512 lines
46 KiB
JSON
512 lines
46 KiB
JSON
{
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"name": "Performant Concurrent Distributed GGUF Runtime",
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"branchName": "ralph/performant-concurrent-distributed-gguf",
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"description": "Benchmark-gated native llama.cpp/GGUF Shards with gRPC streaming, concurrent local KV, continuous batching, real heterogeneous acceptance, and a measured release gate against Transformers/safetensors.",
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"userStories": [
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{
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"id": "DGR-001",
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"title": "Lock the safetensors-versus-GGUF performance contract",
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"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/01-lock-the-safetensors-versus-gguf-performance-contract.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a runtime engineer, I need a controlled baseline so that GGUF work proceeds from measured speed, memory, and quality rather than reputation.",
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"acceptanceCriteria": [
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"Benchmark the same model architecture/revision, machine, prompts, context lengths, output lengths, sampling policy, and concurrency across the current Transformers/safetensors recipe and whole-model llama.cpp recipes.",
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"Separate correctness/quality lanes from quantized performance/fit lanes instead of claiming BF16 and Q4 are numerically equivalent.",
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"Report TTFT, prefill tok/s, decode tok/s, p50/p95 latency, aggregate throughput, RSS, VRAM, artifact size, failures, and output drift in machine-readable JSON.",
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"Add concurrency levels 1 and 4 where memory permits.",
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"Write a versioned performance contract consumed by later release gates, including an explicit stop condition when llama.cpp/GGUF has no meaningful speed or fit benefit.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
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"git diff --check passes",
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"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
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"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
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"Real-model execution is opt-in through MESHNET_ENABLE_REAL_INFERENCE_TESTS=1 and records exact artifact/runtime/hardware evidence",
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"Model artifacts remain on the configured mounted-drive storage and never under /home",
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"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
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"Read and verify every dependency evidence README before relying on dependency behavior",
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"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
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"Write .scratch/distributed-gguf-runtime/evidence/DGR-001/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 2,
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"passes": true,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/01-lock-the-safetensors-versus-gguf-performance-contract.md",
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"dependsOn": []
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},
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{
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"id": "DGR-002",
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"title": "Adopt the versioned gRPC Shard protocol",
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"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/02-adopt-the-versioned-grpc-shard-protocol.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a node developer, I need a battle-proven streaming protocol so that Python and C++ Shards communicate without a custom socket protocol.",
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"acceptanceCriteria": [
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"Add a Protocol Buffers schema for capability, health, session stream, release, and cancellation operations.",
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"Define one long-lived bidirectional gRPC stream per Route Session Activation Seam with deadlines, cancellation, flow control, and structured errors.",
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"Define bounded chunking for prefill and a small decode fast path.",
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"Carry schema version, request/work ID, Route Session ID, route epoch, artifact/recipe fingerprint, Shard range/effective start, phase, position, idempotency step, cache expectation, compression, and checksum.",
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"Define a versioned named-tensor bundle with per-tensor name, shape, dtype, byte order, and payload fragments.",
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"Add generated-schema round-trip and compatibility tests in Python and C++.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
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"git diff --check passes",
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"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
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"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
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"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
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"Read and verify every dependency evidence README before relying on dependency behavior",
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"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
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"Write .scratch/distributed-gguf-runtime/evidence/DGR-002/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 1,
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"passes": true,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/02-adopt-the-versioned-grpc-shard-protocol.md",
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"dependsOn": []
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},
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{
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"id": "DGR-003",
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"title": "Define exact Artifact and runtime recipe identity",
