mirror of
https://github.com/ruvnet/RuView
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f6a85fe7db79d7317af6b7c4e48aa2f75a61838e
86 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 ruv
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f6a85fe7db |
feat(adr-110): NodeSyncSnapshot.staleness_ms — sync age in milliseconds
Iter 34 — adds an optional `staleness_ms` field to the iter-23
NodeSyncSnapshot that exposes (Instant::now() - latest_sync_at).
Dashboards / Prometheus exporters / UI badges can now decay sync
freshness without re-deriving it from latest_sync_at on the host.
Wire compatibility: new field is `#[serde(skip_serializing_if =
"Option::is_none")]` so pre-iter-34 clients that strict-parse via
serde + deny_unknown_fields are unaffected (default serde_json
strategy is to ignore unknown fields anyway).
Sensing-server changes:
+ NodeSyncSnapshot.staleness_ms: Option<u64>
+ sync_snapshot() populates it via latest_sync_at.elapsed().as_millis()
+ iter-24 serialization tests now check 8 contract fields, not 7
+ new test `snapshot_staleness_ms_tracks_apply_time` pins
latest_sync_at to a past Instant and asserts the snapshot reports
~750 ms staleness with ±500 ms tolerance for scheduler delay
User-guide updates:
+ REST/WebSocket field table grows a `staleness_ms` row with the
UI-rendering thresholds (fade at 5 s, drop at 9 s to match the
firmware's VALID_WINDOW_MS-derived gate).
Tests passing:
sync_snapshot_helper_tests: 7/7
node_sync_snapshot_serialization_tests: 3/3 (8-field assertion green)
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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bea7edee1f |
test(adr-110): lock the 9-second staleness gate on mesh_aligned_us_for_csi_frame
Iter 33 — closes a real test-coverage gap. The iter 17 staleness gate (returns None when latest_sync_at is older than 9 s = 3 × the firmware's VALID_WINDOW_MS) was shipped but never directly tested. A future careless edit changing `from_secs(9)` to e.g. `from_secs(90)` would silently break ADR-029/030 multistatic fusion freshness guarantees. Test (3 assertions, no sleep — uses `Instant::checked_sub` to set latest_sync_at to past values directly): * 1 s old → Some (fresh) * 8 s old → Some (just inside the gate) * 10 s old → None (just outside the gate) If anyone widens or narrows the gate, exactly one of these assertions fires and points at the off-by-one. Total time for the test < 1 ms. sync_snapshot_helper_tests: 6/6 green. Branch-coord clean — main.rs only. Co-Authored-By: claude-flow <ruv@ruv.net> |
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ruv
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8805c8ec0b |
test+refactor(adr-110): NodeState::apply_sync_packet + 2 tests for the receive-side dispatch
Iter 32 — completes the helper-extraction discipline started in iter 30.
The iter 15 inline `ns.latest_sync = Some(sync); ns.latest_sync_at = ...`
was the LAST untested receive-side mutation; now it's a named method
with 2 tests covering its full state-transition surface.
Refactor:
Add `NodeState::apply_sync_packet(pkt, now)` taking an Instant so
the test can pass deterministic timing.
udp_receiver_task now calls the method instead of touching the
fields inline — one less place to break the staleness gate.
Tests (2 new — sync_snapshot_helper_tests module now at 5 tests):
apply_sync_packet_populates_a_fresh_node
Mirrors udp_receiver_task's first-packet-from-unknown-node path:
asserts latest_sync goes from None → Some, latest_sync_at matches
the passed Instant exactly (no clock skew from real Instant::now()),
and sync_snapshot() now returns Some (REST 200 OK path lit up).
apply_sync_packet_overwrites_older_data
Subsequent packets must replace, not accumulate. Asserts sequence,
local_us advance, and the staleness clock resets. This is what
keeps the §A0.10-smoothed offset tracking the latest beacon rather
than drifting with stale state.
cargo test sync_snapshot_helper → 5/5 green.
Branch-coord clean — no Cargo.toml / cli.rs touched.
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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a07deb9180 |
test+refactor(adr-110): NodeState::sync_snapshot + 3 helper tests, dedupe 4 call sites
Iter 30 — defends the iter 29 REST endpoints + iter 23 WebSocket
broadcast with tests, AND deduplicates the four call sites that all
built the same NodeSyncSnapshot inline.
Refactor:
Add `NodeState::sync_snapshot() -> Option<NodeSyncSnapshot>` as the
single source of truth. All four call sites simplified:
1. node_sync_endpoint (REST /api/v1/nodes/:id/sync) — 12 → 5 lines
2. mesh_endpoint (REST /api/v1/mesh) — 11 → 3 lines
3. WebSocket vitals-only NodeInfo (line 4284) — 9 → 1 line
4. WebSocket CSI-frame NodeInfo (line 4617) — 9 → 1 line
Net: -35 lines, single point of contact for any future schema change.
Tests (3 new, all green; brings binary suite to 95+):
fresh_node_with_no_sync_returns_none
Mirrors REST 404 "no_sync" + WebSocket sync omission paths.
node_with_latest_sync_produces_correct_snapshot
Mirrors REST 200 OK + WebSocket sync field paths.
Asserts §A0.10's measured 1_163_565 µs offset survives the helper.
snapshot_reflects_leader_state
Leader-case shape: is_leader=true, offset≈0 (–7 µs call-stack).
These tests cover BOTH REST routes and BOTH WebSocket NodeInfo sites
through the shared helper — one test per behavioral path, no axum
state plumbing required. cargo check -p ...sensing-server → green.
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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c6a0d5dbf5 |
feat(adr-110): REST endpoints /api/v1/nodes/:id/sync and /api/v1/mesh
Iter 29 — extends the iter 23 WebSocket NodeSyncSnapshot publication
with an HTTP surface so non-streaming clients (curl scripts, Home
Assistant REST sensors, Prometheus exporters, automation rule probes)
can poll mesh state without holding a WebSocket connection.
GET /api/v1/nodes/:id/sync
200 → Json(NodeSyncSnapshot) when latest_sync is present
404 → {"error": "unknown_node" | "no_sync", "node_id": N}
— "no_sync" includes a `hint` pointing operators at the
"no mesh peer or not v0.6.9+" diagnostic.
GET /api/v1/mesh
200 → { "nodes": { "<id>": NodeSyncSnapshot, ... }, "total": N }
Nodes without a recent sync are omitted; an empty `nodes` object
means no mesh peers reachable.
Both handlers reuse the iter 23 NodeSyncSnapshot struct (same JSON
shape as the WebSocket broadcast — clients get one schema, two
delivery modes). The Path<u8> extractor returns 404 on overflow
automatically (axum), so /api/v1/nodes/256/sync gives a clean error.
cargo check -p wifi-densepose-sensing-server --no-default-features → green.
Curl quick-start (added to operator playbook material in a follow-up):
curl http://localhost:3000/api/v1/mesh # full fleet
curl http://localhost:3000/api/v1/nodes/9/sync # one node
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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e764504dc5 |
test(adr-110): lock NodeSyncSnapshot JSON wire contract (iter 24)
Iter 24 — ultra-opt for public-API stability. Iter 23 added a new JSON
field that UI clients (viz.html, future Tauri desktop, automation) now
depend on; this iter locks its exact shape so any future rename /
removal fails a named test instead of silently breaking consumers.
New module `node_sync_snapshot_serialization_tests` (3 tests, all green):
* sync_present_serializes_all_seven_fields
Builds NodeInfo with Some(sample_sync), serializes to serde_json::Value,
asserts all 7 documented field names exist (offset_us, is_leader,
is_valid, smoothed, sequence, csi_fps_ema, csi_fps_samples) and
spot-checks numeric values.
* sync_absent_omits_the_key_entirely
Builds NodeInfo with sync = None, asserts the `sync` JSON key is
DROPPED entirely (not emitted as `"sync": null`). This is the
backwards-compat contract that lets pre-iter-23 UI clients ignore
mesh-aware nodes silently.
* sync_round_trips_through_serde
to_string / from_str round-trip on a populated NodeInfo recovers
every field of the sync sub-object byte-for-byte (modulo float tol).
Test infrastructure: pure pure serde_json — no network, no fixtures,
no I/O. Adds 92 lines, 0 runtime allocs in the steady path.
Branch-coord clean (no Cargo.toml or cli.rs touched).
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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41f28ae85e |
feat(adr-110): surface NodeSyncSnapshot in WebSocket sensing_update JSON
Iter 23 — converts the iter 1-21 firmware-side mesh substrate from
"works internally" to "visible to UI clients". WebSocket sensing_update
broadcasts now carry a per-node optional `sync` object exposing the
mesh state the iter 15-22 wire and storage capture:
{
"type": "sensing_update",
...
"nodes": [
{
"node_id": 9,
...
"sync": {
"offset_us": 1163565, // §A0.10's measured 1.16 s
"is_leader": false,
"is_valid": true,
"smoothed": true, // EMA seeded
"sequence": 20, // §A0.12 pairing key
"csi_fps_ema": 10.0, // iter 18 measured rate
"csi_fps_samples": 47 // ≥5 means trust csi_fps_ema
}
}
],
...
}
`sync` is `Option<NodeSyncSnapshot>` with `#[serde(skip_serializing_if =
"Option::is_none")]` so non-mesh paths (multi-BSSID scan / synthetic RSSI
/ simulation) emit no `sync` key — preserves backwards compatibility
with existing UI clients.
Plumbed into all four NodeInfo construction sites:
1. multi-BSSID scan path → sync: None
2. synthetic-RSSI fallback → sync: None
3. simulated frame path → sync: None
4. real ESP32 CSI path (line 4528) → sync: snapshot from NodeState
5. ADR-039 vitals-only path (line 4207) → sync: snapshot from NodeState
cargo check -p wifi-densepose-sensing-server --no-default-features → green.
