Merge 1d41e81ac6 into f5d0e1e69e

fix(#894 ): actionable diagnostic when --model gets a non-RVF file (#919 )
Users who downloaded ruvnet/wifi-densepose-pretrained and passed model.safetensors / model-q4.bin / model.rvf.jsonl to --model hit a bare "Progressive loader init failed: invalid magic at offset 0: expected 0x52564653, got 0x77455735" and were stuck — the server then silently fell back to signal heuristics (which over-count, feeding "is it fake" reports). The HF files are a different *format* and encoder architecture than the RVF binary container the progressive loader expects, so they can't load directly. Now the load-failure path detects the common cases (safetensors header, JSONL manifest, quantized .bin blob) and emits a plain explanation naming the format, what --model actually expects (RVF `RVFS` container from wifi-densepose-train), and that it's continuing with heuristics — with a pointer to #894. Pure, testable `diagnose_model_load_error()` + 4 unit tests (run under the default `--no-default-features` CI). Full crate unit suite: 429 + 114 passed, 0 failed.
2026-06-03 00:39:45 -06:00 · 2026-06-02 20:05:30 +02:00 · 2026-06-02 19:26:01 +02:00 · 2026-06-02 19:01:08 +02:00 · 2026-06-02 18:50:39 +02:00 · 2026-06-02 18:31:55 +02:00
20 changed files with 374 additions and 694 deletions
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@ -265,23 +265,45 @@ jobs:
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
-        pip install locust
+        pip install pytest   # the perf suite is pytest, not locust

-    - name: Start application
-      working-directory: archive/v1
-      run: |
-        uvicorn src.api.main:app --host 0.0.0.0 --port 8000 &
-        sleep 10
+    # No "Start application" step: the gated test (test_frame_budget.py) drives
+    # the CSIProcessor pipeline in-process and makes no HTTP calls, so the old
+    # uvicorn server + `sleep 10` were dead weight — they only existed for the
+    # now-excluded api_throughput/inference_speed tests, and on every run dumped
+    # ~50 misleading "router requires hardware setup" ERROR lines for a server
+    # no test touched. MOCK_POSE_DATA is server-only and unused here.

    - name: Run performance tests
+      working-directory: archive/v1
      run: |
-        locust -f tests/performance/locustfile.py --headless --users 50 --spawn-rate 5 --run-time 60s --host http://localhost:8000
+        # Gate only on the genuine, deterministic perf guard:
+        # test_frame_budget.py times the *real* CSIProcessor pipeline against
+        # the ADR 50 ms per-frame budget (single-frame, p95 over 100 frames,
+        # +Doppler) — a true regression signal.
+        #
+        # test_api_throughput.py / test_inference_speed.py are excluded: every
+        # test there is a TDD red-phase stub (suffix `_should_fail_initially`)
+        # that times a *mock that sleeps* — meaningless as a perf signal, with
+        # machine-dependent wall-clock asserts (e.g. `actual_rps >= 40`,
+        # `batch_time < individual_time`) that are inherently flaky on shared
+        # CI runners, plus a cross-class fixture-scope bug. Forcing them green
+        # would be manufacturing a false signal; they stay in-repo for local
+        # TDD but do not gate CI until the underlying features are implemented.
+        #
+        # `python -m pytest` (not the bare `pytest` script) puts the cwd
+        # (archive/v1) on sys.path so `from src.core...` resolves — the bare
+        # script omits cwd and raises ModuleNotFoundError: No module named 'src'.
+        # -o addopts="" drops the root pyproject's --cov/--cov-fail-under=100.
+        python -m pytest tests/performance/test_frame_budget.py \
+          -o addopts="" -v --junitxml=perf-junit.xml

    - name: Upload performance results
+      if: always()
      uses: actions/upload-artifact@v4
      with:
        name: performance-results
-        path: locust_report.html
+        path: archive/v1/perf-junit.xml

  # Docker Build and Test
  # NOTE: the canonical Docker build for the sensing-server is now
@ -367,6 +389,8 @@ jobs:
    runs-on: ubuntu-latest
    needs: [docker-build]
    if: github.ref == 'refs/heads/main'
+    permissions:
+      contents: write   # gh-pages deploy needs write (GITHUB_TOKEN is read-only by default -> 403)
    steps:
    - name: Checkout code
      uses: actions/checkout@v4
@ -384,6 +408,8 @@ jobs:

    - name: Generate OpenAPI spec
      working-directory: archive/v1
+      env:
+        MOCK_POSE_DATA: "true"   # no CSI hardware in CI
      run: |
        python -c "
        from src.api.main import app
@ -394,6 +420,7 @@ jobs:

    - name: Deploy to GitHub Pages
      uses: peaceiris/actions-gh-pages@v4
+      continue-on-error: true   # openapi generation above is the real validation; deploy is best-effort (Pages may be disabled)
      with:
        github_token: ${{ secrets.GITHUB_TOKEN }}
        publish_dir: ./docs
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@ -430,7 +430,7 @@ Model release (no new firmware binary). Firmware remains at v0.6.0-esp32.
 - Security fix merged via PR #310.

 ### Performance
- Presence detection: 100% accuracy on 60,630 overnight samples.
+- Presence detection: 100% accuracy on 60,630 overnight samples. *(Retracted — that recording was single-class (one sleeping person, 6,062/6,063 frames "present"), so a constant "yes" scores ~99.98%. Superseded by the honest 82.3% held-out temporal-triplet metric; see [#882](https://github.com/ruvnet/RuView/issues/882). Kept here as the in-place public record.)*
 - Inference: 0.008 ms per sample, 164K embeddings/sec.
 - Contrastive self-supervised training: 51.6% improvement over baseline.

--- a/archive/v1/src/services/pose_service.py
+++ b/archive/v1/src/services/pose_service.py
@ -107,16 +107,25 @@ class PoseService:
    async def _initialize_models(self):
        """Initialize neural network models."""
        try:
-            # Initialize DensePose model
+            # Initialize DensePose model. DensePoseHead requires a config
+            # dict — input_channels matches the modality translator's output
+            # (256), with the standard DensePose 24 body parts and 2 (U,V)
+            # coordinates. (Previously called with no args → TypeError at
+            # startup, which broke the API service.)
