8 Commits

Author SHA1 Message Date
Dobromir Popov
5b33bf8b99 feat: compare safetensors and gguf on cpu and gpu 2026-07-14 18:45:12 +03:00
Dobromir Popov
c7554ef7d8 feat: add DGR-001 performance contract 2026-07-14 18:13:54 +03:00
Dobromir Popov
7b3399760e chore: wrap up completed story metadata 2026-07-14 17:09:04 +03:00
Dobromir Popov
22467f145c merge: distributed performance baseline benchmark 2026-07-14 17:01:08 +03:00
Dobromir Popov
35af1e21de fix: make model placement controls observable 2026-07-14 16:00:37 +02:00
Dobromir Popov
348b003d6e fix: restore responsive dashboard panel grid 2026-07-14 15:55:24 +02:00
Dobromir Popov
1e64a5b2b9 new dash update 2026-07-14 15:29:11 +02:00
Dobromir Popov
e2f3ae32b8 feat: let admins manage model placement 2026-07-14 15:16:23 +02:00
15 changed files with 701 additions and 47 deletions

View File

@@ -12,4 +12,10 @@ Provide an opt-in, admin-only tracker Dashboard Testing tab that dynamically dis
- One active run.
- Real inference stays separately environment-gated and excluded from default suites.
## Operator workflow
See [`docs/dev/dashboard-test-runner.md`](../../docs/dev/dashboard-test-runner.md)
for launch configuration, default safe suites vs the gated real-inference suite,
and required environment variables.
See `prd.json` for executable Ralph user stories and acceptance criteria.

View File

@@ -51,15 +51,16 @@
"uv run pytest tests/test_dashboard.py tests/test_dynamic_routing.py -q passes."
],
"priority": 3,
"passes": false,
"passes": true,
"notes": "Do not reintroduce --enable-test-runner without implementing its CLI argument in US-001.",
"dependsOn": [
"US-001",
"US-002"
]
],
"completionNotes": "Completed by agent"
}
],
"metadata": {
"updatedAt": "2026-07-11T17:02:30.520Z"
"updatedAt": "2026-07-12T01:58:06.286Z"
}
}

View File

@@ -0,0 +1,68 @@
# DGR-001 — performance contract baseline
## Files changed
- `packages/node/meshnet_node/performance_contract.py`
- `tests/test_performance_contract.py`
- `.scratch/distributed-gguf-runtime/issues/01-lock-the-safetensors-versus-gguf-performance-contract.md`
- `.scratch/distributed-gguf-runtime/evidence/DGR-001/performance-contract.json`
## What this slice does
- Locks the DGR-001 benchmark contract in code.
- Pins the architecture-aligned baseline to **DeepSeek-V2-Lite-Chat** (`deepseek2`).
- Uses the same model on both sides of the comparison:
- **safetensors:** `deepseek-ai/DeepSeek-V2-Lite-Chat` in **BF16**
- **GGUF:** `second-state/DeepSeek-V2-Lite-Chat-GGUF` in **Q2_K**
- Exposes a machine-readable JSON contract with:
- benchmark lanes for `transformers` safetensors and `llama.cpp` GGUF on **CPU** and **GPU**
- concurrency levels `1` and `4`
- the required metrics list
- an explicit stop condition for “no meaningful speed or fit benefit”
## Exact commands and real results
### Targeted tests
```bash
pytest -q tests/test_performance_contract.py tests/test_route_session_benchmark.py
```
Result: `9 passed in 0.14s`
### Contract artifact generation
```bash
PYTHONPATH=packages/node python -m meshnet_node.performance_contract --json-out .scratch/distributed-gguf-runtime/evidence/DGR-001/performance-contract.json
```
Result: wrote `.scratch/distributed-gguf-runtime/evidence/DGR-001/performance-contract.json`
### Python compile check
```bash
python -m compileall packages/node/meshnet_node/performance_contract.py tests/test_performance_contract.py
```
Result: passed
## Limitations
- This slice captures the DGR-001 contract and baseline selection only.
- It does **not** download or run a real model yet.
- Real safetensors vs GGUF execution, TTFT/prefill/decode measurements, RSS/VRAM capture, and output-drift comparison are still to be implemented against the contract.
## Compatibility notes
- The contract stays on the DeepSeek2 family to remain close to the DeepSeek-V4-Flash end goal.
- A smaller non-DeepSeek model can still be used later for loader-plumbing smoke tests, but it does not replace this baseline.
- Model artifacts must stay on the mounted drive and not under `/home`.
## Dependent-story handoff
Next implementation work should attach to this contract and add the live benchmark runner that actually compares:
1. current Transformers/safetensors recipe
2. whole-model llama.cpp GGUF recipe
using the same model architecture/revision and the same prompt/context/concurrency settings.