UI clients (viz.html, future Tauri desktop, downstream automation) can
now render leader/follower badges, jitter histograms, and the §A0.10
clock-skew trajectory without any further firmware or aggregator work.
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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82be960de5 |
test(adr-110): cross-language wire-format conformance gate
Iter 21 — ultra-opt for protocol correctness across the two production decoders. Pin the same 32-byte canonical hex in both Python and Rust tests; if either decoder drifts from the wire, ONE of the tests starts failing — and it's clear which side moved. Canonical packet: COM9 sync-pkt #1 from §A0.12 live capture, expressed as exact little-endian bytes: 10a111c5 09 01 06 00 magic + node + ver + flags + rsvd f26db70100000000 local_us = 28_798_450 c5aca50100000000 epoch_us = 27_634_885 1400000000000000 sequence = 20 + reserved Python test: archive/v1/tests/unit/test_esp32_binary_parser.py::TestSyncPacketParser ::test_canonical_wire_bytes_match_rust_decoder — decodes the pinned hex, asserts every field including the §A0.10 1,163,565 µs offset. Rust test: v2/crates/wifi-densepose-hardware/src/sync_packet.rs::tests ::canonical_wire_bytes_match_python_decoder — decodes the same bytes, asserts the same fields, then re-encodes via to_bytes() and asserts the round-trip produces the EXACT same 32 bytes. So this also catches drift in the Rust encoder. Test counts after this iter: Rust sync_packet: 15/15 green (was 14) Python SyncPacketParser: 7/7 green (was 6) Branch contract: if a future PR changes the firmware wire format, BOTH tests must be updated atomically with the new canonical hex. CI will gate this naturally. Co-Authored-By: claude-flow <ruv@ruv.net> |
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ruv
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40bd6b81b8 |
test(adr-110): end-to-end sync decode → frame mesh recovery integration test
Iter 20 — defensive ultra-opt: one test that exercises the entire iter 14→17 chain in a single assertion, so any future refactor that breaks the contract surfaces as a single, named regression instead of 14 unit-test diffs to triangulate. 1. firmware emits sync packet (bytes built here as a stand-in) 2. host decodes via SyncPacket::from_bytes — assert round-trip 3. a CSI frame arrives 100 sequences later (≈ 5 s @ 20 fps) 4. mesh_aligned_us_for_sequence recovers the mesh timestamp 5. cross-check: same value via raw apply_to_local Asserts mesh_us == sync.epoch_us + 5_000_000 µs exactly, plus both paths (sequence-interpolation + direct local→mesh) agree byte-for-byte. Result: 14/14 sync_packet tests pass, full wifi-densepose-hardware crate at 136/136 (no regression from iter 1-19). Contract for any ADR-029/030 multistatic fusion consumer is now defended by a test that fails loud if either piece of the chain drifts. Co-Authored-By: claude-flow <ruv@ruv.net> |
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ruv
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898a2d7d9f |
feat(adr-110): wire observe_csi_frame_arrival into CSI receive path
Iter 19 — without this call, iter 18's EMA fps tracking was dead code because csi_fps_samples stayed 0 forever and mesh_aligned_us_for_csi_frame always fell back to the 20 Hz constant. In udp_receiver_task's parse_esp32_frame branch, replace the bare last_frame_time assignment with NodeState::observe_csi_frame_arrival, which computes dt vs last_frame_time, feeds update_csi_fps_ema (α=1/8), bumps csi_fps_samples, and sets last_frame_time as a side effect (same value the bare assignment did). Effect: after ~5 CSI frames arrive from any node, mesh_aligned_us_for_csi_frame returns interpolated timestamps using the node's actually-observed frame rate instead of the 20 Hz default. Real bench rate was ~10 fps, so this halves the per-frame timestamp error in §A0.12-style multistatic alignment. cargo check -p wifi-densepose-sensing-server --no-default-features → green. Co-Authored-By: claude-flow <ruv@ruv.net> |
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ruv
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0dfa3d46aa |
feat(adr-115): P1 — Cargo features + CLI flags for MQTT/Matter/Semantic
Adds `mqtt` and `matter` Cargo features (default off) plus 20+ new CLI
flags wired through cli.rs per ADR-115 §3.8 / §3.10 / §3.11 / §3.12:
- MQTT (HA-DISCO): --mqtt, --mqtt-host/--mqtt-port/--mqtt-username/
--mqtt-password-env/--mqtt-client-id/--mqtt-prefix, TLS controls
(--mqtt-tls/--mqtt-ca-file/--mqtt-client-cert/--mqtt-client-key),
rate controls (--mqtt-refresh-secs, --mqtt-rate-{vitals,motion,count,
rssi,pose}, --mqtt-publish-pose).
- Privacy (ADR-106): --privacy-mode strips HR/BR/pose pre-publish.
- Matter (HA-FABRIC): --matter, --matter-setup-file, --matter-reset,
--matter-vendor-id (dev VID 0xFFF1 per §9.9), --matter-product-id.
- Semantic (HA-MIND): --semantic (default ON), thresholds/zones files,
--semantic-baseline-window-days, --no-semantic <PRIMITIVE> repeatable.
rumqttc 0.24 added as optional dep with rustls (Windows-friendly parity
with ureq in this crate). matter-rs deferred to P7 spike per §9.10.
6 unit tests cover defaults, compound flag composition, and repeatable
--no-semantic. Tests pass:
cargo test -p wifi-densepose-sensing-server --no-default-features cli::tests
6 passed; 0 failed.
Branch coordination: this work is on feat/adr-115-ha-mqtt-matter off
main, parallel to ADR-110 work on adr-110-esp32c6 (no file overlap).
Refs #776 (ADR-115 implementation tracking issue).
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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ca2059b07f |
fix(branch-coord): revert ADR-115 Cargo.toml/cli.rs that slipped into iter 18
Iter 18's commit
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ruv
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2997165bc1 |
feat(adr-110): per-node measured CSI fps + EMA for mesh-time interpolation
Iter 18 (after recovery from a cross-branch slip — see commit-history
context below). Replaces the hardcoded 20 Hz CSI_FPS_HZ constant in
mesh_aligned_us_for_csi_frame with a per-node EMA of observed
inter-frame intervals, falling back to 20 Hz until ≥5 samples land.
Real bench data (§A0.12 captures) showed the actual CSI rate at ~10 fps
because the firmware's CSI_MIN_SEND_INTERVAL_US gate combined with
ruv.net's traffic level paces it to that. Using 20 Hz against actual
10 fps inflates Δus 2× and shifts the recovered mesh timestamp by up
to the inter-sync interval / 2 = ~1 s. Measured fps fixes that.
State on NodeState:
csi_fps_ema: f64 — EMA (seeded at 20.0)
csi_fps_samples: u32 — counts inter-frame deltas observed
API:
NodeState::observe_csi_frame_arrival(now) — call once per CSI frame
from udp_receiver_task
update_csi_fps_ema(prev_fps, dt_sec) -> Option<f64> — free fn,
testable
mesh_aligned_us_for_csi_frame now uses the measured fps when samples ≥ 5,
falls back to 20 Hz otherwise.
4 unit tests (fps_ema_tests module, all passing on the binary):
* steady_10hz_converges_toward_10 — 40 samples at 100 ms converge to ±0.1 Hz
* steady_20hz_stays_near_20 — 20 samples at 50 ms stay within 0.05 Hz
* nonpositive_dt_rejected — dt ≤ 0 returns None
* long_gap_rejected_as_implausible — dt > 1 s rejected (likely a dropout)
Branch-coordination note: this iter's working tree was briefly applied
to feat/adr-115-ha-mqtt-matter by a `git checkout` between iter 17 and
iter 18. Stashed the ADR-115 agent's MQTT/Matter Cargo.toml work
(`stash@adr115-pending-work`) before switching back here. No code lost.
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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0c311a202b |
feat(adr-110): SyncPacket::mesh_aligned_us_for_sequence (interpolation) + NodeState hook
Iter 17 — closes the per-frame mesh-time loop for ADR-018 CSI frames
that carry no per-frame local_us field (the v1 wire format reserves no
slot — see WITNESS-LOG-110 §A0.11).
Math: pair the frame's sequence number against the sync packet's
sequence high-water + an assumed CSI frame rate. Δframes × 1/fps
estimates the node-local delta from the sync, then apply_to_local
recovers the mesh epoch.
SyncPacket::mesh_aligned_us_for_sequence(frame_seq: u32, fps_hz: f64) -> u64
3 new unit tests (13 total in sync_packet::tests, all green):
* mesh_aligned_for_sequence_identity_at_sync_point — at sync.sequence
returns sync.epoch_us exactly
* mesh_aligned_for_sequence_extrapolates_forward — 20 frames @ 20 fps
extrapolates by exactly 1 s
* mesh_aligned_for_sequence_handles_seq_wraparound — u32 sequence
wrap doesn't jump backward by 2^32 (wrapping_sub guards it)
NodeState hook:
NodeState::mesh_aligned_us_for_csi_frame(frame_sequence: u32) -> Option<u64>
Wraps the SyncPacket method, defaults fps_hz=20.0 (matches the
firmware's CSI_MIN_SEND_INTERVAL_US-implied ceiling), enforces the
same 9 s staleness gate as mesh_aligned_us.
cargo check -p wifi-densepose-sensing-server --no-default-features → green.
cargo test -p wifi-densepose-hardware sync_packet → 13/13, 122 filtered.
Downstream ADR-029/030 multistatic fusion code can now do:
if frame.adr018_flags.ieee802154_sync_valid {
if let Some(mesh_us) = ns.mesh_aligned_us_for_csi_frame(frame.sequence) {
// pair this frame with frames from sibling nodes by mesh_us
}
}
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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df95360e52 |
feat(adr-110 P10): apply_to_local + NodeState::mesh_aligned_us + full ADR rewrite
Iter 16 closes the math loop and updates ADR-110 to reflect the full
P1-P10 sprint outcome (per user request).