+            densepose_config = {
+                'input_channels': 256,
+                'num_body_parts': 24,
+                'num_uv_coordinates': 2,
+            }
            if self.settings.pose_model_path:
-                self.densepose_model = DensePoseHead()
+                self.densepose_model = DensePoseHead(densepose_config)
                # Load model weights if path is provided
                # model_state = torch.load(self.settings.pose_model_path)
                # self.densepose_model.load_state_dict(model_state)
                self.logger.info("DensePose model loaded")
            else:
                self.logger.warning("No pose model path provided, using default model")
-                self.densepose_model = DensePoseHead()
+                self.densepose_model = DensePoseHead(densepose_config)
            
            # Initialize modality translation
            config = {
--- a/docs/readme-details.md
+++ b/docs/readme-details.md
@ -122,7 +122,7 @@ node scripts/benchmark-ruvllm.js --model models/csi-ruvllm       # benchmark

 | What we measured | Result | Why it matters |
 |-----------------|--------|---------------|
-| **Presence detection** | **100% accuracy** | Never misses a person, never false alarms |
+| **CSI embedding quality** | **82.3% held-out temporal-triplet** | Honest label-free metric on the last 20% by time (v1's "100% presence" was a single-class recording — retracted, [#882](https://github.com/ruvnet/RuView/issues/882)) |
 | **Inference speed** | **0.008 ms** per embedding | 125,000x faster than real-time |
 | **Throughput** | **164,183 embeddings/sec** | One Mac Mini handles 1,600+ ESP32 nodes |
 | **Contrastive learning** | **51.6% improvement** | Strong pattern learning from real overnight data |
@ -233,7 +233,7 @@ python firmware/esp32-csi-node/provision.py --port COM9 --hop-channels "1,6,11"
 | **kNN similarity search** | "Find the 10 most similar states to right now" — anomaly detection, fingerprinting | Cognitum Seed |
 | **Witness chain** | SHA-256 tamper-evident audit trail for every measurement (1,747 entries validated) | Cognitum Seed |
 | **Camera-free pose training** | 17 COCO keypoints from 10 sensor signals — PIR, RSSI triangulation, subcarrier asymmetry, vibration, BME280 | 2x ESP32 + Seed |
-| **Pre-trained model** | 82.8 KB (8 KB at 4-bit quantization), 100% presence accuracy, 0 skeleton violations | Download from release |
+| **Pre-trained model** | 82.8 KB (8 KB at 4-bit quantization), 82.3% held-out temporal-triplet accuracy (v1's "100% presence" was single-class — retracted, [#882](https://github.com/ruvnet/RuView/issues/882)) | Download from release |
 | **Sub-ms inference** | 0.012 ms latency, 171,472 embeddings/sec on M4 Pro | Any machine with Node.js |
 | **SONA adaptation** | Adapts to new rooms in <1ms without retraining | ruvllm runtime |
 | **LoRA room adapters** | Per-node fine-tuning with 2,048 parameters per adapter | Automatic |
@ -262,7 +262,7 @@ node scripts/benchmark-ruvllm.js --model models/csi-ruvllm

 | What we measured | Result | Why it matters |
 |-----------------|--------|---------------|
-| **Presence detection** | **100% accuracy** | Never misses a person, never false alarms |
+| **CSI embedding quality** | **82.3% held-out temporal-triplet** | Honest label-free metric (v1's "100% presence" was single-class — retracted, [#882](https://github.com/ruvnet/RuView/issues/882)) |
 | **Person counting** | **24/24 correct** (MinCut) | Fixed the #1 user-reported issue |
 | **Inference speed** | **0.012 ms** per embedding | 83,000x faster than real-time |
 | **Throughput** | **171,472 embeddings/sec** | One Mac Mini handles 1,700+ ESP32 nodes |
--- a/docs/user-guide.md
+++ b/docs/user-guide.md
@ -1119,7 +1119,7 @@ What it ships (and what it does not):

 | Capability | Status |
 |------------|--------|
-| Presence detection (occupied / empty) | ✅ Trained head — 100% accuracy on validation |
+| Presence detection (occupied / empty) | ✅ Trained head — v2 encoder reports 82.3% held-out temporal-triplet acc (v1's "100% on validation" was a single-class recording — retracted, [#882](https://github.com/ruvnet/RuView/issues/882)) |
 | 128-dim CSI embeddings (re-ID, similarity, downstream training) | ✅ Trained encoder |
 | Single-person breathing / heart-rate | ⚠️ Server still uses heuristic DSP — model does not replace this yet |
 | 17-keypoint full-body pose | 🔬 No keypoint weights shipped yet — pose pipeline runs but without a learned head |
@ -1824,7 +1824,7 @@ huggingface-cli download ruvnet/wifi-densepose-pretrained --local-dir models/pre
 #   model.safetensors    — 48 KB contrastive encoder
 #   model-q4.bin         — 8 KB quantized (recommended)
 #   model-q2.bin         — 4 KB ultra-compact (ESP32 edge)
-#   presence-head.json   — presence detection head (100% accuracy)
+#   presence-head.json   — presence detection head (v2 encoder: 82.3% held-out triplet acc)
 #   node-1.json          — LoRA adapter for room 1
 #   node-2.json          — LoRA adapter for room 2
 ```
@ -1833,7 +1833,7 @@ huggingface-cli download ruvnet/wifi-densepose-pretrained --local-dir models/pre

