From 51a783389656bbb45f408788425c1f70d1b41a4e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=9A=D1=83=D1=80=D0=BD=D0=B0=D1=82=20=D0=90=D0=BD=D0=B4?=
 =?UTF-8?q?=D1=80=D0=B5=D0=B9?= <sevenhill@live.ru>
Date: Tue, 14 Jul 2026 23:28:53 +0300
Subject: [PATCH] fix: calibrate dynamic model symbols

---
 tests/test_calibrate_thresholds.py  | 16 ++++++++++++++++
 tools/calibrate_torch_thresholds.py | 29 +++++++++++++++++++++++++----
 2 files changed, 41 insertions(+), 4 deletions(-)

diff --git a/tests/test_calibrate_thresholds.py b/tests/test_calibrate_thresholds.py
index d720478..6ac1b97 100644
--- a/tests/test_calibrate_thresholds.py
+++ b/tests/test_calibrate_thresholds.py
@@ -8,6 +8,7 @@ from tools.calibrate_torch_thresholds import (
     _average_selected_predictions,
     _apply_platt_calibration,
     _build_torch_model,
+    _calibration_symbols,
     _choose_recommendation,
     _full_backtest,
     _fit_platt_calibration,
@@ -62,6 +63,21 @@ def _record(index: int, probability: float, future: float) -> ForecastRecord:
     )
 
 
+def test_calibration_symbols_follow_explicit_configured_artifact_precedence() -> None:
+    artifact = {"symbols": {"btcusdt": {}, "ethusdt": {}}}
+
+    assert _calibration_symbols("solusdt, xrpusdt", ("ADAUSDT",), artifact) == [
+        "SOLUSDT",
+        "XRPUSDT",
+    ]
+    assert _calibration_symbols("", ("ADAUSDT",), artifact) == ["ADAUSDT"]
+    assert _calibration_symbols("", (), artifact) == ["BTCUSDT", "ETHUSDT"]
+
+
+def test_calibration_symbols_reject_malformed_artifact_symbols() -> None:
+    assert _calibration_symbols("", (), {"symbols": []}) == []
+
+
 def test_calibration_does_not_fallback_to_too_few_trades() -> None:
     selected = _choose_recommendation(
         [_result(trades=1, average=2.0, total=2.0, profit_factor=999.0)],
diff --git a/tools/calibrate_torch_thresholds.py b/tools/calibrate_torch_thresholds.py
index 73615bc..481a823 100644
--- a/tools/calibrate_torch_thresholds.py
+++ b/tools/calibrate_torch_thresholds.py
@@ -88,13 +88,13 @@ def main() -> None:
     if torch is not None and args.threads > 0:
         torch.set_num_threads(args.threads)
     settings = load_settings(args.env)
-    client = BybitClient(settings)
-    symbols = _symbols(args.symbols, settings.symbols)
-    context_symbols = sorted(set(symbols + _symbols(args.context_symbols, ())))
     artifact_path = Path(args.artifact or settings.time_series_lstm_model_path)
     artifact_bytes = artifact_path.read_bytes()
     artifact_sha256 = hashlib.sha256(artifact_bytes).hexdigest()
     artifact = json.loads(artifact_bytes.decode("utf-8"))
+    client = BybitClient(settings)
+    symbols = _calibration_symbols(args.symbols, settings.symbols, artifact)
+    context_symbols = sorted(set(symbols + _symbols(args.context_symbols, ())))
     horizon = args.horizon if args.horizon > 0 else settings.time_series_forecast_horizon
     round_trip_cost = _artifact_round_trip_cost(artifact, settings)
 
@@ -277,7 +277,11 @@ def _parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(description="Calibrate TradeBot Torch forecast entry thresholds.")
     parser.add_argument("--env", default=None, help="Path to .env file.")
     parser.add_argument("--artifact", default="", help="Path to lstm_forecaster.json.")
-    parser.add_argument("--symbols", default="", help="Comma-separated symbols. Defaults to configured fixed symbols.")
+    parser.add_argument(
+        "--symbols",
+        default="",
+        help="Comma-separated symbols. Defaults to configured fixed symbols, then artifact symbols.",
+    )
     parser.add_argument("--context-symbols", default="BTCUSDT,ETHUSDT", help="Cross-asset context symbols.")
     parser.add_argument("--limit", type=int, default=2000, help="Hourly candles per symbol.")
     parser.add_argument("--trend-limit", type=int, default=320, help="Daily candles per symbol.")
@@ -308,6 +312,23 @@ def _symbols(raw: str, fallback: tuple[str, ...] | list[str]) -> list[str]:
     return [str(item).upper() for item in fallback]
 
 
+def _calibration_symbols(
+    raw: str,
+    configured: tuple[str, ...] | list[str],
+    artifact: dict[str, Any],
+) -> list[str]:
+    explicit = _symbols(raw, ())
+    if explicit:
+        return explicit
+    fixed = _symbols("", configured)
+    if fixed:
+        return fixed
+    artifact_symbols = artifact.get("symbols")
+    if not isinstance(artifact_symbols, dict):
+        return []
+    return [str(symbol).strip().upper() for symbol in artifact_symbols if str(symbol).strip()]
+
+
 def _forecast_records(
     *,
     symbol: str,