Code (the math layer that converts the iter 15 stored sync into a
per-frame mesh-aligned timestamp):
wifi-densepose-hardware:
SyncPacket::apply_to_local(local_at_frame_us: u64) -> u64
Pure integer math: offset = epoch - local; mesh = local_at_frame + offset.
3 new unit tests (10 total, all green):
- apply_to_local_recovers_packet_epoch (identity at the packet's local_us)
- apply_to_local_preserves_inter_frame_delta (Δlocal == Δmesh)
- apply_to_local_on_leader_is_near_identity (leader offset ≈ 0)
wifi-densepose-sensing-server:
NodeState::mesh_aligned_us(local_at_frame_us: u64) -> Option<u64>
Returns the recovered mesh timestamp using the most-recent sync
packet, or None if no sync seen or last one older than 9 s
(3× firmware VALID_WINDOW_MS = 9 s staleness gate).
cargo check -p wifi-densepose-sensing-server --no-default-features
→ green
ADR-110 substantial rewrite (per user "update adr 110 with details"):
- Status line: P1-P10 complete, firmware-side substrate closed at v0.7.0.
- Front matter now lists all 4 firmware releases + witness link.
- Phase table grows a P10 row capturing the v0.6.8 / v0.6.9 / v0.7.0
arc (EMA smoother + sync packet + bit-4 wire-fix + host crates).
- New §4.1 — /loop 5m SOTA sprint summary table (iters 1-16, 4 releases,
17 commits, 13 unit tests, what shipped each iter).
- New §4.2 — measured numbers table with 99.56% RX, 104.1 µs smoothed
stdev, 3.95x suppression, 1.4 ppm crystal skew, etc — every cell
backed by a witness §A0.x entry and a preserved bench log.
- New §4.3 — host-side production surface listing (sync_packet.rs +
sensing-server NodeState + Python parser, with file paths).
- §5 open question on 802.15.4 channel resolved (Kconfig, default ch26
not ch15, with the witness §D1 rationale).
- New §6 — explicit scope of what's outside this ADR (multistatic fusion
math in ADR-029/030, hardware-gated measurements needing INA / 11ax AP,
IDF upstream fixes pending).
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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23fd8ac371 |
feat(sensing-server): consume ADR-110 §A0.12 sync packets, store per-node
Iter 15 — converts the iter 14 SyncPacket decoder from "shipped" to
"consumed" by wiring it into the sensing-server UDP receive loop.
Wiring:
- Cargo.toml gains wifi-densepose-hardware = path = "../wifi-densepose-hardware"
to pull in the SyncPacket decoder + SYNC_PACKET_MAGIC dispatch constant.
- NodeState gains two new fields:
latest_sync: Option<SyncPacket> — the parsed packet
latest_sync_at: Option<std::time::Instant> — staleness clock
- udp_receiver_task now magic-dispatches every incoming datagram against
SYNC_PACKET_MAGIC (0xC511A110) before falling through to the existing
ADR-039 vitals / ADR-040 WASM / ADR-018 CSI parsers. Same Option-returning
pattern as the other parsers, so future packet types slot in cleanly.
When a sync packet arrives:
* write-lock state, lookup-or-create NodeState by node_id
* stash the SyncPacket + Instant::now() on the node
* debug-log node, leader/valid/smoothed flags, sequence, offset_us
* continue (don't fall through — we know it's not a CSI frame)
Downstream multistatic CSI fusion now has a documented landing pad: any
CSI frame with byte 19 bit 4 set looks up the matching NodeState, applies
ns.latest_sync.epoch_us + (now_local - ns.latest_sync.local_us) to get a
mesh-aligned timestamp. Implementation of that fusion math is the next
ADR-029/030 layer (wifi-densepose-signal).
Verification:
- cargo check -p wifi-densepose-sensing-server --no-default-features → green
- cargo test -p wifi-densepose-hardware sync_packet → 7/7 pass, 122 filtered
- Zero behavioral change for nodes that don't emit sync packets — the
dispatch only fires on magic match.
Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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d72944f887 |
feat(hardware): Rust SyncPacket decoder + 7 unit tests (ADR-110 §A0.12)
Iter 14 — moves the v0.7.0 Python stub into the Rust production tree so the sensing-server can decode incoming UDP datagrams by leading magic and apply mesh-aligned timestamps to in-flight CSI frames. Module: v2/crates/wifi-densepose-hardware/src/sync_packet.rs Public surface (re-exported from the crate root): - SyncPacket — 32-byte decoded packet - SyncPacketFlags — bit0=leader, bit1=valid, bit2=smoothed - SYNC_PACKET_MAGIC = 0xC511A110, SYNC_PACKET_SIZE = 32 Tests (all 7 passing, plus 122 existing hardware-crate tests still pass): * follower_typical_packet_roundtrips — reproduces COM9 sync-pkt #1 from §A0.12, including the 1,163,565 µs offset §A0.10 measured * leader_packet_has_local_close_to_epoch — COM12 leader case (flags=0x03, epoch ≈ local, offset = -7 µs call-stack only) * magic_mismatch_is_typed_error * short_packet_is_typed_error * all_flag_combinations_roundtrip — every (leader,valid,smoothed) triple * sync_and_csi_magics_differ — host can dispatch by leading u32 * wire_size_constant_is_correct Uses the existing ParseError variants (InvalidMagic, InsufficientData) so the sensing-server's dispatch code can treat sync-packet decode failures the same way it treats CSI frame decode failures. Co-Authored-By: claude-flow <ruv@ruv.net> |
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ruv
|
3959fabf31 |
feat(rust): host-side decode for ADR-018 byte 18-19 (ADR-110 closure)
Parse the C6 firmware's HE PPDU type + bandwidth/flags from ADR-018 bytes 18-19 (previously discarded as _reserved). Adds two types to CsiMetadata: ppdu_type (HtLegacy/HeSu/HeMu/HeTb/Unknown) and adr018_flags (bw40/stbc/ldpc/ieee802154_sync_valid). Pre-ADR-110 firmware sends zeros which round-trip as HtLegacy + default flags — fully backwards compatible. 6 new deterministic unit tests: - Pre-ADR-110 backwards compat - HE-SU / HE-MU / HE-TB decode - Unknown PPDU byte -> Unknown - All-bits-set flags round-trip - PpduType byte round-trip Result: 122 wifi-densepose-hardware tests pass, 0 fail. Host decoder now matches the firmware encoder bit-for-bit — HE-LTF metadata path works end-to-end the moment an 11ax AP is in range. Ref: ruvnet/RuView#762 Co-Authored-By: claude-flow <ruv@ruv.net> |
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a85d4e31e4 |
research(sota): kick off SOTA research loop + first R5 saliency measurement (#702)
Sets up docs/research/sota-2026-05-22/ as the autonomous-research output dir, with PROGRESS.md as the canonical 15-vector research agenda spanning spatial intelligence, RF features, RSSI-only, and exotic/long-horizon verticals. Cron d6e5c473 (*/10 * * * *) picks threads from this file and self-terminates at 2026-05-22 08:00 ET. First concrete contribution this tick — R5 subcarrier saliency: * examples/research-sota/r5_subcarrier_saliency.py: pure-numpy port of the count cog's Conv1d encoder + count head, computes per- subcarrier input×gradient saliency via central-difference. 128 samples × 56 subcarriers × 2 forward passes/subcarrier ≈ ~3 s on CPU, no GPU or framework dependency. * docs/research/sota-2026-05-22/R5-subcarrier-saliency.md: research note with motivation, method, novelty argument, and the first measured ranking. Top-8 subcarriers for cog-person-count v0.0.2: [41, 52, 30, 31, 10, 35, 2, 38]. Max/mean ratio 2.85x. * v2/crates/cog-person-count/cog/artifacts/saliency.json: machine- readable per-subcarrier saliency + top-K lists, so future-tick experiments (retrain at K=8/16/32) consume it without re-running. Key insight from the first measurement: top-8 saliency is *band- spread* (indices span 2-52), not concentrated. This directly raises R8's (RSSI-only) feasibility ceiling, because RSSI is a band- aggregate — it retains the integral of a band-spread signal. First- order estimate: RSSI-only should hit ~60% of full-CSI accuracy for the count task. R7 (adversarial defence) inherits a concrete defender- priority list: corroborate these 8 subcarriers across nodes. This commit is the first of many short, focused contributions over the next ~12 hours. PROGRESS.md is the canonical pointer for the next tick to pick up the next thread. |
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b3a5012dbd |
feat(cog-person-count): v0.0.2 — K-fold + label-smoothing + temperature-calibrated (#699)
* chore: stage v0.0.2 artifacts + temperature scalar for build pipeline
Stages count_v1.{safetensors,onnx,temperature,train_results.json}
ahead of the build/sign/upload step. This commit is a momentary
side-effect — the next commit will refresh the per-arch manifests
with the new binary SHAs once ruvultra finishes the cross-build.
The .temperature file holds the calibration scalar from LBFGS over the
held-out conf logits. The Rust cog will read it post-load and divide
conf_logits by it before sigmoid, exactly matching the Python eval.
* feat(cog-person-count): v0.0.2 — K-fold validated, label smoothing + early stop + temp scale
The v0.0.1 "65.1% but class-1=0%" result was an unlucky temporal split
that let a degenerate "always predict 0" classifier hit eval acc =
class-0 fraction. 5-fold stratified random CV proved the architecture
actually learns ~57.1% class-1 accuracy under fair splits — a real,
modestly useful signal.
v0.0.2 ships a retrained model that:
* **Splits randomly (seed=42) 80/20** instead of temporally — eliminates
the trailing-window-class-imbalance cheat.
* **Class-balanced sampler** (multinomial with replacement, weighted by
inverse class frequency) — per-batch expected counts are equal
regardless of dataset distribution.
* **Label smoothing 0.1** on the cross-entropy — reduces confidence
saturation that drove v0.0.1's all-or-nothing predictions.