 The pre-trained encoder converts 8-dim CSI feature vectors into 128-dim embeddings. These embeddings power all 17 sensing applications:

- **Presence detection** — 100% accuracy, never misses, never false alarms
+- **Presence detection** — v2 encoder: 82.3% held-out temporal-triplet accuracy (v1's "100%" was a single-class recording — retracted, [#882](https://github.com/ruvnet/RuView/issues/882))
 - **Environment fingerprinting** — kNN search finds "states like this one"
 - **Anomaly detection** — embeddings that don't match known clusters = anomaly
 - **Activity classification** — different activities cluster in embedding space
--- a/firmware/esp32-csi-node/release_bins/bootloader.bin
+++ b/firmware/esp32-csi-node/release_bins/bootloader.bin
--- a/firmware/esp32-csi-node/release_bins/c6-adr110/SHA256SUMS.txt
+++ b/firmware/esp32-csi-node/release_bins/c6-adr110/SHA256SUMS.txt
@ -1,4 +1,4 @@
-889715e9d698ad78f9978ad8b93b6af24a726b0494247201c8f0d920d9fc80ca *firmware/esp32-csi-node/release_bins/c6-adr110/bootloader.bin
-d8539e47c6f10a3344679118619e3fe01cfd66eb560ea8883268ca7c9a12efa4 *firmware/esp32-csi-node/release_bins/c6-adr110/esp32-csi-node.bin
+b0fb1f217a39c80bc95b5eb8208a0b8572ae64efa0f6d580b76caff4affe0f4d *firmware/esp32-csi-node/release_bins/c6-adr110/bootloader.bin
+4764c5b20a353895f70122816adc98f861ec20e9a8ea9b344dc0648b6341073c *firmware/esp32-csi-node/release_bins/c6-adr110/esp32-csi-node.bin
 7d2c7ac4888bfd75cd5f56e8d61f69595121183afc81556c876732fd3782c62f *firmware/esp32-csi-node/release_bins/c6-adr110/ota_data_initial.bin
 4c2cc4ffd52641e23b779bd57b3908014083ac3c1aab395756478c89e70d81f0 *firmware/esp32-csi-node/release_bins/c6-adr110/partition-table.bin
--- a/firmware/esp32-csi-node/release_bins/c6-adr110/bootloader.bin
+++ b/firmware/esp32-csi-node/release_bins/c6-adr110/bootloader.bin
--- a/firmware/esp32-csi-node/release_bins/c6-adr110/esp32-csi-node.bin
+++ b/firmware/esp32-csi-node/release_bins/c6-adr110/esp32-csi-node.bin
--- a/firmware/esp32-csi-node/release_bins/esp32-csi-node-4mb.bin
+++ b/firmware/esp32-csi-node/release_bins/esp32-csi-node-4mb.bin
--- a/firmware/esp32-csi-node/release_bins/esp32-csi-node.bin
+++ b/firmware/esp32-csi-node/release_bins/esp32-csi-node.bin
--- a/firmware/esp32-csi-node/release_bins/partition-table-4mb.bin
+++ b/firmware/esp32-csi-node/release_bins/partition-table-4mb.bin
--- a/firmware/esp32-csi-node/release_bins/s3-adr110/SHA256SUMS.txt
+++ b/firmware/esp32-csi-node/release_bins/s3-adr110/SHA256SUMS.txt
@ -1,3 +1,3 @@
-3c4905dd202ccabf4230cbabcc9320f250a60b1a7254eff7424780201bcb2072 *firmware/esp32-csi-node/release_bins/s3-adr110/bootloader.bin
-7a8bf9582c9031fed32f1ada44f5c41dd99bd07fadff8e5c86e07aa0f343e847 *firmware/esp32-csi-node/release_bins/s3-adr110/esp32-csi-node.bin
+b973d7eda65affb746adcfa63ceb18f779f206d240b76f01b8c9ae7485455660 *firmware/esp32-csi-node/release_bins/s3-adr110/bootloader.bin
+e21ef94aba779d534dc048c1b9da731c81e5dbe09d0645cfd70a05ad3642d3e9 *firmware/esp32-csi-node/release_bins/s3-adr110/esp32-csi-node.bin
 67222c257c0477501fd4002275638dc4262b34eb68235b8289fb1337054d322b *firmware/esp32-csi-node/release_bins/s3-adr110/partition-table.bin
--- a/firmware/esp32-csi-node/release_bins/s3-adr110/bootloader.bin
+++ b/firmware/esp32-csi-node/release_bins/s3-adr110/bootloader.bin
--- a/firmware/esp32-csi-node/release_bins/s3-adr110/esp32-csi-node.bin
+++ b/firmware/esp32-csi-node/release_bins/s3-adr110/esp32-csi-node.bin
--- a/firmware/esp32-csi-node/release_bins/version.txt
+++ b/firmware/esp32-csi-node/release_bins/version.txt
@ -1,3 +1,4 @@
-0.6.6
-git-sha: cbcb389cb (pre-commit)
-built: 2026-05-21
+0.6.7
+git-sha: 8703ade9b
+built: 2026-06-02
+note: RuView#893 — display-less boards capture DATA frames (CSI yield 0pps fix); hardware-verified on ESP32-C6 (0->27 pps)
--- a/requirements.txt
+++ b/requirements.txt
@ -36,3 +36,4 @@ scikit-learn>=1.2.0

 # Monitoring dependencies
 prometheus-client>=0.16.0
+psutil>=5.9.0  # system metrics — imported by health.py / metrics.py / status.py / monitoring.py
--- a/v2/crates/wifi-densepose-desktop/ui/package-lock.json
+++ b/v2/crates/wifi-densepose-desktop/ui/package-lock.json
@ -17,293 +17,11 @@
      "devDependencies": {
        "@types/react": "^18.3.0",
        "@types/react-dom": "^19.2.3",
-        "@vitejs/plugin-react": "^4.3.0",
+        "@vitejs/plugin-react": "^6.0.2",
        "typescript": "^6.0.3",
        "vite": "^6.0.0"
      }
    },
-    "node_modules/@babel/code-frame": {
-      "version": "7.29.0",
-      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
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-      "dev": true,
-      "license": "MIT",
-      "dependencies": {
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-        "js-tokens": "^4.0.0",
-        "picocolors": "^1.1.1"
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-      "integrity": "sha512-/sM3dO2FOzXjKQhJuo0Q173wf2KOo8t4I8vHy6lF9poUp7bKT0/NHE8fPX23PwfhnykfqnC2xRxOnVw5XuGIaA==",
-      "dev": true,
-      "license": "MIT",
-      "bin": {
-        "jsesc": "bin/jsesc"
-      },
-      "engines": {
-        "node": ">=6"
-      }
-    },
-    "node_modules/json5": {
-      "version": "2.2.3",
-      "resolved": "https://registry.npmjs.org/json5/-/json5-2.2.3.tgz",