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"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/03-define-exact-artifact-and-runtime-recipe-identity.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs the Tracker, I need exact compatibility identity so that only numerically and operationally compatible Shards form an Inference Route.",
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"acceptanceCriteria": [
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"Separate weight quantization, activation dtype, compute dtype, KV dtype/layout, tokenizer revision, architecture adapter, backend, and runtime version.",
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"Bind derivative or split artifacts to an exact source Model Artifact hash and Shard range.",
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"Produce a stable compatibility fingerprint used by capability admission and the gRPC handshake.",
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"Fail closed on mismatched artifact, tokenizer, architecture, range, boundary schema, activation recipe, or cache layout.",
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"Keep unsupported recipes registered-but-dark until a real distributed forward certifies them.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
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"git diff --check passes",
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"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
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"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
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"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
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"Read and verify every dependency evidence README before relying on dependency behavior",
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"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
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"Write .scratch/distributed-gguf-runtime/evidence/DGR-003/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 3,
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"passes": false,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/03-define-exact-artifact-and-runtime-recipe-identity.md",
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"dependsOn": [
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"DGR-002"
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]
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},
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{
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"id": "DGR-004",
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"title": "Create the reproducible pinned llama.cpp patch stack",
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"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/04-create-the-reproducible-pinned-llama-cpp-patch-stack.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a maintainer, I need a small auditable fork boundary so that upstream updates do not turn the runtime into an unmaintainable stitched codebase.",
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"acceptanceCriteria": [
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"Pin one exact llama.cpp commit through a reproducible source dependency mechanism.",
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"Store a numbered minimal patch stack separately from Meshnet networking code.",
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"Add a build script that applies/checks patches and builds the standalone worker without manual source copying.",
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"Record upstream file/ABI assumptions and fail clearly when the pin changes.",
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"Preserve upstream license and attribution notices.",
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"Add a clean rebuild smoke test that does not download a model.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
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"git diff --check passes",
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"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
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"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
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"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
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"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
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"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
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"Read and verify every dependency evidence README before relying on dependency behavior",
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"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
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"Write .scratch/distributed-gguf-runtime/evidence/DGR-004/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 4,
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"passes": false,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/04-create-the-reproducible-pinned-llama-cpp-patch-stack.md",
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"dependsOn": [
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"DGR-001"
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]
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},
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{
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"id": "DGR-005",
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"title": "Implement dense-Llama range-aware GGUF ownership",
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"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/05-implement-dense-llama-range-aware-gguf-ownership.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a node, I need to map only my assigned dense-Llama Shard so that aggregate consumer memory can hold a model larger than one node.",
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"acceptanceCriteria": [
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"Register and allocate only `blk.N.*` tensors in the assigned range.",
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"Load embeddings only for the head and final norm/LM head only for the tail, including tied embeddings.",
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"Prefer range-aware mapping from one exact source GGUF; if derivative sub-GGUFs are used temporarily, verify source/slice hashes and avoid claiming final artifact semantics.",
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"Report authoritative loaded range and endpoint ownership from the model, not operator CLI claims.",