* **Early stopping** with patience=20 — stops at epoch 29 instead of
overfitting through 400.
* **Temperature scaling** of the conf head — LBFGS fits a scalar T on
held-out conf logits; ships as a count_v1.temperature sidecar so the
Rust cog can divide conf_logits by T before sigmoid.
Numbers on the same data:
| Metric | v0.0.1 | v0.0.2 | K-fold (5x100) |
|------------------|--------|--------|----------------|
| Overall acc | 65.1% | 62.3% | 62.2% ± 1.9% |
| Class 0 acc | 100% | 86.2% | 67.4% |
| Class 1 acc | 0% | 34.3% | 57.1% ✓ |
| MAE | 0.349 | 0.377 | 0.378 |
| Spearman | 0.023 | 0.013 | 0.160 |
Class-1 accuracy 0 → 34.3% is the headline win. Net acc moves slightly
because we stopped cheating on class 0. K-fold's 57% says there's
headroom remaining; reaching it needs more independent splits (== more
data), not more training tricks.
Confidence calibration didn't move. Temperature scaling alone can't fix
a confidence head trained against a noisy argmax==truth indicator over
a 62%-accurate classifier — the head's training signal is the issue,
not its post-hoc transform. The honest fix is multi-room data (#645),
not another calibration knob.
Live on cognitum-v0 at /var/lib/cognitum/apps/person-count/ — health
reports candle-cpu backend, count = 1 (was 0 in v0.0.1) on synthetic
zero input.
Files changed:
* scripts/train-count.py — adds --k-fold (no sklearn dep, hand-rolled
stratified splits with deterministic shuffle) and --v2 paths.
* v2/.../cog/artifacts/count_v1.safetensors (392 KB, new sha
32996433…) + count_v1.onnx (16 KB) + count_v1.temperature (0.9262
scalar) + count_train_results.json (full epoch trace).
* v2/.../cog/artifacts/manifests/{arm,x86_64}/manifest.json bumped to
version 0.0.2 with the new weights_sha256 + caveats.
* docs/benchmarks/person-count-cog.md — appends a v0.0.2 section
with the K-fold diagnostic table and honest-read paragraph.
GCS:
gs://cognitum-apps/cogs/arm/cog-person-count-count_v1.safetensors
refreshed (binaries unchanged — load weights via mmap at runtime).
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e6a5df36eb |
chore(cog-person-count): refresh GCS manifests after run-wiring rebuild (#698)
The arm + x86_64 manifests committed in #696 referenced the binaries built before #697 wired the `run` subcommand. Rebuilt + re-signed + re-uploaded to GCS, and re-deployed to cognitum-v0: arm sha 15c2fbac…7728ea5 (3,807,456 B, up from 2,168,816 — added Tokio runtime) x86_64 sha 051614ce…cc8388b3 (4,502,960 B, up from 2,615,528) Both re-signed Ed25519 with COGNITUM_OWNER_SIGNING_KEY. Manifests now match the binaries published at gs://cognitum-apps/cogs/{arm, x86_64}/cog-person-count-* and the binary installed at /var/lib/cognitum/apps/person-count/ on cognitum-v0. |
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5c914e63c7 |
feat(cog-person-count): wire run subcommand — v0.0.1 fully functional (#697)
Phase 4 of ADR-103. Adds the long-running polling loop so the cog's
fourth verb (`run`) does real work, completing the ADR-100 runtime
contract end-to-end:
cog-person-count version → "person-count 0.3.0"
cog-person-count manifest → JSON skeleton
cog-person-count health → loads weights + 1-shot infer + emit
cog-person-count run --config → long-running per-frame emit ← THIS
What ships:
* src/runtime.rs (new) — `run_loop` polls sensing_url every poll_ms,
slides a [56, 20] CSI window, runs InferenceEngine::infer, emits
publisher::person_count events. Same shape as
cog-pose-estimation::runtime — fetch_frame extracts amplitudes
from `snapshot.nodes[0].amplitude[]`, fails open on connect errors
with a WARN log rather than crashing.
* src/lib.rs — registers the runtime module.
* src/main.rs — cmd_run now loads RunConfig from a JSON file, builds
the InferenceEngine (with weights if cfg.model_path is set,
otherwise auto-discover), emits a run.started event, and hands off
to the Tokio multi-thread runtime's block_on(run_loop). Single-node
fusion is a no-op for N=1 today; v0.2.0 will append predictions
from sibling nodes and call fusion::fuse_confidence_weighted before
emit.
Verified locally:
cargo check -p cog-person-count --no-default-features → clean
cargo test -p cog-person-count → 15/15 pass (no regressions)
cargo build -p cog-person-count --release → 2.36 MB unchanged
./cog-person-count run --config bad-config.json:
line 1: {"event":"run.started","fields":{"cog":"person-count",
"sensing_url":"http://127.0.0.1:9999/...",poll_ms:100,
"model_path":"(auto-discover)"}}
line 2: WARN sensing-server fetch failed
error=Connection Failed: Connect error: actively refused
(loop alive — exits cleanly on SIGTERM, no crash, no NaN)
Also adds a "Relationship to the in-process score_to_person_count
heuristic" section to cog/README.md explaining the dual-emitter
design (sensing-server keeps emitting the PR #491 slot heuristic;
the cog runs out-of-process and emits person.count events from the
learned model). Operators choose by installing the cog or not — no
sensing-server rebuild required.
ADR-103 §"Migration" status:
1. Land ADR + scaffold ........... done (#693, #694)
2. Train count_v1 ................ done (#695)
3. Cross-compile + sign + GCS .... done (#696)
4. Server-side wiring ............ done — out-of-process design
means no rewire needed; this
cog is the wiring.
5. v0.2.0 multi-room + LoRA ...... data-bound (#645)
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a5e99670f8 |
feat(cog-person-count): release v0.0.1 — signed binaries on GCS, live on cognitum-v0 (#696)
Phase 3 of ADR-103. Cross-compiled aarch64 + x86_64 on ruvultra, signed
with COGNITUM_OWNER_SIGNING_KEY (Ed25519), uploaded to GCS, and live-
installed on the cognitum-v0 Pi 5 alongside cog-pose-estimation.
Real-hardware bench on cognitum-v0:
./cog-person-count-arm health
→ backend=candle-cpu, count=0, confidence=0.49, p95=[0,7]
30 sequential health invocations: 0.276 s → 9.2 ms/invocation cold
Compares to cog-pose-estimation's 8.4 ms — count cog is ~10% slower
because the dual-head (count softmax + confidence sigmoid) does ~2x
the work after the shared encoder.
GCS release artifacts (publicly downloadable, SHA-verified):
arm/cog-person-count-arm 2,168,816 B
sha: 36bc0bb0...0d47b507b3c3
sig: R/00xdzHriyr/2r...JK+a6k71NDg== (Ed25519)
x86_64/cog-person-count-x86_64 2,615,528 B
sha: 76cdd1ec...3923 7392b01db
sig: QB+8cnGSMQmu...ZtTNIQ2rDg== (Ed25519)
arm/cog-person-count-count_v1.safetensors 392,088 B
sha: dacb0551...e6e04ff56d15c3a65a9ff
Live install at /var/lib/cognitum/apps/person-count/ on cognitum-v0
matches the layout of every other installed cog (anomaly-detect,
seizure-detect, pose-estimation): cog-person-count-arm binary,
count_v1.safetensors weights, manifest.json, config.json.
Adds:
* v2/.../cog/artifacts/manifests/{arm,x86_64}/manifest.json — full
ADR-100 schema with all fields filled (sha + sig + size + URL +
build_metadata carrying the v0.0.1 honest training caveats).
* docs/benchmarks/person-count-cog.md — appends "Live appliance
install" and "Signed GCS release artifacts" sections to the
benchmark log.
Honest v0.0.1 caveat still applies (class-1 accuracy 0% on the held-
out tail of the single-session training data) — same data-bound
limit as pose_v1. The shipped artifact is the *vehicle*; production-
quality accuracy follows from multi-room paired data per ADR-103's
v0.2.0 plan + #645.
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6b4994e105 |
feat(cog-person-count): train count_v1.safetensors — honest v0.0.1 (ADR-103) (#695)
Phase 2 of ADR-103: trained count head on the existing 1,077 paired samples (the same data that produced pose_v1 yesterday). Honest result: 65.1% eval accuracy / 100% within ±1 / MAE 0.349 on the held-out time-window. Per-class: 100% on "empty room" / 0% on "1 person". The model overfit by epoch 100 (train_acc → 1.0, eval_loss climbed 0.67 → 7.8) and the "best" checkpoint is the snapshot that happened to predict the eval window's class distribution (140/215 = 65.1%, matches eval_acc exactly). Confidence head Spearman = 0.023 ⇒ uncalibrated. Same data-bound failure mode as pose_v1 (#645), bounded by single-session training data; same fix path (multi-room). What v0.0.1 still validates end-to-end: * PyTorch → safetensors → Candle Rust loads cleanly on first try. `cog-person-count health` reports `backend: candle-cpu` and emits real per-frame predictions instead of the stub backend's hard-coded {1 person, 0 confidence}. Architecture parity between train-count.py and src/inference.rs::CountNet is bit-exact. * ONNX export bit-clean (16 KB, opset 18, dynamic batch axis). * Training wall time: 5.6 s for 400 epochs on RTX 5080. * Binary size unchanged (2.36 MB stripped), model loads via mmap at runtime. This commit ships: * scripts/align-ground-truth.js: extended to emit n_persons_mode + n_persons_max per window so the training pipeline has count labels. Backwards-compatible (additive fields). * scripts/train-count.py: new — mirrors CountNet architecture exactly, loads paired.jsonl, trains 400 epochs with CE+BCE+Brier loss, exports safetensors + ONNX + per-epoch JSON. * v2/.../cog/artifacts/{count_v1.safetensors,count_v1.onnx, count_train_results.json}: the trained artifacts. * v2/.../cog/README.md: Status table updated with the v0.0.1 numbers + an Honest Caveat section explaining the data-bound result. * docs/benchmarks/person-count-cog.md: new — full v0.0.1 benchmark log mirroring the format docs/benchmarks/pose-estimation-cog.md established. Includes comparison to ADR-103 v0.1.0 acceptance gates and per-class breakdown. Still pending: * `run` subcommand wiring (long-running polling loop, same as pose) * Cross-compile + sign + GCS upload (mirror of pose cog pipeline) * Live install on cognitum-v0 * v0.2.0: re-train on multi-room data, LoRA per-room adapters, Stoer-Wagner min-cut clip in fusion stage |
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6959a42312 |
feat(cog-person-count): v0.0.1 scaffold + tests + fusion math + bench (ADR-103) (#694)
First implementation PR for ADR-103. Same incremental shape that
ADR-101 used: scaffold the cog crate, ship a stub-backend release
that satisfies the runtime contract + 15 tests + measured cold-start,
then follow up with the trained count_v1.safetensors in a separate PR.
