# Iteration 1 Log

## Metadata

- **Task ID**: DGR-006
- **Task Title**: Implement architecture-defined boundary input/output
- **Description**: MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/06-implement-architecture-defined-boundary-input-output.md` com...
- **Status**: completed
- **Task Completed**: Yes
- **Promise Detected**: Yes
- **Started At**: 2026-07-15T18:13:12.621Z
- **Ended At**: 2026-07-15T18:35:21.242Z
- **Duration**: 22m 8s
- **Input Tokens**: 290
- **Output Tokens**: 53285
- **Total Tokens**: 53575
- **Agent**: claude
- **Model**: claude-opus-4-8
- **Sandbox Mode**: auto
- **Sandbox Network**: Enabled
--- RAW OUTPUT ---
I'll start by reading the mandatory context files before doing anything else.
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md[0m
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.scratch/distributed-gguf-runtime/issues/06-implement-architecture-defined-boundary-input-output.md[0m
Now let me read the dependency evidence and progress files.
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.scratch/distributed-gguf-runtime/evidence/DGR-005/README.md[0m
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.scratch/distributed-gguf-runtime/evidence/DGR-002/README.md[0m
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.ralph-tui/progress.md[0m
Progress log is empty. Let me verify prd.json dependency `passes` state and inspect key source files.
[94m[Bash][0m $ print(json.dumps(d, indent=1)[:2000])"
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/packages/node/meshnet_node/gguf_ownership.py[0m
Let me check the prd.json format and inspect the model_backend and torch_server.
[94m[Bash][0m $ python3 -c " import json d=json.load(open('.scratch/distributed-gguf-runtime/prd.json')) print('keys...
[94m[Bash][0m $ python3 -c " import json d=json.load(open('.scratch/distributed-gguf-runtime/prd.json')) for t in d[...
DGR-005 shows `passes=False` in prd.json but its evidence README says "done" and `gguf_ownership.py` exists and is complete. This is a ralph-loop flag lag, not a defect — the artifacts are present and verified. Let me inspect the backend execution seam.
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/packages/node/meshnet_node/model_backend.py[0m
Now let me look at how existing tests build synthetic models, the native_protocol package, and torch_server reference.
[94m[Bash][0m $ print('transformers', transformers.__version__)" 2>&1 | head -3
torch/transformers are absent in the default venv, so the parity test must be pure-numpy/Python. Let me check numpy and review the native_protocol loader and existing test style.
[94m[Bash][0m $ print('numpy', numpy.__version__)" 2>&1 | head -3 echo "=== native_protocol __init__ head ===" sed -...
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/tests/test_gguf_ownership.py[0m
Let me look at runtime_recipe.py and how certification/architecture admission works currently.
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/packages/node/meshnet_node/runtime_recipe.py[0m
torch/transformers aren't installed; numpy 2.4.3 is. So the parity harness must be a pure-numpy deterministic dense-Llama reference. Let me confirm no existing boundary module and check the conftest/path setup and DGR-004 evidence existence.
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime echo "=== ...
[94m[Bash][0m $ print(meshnet_node.__file__)"

[91m[Error: Exit code 1
=== conftest full ===
13:    meshnet_node.hardware and are not affected by this patch.
16:        import meshnet_node.startup as startup_mod
=== architecture_adapter in capability.py ===
544:    architecture_adapter: str | None = None,
603:            architecture_adapter=architecture_adapter,
=== how tests import meshnet_node (sanity) ===
Traceback (most recent call last):
  File "<string>", line 1, in <module>
ModuleNotFoundError: No module named 'meshnet_node'][0m
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime echo "=== ...
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/conftest.py[0m
I have a complete picture. Now I'll write the boundary adapter module.
[94m[Write][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/packages/node/meshnet_node/boundary_adapter.py[0m """"Architecture-defined boundary input/output for distributed Shards (DGR-006).

A public-network Shard is a contiguous range of transformer layers (RALPH runtime
decision #1). For disjoint processes ... (19311 chars)"
Now the parity test with a pure-numpy dense-Llama reference model.
[94m[Write][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/tests/test_boundary_adapter.py[0m """"Architecture-defined boundary input/output and dense-Llama parity (DGR-006).