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"Demonstrate mapped/resident memory scales with owned tensors rather than full model size.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
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"git diff --check passes",
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"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
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"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
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"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
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"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
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"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
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"Read and verify every dependency evidence README before relying on dependency behavior",
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"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
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"Write .scratch/distributed-gguf-runtime/evidence/DGR-005/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 5,
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"passes": false,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/05-implement-dense-llama-range-aware-gguf-ownership.md",
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"dependsOn": [
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"DGR-003",
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"DGR-004"
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]
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},
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{
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"id": "DGR-006",
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"title": "Implement architecture-defined boundary input/output",
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"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` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a Shard, I need to consume and emit the correct transformer boundary state so that disjoint processes reproduce whole-model execution.",
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"acceptanceCriteria": [
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"Head accepts token IDs and owns token embedding.",
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"Middle/tail bypass token embedding and accept the named boundary bundle.",
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"Non-tail emits the unnormalized architecture-defined residual/boundary before final norm/head and before tail-only row pruning.",
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"Tail emits logits or token output through an explicit sampling contract.",
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"Dense-Llama whole-model versus two-range prefill and greedy-decode parity passes the documented tolerance.",
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"The adapter interface fails closed for uncertified architectures.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
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"git diff --check passes",
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"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
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"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
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"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
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"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
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"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
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"Read and verify every dependency evidence README before relying on dependency behavior",
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"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
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"Write .scratch/distributed-gguf-runtime/evidence/DGR-006/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 6,
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"passes": false,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/06-implement-architecture-defined-boundary-input-output.md",
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"dependsOn": [
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"DGR-002",
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"DGR-005"
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]
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},
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{
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"id": "DGR-007",
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"title": "Add isolated concurrent local Hot KV State",
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"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/07-add-isolated-concurrent-local-hot-kv-state.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a client, I need concurrent Route Sessions to retain independent per-Shard cache so that one request cannot clear or corrupt another.",
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"acceptanceCriteria": [
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"Map `(Route Session ID, route epoch)` to an isolated llama sequence or bounded context.",
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"Allocate KV only for owned layers.",
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"Support prefill append, decode append, truncate, release, TTL/LRU eviction, and explicit cache-miss response.",
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"Reject stale epochs and incompatible cache recipes.",
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"At least four concurrent sessions on a small model complete without token or KV cross-talk.",
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"Cancellation/release of one session leaves other sessions intact and memory returns to the configured budget.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
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"git diff --check passes",
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"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
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"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
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"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
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"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
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"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