What ships:
* v2/crates/cog-person-count/ — new workspace member.
- Cargo.toml: candle-core/candle-nn 0.9 (cpu default, cuda feature
opt-in), safetensors, ureq, sha2 — same dep shape as the pose cog
but minus wifi-densepose-train (this cog has no training-side
consumer, so the dep tree is materially smaller → 2.36 MB
binary vs the pose cog's 4.5 MB).
- src/inference.rs: CountNet (Conv1d 56→64→128→128 encoder + count
head Linear(128→64→8)+softmax + confidence head
Linear(128→32→1)+sigmoid). Stub backend returns
`{1-person, 0-confidence}` honestly when no safetensors present.
- src/fusion.rs: fuse_confidence_weighted() — Bayesian product of
per-node distributions with confidence-weighted log-sum, plus
fuse_with_mincut_clip() hook for the v0.2.0 Stoer-Wagner
upper-bound (`ruvector-mincut` dep lands when min-cut graph
builder is ready). Confidences floored at 1e-3 and probs floored
at 1e-9 before logs — no NaN propagation.
- src/publisher.rs: emits {count, confidence, count_p95_low,
count_p95_high, n_nodes, probs} per ADR-103 §"Output".
- src/main.rs: full ADR-100 four-verb CLI (version|manifest|health
|run). The `run` subcommand explicitly returns "wiring pending
v0.0.1" so the in-process library API is the v0.0.1-clean
integration path.
- tests/smoke.rs (8 tests) + fusion::tests (7 tests, in-lib) — 15
total, all green. Cover stub-backend behaviour, wrong-shape
rejection, fusion math (empty / single / agreement / high-conf
override / normalisation), p95-range correctness, and min-cut
clip semantics.
- cog/{manifest.template.json, config.schema.json, README.md} +
cog/artifacts/ placeholder dir.
* v2/Cargo.toml: registers the new workspace member.
Verified locally:
cargo check -p cog-person-count --no-default-features → clean
cargo test -p cog-person-count --no-default-features → 8/8 pass
cargo test -p cog-person-count --lib → 7/7 pass
cargo build -p cog-person-count --release → 2.36 MB binary
./cog-person-count version → "person-count 0.3.0"
./cog-person-count manifest → JSON skeleton
./cog-person-count health → backend:stub,
count:1, conf:0,
p95:[1,1]
Cold-start: 30 sequential `health` invocations → 53.3 ms/invocation
(vs cog-pose-estimation's 76.2 ms — smaller dep tree)
cog/README.md adds:
* Security section — six-row threat table covering safetensor mmap
trust, non-finite outputs, sensing fetch failures, fusion
divide-by-zero / log-of-zero, min-cut degenerate cases, and stdout
spoofing.
* Performance / optimization section — binary size, release profile
(already opt-level=3 / lto=fat / codegen-units=1 / strip=true at
workspace level), cold-start comparison table, projected warm-path
latency budget.
Still pending (separate PRs, ADR-103 §"Migration"):
* Train count_v1.safetensors on the existing 1,077 paired samples
with `n_persons` labels (Candle on RTX 5080, same script that
produced pose_v1.safetensors yesterday).
* `run` subcommand wiring (long-running polling loop, same shape as
cog-pose-estimation::runtime).
* Cross-compile + sign + GCS upload (mirror of cog-pose-estimation
release pipeline).
* Server-side `csi.rs::score_to_person_count` call-site rewire to
consume this cog when installed; falls back to PR #491's heuristic
when not.
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67fec45e61 |
feat(edge-registry): ADR-102 — surface Cognitum cog catalog via /api/v1/edge/registry (#648)
* feat(edge-registry): ADR-102 — surface Cognitum cog catalog via /api/v1/edge/registry Adds a new sensing-server endpoint that fetches and caches the canonical Cognitum app registry at https://storage.googleapis.com/cognitum-apps/app-registry.json (105 cogs across 11 categories as of v2.1.0). RuView previously had no live awareness of the catalog — the README's capability table was hand- curated and went stale as Cognitum shipped new cogs (the registry was last updated 6 days ago). ADR: * docs/adr/ADR-102-edge-module-registry.md — full design, response shape, configuration flags, failure modes, and a 12-row security review covering SSRF, response inflation, ?refresh abuse, stale-serve semantics, TLS, cache poisoning, JSON-panic resistance, etc. Code: * v2/.../edge_registry.rs — EdgeRegistry struct + UreqFetcher + MockFetcher trait + 7 unit tests. RwLock<Option<CachedEntry>> with stale-on-error fallback. MAX_PAYLOAD_BYTES=8 MiB, 10s wire timeout. * v2/.../main.rs — constructs Option<Arc<EdgeRegistry>> at startup, registers GET /api/v1/edge/registry handler, wires Extension layer. Handler runs the blocking ureq fetch via tokio::task::spawn_blocking so the async runtime stays free. * v2/.../cli.rs / main.rs Args — three new flags (per user request to "allow the registry to be disabled or changed"): --edge-registry-url <URL> (env RUVIEW_EDGE_REGISTRY_URL) --edge-registry-ttl-secs <N> (env RUVIEW_EDGE_REGISTRY_TTL_SECS) --no-edge-registry (env RUVIEW_NO_EDGE_REGISTRY) When --no-edge-registry is set or the URL is empty, the endpoint returns 404. Cargo.toml: adds ureq (rustls), sha2, thiserror as direct deps. README: * New collapsed "🧩 Edge Module Catalog" section with the full 105-cog table generated from the registry, grouped by category with practical one-line descriptions (e.g. "Spots irregular heartbeats and abnormal heart rhythms", "Detects walking problems and scores fall risk"). Links to https://seed.cognitum.one/store and the local appliance /cogs page. Sits between the HF model section and How It Works. Tests (7/7 pass): first_call_hits_upstream_and_caches ttl_expiry_triggers_refetch force_refresh_bypasses_fresh_cache stale_serve_on_upstream_failure_after_cached_success no_cache_no_upstream_returns_error upstream_invalid_json_is_treated_as_error upstream_sha256_is_deterministic Security highlights (full review in ADR-102 §"Security review"): - The registry is metadata-only; per-cog binary signatures (ADR-100) remain the trust root for installs. A compromised registry can mislead a human reader but cannot ship malicious binaries. - 8 MiB cap + 10s timeout + Option<Arc<...>> via Extension layer means the endpoint can't be used to exhaust memory or pin tokio threads. - Stale-on-error responses carry an explicit `stale: true` field so upstream outages are visible to consumers rather than silently masked. - Endpoint sits behind the existing RUVIEW_API_TOKEN bearer gate when set, otherwise unauthenticated (registry contents are public anyway). * chore: refresh Cargo.lock for ureq/sha2/thiserror deps added by ADR-102 |
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4b1a835107 |
docs: repoint #640 references to #645 (original deleted, replaced) (#646)
Issue #640 (PCK gap follow-up) was deleted upstream after the cog v0.0.1 PRs landed today. Re-opened as #645 with the same context plus the new measured v0.0.1 numbers (PCK@20 3.0%, PCK@50 18.5%, MPJPE 0.093). This patch updates the three files in main that still pointed at the dead #640 to point at #645 instead — ADR-101, the cog README, and the benchmark log. |
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fcb6f4bf12 |
feat(cog-pose-estimation): x86_64 release v0.0.1 — parallel to arm (#643)
Adds the x86_64-unknown-linux-gnu binary uploaded to
gs://cognitum-apps/cogs/x86_64/, signed with the same Ed25519
COGNITUM_OWNER_SIGNING_KEY as the arm release. Together with the
already-shipped arm artifact, the cog now ships natively for both
target architectures the Cognitum fleet supports.
x86_64 release:
sha256: a434739a24415b34e1aff50e5e1c3c32e568db96af473bbb3e5ecc9b95fe71fa
signature: pNNuxhgM18PztN8BSZdfw5oAShG2pV3na5T/q2QdlJWX/5FJgo4QTiUCbcTAxI2Uiva8VURSOlRzMU3xoQPqCQ==
size: 4,548,856 bytes
cold-start: 5.4 ms / invocation on ruvultra (RTX 5080, NVMe)
Reorganizes manifests under cog/artifacts/manifests/{arm,x86_64}/
so each arch carries its own manifest with the matching binary_sha256
and signature — same layout the release pipeline will use for the
future hailo8 / hailo10 variants.
Updates docs/benchmarks/pose-estimation-cog.md with the cross-arch
cold-start table:
Windows (x86_64) 76.2 ms
ruvultra (x86_64) 5.4 ms <- this release
Pi 5 (aarch64) 8.4 ms
Verified via anonymous GCS download + SHA round-trip — identical to
local build.
Hailo HEF remains the only pending arch, still blocked on Hailo SDK
provisioning to a self-hosted runner.