These tests prove the boundary contract with a *pure-numpy* dense-Llama reference
model: no download, no GPU, no torch,... (20130 chars)"
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime python -m ...
All 22 pass. Now the quality gates.
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime echo "=== ...
The native_shard_protocol errors are the pre-existing protobuf runtime/gencode mismatch documented in DGR-005/DGR-002 evidence, unrelated to my change. Let me confirm and run the full deterministic suite.
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime python -m ...
Confirmed — pre-existing protobuf runtime version mismatch, independent of my change. Now the full deterministic suite to record the baseline.
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime python -m ...
While the full suite runs, let me verify the boundary_adapter module imports cleanly standalone and check the exact new files for this story.
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime git status...
[94m[Read][0m [95m/tmp/claude-1000/-run-media-popov-d-DEV-repos-d-popov-com-AI--claude-worktrees-distributed-gguf-runtime/0ebd26c2-8500-430d-87c2-de77893f91fb/tasks/bv42fdriz.output[0m
Still running. Let me wait for it to complete.
[94m[Bash][0m $ then     break   fi   sleep 5 done tail -6 /tmp/claude-1000/-run-media-popov-d-DEV-repos-d-popov-com...
Full suite: 715 passed (includes my 22), 20 failed + 12 errors. Let me list the failures and confirm they're pre-existing by reproducing with my files removed.
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime grep -E "^...
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime echo "=== ...
The pipe `| tail -8` discarded the failure list. Let me re-run capturing the full failure summary (my two files are purely additive — nothing imports them — so they cannot affect other tests, but I'll record the exact set).
[94m[Bash][0m $ tail -3 /tmp/dgr006_full.txt
While the suite runs, let me draft the evidence README (I'll fill the failure list after).
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime ls -la .sc...
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime mkdir -p ....
[94m[Bash][0m $ fi   sleep 5 done echo "=== summary line ===" grep -E "passed|failed|error" /tmp/dgr006_full.txt | t...
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime grep -qE "...
Still running. Let me wait for the notification via a Monitor-style poll.
[94m[Bash][0m $ grep -E "^ERROR" /tmp/dgr006_full.txt
None of the 20 failures / 12 errors are in `test_boundary_adapter.py` — all are in unrelated modules. Now the clean-tree reproduction: move my two files aside and confirm the failure set is identical.
[94m[Bash][0m $ echo "exit=$?" grep -E "passed|failed|error" /tmp/dgr006_cleantree.txt | tail -1
Let me wait for the clean-tree run and compare failure sets.
[94m[Bash][0m $ ls -la packages/node/meshnet_node/boundary_adapter.py tests/test_boundary_adapter.py
[94m[Bash][0m $ cat /tmp/claude-1000/-run-media-popov-d-DEV-repos-d-popov-com-AI--claude-worktrees-distributed-gguf-...
[94m[Bash][0m $ fi ls -la packages/node/meshnet_node/boundary_adapter.py tests/test_boundary_adapter.py 2>&1 | head
The clean-tree run is still going (my files are safely in /tmp, to be restored by the wrapper). While it runs, let me draft the progress log and evidence README.
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.ralph-tui/progress.md[0m
[94m[Edit][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.ralph-tui/progress.md[0m edit: "## Codebase Patterns (Study These First)

*Add reu..." → "## Codebase Patterns (Study These First)

- **torc..."
[94m[Bash][0m $ fi
Let me append the DGR-006 progress entry while waiting.
[94m[Edit][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.ralph-tui/progress.md[0m edit: "*Add reusable patterns discovered during developme..." → "*Add reusable patterns discovered during developme..."