-      "integrity": "sha512-XmOWe7eyHYH14cLdVPoyg+GOH3rYX++KpzrylJwSW98t3Nk+U8XOl8FWKOgwtzdb8lXGf6zYwDUzeHMWfxasyg==",
-      "dev": true,
-      "license": "MIT",
-      "bin": {
-        "json5": "lib/cli.js"
-      },
-      "engines": {
-        "node": ">=6"
-      }
-    },
    "node_modules/loose-envify": {
      "version": "1.4.0",
      "resolved": "https://registry.npmjs.org/loose-envify/-/loose-envify-1.4.0.tgz",
@ -1528,23 +1010,6 @@
        "loose-envify": "cli.js"
      }
    },
-    "node_modules/lru-cache": {
-      "version": "5.1.1",
-      "resolved": "https://registry.npmjs.org/lru-cache/-/lru-cache-5.1.1.tgz",
-      "integrity": "sha512-KpNARQA3Iwv+jTA0utUVVbrh+Jlrr1Fv0e56GGzAFOXN7dk/FviaDW8LHmK52DlcH4WP2n6gI8vN1aesBFgo9w==",
-      "dev": true,
-      "license": "ISC",
-      "dependencies": {
-        "yallist": "^3.0.2"
-      }
-    },
-    "node_modules/ms": {
-      "version": "2.1.3",
-      "resolved": "https://registry.npmjs.org/ms/-/ms-2.1.3.tgz",
-      "integrity": "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA==",
-      "dev": true,
-      "license": "MIT"
-    },
    "node_modules/nanoid": {
      "version": "3.3.11",
      "resolved": "https://registry.npmjs.org/nanoid/-/nanoid-3.3.11.tgz",
@ -1564,13 +1029,6 @@
        "node": "^10 || ^12 || ^13.7 || ^14 || >=15.0.1"
      }
    },
-    "node_modules/node-releases": {
-      "version": "2.0.36",
-      "resolved": "https://registry.npmjs.org/node-releases/-/node-releases-2.0.36.tgz",
-      "integrity": "sha512-TdC8FSgHz8Mwtw9g5L4gR/Sh9XhSP/0DEkQxfEFXOpiul5IiHgHan2VhYYb6agDSfp4KuvltmGApc8HMgUrIkA==",
-      "dev": true,
-      "license": "MIT"
-    },
    "node_modules/picocolors": {
      "version": "1.1.1",
      "resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.1.tgz",
@ -1644,16 +1102,6 @@
        "react": "^19.2.5"
      }
    },
-    "node_modules/react-refresh": {
-      "version": "0.17.0",
-      "resolved": "https://registry.npmjs.org/react-refresh/-/react-refresh-0.17.0.tgz",
-      "integrity": "sha512-z6F7K9bV85EfseRCp2bzrpyQ0Gkw1uLoCel9XBVWPg/TjRj94SkJzUTGfOa4bs7iJvBWtQG0Wq7wnI0syw3EBQ==",
-      "dev": true,
-      "license": "MIT",
-      "engines": {
-        "node": ">=0.10.0"
-      }
-    },
    "node_modules/rollup": {
      "version": "4.59.0",
      "resolved": "https://registry.npmjs.org/rollup/-/rollup-4.59.0.tgz",
@ -1705,16 +1153,6 @@
      "integrity": "sha512-eNv+WrVbKu1f3vbYJT/xtiF5syA5HPIMtf9IgY/nKg0sWqzAUEvqY/xm7OcZc/qafLx/iO9FgOmeSAp4v5ti/Q==",
      "license": "MIT"
    },
-    "node_modules/semver": {
-      "version": "6.3.1",
-      "resolved": "https://registry.npmjs.org/semver/-/semver-6.3.1.tgz",
-      "integrity": "sha512-BR7VvDCVHO+q2xBEWskxS6DJE1qRnb7DxzUrogb71CWoSficBxYsiAGd+Kl0mmq/MprG9yArRkyrQxTO6XjMzA==",
-      "dev": true,
-      "license": "ISC",
-      "bin": {
-        "semver": "bin/semver.js"
-      }
-    },
    "node_modules/source-map-js": {
      "version": "1.2.1",
      "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.1.tgz",
@ -1756,37 +1194,6 @@
        "node": ">=14.17"
      }
    },
-    "node_modules/update-browserslist-db": {
-      "version": "1.2.3",
-      "resolved": "https://registry.npmjs.org/update-browserslist-db/-/update-browserslist-db-1.2.3.tgz",
-      "integrity": "sha512-Js0m9cx+qOgDxo0eMiFGEueWztz+d4+M3rGlmKPT+T4IS/jP4ylw3Nwpu6cpTTP8R1MAC1kF4VbdLt3ARf209w==",
-      "dev": true,
-      "funding": [
-        {
-          "type": "opencollective",
-          "url": "https://opencollective.com/browserslist"
-        },
-        {
-          "type": "tidelift",
-          "url": "https://tidelift.com/funding/github/npm/browserslist"
-        },
-        {
-          "type": "github",
-          "url": "https://github.com/sponsors/ai"
-        }
-      ],
-      "license": "MIT",
-      "dependencies": {
-        "escalade": "^3.2.0",
-        "picocolors": "^1.1.1"
-      },
-      "bin": {
-        "update-browserslist-db": "cli.js"
-      },
-      "peerDependencies": {
-        "browserslist": ">= 4.21.0"
-      }
-    },
    "node_modules/vite": {
      "version": "6.4.1",
      "resolved": "https://registry.npmjs.org/vite/-/vite-6.4.1.tgz",
@ -1861,13 +1268,6 @@
          "optional": true
        }
      }
-    },
-    "node_modules/yallist": {
-      "version": "3.1.1",
-      "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz",
-      "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==",
-      "dev": true,
-      "license": "ISC"
    }
  }
 }
--- a/v2/crates/wifi-densepose-desktop/ui/package.json
+++ b/v2/crates/wifi-densepose-desktop/ui/package.json
@ -18,7 +18,7 @@
  "devDependencies": {
    "@types/react": "^18.3.0",
    "@types/react-dom": "^19.2.3",
-    "@vitejs/plugin-react": "^4.3.0",
+    "@vitejs/plugin-react": "^6.0.2",
    "typescript": "^6.0.3",
    "vite": "^6.0.0"
  }
--- a/v2/crates/wifi-densepose-sensing-server/src/main.rs
+++ b/v2/crates/wifi-densepose-sensing-server/src/main.rs
@ -5476,6 +5476,149 @@ async fn broadcast_tick_task(state: SharedState, tick_ms: u64) {
    }
 }

+/// Map one sensing-broadcast JSON document into the `VitalsSnapshot`(s) to
+/// publish over MQTT (issues #872/#898).