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"Read and verify every dependency evidence README before relying on dependency behavior",
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"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
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"Write .scratch/distributed-gguf-runtime/evidence/DGR-007/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 7,
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"passes": false,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/07-add-isolated-concurrent-local-hot-kv-state.md",
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"dependsOn": [
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"DGR-006"
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]
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},
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{
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"id": "DGR-008",
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"title": "Build the standalone C++ gRPC Shard worker",
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"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/08-build-the-standalone-c-grpc-shard-worker.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a node runtime, I need one supervised native process so that llama.cpp internals remain behind a stable project-owned protocol.",
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"acceptanceCriteria": [
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"Worker exposes capability, health, session stream, release, cancellation, and metrics services from DGR-002.",
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"Worker loads one exact Artifact/recipe/Shard identity and refuses mismatched requests.",
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"Streaming path enforces bounded messages, flow control, deadlines, idempotency, and independent session cancellation.",
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"Worker does not expose raw llama.cpp RPC or arbitrary GGML graph execution.",
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"Graceful shutdown releases sessions; crash behavior is bounded and observable.",
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"Python integration tests run against a fake model mode without model downloads.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
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"git diff --check passes",
|
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"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
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"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
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"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
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"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-008/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
|
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 8,
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"passes": false,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/08-build-the-standalone-c-grpc-shard-worker.md",
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"dependsOn": [
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"DGR-002",
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"DGR-003",
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"DGR-004",
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"DGR-006",
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"DGR-007"
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]
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},
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{
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"id": "DGR-009",
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"title": "Integrate the native worker with Meshnet",
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"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/09-integrate-the-native-worker-with-meshnet.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs the existing node service, I need a GGUF Shard backend adapter so that the Tracker, relay, billing, telemetry, and capability admission remain the sole control plane.",
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"acceptanceCriteria": [
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"Implement the existing model-backend surface without changing Transformers behavior.",
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"Registration carries exact validated GGUF recipe, Shard, backend and concurrency/KV capacity.",
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"Tracker forms only complete compatible routes and keeps uncertified recipes dark.",
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"Direct routes use gRPC streams; relayed routes carry the same versioned protobuf frames as opaque binary through the existing relay seam.",
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"Existing request/work IDs, cancellation, Generation Telemetry, billing, and per-node attribution remain correlated.",
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"No vLLM, Nakshatra, prima.cpp, or custom-engine control plane becomes a core dependency.",
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"Targeted pytest tests pass",
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"python -m compileall packages tests passes for Python changes",
|
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"git diff --check passes",
|
|
"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
|
"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
|
"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
|
"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-009/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
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"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
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],
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"priority": 9,
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"passes": false,
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"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/09-integrate-the-native-worker-with-meshnet.md",
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"dependsOn": [
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"DGR-003",
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"DGR-008"
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]
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},
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{
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"id": "DGR-010",
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"title": "Pass local real-model two-process acceptance",
