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Move issues (01–29) and PRD from .scratch/distributed-inference-network/ into docs/issues/ and docs/. Update ralph_progress.py DEFAULT_PRD path and rewrite docs/agents/issue-tracker.md to reflect the new layout. The distributed_inference_network.egg-info/docs/ mirror is a build artifact already covered by *.egg-info/ in .gitignore — not committed. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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US-022 — X-Meshnet-Start-Layer: overlapping shard execution protocol
Status: done Priority: High Stage: Implemented
Context
Two nodes may register overlapping shard ranges (node A: 0–15, node B: 12–23) to increase redundancy or to enable partial-model nodes to form a complete route. Without coordination, node B would re-run layers 12–15 on top of activations that already include them, producing wrong output.
The X-Meshnet-Start-Layer header tells each downstream node which model layer the incoming
activation tensor represents, so the node skips layers it has already been told to skip.
Decision
Option A: tracker injects start_layer into X-Meshnet-Route hops at proxy time. The head
node passes it per-hop as X-Meshnet-Start-Layer. No peer-to-peer negotiation needed.
Acceptance criteria
- Tracker
_handle_proxy_chatbuilds route hops withstart_layer=covered_up_to + 1 _handle_binary_forwardreadsX-Meshnet-Start-Layerand passes it tobackend.forward_bytes_get_remaining_routeparsesstart_layerfrom injected header and from/v1/routeslow-pathTorchModelShard.forward_bytesaccepts optionalstart_layerand skips layers below it- Test: overlapping two-node route produces correct output without double-computing layers
python -m pytestpasses