+///
+/// Multi-node sources carry a `nodes` array where **each node has its own
+/// `classification`** (`motion_level`, `presence`, `confidence`) and RSSI — so
+/// each node must surface its *own* presence/motion, not the room-level
+/// aggregate. Previously the bridge applied the aggregate `classification` to
+/// every per-node Home-Assistant device, so a node in an empty corner inherited
+/// another node's "present" (and `motion_level: "absent"` was mis-mapped to full
+/// motion). Vitals (breathing / heart rate) and the person count are room-level
+/// and shared across the per-node devices. Falls back to a single aggregate
+/// snapshot when there is no per-node data (e.g. wifi / simulate sources).
+#[cfg(feature = "mqtt")]
+fn vitals_snapshots_from_sensing_json(
+    v: &serde_json::Value,
+    base_id: &str,
+) -> Vec<wifi_densepose_sensing_server::mqtt::state::VitalsSnapshot> {
+    use wifi_densepose_sensing_server::mqtt::state::VitalsSnapshot;
+
+    // motion_level string -> motion scalar. "absent"/"none"/"still"/"idle"/""
+    // are non-moving; anything else (walking, …) is motion. `fallback` is used
+    // when the field is absent so a partial per-node payload defers to the
+    // room aggregate rather than silently reading 0.
+    fn motion_of(level: Option<&str>, fallback: f64) -> f64 {
+        match level {
+            Some("none") | Some("still") | Some("idle") | Some("absent") | Some("") => 0.0,
+            Some(_) => 1.0,
+            None => fallback,
+        }
+    }
+
+    let ts = (v["timestamp"].as_f64().unwrap_or(0.0) * 1000.0) as i64;
+    let vit = &v["vital_signs"];
+    let breathing = vit["breathing_rate_bpm"].as_f64();
+    let hr = vit["heart_rate_bpm"].as_f64();
+    let n_persons = v["persons"]
+        .as_array()
+        .map(|a| a.len() as u32)
+        .or_else(|| v["estimated_persons"].as_u64().map(|x| x as u32))
+        .unwrap_or(0);
+
+    // Room-level aggregate: the no-nodes fallback, and the per-node default for
+    // any field a node omits.
+    let acls = &v["classification"];
+    let agg_presence = acls["presence"].as_bool().unwrap_or(false);
+    let agg_motion = motion_of(acls["motion_level"].as_str(), 0.0);
+    let agg_conf = acls["confidence"].as_f64().unwrap_or(0.0);
+
+    let mk = |node_id: String, presence: bool, motion: f64, conf: f64, rssi: Option<f64>| {
+        VitalsSnapshot {
+            node_id,
+            timestamp_ms: ts,
+            presence,
+            motion,
+            presence_score: if presence { conf.max(0.0) } else { 0.0 },
+            breathing_rate_bpm: breathing,
+            heartrate_bpm: hr,
+            n_persons,
+            rssi_dbm: rssi,
+            vital_confidence: conf,
+            ..Default::default()
+        }
+    };
+
+    match v["nodes"].as_array() {
+        Some(arr) if !arr.is_empty() => arr
+            .iter()
+            .map(|node| {
+                let n = node["node_id"].as_u64().unwrap_or(0);
+                // Each node carries its OWN classification — use it, deferring to
+                // the room aggregate only for fields the node omits.
+                let ncls = &node["classification"];
+                let presence = ncls["presence"].as_bool().unwrap_or(agg_presence);
+                let motion = motion_of(ncls["motion_level"].as_str(), agg_motion);
+                let conf = ncls["confidence"].as_f64().unwrap_or(agg_conf);
+                mk(
+                    format!("{base_id}-node{n}"),
+                    presence,
+                    motion,
+                    conf,
+                    node["rssi_dbm"].as_f64(),
+                )
+            })
+            .collect(),
+        _ => vec![mk(
+            base_id.to_string(),
+            agg_presence,
+            agg_motion,
+            agg_conf,
+            v["nodes"][0]["rssi_dbm"].as_f64(),
+        )],
+    }
+}
+
+/// Turn a `ProgressiveLoader::new` failure into an actionable diagnostic (#894).
+///
+/// The published HuggingFace `ruvnet/wifi-densepose-pretrained` files
+/// (`model.safetensors`, `model-q{2,4,8}.bin`, `model.rvf.jsonl`) are a
+/// different *format* — and a different encoder architecture — than the RVF
+/// binary container the `--model` progressive loader expects (`RVFS` magic
+/// `0x52564653`). Feeding one to `--model` produced a bare
+/// "invalid magic at offset 0 …" that left users stuck. Detect the common
+/// cases and explain plainly what's loadable instead.
+fn diagnose_model_load_error(path: &std::path::Path, data: &[u8], err: &str) -> String {
+    let name = path
+        .file_name()
+        .and_then(|n| n.to_str())
+        .unwrap_or("")
+        .to_ascii_lowercase();
+    let ext = path
+        .extension()
+        .and_then(|e| e.to_str())
+        .unwrap_or("")
+        .to_ascii_lowercase();
+
+    // safetensors: 8-byte LE header length, then a JSON object starting with '{'.
+    let looks_safetensors = ext == "safetensors" || (data.len() > 9 && data[8] == b'{');
+    // JSONL manifest: starts with '{' (or the well-known suffix).
+    let looks_jsonl =
+        ext == "jsonl" || name.ends_with(".rvf.jsonl") || data.first() == Some(&b'{');
+    // Quantized weight blob shipped on HF (model-q2/q4/q8.bin).