View File

@@ -0,0 +1,75 @@
{
"benchmark_lanes": [
{
"concurrency_levels": [
1,
4
],
"device": "cpu",
"id": "transformers-safetensors-cpu",
"recipe": "current safetensors recipe",
"runtime": "transformers"
},
{
"concurrency_levels": [
1,
4
],
"device": "cpu",
"id": "llama-cpp-gguf-cpu",
"recipe": "whole-model GGUF recipe",
"runtime": "llama.cpp"
},
{
"concurrency_levels": [
1,
4
],
"device": "gpu",
"id": "transformers-safetensors-gpu",
"recipe": "current safetensors recipe",
"runtime": "transformers"
},
{
"concurrency_levels": [
1,
4
],
"device": "gpu",
"id": "llama-cpp-gguf-gpu",
"recipe": "whole-model GGUF recipe",
"runtime": "llama.cpp"
}
],
"metrics": [
"ttft_ms",
"prefill_tok_per_sec",
"decode_tok_per_sec",
"p50_latency_ms",
"p95_latency_ms",
"aggregate_throughput_tok_per_sec",
"rss_bytes",
"vram_bytes",
"artifact_bytes",
"failure_count",
"output_drift"
],
"model_target": {
"architecture": "deepseek2",
"comparison_policy": "same model/revision, closest practical low-footprint precision pair: BF16 safetensors versus Q2_K GGUF",
"gguf_quant": "Q2_K",
"gguf_repo": "second-state/DeepSeek-V2-Lite-Chat-GGUF",
"gguf_size_gb": 6.43,
"name": "DeepSeek-V2-Lite-Chat",
"rationale": "Smallest DeepSeek-family benchmark anchor that still points toward DeepSeek-V4-Flash; keeps the runtime on the DeepSeek2 path instead of falling back to a tiny but architecture-mismatched smoke model.",
"safetensors_precision": "bfloat16",
"safetensors_repo": "deepseek-ai/DeepSeek-V2-Lite-Chat"
},
"notes": [
"Real model execution stays opt-in and must keep model artifacts on the mounted drive.",
"Use the tiny fallback only for loader plumbing smoke tests; it does not replace the architecture-aligned baseline."
],
"schema_version": 1,
"stop_condition": "Stop if GGUF does not provide a meaningful speed or fit benefit over the safetensors baseline for the chosen DeepSeek-family model target.",
"story_id": "DGR-001"
}

View File

@@ -13,6 +13,15 @@ Status: ready-for-agent
As a runtime engineer, I need a controlled baseline so that GGUF work proceeds from measured speed, memory, and quality rather than reputation.
## Baseline model target
Use the same model on both sides of the comparison, with the closest practical low-footprint precision pair:
- **safetensors:** `deepseek-ai/DeepSeek-V2-Lite-Chat` in **BF16**
- **GGUF:** `second-state/DeepSeek-V2-Lite-Chat-GGUF` in **Q2_K** (~6.5GB)
Keep the benchmark matrix explicit for **CPU** and **GPU** runs. Reserve smaller non-DeepSeek fallback models only for loader plumbing smoke tests if needed; they do not count as the DGR-001 architecture-aligned baseline.
## Expected durable outputs
- Benchmark harness and deterministic tests

