)
-    bot = CryptoSpotBot(settings, storage, market, broker, strategy, pattern_analyzer, learner, forecaster)
+    runtime_dir = settings.time_series_lstm_model_path.parent
+    shadow_forecaster = TimeSeriesForecaster(
+        settings,
+        model_path=runtime_dir / "lstm_forecaster.shadow.json",
+        calibration_path=runtime_dir / "torch_shadow_calibration.json",
+    )
+    bot = CryptoSpotBot(
+        settings,
+        storage,
+        market,
+        broker,
+        strategy,
+        pattern_analyzer,
+        learner,
+        forecaster,
+        shadow_forecaster,
+    )
     training = TrainingCoordinator(settings.time_series_lstm_model_path.parent)
     authorizer = ApiAuthorizer(settings)
 
@@ -143,12 +160,31 @@ def create_app(settings: Settings | None = None) -> FastAPI:
     async def retrain(_: None = Depends(authorizer.require)) -> dict[str, Any]:
         data = _runtime_json(settings, "torch_retrain_guard.json")
         data["coordination"] = training.status()
+        data["shadow"] = shadow_gate_snapshot(storage, shadow_forecaster.artifact_sha256())
         return data
 
     @app.get("/api/training/status")
     async def training_status(_: None = Depends(authorizer.require)) -> dict[str, Any]:
         return training.status()
 
+    @app.get("/api/training/shadow")
+    async def training_shadow_status(
+        _: None = Depends(authorizer.require),
+    ) -> dict[str, Any]:
+        return shadow_gate_snapshot(storage, shadow_forecaster.artifact_sha256())
+
+    @app.post("/api/training/shadow/promote")
+    async def training_shadow_promote(
+        _: None = Depends(authorizer.require),
+    ) -> dict[str, Any]:
+        gate = shadow_gate_snapshot(storage, shadow_forecaster.artifact_sha256())
+        if not gate.get("passed"):
+            raise HTTPException(status_code=409, detail={"message": "shadow forward gate has not passed", "gate": gate})
+        try:
+            return training.promote_shadow(gate)
+        except ValueError as exc:
+            raise HTTPException(status_code=400, detail=str(exc)) from exc
+
     @app.get("/api/training/market-observations")
     async def training_market_observations(
         symbol: str,
@@ -170,6 +206,16 @@ def create_app(settings: Settings | None = None) -> FastAPI:
             "next_after_id": int(items[-1]["id"]) if items else max(0, after_id),
         }
 
+    @app.get("/api/training/market-observations/manifest")
+    async def training_market_observation_manifest(
+        _: None = Depends(authorizer.require_training),
+    ) -> dict[str, Any]:
+        items = storage.market_observation_manifest()
+        return {
+            "items": items,
+            "total_samples": sum(int(item.get("samples", 0) or 0) for item in items),
+        }
+
     @app.post("/api/training/retrain")
     async def training_retrain(
         payload: dict[str, Any] | None = None,
@@ -233,6 +279,10 @@ def create_app(settings: Settings | None = None) -> FastAPI:
         row_limit = 220
         retrain_data = _runtime_json(settings, "torch_retrain_guard.json")
         retrain_data["coordination"] = training.status()
+        retrain_data["shadow"] = shadow_gate_snapshot(
+            storage,
+            shadow_forecaster.artifact_sha256(),
+        )
         return {
             "health": {
                 "ok": True,