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|
"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/10-pass-local-real-model-two-process-acceptance.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a release engineer, I need real local distributed parity before involving network variability.",
|
|
"acceptanceCriteria": [
|
|
"Two local worker processes open disjoint dense-Llama ranges from the certified Artifact.",
|
|
"Prefill and at least 32 greedy decode tokens match whole-model llama.cpp within the certified tolerance.",
|
|
"Each worker retains only its own tensors and Hot KV State.",
|
|
"Four concurrent Route Sessions pass isolation and cleanup checks.",
|
|
"Report TTFT, prefill/decode throughput, seam bytes/latency, worker RSS/VRAM, KV memory, batch size, and queue time.",
|
|
"Killing one worker produces a bounded structured failure rather than a deadlock.",
|
|
"Targeted pytest tests pass",
|
|
"python -m compileall packages tests passes for Python changes",
|
|
"git diff --check passes",
|
|
"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
|
"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
|
"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
|
"Real-model execution is opt-in through MESHNET_ENABLE_REAL_INFERENCE_TESTS=1 and records exact artifact/runtime/hardware evidence",
|
|
"Model artifacts remain on the configured mounted-drive storage and never under /home",
|
|
"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-010/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
|
|
"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
|
|
],
|
|
"priority": 10,
|
|
"passes": false,
|
|
"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/10-pass-local-real-model-two-process-acceptance.md",
|
|
"dependsOn": [
|
|
"DGR-009"
|
|
]
|
|
},
|
|
{
|
|
"id": "DGR-011",
|
|
"title": "Pass a real heterogeneous two-machine route",
|
|
"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/11-pass-a-real-heterogeneous-two-machine-route.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a consumer-hardware operator, I need two physical machines to execute one GGUF model so that the distributed claim is real.",
|
|
"acceptanceCriteria": [
|
|
"Tracker selects two physical nodes with disjoint Shards and one exact certified recipe/compatibility class.",
|
|
"Actual CPU/GPU execution occurs on both nodes; synthetic workers do not satisfy acceptance.",
|
|
"Prefill/decode, concurrent-session isolation, telemetry, cancellation, and cleanup pass over the real transport/relay path.",
|
|
"Exact hardware, network, backend, model hash, route, commands, and raw metrics are recorded.",
|
|
"A model or recipe larger than one participating node's admitted memory is exercised when available.",
|
|
"Output drift is measured and incompatible mixed backends fail closed.",
|
|
"Targeted pytest tests pass",
|
|
"python -m compileall packages tests passes for Python changes",
|
|
"git diff --check passes",
|
|
"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
|
"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
|
"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
|
"Real-model execution is opt-in through MESHNET_ENABLE_REAL_INFERENCE_TESTS=1 and records exact artifact/runtime/hardware evidence",
|
|
"Model artifacts remain on the configured mounted-drive storage and never under /home",
|
|
"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-011/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
|
|
"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
|
|
],
|
|
"priority": 11,
|
|
"passes": false,
|
|
"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/11-pass-a-real-heterogeneous-two-machine-route.md",
|
|
"dependsOn": [
|
|
"DGR-010"
|
|
]
|
|
},
|
|
{
|
|
"id": "DGR-012",
|
|
"title": "Implement continuous batching and bounded admission",
|
|
"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/12-implement-continuous-batching-and-bounded-admission.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a node operator, I need active sessions batched safely so that concurrency increases aggregate throughput rather than serializing every request.",
|
|
"acceptanceCriteria": [
|
|
"Node scheduler admits sessions against weight, KV, scratch, and queue budgets.",
|
|
"Compatible decode steps from multiple sessions form llama.cpp batches while preserving per-session positions and outputs.",
|
|
"Prefill does not starve decode; scheduling policy and bounds are explicit.",
|
|
"Backpressure prevents unbounded queued activations or KV growth.",
|
|
"Capability telemetry reports active sessions, queue depth, batch occupancy, KV pressure, prefill/decode rates, and rejected admissions.",
|
|
"Concurrency 1/2/4/8 benchmark identifies saturation and shows no cross-session corruption.",
|
|
"Targeted pytest tests pass",
|
|
"python -m compileall packages tests passes for Python changes",
|
|
"git diff --check passes",
|
|
"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
|
"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
|
"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
|
"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-012/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
|
|
"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
|
|
],
|
|
"priority": 12,
|
|
"passes": false,
|
|
"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/12-implement-continuous-batching-and-bounded-admission.md",
|
|
"dependsOn": [
|
|
"DGR-007",
|
|
"DGR-009",
|
|
"DGR-010"
|
|
]
|
|
},
|
|
{
|
|
"id": "DGR-013",
|
|
"title": "Harden failure, cancellation, and restart semantics",
|
|
"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/13-harden-failure-cancellation-and-restart-semantics.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a client, I need failures to be bounded and explicit so that distributed speed does not come with hanging or corrupted generations.",
|
|
"acceptanceCriteria": [
|
|
"Deadlines and heartbeat/health loss terminate blocked stream operations.",
|
|
"Cancellation propagates across every Shard and releases local KV and queued buffers.",
|
|
"Duplicate steps are idempotent; uncertain mutations are never replayed silently.",
|
|
"Alpha failover restarts from token zero on a newly compatible route rather than importing unverified KV.",
|
|
"Worker death, stream reset, malformed bundle, stale epoch, and cache miss tests pass.",
|
|
"Billing/work records distinguish completed, cancelled, failed, and unverified work.",
|
|
"Targeted pytest tests pass",
|
|
"python -m compileall packages tests passes for Python changes",
|
|
"git diff --check passes",
|
|
"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
|
"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
|
"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
|
"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-013/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