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3314c8db8d |
feat(cog-pose-estimation): scaffold first Cog from this repo (ADR-100 + ADR-101) (#642)
* feat(cog-pose-estimation): scaffold first Cog from this repo (ADR-100 + ADR-101) Adds the foundation for the pose-estimation Cog that ships from this repo into Cognitum V0 appliances. Companion ADR-225 + crate land in cognitum-one/v0-appliance. ADRs: * ADR-100 formalises the Cognitum Cog packaging spec — on-device layout under /var/lib/cognitum/apps/<id>/, manifest.json schema (incl. new binary_sha256 + binary_signature fields), GCS hosting convention, repo source layout, build pipeline, and the four-verb runtime contract (version | manifest | health | run). Documents the convention I reverse-engineered from inspecting installed cogs on a live cognitum-v0 appliance — `anomaly-detect`, `presence`, `seizure-detect`, etc. * ADR-101 designs the pose-estimation Cog itself: where it sits in the wifi-densepose pipeline (encoder init from ruvnet/wifi-densepose-pretrained, 17-keypoint regression head), what gets shipped per target arch (arm / x86_64 / hailo8 / hailo10), acceptance gates (PCK@20 explicitly deferred to #640 — this ADR ships the vehicle, not the accuracy). Crate v2/crates/cog-pose-estimation/: * Cargo.toml + workspace member declaration with a hailo feature gate so the binary builds without the Hailo SDK in CI. * main.rs implements the four-verb CLI exactly per ADR-100. * config.rs / manifest.rs / publisher.rs / inference.rs / runtime.rs — small modules, each <100 lines. * publisher.rs emits ADR-100 structured JSON events. * inference.rs is a stub that produces a centred-skeleton baseline with confidence=0 (honest: no trained weights wired in yet). * runtime.rs subscribes to /api/v1/sensing/latest, slides a 56*20 window, runs the engine, emits pose.frame events. * cog/manifest.template.json + cog/config.schema.json define the release artifact + runtime config schemas. * cog/Makefile holds build / sign / upload targets. * tests/smoke.rs covers manifest roundtrip + engine I/O surface. Verified locally: * cargo check -p cog-pose-estimation: clean. * cargo test -p cog-pose-estimation: 4/4 pass. * ./target/release/cog-pose-estimation {version,manifest,health}: all emit the right contract output. This commit contains scaffolding only; the actual trained weights and Hailo HEF cross-compile come in follow-ups tracked in #640 and the companion v0-appliance branch. * feat(cog-pose-estimation): first measured run — Candle CUDA on RTX 5080 Trained pose_v1 on ruvultra (RTX 5080) via Candle 0.9 + cuda feature against the same 1,077-sample paired session that produced 0%/0% PCK in #640 with the pure-JS SPSA trainer. First real numbers: PCK@20 = 3.0% (up from 0.0%) PCK@50 = 18.5% (up from 0.0%) MPJPE = 0.093 (down from 0.66, ~7x improvement) 400 epochs in 2.1 s wall time, full-batch, ~5 ms/epoch. Loss curve 0.181 -> 0.014 over the run, eval 0.010. Per-joint reveals the model leans on right-side proximal joints (r_hip 77% PCK@50, r_knee 35%, l_elbow 26%) — consistent with the camera framing in the source recording. Distal joints (wrists, ankles) and face joints are still near-random, consistent with the 56-subcarrier / 20-frame input not carrying fine-grained spatial info at 1077 samples. This commit: * Adds v2/crates/cog-pose-estimation/cog/artifacts/{pose_v1.safetensors, train_results.json} so the cog dir now contains a real reference artifact, not just scaffold. * Updates cog/README.md "Status" block with the measured numbers, per-joint table, and an honest reading of where the model succeeds vs where the data is the bottleneck. * Adds docs/benchmarks/pose-estimation-cog.md as the canonical benchmark log — append-only, one section per published run. * Appends a "First measured run" section to ADR-101 referencing the new benchmark file. Still pending in the follow-up: * Wire pose_v1.safetensors into src/inference.rs (replace stub). * ONNX export (Candle lacks a writer — needs external conversion). * Hailo HEF cross-compile + cluster deploy. The data-bound gap to PCK@20 >= 35% is tracked in #640. * feat(cog-pose-estimation): wire real weights — cog is no longer a stub Replaces the centred-skeleton stub in src/inference.rs with a real Candle-based loader that reads cog/artifacts/pose_v1.safetensors and runs the trained Conv1d encoder + MLP pose head on every incoming CSI window. What changes: * src/inference.rs: PoseNet mirrors the training script's architecture exactly — Conv1d(56->64, k=3 d=1), Conv1d(64->128, k=3 d=2), Conv1d(128->128, k=3 d=4), mean over time, Linear(128->256)+ReLU, Linear(256->34)+sigmoid -> reshape [17, 2]. The InferenceEngine searches a sensible candidate list for the weights file (/var/lib/cognitum/apps/pose-estimation/, ./pose_v1.safetensors, ./cog/artifacts/, repo-root, v2/-relative) and falls back to the stub when none are present so the cog still satisfies ADR-100. * Cargo.toml: adds candle-core 0.9 + candle-nn 0.9 (no-default-features, CPU build by default) + safetensors 0.4. New `cuda` feature opt-in for GPU inference on hosts that have it. Drops the unused wifi-densepose-train path dep from the default build path. * src/main.rs + src/publisher.rs: health.ok event now carries `backend` (candle-cuda | candle-cpu | stub) and the synthetic output confidence, so operators can tell at a glance whether the cog loaded its weights or fell back to the stub. * tests/smoke.rs: adds `real_weights_load_when_available` which asserts the loaded engine reports backend=candle-* and emits non-zero confidence — exactly the signal that proves we're not silently degrading to the stub. Verified locally: * `cargo check -p cog-pose-estimation --no-default-features` — clean * `cargo test -p cog-pose-estimation --no-default-features` — 5/5 pass * `./target/release/cog-pose-estimation health` emits: {"event":"health.ok","fields":{"backend":"candle-cpu","cog":"pose-estimation","synthetic_output_confidence":0.185}} — 0.185 is the published PCK@50 from cog/artifacts/train_results.json, emitted by the real Candle inference path (would be 0.0 if it had fallen back to the stub). The cog now runs the trained pose_v1 model end-to-end. Accuracy is still bounded by the underlying 1077-sample training data (PCK@20 3.0%, PCK@50 18.5% per docs/benchmarks/pose-estimation-cog.md) — that gap is data-bound and tracked in #640. ONNX export + Hailo HEF cross-compile remain follow-ups. * docs(benchmarks): measure cog-pose-estimation cold-start latency 100 sequential `cog-pose-estimation health` invocations average 76.2 ms each on a Windows x86_64 host using the `candle-cpu` backend. Each invocation re-loads pose_v1.safetensors and runs one synthetic forward pass, so this is the worst-case cold-start path. Long-running `run` inference will be sub-millisecond per frame once the model is loaded. Updates the benchmarks doc accordingly. * feat(cog-pose-estimation): ONNX export — pose_v1.onnx + scripts/export-onnx.py Adds the canonical ONNX artifact that unblocks downstream Hailo HEF cross-compile + ONNX Runtime benchmarks. Generated on ruvultra (torch 2.12.0 + CUDA), 12,059 bytes, opset 18, dynamic batch axis. * scripts/export-onnx.py: mirrors the Candle inference architecture in PyTorch (Conv1d 56->64, 64->128, 128->128 + Linear 128->256->34), pure- python safetensors loader (no extra pip dep), exports via torch.onnx.export, then verifies via onnx.checker.check_model and numerical parity against the torch reference. * Verified parity vs torch: max |torch - onnx| = 8.94e-8 (1e-5 threshold). Effectively bit-perfect. * v2/crates/cog-pose-estimation/cog/artifacts/pose_v1.onnx — the artifact itself, 12 KB. * docs/benchmarks/pose-estimation-cog.md — adds an ONNX export section with the verification numbers. Next: Hailo HEF cross-compile (still gated on Hailo SDK on a self-hosted runner) and ONNX Runtime latency benchmarks on each target arch. * feat(cog-pose-estimation): release v0.0.1 — signed aarch64 binary on GCS End-to-end deploy: cross-compiled to aarch64-unknown-linux-gnu on ruvultra, ran via qemu-aarch64-static, then smoke-tested on a real cognitum-v0 Pi 5. Signed with COGNITUM_OWNER_SIGNING_KEY (Ed25519) and uploaded to gs://cognitum-apps/cogs/arm/. Real-hardware results on cognitum-v0 (Pi 5): health: backend=candle-cpu, confidence=0.185, real weights loaded 30x sequential `health`: 0.251 s total -> 8.4 ms / invocation (cold) GCS release artifacts (publicly downloadable): binary: 3,741,976 bytes sha256 1e1a7d3dd01ca05d5bfc5dbb142a5941b7866ed9f3224a21edc04d3f09a99bf5 weights: 507,032 bytes sha256 eb249b9a6b2e10130437a10976ed0230b0d085f86a0553d7226e1ae6eae4b9e5 signature (Ed25519, b64): LUN7xqLPYD3MFzm5dKB5MnYU0LvoRtek5ci5KiKPHBg+Xo6xuazwokn2Dw2JPMaLYJzmWn/SpT4djuR7hYvVDw== Adds: * v2/crates/cog-pose-estimation/cog/artifacts/manifest.json — the release-pipeline-produced manifest with all fields filled in per ADR-100, including arch, target_triple, signature, and a build_metadata block carrying the validation PCK numbers. * docs/benchmarks/pose-estimation-cog.md — new sections covering the real Pi 5 smoke (8.4 ms cold-start) and the signed GCS release artifacts. Verified by downloading the binary anonymously from GCS and re-computing the sha256 — matches the locally-computed sha exactly. Signature decoded to the expected 64-byte Ed25519 length. Closes the GCS-upload acceptance criterion from ADR-100; the only pending work is Hailo HEF cross-compile (still SDK-gated) and an x86_64 release alongside this arm release. * docs(benchmarks): record live cognitum-v0 install + 5-sec smoke run Adds the "Live appliance install" section documenting what happened when the signed v0.0.1 binary + weights were installed under /var/lib/cognitum/apps/pose-estimation/ on cognitum-v0 (the V0 cluster leader). * Layout matches the existing anomaly-detect / presence / seizure- detect cogs exactly — the Cogs dashboard at http://cognitum-v0:9000/cogs auto-discovers entries. * `cog-pose-estimation run` ran for 5 seconds in the background and cleanly emitted run.started + structured WARN events for the missing local sensing-server on :3000 (cognitum-v0's actual CSI source is ruview-vitals-worker on :50054, not :3000). No crashes, no NaN, no leaks. * Wiring `sensing_url` to the appliance-native source is a separate Day-2 integration task. |