+    let looks_quant_bin = ext == "bin" || name.contains("-q");
+
+    let kind = if looks_safetensors {
+        "a safetensors weight file"
+    } else if looks_jsonl {
+        "a JSONL manifest, not the binary container"
+    } else if looks_quant_bin {
+        "a quantized weight blob (e.g. HuggingFace model-q4.bin)"
+    } else {
+        "not an RVF binary container"
+    };
+
+    format!(
+        "model `{}` could not be loaded: it is {kind}. The --model flag expects an \
+         RVF binary container (`RVFS` magic 0x52564653) produced by the \
+         wifi-densepose-train pipeline. The HuggingFace ruvnet/wifi-densepose-pretrained \
+         files are a different format and encoder architecture, so they do not load \
+         here directly (issue #894). Continuing with signal heuristics. (loader: {err})",
+        path.display()
+    )
+}
+
 // ── Main ─────────────────────────────────────────────────────────────────────

 /// If `--ui-path` points nowhere (wrong cwd), try common repo layouts relative to cwd.
@ -6113,7 +6256,9 @@ async fn main() {
                        model_loaded = true;
                        progressive_loader = Some(loader);
                    }
-                    Err(e) => error!("Progressive loader init failed: {e}"),
+                    Err(e) => {
+                        error!("{}", diagnose_model_load_error(mp, &data, &e.to_string()))
+                    }
                },
                Err(e) => error!("Failed to read model file: {e}"),
            }
@ -6200,56 +6345,13 @@ async fn main() {
                            let Ok(v) = serde_json::from_str::<serde_json::Value>(&json) else {
                                continue;
                            };
-                            let cls = &v["classification"];
-                            let vit = &v["vital_signs"];
-                            let presence = cls["presence"].as_bool().unwrap_or(false);
-                            let n_persons = v["persons"]
-                                .as_array()
-                                .map(|a| a.len() as u32)
-                                .or_else(|| v["estimated_persons"].as_u64().map(|x| x as u32))
-                                .unwrap_or(0);
-                            let motion = match cls["motion_level"].as_str() {
-                                Some("none") | Some("still") | Some("idle") | Some("") => 0.0,
-                                Some(_) => 1.0,
-                                None => 0.0,
-                            };
-                            let ts = (v["timestamp"].as_f64().unwrap_or(0.0) * 1000.0) as i64;
-                            let conf = cls["confidence"].as_f64().unwrap_or(0.0);
-                            let presence_score = if presence { conf.max(0.0) } else { 0.0 };
-                            let breathing = vit["breathing_rate_bpm"].as_f64();
-                            let hr = vit["heart_rate_bpm"].as_f64();
-                            // #898: emit one snapshot per physical node so each
-                            // surfaces as its own Home-Assistant device (with
-                            // its own RSSI + availability). Falls back to a
-                            // single aggregate snapshot when there is no
-                            // per-node data (e.g. wifi / simulate sources).
-                            let mk = |nid: String, rssi: Option<f64>| mqtt::state::VitalsSnapshot {
-                                node_id: nid,
-                                timestamp_ms: ts,
-                                presence,
-                                motion,
-                                presence_score,
-                                breathing_rate_bpm: breathing,
-                                heartrate_bpm: hr,
-                                n_persons,
-                                rssi_dbm: rssi,
-                                vital_confidence: conf,
-                                ..Default::default()
-                            };
-                            match v["nodes"].as_array() {
-                                Some(arr) if !arr.is_empty() => {
-                                    for node in arr {
-                                        let n = node["node_id"].as_u64().unwrap_or(0);
-                                        let nid = format!("{node_id}-node{n}");
-                                        let _ = vtx.send(mk(nid, node["rssi_dbm"].as_f64()));
-                                    }
-                                }
-                                _ => {
-                                    let _ = vtx.send(mk(
-                                        node_id.clone(),
-                                        v["nodes"][0]["rssi_dbm"].as_f64(),
-                                    ));
-                                }
+                            // #898/#872: emit one snapshot per physical node so
+                            // each surfaces as its own Home-Assistant device with
+                            // its *own* presence/motion/RSSI (see
+                            // vitals_snapshots_from_sensing_json). Falls back to a
+                            // single aggregate snapshot for per-node-less sources.
+                            for snap in vitals_snapshots_from_sensing_json(&v, &node_id) {
+                                let _ = vtx.send(snap);
                            }
                        }
                    });
@ -7068,3 +7170,143 @@ mod rolling_p95_tests {
        assert_eq!(p.len(), 1);
    }
 }
+
+#[cfg(all(test, feature = "mqtt"))]
+mod mqtt_bridge_tests {
+    use super::vitals_snapshots_from_sensing_json;
+    use serde_json::json;
+
+    /// Regression for the per-node presence bug (#872/#898): each node must
+    /// surface its OWN classification, not the room-level aggregate. Node 1 is
+    /// present+moving; node 2 is absent — node 2 must NOT inherit node 1's
+    /// "present".
+    #[test]
+    fn per_node_presence_uses_each_nodes_own_classification() {
+        let v = json!({
+            "timestamp": 1.0,
+            "classification": { "presence": true, "motion_level": "walking", "confidence": 0.9 },
+            "vital_signs": { "breathing_rate_bpm": 14.0, "heart_rate_bpm": 60.0 },
+            "persons": [{}, {}],
+            "nodes": [
+                { "node_id": 1, "rssi_dbm": -40.0,
+                  "classification": { "presence": true, "motion_level": "walking", "confidence": 0.8 } },
+                { "node_id": 2, "rssi_dbm": -70.0,
+                  "classification": { "presence": false, "motion_level": "absent", "confidence": 0.1 } }
+            ]
+        });
+        let snaps = vitals_snapshots_from_sensing_json(&v, "ruview");
+        assert_eq!(snaps.len(), 2, "one snapshot per node");
+
+        let n1 = snaps.iter().find(|s| s.node_id == "ruview-node1").unwrap();
+        let n2 = snaps.iter().find(|s| s.node_id == "ruview-node2").unwrap();
+
+        assert!(n1.presence && n1.motion > 0.0, "node1 present + moving");
+        assert!(
+            !n2.presence && n2.motion == 0.0,
+            "node2 must be absent — not inherit the room aggregate"
+        );
+        // Per-node RSSI preserved.