|
|
"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
|
|
],
|
|
"priority": 13,
|
|
"passes": false,
|
|
"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/13-harden-failure-cancellation-and-restart-semantics.md",
|
|
"dependsOn": [
|
|
"DGR-008",
|
|
"DGR-009",
|
|
"DGR-012"
|
|
]
|
|
},
|
|
{
|
|
"id": "DGR-014",
|
|
"title": "Enforce the GGUF-versus-safetensors release gate",
|
|
"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/14-enforce-the-gguf-versus-safetensors-release-gate.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs the product owner, I need an end-to-end comparison so that the native runtime ships only if it advances model access or performance.",
|
|
"acceptanceCriteria": [
|
|
"Run current distributed safetensors and distributed GGUF routes on the same certified model/hardware/network scenario where technically comparable.",
|
|
"Report quality, TTFT, prefill/decode throughput, aggregate concurrency throughput, p95 latency, seam cost, memory, KV pressure, failures, and cleanup.",
|
|
"Evaluate against the DGR-001 performance contract without changing thresholds after seeing results.",
|
|
"Ship recommendation is one of: promote GGUF, optimize a measured bottleneck with a new bounded task, or stop the native track.",
|
|
"Results clearly separate quantization gains from transport/runtime gains.",
|
|
"Targeted pytest tests pass",
|
|
"python -m compileall packages tests passes for Python changes",
|
|
"git diff --check passes",
|
|
"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
|
"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
|
"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
|
"Real-model execution is opt-in through MESHNET_ENABLE_REAL_INFERENCE_TESTS=1 and records exact artifact/runtime/hardware evidence",
|
|
"Model artifacts remain on the configured mounted-drive storage and never under /home",
|
|
"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-014/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
|
|
"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
|
|
],
|
|
"priority": 14,
|
|
"passes": false,
|
|
"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/14-enforce-the-gguf-versus-safetensors-release-gate.md",
|
|
"dependsOn": [
|
|
"DGR-001",
|
|
"DGR-011",
|
|
"DGR-012",
|
|
"DGR-013"
|
|
]
|
|
},
|
|
{
|
|
"id": "DGR-015",
|
|
"title": "Add and certify a Qwen3/Qwen3-MoE adapter",
|
|
"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/15-add-and-certify-a-qwen3-qwen3-moe-adapter.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a client seeking top models, I need a separately certified MoE-capable architecture after the dense runtime proves stable.",
|
|
"acceptanceCriteria": [
|
|
"Implement explicit tensor ownership, router/top-k, expert/shared-expert, Q/K normalization, boundary bundle, and cache semantics for the selected Qwen3 family recipe.",
|
|
"Do not reuse the dense-Llama adapter through unchecked name substitutions.",
|
|
"Whole-model versus distributed prefill/decode parity passes the architecture-specific tolerance.",
|
|
"Expert memory ownership and communication are measured.",
|
|
"Real consumer-hardware acceptance and capability admission pass before the recipe becomes routable.",
|
|
"Targeted pytest tests pass",
|
|
"python -m compileall packages tests passes for Python changes",
|
|
"git diff --check passes",
|
|
"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
|
"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
|
"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
|
"Real-model execution is opt-in through MESHNET_ENABLE_REAL_INFERENCE_TESTS=1 and records exact artifact/runtime/hardware evidence",
|
|
"Model artifacts remain on the configured mounted-drive storage and never under /home",
|
|
"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-015/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
|
|
"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
|
|
],
|
|
"priority": 15,
|
|
"passes": false,
|
|
"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/15-add-and-certify-a-qwen3-qwen3-moe-adapter.md",
|
|
"dependsOn": [
|
|
"DGR-014"
|
|
]
|
|
},
|
|
{
|
|
"id": "DGR-016",
|
|
"title": "Produce the upstream llama.cpp collaboration package",
|
|
"description": "MANDATORY FRESH-SESSION CONTEXT: Read `.scratch/distributed-gguf-runtime/RALPH-CONTEXT.md` and `.scratch/distributed-gguf-runtime/issues/16-produce-the-upstream-llama-cpp-collaboration-package.md` completely before coding. Read the evidence handoff for every dependency. The global goal is performant concurrent inference for models larger than one consumer node, using Meshnet as the sole control plane, gRPC/Protobuf as the Shard protocol, and a small pinned llama.cpp worker—not a stitched collection of runtimes.\n\nAs a maintainer, I need narrow upstreamable proposals so that our patch burden can shrink without asking llama.cpp to own Meshnet networking.",
|
|
"acceptanceCriteria": [
|
|
"Separate generic llama.cpp hooks from Meshnet protocol/control-plane code.",
|
|
"Prepare minimal reproducible examples and tests for range-aware loading, boundary input/output, and layer-filtered KV.",
|
|
"Compare the proposal with Nakshatra and prima.cpp evidence and explain why the API is generally useful.",
|
|
"Preserve one scoped commit/patch per concern against the exact upstream pin.",
|
|
"Produce an outreach document suitable for Georgi/llama.cpp maintainers; actual sending remains a human action.",
|
|
"Targeted pytest tests pass",
|
|
"python -m compileall packages tests passes for Python changes",
|
|
"git diff --check passes",
|
|
"Default tests remain deterministic, model-download-free, API-credit-free, and GPU-free",
|
|
"Full deterministic pytest -q passes, or the exact pre-existing unrelated failure is recorded with a clean-tree reproduction",
|
|
"Pinned native C++ target builds and focused CTest/protocol tests pass where native code is touched",
|
|
"llama.cpp patch stack applies cleanly to the exact pinned commit where patch code is touched",
|
|
"Read .scratch/distributed-gguf-runtime/RALPH-CONTEXT.md and this story issue completely before changing code",
|
|
"Read and verify every dependency evidence README before relying on dependency behavior",
|
|
"Preserve all pre-existing working-tree changes and stage only files belonging to this story",
|
|
"Write .scratch/distributed-gguf-runtime/evidence/DGR-016/README.md with files changed, exact commands and real results, limitations, compatibility notes, and dependent-story handoff",
|
|
"Update only this story issue to Status: done after every acceptance criterion and quality gate passes"
|
|
],
|
|
"priority": 16,
|
|
"passes": false,
|
|
"notes": "Source issue: .scratch/distributed-gguf-runtime/issues/16-produce-the-upstream-llama-cpp-collaboration-package.md",
|
|
"dependsOn": [
|
|
"DGR-010"
|
|
]
|
|
}
|
|
]
|
|
}
|