View File

@@ -16,8 +16,9 @@
],
"priority": 1,
"passes": true,
"notes": "Completed 2026-07-14. Deterministic direct/relay and cached/stateless stub benchmark with JSON/summary attribution; focused test suite passes (7). Source issue: .scratch/distributed-inference-performance/issues/01-baseline-profiling-harness.md",
"dependsOn": []
"notes": "Source issue: .scratch/distributed-inference-performance/issues/01-baseline-profiling-harness.md",
"dependsOn": [],
"completionNotes": "Completed by agent"
},
{
"id": "DIP-002",
@@ -31,9 +32,12 @@
"Tests cover binary, JSON, timeout, disconnect, cancellation, and cleanup"
],
"priority": 2,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/distributed-inference-performance/issues/02-relay-session-compatibility.md",
"dependsOn": ["DIP-001"]
"dependsOn": [
"DIP-001"
],
"completionNotes": "Completed by agent"
},
{
"id": "DIP-003",
@@ -47,9 +51,12 @@
"Benchmark shows healthy-session connection count independent of token count"
],
"priority": 3,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/distributed-inference-performance/issues/03-http-keepalive.md",
"dependsOn": ["DIP-001"]
"dependsOn": [
"DIP-001"
],
"completionNotes": "Completed by agent"
},
{
"id": "DIP-004",
@@ -63,9 +70,12 @@
"Tests verify cadence and cleanup"
],
"priority": 4,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/distributed-inference-performance/issues/04-seam-telemetry.md",
"dependsOn": ["DIP-001"]
"dependsOn": [
"DIP-001"
],
"completionNotes": "Completed by agent"
},
{
"id": "DIP-005",
@@ -79,9 +89,12 @@
"Tests cover compressible, incompressible, threshold, malformed, and legacy bodies"
],
"priority": 5,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/distributed-inference-performance/issues/05-adaptive-compression.md",
"dependsOn": ["DIP-001"]
"dependsOn": [
"DIP-001"
],
"completionNotes": "Completed by agent"
},
{
"id": "DIP-006",
@@ -95,9 +108,12 @@
"Wire and token-output regression tests pass"
],
"priority": 6,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/distributed-inference-performance/issues/06-activation-framing-copies.md",
"dependsOn": ["DIP-001"]
"dependsOn": [
"DIP-001"
],
"completionNotes": "Completed by agent"
},
{
"id": "DIP-007",
@@ -111,9 +127,13 @@
"Tests cover chunking, slow consumers, failure, and legacy peers"
],
"priority": 7,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/distributed-inference-performance/issues/07-prefill-backpressure.md",
"dependsOn": ["DIP-001", "DIP-004"]
"dependsOn": [
"DIP-001",
"DIP-004"
],
"completionNotes": "Completed by agent"
},
{
"id": "DIP-008",
@@ -127,9 +147,20 @@
"Gate verifies token identity, session stability, and resource cleanup"
],
"priority": 8,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/distributed-inference-performance/issues/08-end-to-end-performance-gate.md",
"dependsOn": ["DIP-002", "DIP-003", "DIP-004", "DIP-005", "DIP-006", "DIP-007"]
"dependsOn": [
"DIP-002",
"DIP-003",
"DIP-004",
"DIP-005",
"DIP-006",
"DIP-007"
],
"completionNotes": "Completed by agent"
}
]
],
"metadata": {
"updatedAt": "2026-07-12T02:35:28.752Z"
}
}

View File

@@ -35,11 +35,12 @@
"Full pytest passes or an exact unrelated blocker is recorded"
],
"priority": 2,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/node-capability-admission/issues/02-doctor-real-forward.md",
"dependsOn": [
"NCA-001"
]
],
"completionNotes": "Completed by agent"
},
{
"id": "NCA-003",
@@ -54,12 +55,13 @@
"Full pytest passes or an exact unrelated blocker is recorded"
],
"priority": 3,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/node-capability-admission/issues/03-fail-closed-startup-admission.md",
"dependsOn": [
"NCA-001",
"NCA-002"
]
],
"completionNotes": "Completed by agent"
},
{
"id": "NCA-004",
@@ -76,12 +78,13 @@
"Full pytest passes or an exact unrelated blocker is recorded"
],
"priority": 4,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/node-capability-admission/issues/04-tracker-validated-capability-routing.md",
"dependsOn": [
"NCA-001",
"NCA-003"
]
],
"completionNotes": "Completed by agent"
},
{
"id": "NCA-005",
@@ -96,15 +99,16 @@
"Full pytest passes or an exact unrelated blocker is recorded"
],
"priority": 5,
"passes": false,
"passes": true,
"notes": "Source issue: .scratch/node-capability-admission/issues/05-docs-hardware-lane-contract.md",
"dependsOn": [
"NCA-002",
"NCA-004"
]
],
"completionNotes": "Completed by agent"
}
],
"metadata": {
"updatedAt": "2026-07-11T19:16:52.768Z"
"updatedAt": "2026-07-12T01:54:03.030Z"
}
}

View File

@@ -1,9 +1,16 @@
# US-042 — GGUF/llama.cpp node backend
Status: planned
Priority: High (whole-model GGUF shortcut; distributed path in [ADR-0024](../adr/0024-distributed-gguf-runtime.md))
Priority: High (unlocks DeepSeek-V4-Flash on volunteer hardware — the pool's core value)
Stage: Draft design
## Goal
Run **DeepSeek-V4-Flash** as the first real large-model target on volunteer
hardware via GGUF/llama.cpp. This epic is no longer GLM-oriented: the initial
objective is to prove that DeepSeek-V4-Flash can load and serve correctly on
consumer/unified-memory nodes, then expand from there.
## Context
The node backend is transformers-only (`model_backend.py`
@@ -35,17 +42,7 @@ to it (single-hop route). Smallest step, no cross-node activation work, and
already useful: Strix Halo 128 GB serves DeepSeek-V4-Flash IQ3_XXS (114 GB)
via llama.cpp Vulkan today.
Recommended sequencing: **C first** (US-042), then **ADR-0024 benchmark gate** (DGR-001), then distributed native worker (DGR-002+). Direction B (llama.cpp RPC) is rejected per ADR-0024.
## Runtime sequencing
| Stage | Track | Delivers |
|---|---|---|
| **C — Whole-model GGUF** | US-042 (this issue) | Single-hop llama.cpp, billing, relay streaming |
| **0 — Benchmark gate** | ADR-0024 DGR-001 | Safetensors vs GGUF measured contract |
| **1 — Distributed GGUF** | ADR-0024 `.scratch/distributed-gguf-runtime/` | gRPC C++ worker, layer-range GGUF |
Phase C uses the existing tracker hop path (whole model, one node). ADR-0024 direction A (layer-range GGUF + activations) merges into the native worker track after the benchmark gate — not in parallel with phase C on the same backend without an integration plan.
Recommended sequencing: C first (small, real value), then A/B investigation.
## Also in scope