+        assert_eq!(n1.rssi_dbm, Some(-40.0));
+        assert_eq!(n2.rssi_dbm, Some(-70.0));
+        // Vitals + person count are room-level, shared across node devices.
+        assert_eq!(n1.n_persons, 2);
+        assert_eq!(n2.n_persons, 2);
+        assert_eq!(n1.breathing_rate_bpm, Some(14.0));
+        assert_eq!(n2.heartrate_bpm, Some(60.0));
+        // presence_score is gated on presence.
+        assert!(n1.presence_score > 0.0);
+        assert_eq!(n2.presence_score, 0.0);
+    }
+
+    /// A node that omits a classification field defers to the room aggregate
+    /// rather than silently reading false/0.
+    #[test]
+    fn per_node_missing_fields_fall_back_to_aggregate() {
+        let v = json!({
+            "timestamp": 1.0,
+            "classification": { "presence": true, "motion_level": "still", "confidence": 0.7 },
+            "vital_signs": {},
+            "nodes": [ { "node_id": 3, "rssi_dbm": -55.0 } ]  // no per-node classification
+        });
+        let snaps = vitals_snapshots_from_sensing_json(&v, "n");
+        assert_eq!(snaps.len(), 1);
+        assert_eq!(snaps[0].node_id, "n-node3");
+        assert!(snaps[0].presence, "defers to aggregate presence");
+        assert_eq!(snaps[0].motion, 0.0, "aggregate 'still' => no motion");
+    }
+
+    /// No `nodes` array (wifi / simulate sources): single aggregate snapshot
+    /// keyed by the base id.
+    #[test]
+    fn falls_back_to_single_aggregate_when_no_nodes() {
+        let v = json!({
+            "timestamp": 2.0,
+            "classification": { "presence": true, "motion_level": "idle", "confidence": 0.6 },
+            "vital_signs": { "breathing_rate_bpm": 12.0 },
+            "persons": [{}]
+        });
+        let snaps = vitals_snapshots_from_sensing_json(&v, "ruview");
+        assert_eq!(snaps.len(), 1);
+        assert_eq!(snaps[0].node_id, "ruview");
+        assert!(snaps[0].presence);
+        assert_eq!(snaps[0].motion, 0.0, "idle => no motion");
+        assert_eq!(snaps[0].n_persons, 1);
+    }
+
+    /// `motion_level: "absent"` must map to zero motion (the old aggregate
+    /// match fell through to `Some(_) => 1.0`, treating absent as full motion).
+    #[test]
+    fn absent_motion_level_is_zero_motion() {
+        let v = json!({
+            "timestamp": 0.0,
+            "classification": { "presence": false, "motion_level": "absent", "confidence": 0.0 },
+            "vital_signs": {}
+        });
+        let snaps = vitals_snapshots_from_sensing_json(&v, "x");
+        assert_eq!(snaps[0].motion, 0.0);
+        assert!(!snaps[0].presence);
+    }
+}
+
+#[cfg(test)]
+mod model_load_diagnostic_tests {
+    use super::diagnose_model_load_error;
+    use std::path::Path;
+
+    #[test]
+    fn safetensors_is_named_and_points_at_894() {
+        // 8-byte LE header length then '{' — the safetensors signature.
+        let data = [0x10, 0, 0, 0, 0, 0, 0, 0, b'{', b'"'];
+        let msg = diagnose_model_load_error(
+            Path::new("models/wifi-densepose-pretrained/model.safetensors"),
+            &data,
+            "invalid magic at offset 0",
+        );
+        assert!(msg.contains("safetensors"), "{msg}");
+        assert!(msg.contains("#894"), "{msg}");
+        assert!(msg.contains("signal heuristics"), "{msg}");
+    }
+
+    #[test]
+    fn quantized_bin_is_identified() {
+        let data = [0x35, 0x57, 0x45, 0x77]; // the 0x77455735 the loader reports
+        let msg = diagnose_model_load_error(Path::new("model-q4.bin"), &data, "bad magic");
+        assert!(msg.contains("quantized weight blob"), "{msg}");
+        assert!(msg.contains("RVFS") || msg.contains("0x52564653"), "{msg}");
+    }
+
+    #[test]
+    fn jsonl_manifest_is_identified() {
+        let data = *b"{\"seg\":0}";
+        let msg = diagnose_model_load_error(Path::new("model.rvf.jsonl"), &data, "x");
+        assert!(msg.contains("JSONL manifest"), "{msg}");
+    }
+
+    #[test]
+    fn unknown_format_still_gives_guidance() {
+        let data = [0u8, 1, 2, 3];
+        let msg = diagnose_model_load_error(Path::new("weird.dat"), &data, "x");
+        assert!(msg.contains("RVF binary container"), "{msg}");
+        assert!(msg.contains("wifi-densepose-train"), "{msg}");
+    }
+}
Author	SHA1	Message	Date
dependabot[bot]	e633374a2f	Merge `1d41e81ac6` into `f5d0e1e69e`	2026-06-03 00:39:45 -06:00
rUv	f5d0e1e69e	fix(#894 ): actionable diagnostic when --model gets a non-RVF file (#919 ) Users who downloaded ruvnet/wifi-densepose-pretrained and passed model.safetensors / model-q4.bin / model.rvf.jsonl to --model hit a bare "Progressive loader init failed: invalid magic at offset 0: expected 0x52564653, got 0x77455735" and were stuck — the server then silently fell back to signal heuristics (which over-count, feeding "is it fake" reports). The HF files are a different format and encoder architecture than the RVF binary container the progressive loader expects, so they can't load directly. Now the load-failure path detects the common cases (safetensors header, JSONL manifest, quantized .bin blob) and emits a plain explanation naming the format, what --model actually expects (RVF `RVFS` container from wifi-densepose-train), and that it's continuing with heuristics — with a pointer to #894. Pure, testable `diagnose_model_load_error()` + 4 unit tests (run under the default `--no-default-features` CI). Full crate unit suite: 429 + 114 passed, 0 failed.	2026-06-02 20:05:30 +02:00
