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    ISidecarTrainer backed by the self-managing MLSidecar client. Lazily starts the sidecar on first use (managed or remote mode is decided by MLSidecar from options/env). Defaults to the process-shared MLSidecarProvider instance rather than constructing a private MLSidecar — see that class's doc comment for why a per-instance sidecar leaked a Python child process per action run. Tests (and callers that genuinely need an isolated sidecar) can still inject their own via the constructor parameter.

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    • Train a model from an assembled feature matrix. The implementation is responsible for sidecar lifecycle (start/connect); the engine only calls this method.

      The engine carves the locked holdout (plan §8.2) in TypeScript before calling this — req.data contains ONLY the training portion (the rows the model may train and tune on). The locked-holdout rows travel separately in the optional second argument so the sidecar scores them exactly once and returns holdout_metrics; they never enter req.data. Keeping the holdout out of the public TrainRequest shape preserves that contract while making the carve auditable and deterministic on the orchestrator side.

      Parameters

      • req: TrainRequest

        the fully-built train request (training matrix + schema + preprocessing + validation)

      • OptionallockedHoldout: MatrixData

        the carved-off holdout matrix to score exactly once (optional)

      Returns Promise<TrainResponse>