DGR-005 — dense-Llama range-aware GGUF ownership evidence

Status: done Date: 2026-07-15 Evidence kind: synthetic-unit + repo checks. No model download, no GPU, no network, no API credits.

Summary

Implemented range-aware dense-Llama ownership so the node reports and admits only the tensors it actually loads:

blk.N.* tensors are selected strictly by assigned layer range.
Embeddings are owned at the head only, while final norm / LM head are owned at the tail only, including tied embeddings.
Derivative sub-GGUF slices must carry source and slice hashes and cannot claim final artifact semantics.
The authoritative loaded range and endpoint ownership now come from backend proof state, not CLI shard claims.
Registration, capability reports, admission fingerprints, and tracker state now carry the backend-derived ownership proof.

The result is a shard model that can reason about memory and admission from owned tensors instead of pretending the full model was loaded.

Files changed

packages/node/meshnet_node/gguf_ownership.py - dense-Llama tensor selection and authoritative ownership helpers.
packages/node/meshnet_node/capability.py - shard reports now carry endpoint ownership and parse it round-trip.
packages/node/meshnet_node/doctor.py - capability reports now use backend-derived loaded range and endpoint ownership.
packages/node/meshnet_node/testing.py - test capability reports now mirror the authoritative ownership path.
packages/node/meshnet_node/admission.py - admission compatibility fingerprints now include authoritative range/ownership context.
packages/node/meshnet_node/model_backend.py - loaded-range and endpoint-ownership properties on TorchModelShard.
packages/node/meshnet_node/startup.py - registration payloads now use the proof-driven shard range.
packages/tracker/meshnet_tracker/capability.py - tracker capability state preserves endpoint ownership.
tests/test_gguf_ownership.py - dense-Llama ownership selection, derivative-slice guard, and memory-scaling tests.
tests/test_node_capability.py - capability report ownership round-trip tests.
tests/test_node_admission.py - backend-loaded range beats CLI claim regression tests.
tests/test_tracker_capability_admission.py - tracker capability proof parsing tests.

Exact commands and real results

Targeted pytest slices

python -m pytest -q tests/test_gguf_ownership.py tests/test_node_capability.py tests/test_node_admission.py

Result: 73 passed

python -m pytest -q tests/test_tracker_capability_admission.py -k 'test_a_passing_report_that_covers_the_registration_is_admitted or test_a_missing_report_is_absent_not_admitted or test_a_failed_report_is_recorded_as_failed or test_a_report_for_a_different_model_is_a_model_mismatch or test_a_report_for_a_different_shard_is_a_shard_mismatch or test_a_report_for_a_different_recipe_than_the_node_declares_is_a_recipe_mismatch or test_a_report_for_a_different_compatibility_fingerprint_is_a_compatibility_mismatch or test_an_older_recipe_catalogue_is_incompatible or test_an_unparseable_catalogue_version_is_incompatible or test_a_stale_report_is_not_admitted or test_a_future_dated_report_is_not_admitted or test_a_report_from_an_unknown_schema_version_is_invalid or test_a_malformed_report_is_invalid_and_never_admitted or test_recorded_detail_carries_no_credentials_from_node_diagnostics or test_compat_policy_routes_a_legacy_node_but_never_a_broken_proof or test_the_policy_is_read_from_the_environment_and_defaults_to_compat'

Result: 22 passed, 13 deselected

Python compile check

python -m compileall -q packages tests

Result: exit 0

Diff hygiene

git diff --check

Result: exit 0

Full deterministic pytest

python -m pytest -q

Result: 211 failed, 428 passed, 13 skipped, 14 warnings, 86 errors in 135.03s

The failing set is not caused by this story. The dominant environment issues were:

tracker and HTTP/socket-backed tests fail with PermissionError: [Errno 1] Operation not permitted when the tracker tries to bind sockets in this sandbox
native protocol tests fail early with a protobuf runtime/gencode mismatch: generated code expects protobuf 7.35.0 while the installed runtime is 6.33.6

Limitations

This evidence is intentionally deterministic and model-free.
The memory-scaling check is synthetic: it validates that owned tensor bytes scale with selected tensors, not a live GGUF download.
Native C++ code was not changed by this story, so the pinned llama.cpp build validation remains covered by DGR-004 rather than repeated here.

Compatibility notes

Dense-Llama ownership is range-first: the shard interior is blk.N.*, and endpoint tensors are only attributed to the head or tail owner as appropriate.
Derivative GGUF slices are explicitly not final artifacts; they must preserve source and slice hashes if used as a temporary compatibility bridge.
The model proof path is authoritative for reported range and endpoint ownership, so operator CLI claims no longer control what the node advertises.
Admission and tracker state now consume the same proof-derived ownership shape, keeping capability reports aligned end to end.

Handoff for dependent stories

DGR-006 can reuse gguf_ownership.py and the new capability fields to wire the shard protocol to proof-derived ownership without re-deriving tensor names.
DGR-008 and later routing work should continue to treat endpoint ownership as metadata and blk.N.* ownership as the core range contract.
If a future temporary slice path is needed, it should keep source/slice hashes visible and avoid claiming final-artifact semantics until a real proof exists.