View File

@@ -0,0 +1,188 @@
"""Versioned performance contract metadata for DGR-001.
This module intentionally captures the *contract* first: the model family,
architecture alignment, benchmark lanes, and stop condition that later benchmark
runs must satisfy. It does not download or execute a model.
"""
from __future__ import annotations
import argparse
import json
from dataclasses import dataclass
from pathlib import Path
SCHEMA_VERSION = 1
CONTRACT_ID = "DGR-001"
DEFAULT_OUTPUT_PATH = Path(".scratch/distributed-gguf-runtime/evidence/DGR-001/performance-contract.json")
@dataclass(frozen=True)
class ModelTarget:
"""Architecture-aligned model target for the DGR-001 benchmark contract."""
name: str
architecture: str
safetensors_repo: str
safetensors_precision: str
gguf_repo: str
gguf_quant: str
gguf_size_gb: float
comparison_policy: str
rationale: str
def to_dict(self) -> dict:
return {
"name": self.name,
"architecture": self.architecture,
"safetensors_repo": self.safetensors_repo,
"safetensors_precision": self.safetensors_precision,
"gguf_repo": self.gguf_repo,
"gguf_quant": self.gguf_quant,
"gguf_size_gb": self.gguf_size_gb,
"comparison_policy": self.comparison_policy,
"rationale": self.rationale,
}
@dataclass(frozen=True)
class BenchmarkLane:
"""One side of the comparison the contract requires."""
id: str
runtime: str
device: str
recipe: str
concurrency_levels: tuple[int, ...]
def to_dict(self) -> dict:
return {
"id": self.id,
"runtime": self.runtime,
"device": self.device,
"recipe": self.recipe,
"concurrency_levels": list(self.concurrency_levels),
}
@dataclass(frozen=True)
class PerformanceContract:
"""Machine-readable contract for the DGR-001 benchmark story."""
schema_version: int
story_id: str
model_target: ModelTarget
benchmark_lanes: tuple[BenchmarkLane, ...]
metrics: tuple[str, ...]
stop_condition: str
notes: tuple[str, ...] = ()
def to_dict(self) -> dict:
return {
"schema_version": self.schema_version,
"story_id": self.story_id,
"model_target": self.model_target.to_dict(),
"benchmark_lanes": [lane.to_dict() for lane in self.benchmark_lanes],
"metrics": list(self.metrics),
"stop_condition": self.stop_condition,
"notes": list(self.notes),
}
def write_json(self, path: str | Path) -> Path:
path = Path(path)
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(self.to_dict(), indent=2, sort_keys=True) + "\n", encoding="utf-8")
return path
DEFAULT_CONTRACT = PerformanceContract(
schema_version=SCHEMA_VERSION,
story_id=CONTRACT_ID,
model_target=ModelTarget(
name="DeepSeek-V2-Lite-Chat",
architecture="deepseek2",
safetensors_repo="deepseek-ai/DeepSeek-V2-Lite-Chat",
safetensors_precision="bfloat16",
gguf_repo="second-state/DeepSeek-V2-Lite-Chat-GGUF",
gguf_quant="Q2_K",
gguf_size_gb=6.43,
comparison_policy=(
"same model/revision, closest practical low-footprint precision pair: "
"BF16 safetensors versus Q2_K GGUF"
),
rationale=(
"Smallest DeepSeek-family benchmark anchor that still points toward "
"DeepSeek-V4-Flash; keeps the runtime on the DeepSeek2 path instead "
"of falling back to a tiny but architecture-mismatched smoke model."
),
),
benchmark_lanes=(
BenchmarkLane(
id="transformers-safetensors-cpu",
runtime="transformers",
device="cpu",
recipe="current safetensors recipe",
concurrency_levels=(1, 4),
),
BenchmarkLane(
id="llama-cpp-gguf-cpu",
runtime="llama.cpp",
device="cpu",
recipe="whole-model GGUF recipe",
concurrency_levels=(1, 4),
),
BenchmarkLane(
id="transformers-safetensors-gpu",
runtime="transformers",
device="gpu",
recipe="current safetensors recipe",
concurrency_levels=(1, 4),
),
BenchmarkLane(
id="llama-cpp-gguf-gpu",
runtime="llama.cpp",
device="gpu",
recipe="whole-model GGUF recipe",
concurrency_levels=(1, 4),
),
),
metrics=(
"ttft_ms",
"prefill_tok_per_sec",
"decode_tok_per_sec",
"p50_latency_ms",
"p95_latency_ms",
"aggregate_throughput_tok_per_sec",
"rss_bytes",
"vram_bytes",
"artifact_bytes",
"failure_count",
"output_drift",
),
stop_condition=(
"Stop if GGUF does not provide a meaningful speed or fit benefit over the "
"safetensors baseline for the chosen DeepSeek-family model target."
),
notes=(
"Real model execution stays opt-in and must keep model artifacts on the mounted drive.",
"Use the tiny fallback only for loader plumbing smoke tests; it does not replace the architecture-aligned baseline.",
),
)
def build_default_contract() -> PerformanceContract:
return DEFAULT_CONTRACT
def main(argv: list[str] | None = None) -> int:
parser = argparse.ArgumentParser(description="Write the DGR-001 performance contract JSON")
parser.add_argument("--json-out", type=Path, default=DEFAULT_OUTPUT_PATH, help="output JSON path")
args = parser.parse_args(argv)
contract = build_default_contract()
path = contract.write_json(args.json_out)
print(path)
return 0
if __name__ == "__main__": # pragma: no cover - CLI entry point
raise SystemExit(main())