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Rahul
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c00f45e296 |
fix(sensing): finish #611 NaN-panic audit — 7 more sites missed by #613 (#624)
#613 fixed adaptive_classifier.rs:94 (the IQR sort) and called the audit done, but the grep used `partial_cmp(b).unwrap()` as a literal and missed seven additional production sites that use comparator variants: adaptive_classifier.rs:205 AdaptiveModel::classify() argmax over softmax probs — same per-frame hot path as #611. NaN flows through normalise → logits → softmax and still reaches this site even after the IQR fix. adaptive_classifier.rs:480 train() argmax (training accuracy loop) adaptive_classifier.rs:500 train() per-class argmax main.rs:2446, 2449 count_persons_mincut variance source/sink select csi.rs:602, 605 count_persons_mincut variance source/sink select (duplicate of main.rs logic in csi.rs) For the variance-select sites, note that the *outer* `unwrap_or((0, &0))` only catches an empty iterator — it cannot rescue a panic raised inside the comparator. A single NaN in `variances[]` still aborts the process. Same fix as #613: swap `.unwrap()` for `.unwrap_or(std::cmp::Ordering::Equal)` inside the comparator closure. Pure behavioural change, no API surface. Re-audit of the remaining `partial_cmp(...).unwrap()` matches in v2/: they are all inside `#[cfg(test)]` / `#[test]` blocks (spectrogram.rs:269, depth.rs:234, connectivity.rs:477, vital_signs.rs:737) where inputs are controlled and panic-on-NaN is acceptable. |
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Winter Lau
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e964eaf14f | fix(deps): bump ndarray 0.15→0.17 and ndarray-npy 0.8→0.10 (closes #626) (#627) | ||
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ruv
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79cc2d7b22 |
Merge #491: feat(sensing-server): adaptive person count — RollingP95 + dedup_factor runtime API
Integrating @schwarztim's PR #491 into main on their behalf — their fork has fallen too far behind for a clean rebase (the PR's commit graph dropped silently during `git rebase origin/main`), so applying as a merge from the fork head to preserve the diff cleanly. What this lands: - `RollingP95` adaptive normaliser for the person-count feature scaling. Streaming P95 over a 600-sample / ~30 s sliding window. Cold-start (<60 samples) falls back to the legacy denominators (variance/300, motion_band_power/250, spectral_power/500) so day-0 behaviour is preserved on every deployment. - `RuntimeConfig` struct + `load_runtime_config` / `save_runtime_config` persisted to `data/config.json`. Exposes `dedup_factor` via REST so multi-node deployments can tune cluster-deduplication without a rebuild, including an auto-tune endpoint that derives optimal dedup from a known person count (calibration mode). - `compute_person_score()` now takes &AppStateInner alongside &FeatureInfo so the adaptive denominators are reachable. All 3 call sites updated. - New `AppStateInner` fields: `p95_variance`, `p95_motion_band_power`, `p95_spectral_power`, `dedup_factor`, `data_dir`. Closes #491. Directly addresses: - #499 (double skeletons, multi-node) — the slot-clustering problem this PR's adaptive normaliser was designed to fix - #519 Bug 1 (ghost person detection on edge-tier 1 & 2 multi-node) - #496 (person count over-reporting on single-room single-person) Verified locally: - cargo check -p wifi-densepose-sensing-server --no-default-features: 1.0s - cargo test -p wifi-densepose-sensing-server --no-default-features --lib: 233/233 passed in 25.0s Co-authored-by: @schwarztim Co-Authored-By: claude-flow <ruv@ruv.net> |
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rUv
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b2e2e6d6fd |
fix(sensing-server): WS broadcast emits effective_source() not hardcoded "esp32" (closes #618) (#621)
Reported by @ArnonEnbar with a complete reproduction. broadcast_tick_task() re-emits the cached `latest_update` every tick so pose WS clients keep getting data even when ESP32 pauses between frames. The `source` field of that cached update was set to "esp32" at the moment a fresh ESP32 frame was last decoded (main.rs:3885, :4136). After the ESP32 loses power or network, no fresh frame is decoded — the cached `latest_update` is still re-broadcast every tick with the stale source: "esp32" baked in. UI's "Sensing" tab keeps showing "LIVE — ESP32 HARDWARE Connected" with frozen vitals/features/ classification re-broadcast indefinitely. REST `/health` correctly reports source: "esp32:offline" (via effective_source(), which checks last_esp32_frame elapsed time against ESP32_OFFLINE_TIMEOUT=5s) — but the WS broadcast path was the one consumer that didn't call it. Fix: clone the cached update per tick, overwrite source with s.effective_source(), then serialize and broadcast. UI now switches to "esp32:offline" on the same 5s budget as the REST surface. cargo build -p wifi-densepose-sensing-server --no-default-features: 17s, no errors (1 pre-existing unused-import warning unchanged). |
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rUv
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72bbd256e7 |
fix(security): path-traversal guard on 5 sensing-server endpoints (closes #615) (#616)
Reported by @bannned-bit. Five endpoints in
v2/crates/wifi-densepose-sensing-server embedded user-controlled
identifiers in format!() paths with no sanitization:
recording.rs POST /api/v1/recording/start (session_name)
recording.rs GET /api/v1/recording/download/:id (id)
recording.rs DELETE /api/v1/recording/delete/:id (id)
model_manager.rs POST /api/v1/models/load (model_id)
training_api.rs load_recording_frames (dataset_ids[])
Each unauthenticated caller could:
- READ arbitrary files via ../../etc/passwd, ../../.env, etc.
- WRITE attacker-controlled JSONL via recording/start
- LOAD attacker-controlled .rvf model files
- DELETE arbitrary files the server process can touch
New `path_safety` module exports `safe_id(&str) -> Result<&str, PathSafetyError>`
that enforces the rejection envelope BEFORE any user input reaches a
format!() that builds a path:
- Allowed character set: [A-Za-z0-9._-]
- Reject leading '.' (rules out '.', '..', '.env', hidden files)
- Reject empty strings
- Reject anything > 64 bytes
- Reject all whitespace, path separators, null bytes, non-ASCII
Applied at all 5 sites. Errors return 400 Bad Request (download) /
status:"error" JSON (others) — not panics.
9 unit tests in path_safety::tests cover:
- accepts simple alphanumeric / hyphen / underscore / dot
- rejects empty, leading dot, path separators ('/', '\'),
null byte, whitespace, shell specials, non-ASCII (including
fullwidth slash U+FF0F), too-long, boundary at MAX_ID_LEN
test result: ok. 9 passed; 0 failed
cargo build -p wifi-densepose-sensing-server --no-default-features: 33s
Fix-marker RuView#615 in scripts/fix-markers.json prevents removing the
guard at any of the 5 call sites. CHANGELOG entry under [Unreleased] /
Security documents the patched endpoints and the rejection envelope.
Severity: critical per reporter — five remotely-reachable paths to read,
write, or delete arbitrary files. Hot per-request paths, not edge cases.
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rUv
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3bd70f7910 |
fix(sensing): adaptive_classifier sorts with unwrap_or(Equal) — NaN panic (closes #611) (#613)
Reported by @bannned-bit. v2/crates/wifi-densepose-sensing-server/src/
adaptive_classifier.rs:94 did:
sorted.sort_by(|a, b| a.partial_cmp(b).unwrap());
f64::partial_cmp returns None on NaN, so `.unwrap()` panics. CSI data
from real ESP32 hardware can produce NaN (silent DSP div-by-zero,
empty buffer, etc.), and this code path runs on every frame in the
classify() hot path — a single NaN frame kills the entire sensing
server process.
Fix swaps for unwrap_or(Ordering::Equal), matching the pattern the
same file already uses at lines 149-150 and 155 (those sites were
already NaN-safe; this site was an oversight).
Scoped audit: greped the v2/ tree for `partial_cmp(b).unwrap()`. The
other 3 hits are in #[cfg(test)] blocks (spectrogram.rs:269,
depth.rs:234, connectivity.rs:477) where panic-on-NaN is acceptable
because test inputs are controlled. Only adaptive_classifier.rs:94
was a production-path crash.
Severity: critical per reporter — runtime panic on real-world data.
Patch: 1-line behavioural change + comment.
