Kaz integration#7
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RNN models require series length >= training_length + 1, but the filter only checked input_chunk_length + forecast_horizon + 1, letting too-short series through and crashing darts. Thread training_length into _build_darts_timeseries and use max(input+horizon, training_length)+1. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
apply_static_scalers returns every static column, so SapphirePredictor attached all of them as static covariates while training filtered to config.static_features via filter_static_columns. Any static_df with extra columns (e.g. LAT/LON metadata) caused a component-count mismatch and failed every predict/hindcast call. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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