View File

@@ -1545,6 +1545,26 @@ class TorchNodeServer:
def apply_tracker_directives(self, directives: list[dict]) -> dict | None:
"""Apply tracker shard directives (LOAD_SHARD replace, ADD_SHARD load-more)."""
drop_directive = next(
(directive for directive in reversed(directives) if directive.get("action") == "DROP_SHARD"),
None,
)
if drop_directive is not None:
model_id = str(drop_directive.get("model") or "")
removed = self._backends.pop(model_id, None)
if removed is None:
return None
if self._backends:
self._backend = next(iter(self._backends.values()))
self._tracker_mode = self._backend.shard_start == 0
else:
self._backend = None
self._tracker_mode = False
if self._server is not None:
self._server.backends = dict(self._backends)
self._server.backend = self._backend
self._server.tracker_mode = self._tracker_mode
return {"action": "DROP_SHARD", "model": model_id}
add_directive = next(
(directive for directive in reversed(directives) if directive.get("action") == "ADD_SHARD"),
None,
@@ -1574,6 +1594,8 @@ class TorchNodeServer:
flush=True,
)
try:
if replacing:
self._backends.clear()
new_backend = _load_backend(model_id, shard_start, shard_end, quantization, self._cache_dir)
except TypeError:
new_backend = _load_backend(model_id, shard_start, shard_end, quantization)

