refactor(sdk): add artifact-centered runtime realization

[wolegechu]

Summary

• Move model-runtime realization toward the artifact-runtime boundary and remove public tensorcast.serving runtime surfaces.
• Preserve serving-publication ABI helpers under store/builder modules while keeping root tensorcast focused on artifact/runtime APIs.
• Update tests, examples, and docs for the artifact-centered model-runtime realization path.

Why

This follows the artifact-first runtime realization design: artifact identity, lifecycle, retained handoff, and runtime diagnostics should be expressed through artifact/runtime concepts instead of a parallel serving-session surface.

Validation

• ruff check via pre-commit
• ruff format via pre-commit
• TENSORCAST_SKIP_TORCH_ABI_CHECK=1 pytest tests/python/api/test_public_surface.py tests/python/test_serving_publication_types.py tests/python/artifact_runtime/artifact/test_resolver.py tests/python/artifact_runtime/test_fake_framework_boundary.py tests/python/artifact_runtime/test_lifecycle.py tests/python/artifact_runtime/test_readiness.py tests/python/artifact_runtime/recipe/test_build_session.py tests/python/artifact_runtime/recipe/test_validation.py tests/python/test_pytorch_module_binding.py -q

[chatgpt-codex-connector]

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[chatgpt-codex-connector]

Keep publication constructor public on ArtifactRealizationSpec

Renaming ArtifactRealizationSpec.publication(...) to _publication(...) removes an existing public constructor without providing a replacement, so callers upgrading to this commit will hit AttributeError when building publication realization specs through the documented classmethod path. Because the publication target kind is still implemented, this is a behavioral regression rather than an intentional removal of the feature; keep a public publication classmethod (or a compatibility alias) to preserve runtime behavior.

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