Remove legacy LSTM retraining

tests/test_time_series.py

@@ -76,32 +76,13 @@ def test_time_series_forecaster_blocks_negative_edge(make_settings, tmp_path) ->
     assert forecast.block_entry is True
 
 
-def test_time_series_forecaster_includes_lstm_candidate(make_settings, tmp_path) -> None:
-    settings = make_settings(
-        tmp_path,
-        time_series_min_candles=80,
-        time_series_validation_window=20,
-        time_series_lstm_enabled=True,
-        time_series_lstm_lookback=12,
-        time_series_lstm_units=4,
-    )
-    returns = []
-    for index in range(140):
-        seasonal = 0.00018 if index % 5 in {0, 1, 2} else -0.00011
-        returns.append(seasonal + 0.00002 * ((index % 7) - 3))
-
-    forecast = TimeSeriesForecaster(settings).forecast(_candles_from_returns(returns), symbol="BTCUSDT")
-
-    assert forecast.usable is True
-    assert any(candidate["model"] == "lstm" for candidate in forecast.candidates)
-
-
-def test_time_series_forecaster_reads_lstm_artifact(make_settings, tmp_path) -> None:
+def test_time_series_forecaster_ignores_legacy_lstm_artifact(make_settings, tmp_path) -> None:
     artifact_path = tmp_path / "lstm_forecaster.json"
     artifact_path.write_text(
         json.dumps(
             {
                 "version": 1,
+                "type": "lstm_reservoir_ridge_params",
                 "symbols": {
                     "BTCUSDT": {"lookback": 10, "units": 3, "ridge": 0.01},
                 },
@@ -121,7 +102,7 @@ def test_time_series_forecaster_reads_lstm_artifact(make_settings, tmp_path) ->
     forecast = TimeSeriesForecaster(settings).forecast(_candles_from_returns(returns), symbol="BTCUSDT")
 
     assert forecast.usable is True
-    assert any(candidate["model"] == "lstm" for candidate in forecast.candidates)
+    assert all(candidate["model"] != "lstm" for candidate in forecast.candidates)
 
 
 def test_time_series_forecaster_reads_torch_gru_artifact(make_settings, tmp_path) -> None: