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Replace the recipe-only `set_recipe_container_exec_config` with a single `set_container_exec_config` taking an `object_type`, and move it to its own module since it now spans several object families. Supported types and the settings path each one writes: - recipe: params.containerSelection, params.engineParams, or the visual payload's engineParams, refusing a recipe that exposes more than one - ml_task: the mltask settings of a single-task analysis - saved_model: miniTask.containerSelection, the retrain placement - webapp: params.infra.containerSelection, the backend placement - knowledge_bank and agent_tool: containerExecSelection Verified against DSS 15.0.0: 20 objects resolved read-only, and each type round-tripped through EXPLICIT_CONTAINER and NONE back to its original value. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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Summary
set_container_exec_configtaking anobject_typeINHERIT,NONE, andEXPLICIT_CONTAINERon recipes, ML tasks, saved-model retrain, WebApp backends, Knowledge Banks, and agent toolsreferences/container-execution.mdobject_typeobject_idrecipeparams.containerSelection,params.engineParams, or the visual payload'sengineParamsml_taskcontainerSelectionsaved_modelminiTask.containerSelection(retrain placement)webappparams.infra.containerSelection(backend placement)knowledge_bankcontainerExecSelectionagent_toolparams.containerExecSelectionObjects that run no code of their own — an MLflow-imported saved model, a built-in agent tool — expose no selection, and the tool fails without saving rather than inventing one. Same for an analysis that does not hold exactly one ML task.
The exception stays placement-only: it does not open Knowledge Banks or agent tools to any other direct write. Agents and Retrieval-Augmented LLMs are deliberately out of scope — their placement sits per version under a flavor-specific settings block, so a write needs a rule for which version and which flavor is live.