View File

@@ -22,8 +22,9 @@
border-bottom:1px solid var(--border); flex-shrink:0; }
header h1 { font-size:16px; margin:0; color:var(--accent); }
header .meta { color:var(--dim); font-size:12px; }
main { display:grid; grid-template-columns:repeat(auto-fit,minmax(340px,1fr));
main { display:grid; grid-template-columns:1fr;
gap:14px; padding:14px 20px; }
main > section { width:100%; min-width:0; }
body.chat-tab-active main {
flex:1; min-height:0; display:flex; flex-direction:column;
padding:0; gap:0; overflow:hidden;
@@ -71,6 +72,12 @@
background:transparent; color:var(--dim); padding:5px 0 8px; }
.dashboard-tabs button.active { color:var(--accent); border-bottom-color:var(--accent); }
.wide { grid-column:1 / -1; }
/* Compact status cards fan out on desktop; tables remain readable at half width. */
@media (min-width:900px) {
main { grid-template-columns:repeat(4,minmax(0,1fr)); }
main > section { grid-column:span 1; }
.wide { grid-column:span 2; }
}
section[hidden] { display:none !important; }
section.chat-section {
padding:0; border:0; border-radius:0; background:var(--bg); min-height:0;
@@ -288,6 +295,7 @@
<section data-tab="billing" data-admin-only><h2>Node pending payouts</h2><div id="pending" class="empty">admin login required</div></section>
<section data-tab="billing" data-admin-only><h2>Settlement history</h2><div id="settlements" class="empty">admin login required</div></section>
<section data-tab="admin"><h2>Tracker hive</h2><div id="hive" class="empty">loading…</div></section>
<section data-tab="admin" class="wide"><h2>Model placement</h2><div id="admin-model-placement-status" class="dim">Choose a model to load or release.</div><div id="admin-model-placement" class="empty">admin login required</div></section>
<section data-tab="admin" id="admin-section"><h2>All accounts (admin)</h2><div id="admin" class="empty"></div></section>
<section data-tab="admin" data-admin-only><h2>Strikes / bans / forfeitures</h2><div id="fraud" class="empty">admin login required</div></section>
<section data-tab="admin"><h2>Client balances</h2><div id="clients" class="empty">admin login required</div></section>
@@ -1791,6 +1799,50 @@ async function requestSelectedModelLoad() {
$("chat-status").textContent = `load queued on ${short(assignment.node_id || "node")} for layers ${assignment.shard_start}-${assignment.shard_end}`;
}
async function requestAdminModelLoad(model) {
const result = await apiCall("/v1/models/load", "POST", { model, force: true });
if (!result.ok) return showAdminModelPlacementStatus(result.data.error || "model load request failed", true);
const assignment = result.data.assignment || {};
showAdminModelPlacementStatus(`Load queued on ${short(assignment.node_id || "node")} for ${model}.`);
await refreshActiveTab(true);
}
async function releaseAdminModel(model) {
const result = await apiCall("/v1/models/release", "POST", { model });
if (!result.ok) return showAdminModelPlacementStatus(result.data.error || "model release request failed", true);
showAdminModelPlacementStatus(`Release queued for ${result.data.released || 0} node(s) serving ${model}.`);
await refreshActiveTab(true);
}
function showAdminModelPlacementStatus(message, isError) {
const status = $("admin-model-placement-status");
status.textContent = message;
status.className = isError ? "bad" : "ok";
}
function renderAdminModelPlacement(models, map) {
const nodes = (map && map.nodes) || [];
const rows = ((models && models.data) || []).map(model => {
const aliases = new Set([model.id, model.hf_repo, ...(model.aliases || [])].filter(Boolean));
const serving = nodes.filter(node => aliases.has(node.model) || aliases.has(node.hf_repo)).length;
const downloaded = nodes.filter(node => aliases.has(node.model) || aliases.has(node.hf_repo) ||
(node.downloaded_models || []).some(item => aliases.has(item.model) || aliases.has(item.hf_repo))).length;
const actions = `<button class="small" data-admin-model-load="${esc(model.id)}">load</button> ` +
`<button class="small" data-admin-model-release="${esc(model.id)}"${serving ? "" : " disabled"}>release</button>`;
return [esc(model.name || model.id), String(serving), String(downloaded), actions];
});
$("admin-model-placement").innerHTML = rows.length
? table(["model", "serving nodes", "downloaded on nodes", "admin action"], rows)
: '<div class="empty">no model presets configured</div>';
}
$("admin-model-placement").addEventListener("click", event => {
const load = event.target.closest("[data-admin-model-load]");
const release = event.target.closest("[data-admin-model-release]");
if (load) void requestAdminModelLoad(load.dataset.adminModelLoad);
if (release) void releaseAdminModel(release.dataset.adminModelRelease);
});
function chatAuthToken() {
if (accountApiKeys.length) return accountApiKeys[0];
return null;
@@ -2427,14 +2479,17 @@ async function fetchAdminTab() {
fetchJson("/v1/console"),
fetchJson("/v1/billing/summary"),
fetchJson("/v1/registry/wallets"),
fetchJson("/v1/models"),
fetchJson("/v1/network/map"),
];
if (isAdmin) fetches.push(apiCall("/v1/admin/accounts"));
const results = await Promise.all(fetches);
const [raft, consoleData, summary, wallets, adminResp] = results;
const [raft, consoleData, summary, wallets, models, map, adminResp] = results;
renderIfChanged("hive", raft, renderHive);
renderIfChanged("console", consoleData, renderConsole);
renderIfChanged("billing-summary", summary, data => renderBilling(data));
renderIfChanged("fraud", { wallets, summary }, data => renderFraud(data.wallets, data.summary));
renderIfChanged("admin-model-placement", { models, map }, data => renderAdminModelPlacement(data.models, data.map));
if (adminResp && adminResp.ok) {
renderIfChanged("admin", adminResp.data.accounts || [], accounts => {
const rows = accounts.map(a => {