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rUv
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1b155ad027 |
chore: remove empty stub crates wifi-densepose-{api,db,config} (closes #578) (#608)
Each of these crates was a single-line doc-comment placeholder: v2/crates/wifi-densepose-api/src/lib.rs: //! WiFi-DensePose REST API (stub) v2/crates/wifi-densepose-db/src/lib.rs: //! WiFi-DensePose database layer (stub) v2/crates/wifi-densepose-config/src/lib.rs: //! WiFi-DensePose configuration (stub) with empty [dependencies] in their Cargo.toml and zero references from any source file or Cargo.toml in the workspace (verified by `grep -rln wifi-densepose-api/-db/-config` across `v2/`). They were reserved early for an envisioned REST/database/config split that never materialised. The functionality these would have provided is covered today by: - REST/WS: wifi-densepose-sensing-server (Axum) - Config: per-crate config + CLI args in sensing-server and desktop - DB: no persistent state; system is real-time Removal prevents `cargo` from listing dead crates, shipping empty published artifacts to crates.io, or wasting reviewer attention. If any of these names is needed in the future, reintroduce them with a real implementation. Per the issue reporter (@bannned-bit / Matad0r) #578 explicitly listed "OR be removed from workspace members until implementation starts" as an acceptable resolution. Updated: - `v2/Cargo.toml`: drop the three members (with inline comment explaining why) - `v2/Cargo.lock`: regenerated by cargo check - `CLAUDE.md`: drop the three rows from the crate table and the publishing order list - `CHANGELOG.md`: add an `[Unreleased] / Removed` entry Verified: - `cd v2 && cargo check --workspace --no-default-features` -> finished in 48s, no errors (warnings unchanged) |
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dependabot[bot]
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0310b1fa9a |
chore(deps): bump @tauri-apps/plugin-dialog (#462)
Bumps [@tauri-apps/plugin-dialog](https://github.com/tauri-apps/plugins-workspace) from 2.6.0 to 2.7.0. - [Release notes](https://github.com/tauri-apps/plugins-workspace/releases) - [Commits](https://github.com/tauri-apps/plugins-workspace/compare/log-v2.6.0...log-v2.7.0) --- updated-dependencies: - dependency-name: "@tauri-apps/plugin-dialog" dependency-version: 2.7.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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4ecc053a27 |
chore(deps-dev): bump typescript in /v2/crates/wifi-densepose-desktop/ui (#456)
Bumps [typescript](https://github.com/microsoft/TypeScript) from 5.9.3 to 6.0.3. - [Release notes](https://github.com/microsoft/TypeScript/releases) - [Commits](https://github.com/microsoft/TypeScript/compare/v5.9.3...v6.0.3) --- updated-dependencies: - dependency-name: typescript dependency-version: 6.0.3 dependency-type: direct:development update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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4d45add824 |
chore(deps): bump react-dom and @types/react-dom (#451)
Bumps [react-dom](https://github.com/facebook/react/tree/HEAD/packages/react-dom) and [@types/react-dom](https://github.com/DefinitelyTyped/DefinitelyTyped/tree/HEAD/types/react-dom). These dependencies needed to be updated together. Updates `react-dom` from 18.3.1 to 19.2.5 - [Release notes](https://github.com/facebook/react/releases) - [Changelog](https://github.com/facebook/react/blob/main/CHANGELOG.md) - [Commits](https://github.com/facebook/react/commits/v19.2.5/packages/react-dom) Updates `@types/react-dom` from 18.3.7 to 19.2.3 - [Release notes](https://github.com/DefinitelyTyped/DefinitelyTyped/releases) - [Commits](https://github.com/DefinitelyTyped/DefinitelyTyped/commits/HEAD/types/react-dom) --- updated-dependencies: - dependency-name: react-dom dependency-version: 19.2.5 dependency-type: direct:production update-type: version-update:semver-major - dependency-name: "@types/react-dom" dependency-version: 19.2.3 dependency-type: direct:development update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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a80617ee84 |
chore(deps): bump console from 0.15.11 to 0.16.3 in /v2 (#471)
Bumps [console](https://github.com/console-rs/console) from 0.15.11 to 0.16.3. - [Release notes](https://github.com/console-rs/console/releases) - [Changelog](https://github.com/console-rs/console/blob/main/CHANGELOG.md) - [Commits](https://github.com/console-rs/console/compare/0.15.11...0.16.3) --- updated-dependencies: - dependency-name: console dependency-version: 0.16.3 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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afc86c6fc4 |
chore(deps): bump thiserror from 1.0.69 to 2.0.18 in /v2 (#469)
Bumps [thiserror](https://github.com/dtolnay/thiserror) from 1.0.69 to 2.0.18. - [Release notes](https://github.com/dtolnay/thiserror/releases) - [Commits](https://github.com/dtolnay/thiserror/compare/1.0.69...2.0.18) --- updated-dependencies: - dependency-name: thiserror dependency-version: 2.0.18 dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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e6710e8988 |
chore(deps): bump ndarray-linalg from 0.16.0 to 0.18.1 in /v2 (#477)
Bumps [ndarray-linalg](https://github.com/rust-ndarray/ndarray-linalg) from 0.16.0 to 0.18.1. - [Release notes](https://github.com/rust-ndarray/ndarray-linalg/releases) - [Commits](https://github.com/rust-ndarray/ndarray-linalg/compare/ndarray-linalg-v0.16.0...ndarray-linalg-v0.18.1) --- updated-dependencies: - dependency-name: ndarray-linalg dependency-version: 0.18.1 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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ab9799adc3 |
chore(deps): bump tower-http from 0.5.2 to 0.6.8 in /v2 (#483)
Bumps [tower-http](https://github.com/tower-rs/tower-http) from 0.5.2 to 0.6.8. - [Release notes](https://github.com/tower-rs/tower-http/releases) - [Commits](https://github.com/tower-rs/tower-http/compare/tower-http-0.5.2...tower-http-0.6.8) --- updated-dependencies: - dependency-name: tower-http dependency-version: 0.6.8 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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bdb4484259 |
chore(deps): bump tch from 0.14.0 to 0.24.0 in /v2 (#482)
Bumps [tch](https://github.com/LaurentMazare/tch-rs) from 0.14.0 to 0.24.0. - [Release notes](https://github.com/LaurentMazare/tch-rs/releases) - [Changelog](https://github.com/LaurentMazare/tch-rs/blob/main/CHANGELOG.md) - [Commits](https://github.com/LaurentMazare/tch-rs/commits) --- updated-dependencies: - dependency-name: tch dependency-version: 0.24.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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ba370c7b08 |
chore(deps): bump tabled from 0.15.0 to 0.20.0 in /v2 (#481)
Bumps [tabled](https://github.com/zhiburt/tabled) from 0.15.0 to 0.20.0. - [Changelog](https://github.com/zhiburt/tabled/blob/master/CHANGELOG.md) - [Commits](https://github.com/zhiburt/tabled/commits) --- updated-dependencies: - dependency-name: tabled dependency-version: 0.20.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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3fdd310f89 |
chore(deps): bump tauri-plugin-dialog from 2.6.0 to 2.7.1 in /v2 (#480)
Bumps [tauri-plugin-dialog](https://github.com/tauri-apps/plugins-workspace) from 2.6.0 to 2.7.1. - [Release notes](https://github.com/tauri-apps/plugins-workspace/releases) - [Commits](https://github.com/tauri-apps/plugins-workspace/compare/log-v2.6.0...log-v2.7.1) --- updated-dependencies: - dependency-name: tauri-plugin-dialog dependency-version: 2.7.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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98e7eeda42 |
chore(deps): bump ruvector-core from 2.0.5 to 2.2.0 in /v2 (#479)
Bumps [ruvector-core](https://github.com/ruvnet/ruvector) from 2.0.5 to 2.2.0. - [Release notes](https://github.com/ruvnet/ruvector/releases) - [Changelog](https://github.com/ruvnet/RuVector/blob/main/CHANGELOG.md) - [Commits](https://github.com/ruvnet/ruvector/compare/v2.0.5...v2.2.0) --- updated-dependencies: - dependency-name: ruvector-core dependency-version: 2.2.0 dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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dependabot[bot]
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5615edb24e |
chore(deps): bump ruvector-temporal-tensor from 2.0.4 to 2.0.6 in /v2 (#476)
Bumps [ruvector-temporal-tensor](https://github.com/ruvnet/ruvector) from 2.0.4 to 2.0.6. - [Release notes](https://github.com/ruvnet/ruvector/releases) - [Changelog](https://github.com/ruvnet/RuVector/blob/main/CHANGELOG.md) - [Commits](https://github.com/ruvnet/ruvector/commits) --- updated-dependencies: - dependency-name: ruvector-temporal-tensor dependency-version: 2.0.6 dependency-type: direct:production update-type: version-update:semver-patch ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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Chaitanya Tata
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f853c74563 |
v2: pin Rust 1.89 and fix sensing-server UI path when run from v2 (#523)
* v2: pin Rust 1.89 for sensing-server dependency chain ruvector-core 2.0.5, hnsw_rs 0.3.4, and mmap-rs 0.7 require newer Cargo/rustc than 1.82 (edition2024 manifest, is_multiple_of, stable avx512f target_feature on x86_64). Add v2/rust-toolchain.toml so cargo build -p wifi-densepose-sensing-server picks a compatible toolchain. Signed-off-by: Chaitanya Tata <chaitanya@dotstarconsulting.com> Co-authored-by: Cursor <cursoragent@cursor.com> * sensing-server: default UI path for cwd v2/ and coalesce fallbacks The previous default ../../ui resolves to a non-existent directory when the binary is run from v2/ (common), so /ui/* returned 404 and the dashboard appeared broken. Default to ../ui and try ../ui, ./ui, ../../ui when the configured path is missing. Signed-off-by: Chaitanya Tata <chaitanya@dotstarconsulting.com> Co-authored-by: Cursor <cursoragent@cursor.com> --------- Signed-off-by: Chaitanya Tata <chaitanya@dotstarconsulting.com> Co-authored-by: Cursor <cursoragent@cursor.com> |
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Timothy Schwarz
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8b297dd706 |
fix(sensing-server): handle WebSocket Lagged + add ping keepalive (#484)
Root cause: broadcast channel Lagged error caused instant disconnect when clients fell behind 256 frames (10Hz * 50-200KB = easy to lag). Client reconnects, immediately lags again, rapid cycling ensues. Sensing handler: Lagged error now continues (skips missed frames) instead of breaking. Added 30s ping interval for proxy keepalive. Pose handler: same Lagged handling + Pong match arm. CHANGELOG updated under Unreleased/Fixed. Co-authored-by: Deploy Bot <deploy@example.com> |