[91m[Error: <tool_use_error>String to replace not found in file.
String: *Add reusable patterns discovered during development here.*</tool_use_error>][0m
[94m[Read][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.ralph-tui/progress.md[0m
[94m[Edit][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.ralph-tui/progress.md[0m edit: "- **Pre-existing full-suite failures on this branc..." → "- **Pre-existing full-suite failures on this branc..."
[94m[Bash][0m $ fi
Clean-tree reproduction confirms identical failure/error set (693 vs 715 = exactly my 22 tests, no other change). Let me verify my files are restored and finalize.
[94m[Bash][0m $ cd /run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime ls package...
All gates pass and files are restored. Now let me write the evidence README and machine-readable evidence.
[94m[Write][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.scratch/distributed-gguf-runtime/evidence/DGR-006/README.md[0m "# DGR-006 — Architecture-defined boundary input/output: evidence

Status: done
Date: 2026-07-15
Evidence kind: **synthetic-unit** (pure-numpy dense-Llama reference + boundary
contract). No model downl... (11215 chars)"
Now the machine-readable evidence files.
[94m[Write][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.scratch/distributed-gguf-runtime/evidence/DGR-006/commands.txt[0m "# DGR-006 exact commands (run from repo worktree root)

# Targeted boundary-adapter tests
python -m pytest -q tests/test_boundary_adapter.py
# -> 22 passed in 0.26s

# Python compile check for changed... (985 chars)"
[94m[Bash][0m $ PY
Now update the source issue to `Status: done`.
[94m[Edit][0m [95m/run/media/popov/d/DEV/repos/d-popov.com/AI/.claude/worktrees/distributed-gguf-runtime/.scratch/distributed-gguf-runtime/issues/06-implement-architecture-defined-boundary-input-output.md[0m edit: "# 06 — Implement architecture-defined boundary inp..." → "# 06 — Implement architecture-defined boundary inp..."
Let me verify the final working-tree state — my story files plus preserved pre-existing changes.
[94m[Bash][0m $ print('OK', b.BOUNDARY_SCHEMA_VERSION, sorted({v.adapter for v in b._CERTIFIED_ARCHITECTURES.values(...
All acceptance criteria are met. Summary of what I did for **DGR-006 — Architecture-defined boundary input/output**:

## Implementation

**`packages/node/meshnet_node/boundary_adapter.py`** (new) — the boundary contract:
- **Fail-closed certification** — `certified_architecture()` maps only dense-Llama spellings (`dense-llama`/`llama`/`LlamaForCausalLM`/...) to an adapter; everything else (Qwen3, Mixtral, gpt2, empty/None) raises `UncertifiedArchitectureError`.
- **`BoundaryAdapter`** drives a duck-typed `ShardComputation` and enforces per-role rules: head embeds token IDs (refuses a bundle); middle/tail bypass embedding (refuse token IDs); non-tail emits the **unnormalized** residual with all position rows (no final norm, no LM head, no pruning); tail normalizes → LM head → prunes to last row → samples via an explicit `SamplingContract` (greedy).
- **`BoundaryBundle`** — versioned named-tensor bundle carrying the residual + positions + seam `next_layer`, with `pack()`/`unpack()` for disjoint-process round-trip and `named_tensor_fields()` mapping onto the DGR-002 `NamedTensor` shape.

**`tests/test_boundary_adapter.py`** (new) — a pure-numpy dense-Llama reference (RMSNorm + RoPE + SwiGLU) satisfying the same protocol; 22 tests proving whole-model vs **two-range and three-range** prefill + greedy-decode parity (identical greedy tokens, logits `atol=1e-6`), plus every contract/fail-closed path.

## Verification (real results)
- Targeted: **22 passed**
- `compileall`: exit 0 · `git diff --check`: clean
- Full suite: `20 failed, 715 passed, 13 skipped, 12 errors` — **clean-tree reproduction** (files moved aside) gives `693 passed` with a **byte-identical** failure/error set, proving DGR-006 introduced zero failures. The pre-existing failures (protobuf gencode mismatch + tracker/routing/optional-dep) are recorded in `results.json`.

torch/transformers aren't installed in the default venv, so the numpy reference is the only deterministic, GPU-free, download-free way to prove parity — the identical protocol will be satisfied by the C++ worker (DGR-008). Native C++ / llama.cpp patch gates are N/A (no native code touched), documented in evidence.

Evidence written to `.scratch/distributed-gguf-runtime/evidence/DGR-006/` (README + commands.txt + results.json); progress log and issue `Status: done` updated. Pre-existing working-tree changes preserved; no commits created.

<promise>COMPLETE</promise>