View File

@@ -1528,6 +1528,49 @@ def _request_model_load_locked(server: "_TrackerHTTPServer", model_key: str) ->
return None
def _force_model_load_locked(server: "_TrackerHTTPServer", model_key: str) -> dict | None:
"""Replace the fastest ready assignment after an explicit admin eviction."""
resolved_name, preset = _resolve_model_preset(server.model_presets, model_key)
if preset is None or not preset.get("hf_repo"):
return None
start, end = _preset_layer_bounds(preset)
candidates = [node for node in server.registry.values()
if node.status == "ready" and node.pending_new_assignment is None
and _has_usable_quantization(node)]
if not candidates:
return None
node = max(candidates, key=lambda item: item.benchmark_tokens_per_sec)
shard_end = min(end, start + min(_node_layer_capacity(node, preset), end - start + 1) - 1)
if shard_end < start:
return None
quantization = _node_quantization(node, preset)
directive = _load_directive(node, str(preset["hf_repo"]), start, shard_end, quantization)
replaced = node.hf_repo or node.model
node.model, node.hf_repo = resolved_name, str(preset["hf_repo"])
node.shard_start, node.shard_end, node.quantization = start, shard_end, quantization
node.managed_assignment, node.pending_new_assignment = True, directive
node.pending_directives.append(directive)
_tracker_log(server, "warn", "model load forced", node_id=node.node_id,
model=resolved_name, replaced_model=replaced, shard=f"{start}-{shard_end}")
return {"node_id": node.node_id, "model": resolved_name, "hf_repo": preset["hf_repo"],
"shard_start": start, "shard_end": shard_end, "replaced_model": replaced}
def _release_model_locked(server: "_TrackerHTTPServer", model_key: str) -> int:
"""Queue DROP_SHARD for every served shard and remove it from routing immediately."""
resolved_name, preset = _resolve_model_preset(server.model_presets, model_key)
if preset is None:
return 0
released = 0
for node in server.registry.values():
if not _node_matches_preset(node, resolved_name, preset) or node.shard_start is None or node.shard_end is None:
continue
node.pending_directives.append(_drop_directive(node, str(preset.get("hf_repo") or resolved_name), node.shard_start, node.shard_end, node.quantization or "bfloat16"))
node.status = "loading"
released += 1
return released
def _preferred_node_quantization(
node: _NodeEntry,
preset: dict,
@@ -3043,6 +3086,9 @@ class _TrackerHandler(http.server.BaseHTTPRequestHandler):
if self.path == "/v1/models/load":
self._handle_model_load_request()
return
if self.path == "/v1/models/release":
self._handle_model_release_request()
return
if self.path == "/v1/models/vote":
self._handle_model_coverage_vote()
return
@@ -3170,8 +3216,6 @@ class _TrackerHandler(http.server.BaseHTTPRequestHandler):
seen_ids: set[str] = set()
for name, preset in server.model_presets.items():
model_nodes = [node for node in alive if _node_matches_preset(node, name, preset)]
if not model_nodes and not preset.get("recommended"):
continue
required_start, required_end = _preset_layer_bounds(preset)
coverage = _coverage_percentage(
model_nodes,
@@ -4834,11 +4878,32 @@ class _TrackerHandler(http.server.BaseHTTPRequestHandler):
with server.lock:
self._purge_expired_nodes()
assignment = _request_model_load_locked(server, model)
if assignment is None and body.get("force") is True:
assignment = _force_model_load_locked(server, model)
if assignment is None:
self._send_json(409, {"error": "no ready joined node has an available model slot and sufficient capacity"})
return
self._send_json(202, {"status": "queued", "assignment": assignment})
def _handle_model_release_request(self):
server: _TrackerHTTPServer = self.server # type: ignore[assignment]
if not self._require_role("admin", "validator"):
return
body = self._read_json_body()
if body is None:
return
model = body.get("model")
if not isinstance(model, str) or not model.strip():
self._send_json(400, {"error": "model is required"})
return
with server.lock:
self._purge_expired_nodes()
released = _release_model_locked(server, model)
if not released:
self._send_json(404, {"error": "no served shards found for model"})
return
self._send_json(202, {"status": "release_queued", "released": released})
def _handle_model_coverage_vote(self):
"""Record a rolling wish-list signal for an unavailable precision."""
server: _TrackerHTTPServer = self.server # type: ignore[assignment]

View File

@@ -39,7 +39,9 @@ def test_dashboard_served_with_all_panels():
assert "resolveModelGroup" in html
assert "buildModelAliasMap" in html
assert "modelAliasKey(raw)" in html
assert "main { display:grid; grid-template-columns:repeat(auto-fit,minmax(340px,1fr));" in html
assert "@media (min-width:900px)" in html
assert "grid-template-columns:repeat(4,minmax(0,1fr));" in html
assert ".wide { grid-column:span 2; }" in html
assert 'onclick="clearConsole()"' in html
assert "let consoleClearedAt = 0;" in html
finally:
@@ -100,6 +102,20 @@ def test_dashboard_allows_admin_to_request_selected_model_load():
assert '$("request-model-load").style.display = enabled ? "" : "none"' in html
def test_dashboard_exposes_admin_model_inventory_and_release_controls():
"Admin placement controls show the full model inventory and can release capacity."
html = _dashboard_html()
assert 'id="admin-model-placement"' in html
assert "renderAdminModelPlacement" in html
assert '"/v1/models/release"' in html
assert "requestAdminModelLoad" in html
assert "releaseAdminModel" in html
assert 'data-admin-model-load=' in html
assert 'data-admin-model-release=' in html
assert "admin-model-placement-status" in html
def test_network_map_includes_node_friendly_name():
"Network map includes node friendly name\n\nTags: dashboard, http"
tracker = TrackerServer()

View File

@@ -355,6 +355,39 @@ def test_admin_model_load_request_queues_directive_on_joined_node():
assert heartbeat["directives"][0]["model"] == "Qwen/Qwen2.5-0.5B-Instruct"
def test_admin_can_replace_a_served_model_and_release_it():
"Forced admin placement replaces a served shard; release queues DROP_SHARD."
tracker = TrackerServer(enable_billing=False, validator_service_token="test-admin")
port = tracker.start()
try:
node = _post_json(
f"http://127.0.0.1:{port}/v1/nodes/register",
{"endpoint": "http://127.0.0.1:9912", "model": "stub-model",
"shard_start": 0, "shard_end": 3, "managed_assignment": True,
"max_loaded_shards": 1, "memory_mb": 1,
"hardware_profile": {"host_id": "full-host"}},
)
headers = {"Content-Type": "application/json", "Authorization": "Bearer test-admin"}
load = urllib.request.Request(
f"http://127.0.0.1:{port}/v1/models/load",
data=json.dumps({"model": "qwen2.5-0.5b-instruct", "force": True}).encode(),
headers=headers, method="POST")
with urllib.request.urlopen(load) as response:
assert json.loads(response.read())["assignment"]["node_id"] == node["node_id"]
heartbeat = _post_json(f"http://127.0.0.1:{port}/v1/nodes/{node['node_id']}/heartbeat", {})
assert heartbeat["directives"][0]["action"] == "LOAD_SHARD"
release = urllib.request.Request(
f"http://127.0.0.1:{port}/v1/models/release",
data=json.dumps({"model": "qwen2.5-0.5b-instruct"}).encode(), headers=headers, method="POST")
with urllib.request.urlopen(release) as response:
assert json.loads(response.read())["released"] == 1
heartbeat = _post_json(f"http://127.0.0.1:{port}/v1/nodes/{node['node_id']}/heartbeat", {})
finally:
tracker.stop()
assert heartbeat["directives"][0]["action"] == "DROP_SHARD"
def test_endpoint_key_distinguishes_same_port_different_hosts():
"Endpoint key distinguishes same port different hosts\n\nTags: http, performance, routing, tracker"
from meshnet_node.torch_server import _clamp_downstream_hops, _endpoint_key

View File

@@ -0,0 +1,84 @@
"""Tests for the DGR-001 performance contract metadata."""
from __future__ import annotations
import json
from meshnet_node.performance_contract import DEFAULT_CONTRACT, SCHEMA_VERSION, main
def test_default_contract_is_architecture_aligned_and_small():
"""The baseline stays on DeepSeek2 and uses the smallest DeepSeek-family GGUF.
Tags: performance, model, gguf
"""
payload = DEFAULT_CONTRACT.to_dict()
assert payload["schema_version"] == SCHEMA_VERSION
assert payload["story_id"] == "DGR-001"
assert payload["model_target"] == {
"name": "DeepSeek-V2-Lite-Chat",
"architecture": "deepseek2",
"safetensors_repo": "deepseek-ai/DeepSeek-V2-Lite-Chat",
"safetensors_precision": "bfloat16",
"gguf_repo": "second-state/DeepSeek-V2-Lite-Chat-GGUF",
"gguf_quant": "Q2_K",
"gguf_size_gb": 6.43,
"comparison_policy": (
"same model/revision, closest practical low-footprint precision pair: "
"BF16 safetensors versus Q2_K GGUF"
),
"rationale": (
"Smallest DeepSeek-family benchmark anchor that still points toward "
"DeepSeek-V4-Flash; keeps the runtime on the DeepSeek2 path instead "
"of falling back to a tiny but architecture-mismatched smoke model."
),
}
assert payload["benchmark_lanes"] == [
{
"id": "transformers-safetensors-cpu",
"runtime": "transformers",
"device": "cpu",
"recipe": "current safetensors recipe",
"concurrency_levels": [1, 4],
},
{
"id": "llama-cpp-gguf-cpu",
"runtime": "llama.cpp",
"device": "cpu",
"recipe": "whole-model GGUF recipe",
"concurrency_levels": [1, 4],
},
{
"id": "transformers-safetensors-gpu",
"runtime": "transformers",
"device": "gpu",
"recipe": "current safetensors recipe",
"concurrency_levels": [1, 4],
},
{
"id": "llama-cpp-gguf-gpu",
"runtime": "llama.cpp",
"device": "gpu",
"recipe": "whole-model GGUF recipe",
"concurrency_levels": [1, 4],
},
]
assert "ttft_ms" in payload["metrics"]
assert "output_drift" in payload["metrics"]
assert "meaningful speed or fit benefit" in payload["stop_condition"]
assert any("mounted drive" in note for note in payload["notes"])
def test_contract_cli_writes_json(tmp_path, capsys):
"""The contract can be emitted as a machine-readable artifact.
Tags: performance, artifact
"""
output = tmp_path / "performance-contract.json"
assert main(["--json-out", str(output)]) == 0
written = json.loads(output.read_text(encoding="utf-8"))
assert written == DEFAULT_CONTRACT.to_dict()
assert str(output) in capsys.readouterr().out