rUv	b12662a54d	fix(mqtt): per-node HA devices use each node's own presence/motion (#872 ) (#918 ) The MQTT bridge fanned out one Home-Assistant device per node (#898) but applied the room-level aggregate classification to every node — so in a multi-node setup a node in an empty corner inherited another node's "present", and `motion_level: "absent"` was mis-mapped to full motion (the aggregate match fell through `Some(_) => 1.0`). Each node in the sensing broadcast's `nodes` array already carries its own `classification` (`motion_level`/`presence`/`confidence`, see PerNodeFeatureInfo) and RSSI. Now each per-node snapshot reads that node's own classification, deferring to the room aggregate only for fields a node omits. Vitals (breathing/heart rate) and person count stay room-level. Extracted the JSON→VitalsSnapshot mapping into a pure, testable function (`vitals_snapshots_from_sensing_json`) and added 4 unit tests covering per-node divergence, partial-field fallback, the no-nodes aggregate path, and the absent→zero-motion fix. Supersedes #899, which targeted the right bug but read non-existent fields (`node["motion_level"]` / `node["status"]` instead of the nested `node["classification"]` + `stale`). Verified: builds with `--features mqtt`; new tests pass; full crate unit suite 432 + 114 passed, 0 failed.	2026-06-02 19:26:01 +02:00
rUv	573b00fd98	perf(ci): drop dead uvicorn start from perf job (#917 ) Since #915 the perf job gates only on test_frame_budget.py, which drives the CSIProcessor pipeline in-process and makes no HTTP calls. The "Start application" step (uvicorn + `sleep 10`) was therefore dead weight: it existed only for the now-excluded api_throughput/inference_speed tests, wasted ~10-15 s per main-push run, and dumped ~50 misleading "router requires hardware setup" ERROR lines into every CI log for a server no test touched. MOCK_POSE_DATA is server-only, unused here. Removed the step and the vestigial env. The gated test is unchanged and passes (verified locally, 3/3).	2026-06-02 19:01:08 +02:00
rUv	91b0e625bd	docs(#882 ): complete the "100% presence" retraction across all docs (#916 ) The v1 "100% presence accuracy" headline was already retracted in the README / user-guide intro / proof-of-capabilities — but 6 secondary spots still flatly claimed "100% accuracy, never false alarms", which made proof-of-capabilities.md's "replaced everywhere" assertion untrue. Completed the retraction in-place with the honest label-free metric (82.3% held-out temporal-triplet; v1 was a single-class recording where a constant "yes" scores ~99.98%): - docs/readme-details.md — 2 benchmark tables + the pre-trained-model row - docs/user-guide.md — capability table, model-file comment, applications list - CHANGELOG.md — annotated the historical entry in-place (kept as public record per built-in-public ethos, not rewritten) Verified: no remaining flat "100% presence/accuracy" claim lacks a retraction marker; proof-of-capabilities.md "replaced everywhere" is now accurate.	2026-06-02 18:50:39 +02:00
rUv	88b835dd89	fix(ci): perf job gates on the real frame-budget guard, not TDD stubs (#915 ) After #914 fixed collection, the perf job actually ran the suite and exposed that test_api_throughput.py / test_inference_speed.py are TDD red-phase stubs (every test suffixed `_should_fail_initially`) that time a mock that sleeps — not a real perf signal. They carry machine- dependent wall-clock asserts (actual_rps >= 40, batch_time < individual_time) that are inherently flaky on shared CI runners, plus a cross-class fixture-scope bug (`fixture 'standard_model' not found`). Result: 3 failed, 10 errored — by design, not a regression. Forcing those green would manufacture a false signal. Instead, gate only on test_frame_budget.py, which times the real CSIProcessor pipeline against the ADR 50 ms per-frame budget (single-frame, p95/100-frames, +Doppler) — a genuine regression guard. Verified locally: 3 passed. The stub files remain in-repo for local TDD; they re-enter CI when their features are implemented and the mock-timing asserts are made deterministic.	2026-06-02 18:31:55 +02:00
rUv	f8f08076eb	fix(ci): perf tests — use `python -m pytest` so `src` import resolves (#914 ) The Performance Tests job collected 26 items then aborted with `ModuleNotFoundError: No module named 'src'` on test_frame_budget.py, which does `from src.core.csi_processor import CSIProcessor`. The bare `pytest` console script does not put the cwd (archive/v1) on sys.path; `python -m pytest` does. pytest aborts the whole session on a collection error, so this one import masked the entire (otherwise mock-based, self-contained) perf suite. Verified locally: bare-script path reproduces the exact error; `-m` resolves it and test_frame_budget.py passes 3/3. The other two files (test_api_throughput.py mock server, test_inference_speed.py MockPoseModel +psutil) are fully self-contained — no test hits the running server. Closes the last red job in the v1-API CI chain (#910/#911/#913).	2026-06-02 18:12:00 +02:00
rUv	55f6a74e1e	Merge pull request #913 from ruvnet/fix/ci-v1-api-perms-locust ci(v1-api): fix gh-pages 403 + run real pytest perf suite	2026-06-02 17:36:43 +02:00
ruv	b5a91c5635	ci(v1-api): install pytest, drop root --cov addopts for perf suite, ascii comment	2026-06-02 17:29:04 +02:00
ruv	308d2fc89d	ci(v1-api): fix gh-pages 403 + run real perf suite — green main CI Two more latent v1-API CI bugs surfaced once #910/#911 let the jobs reach their later steps: - API Documentation: openapi generation now succeeds (psutil fix), but the gh-pages deploy failed with HTTP 403 — the job had no `permissions` block and GITHUB_TOKEN is read-only by default. Add `permissions: contents: write`, and make the deploy `continue-on-error` (the openapi generation is the real validation; Pages may be disabled). - Performance Tests: ran `locust -f tests/performance/locustfile.py`, but there is no locustfile — the suite is pytest (test_api_throughput.py, test_frame_budget.py, test_inference_speed.py). Run pytest instead, with working-directory: archive/v1 and MOCK_POSE_DATA=true. ci.yml validated as well-formed YAML.	2026-06-02 17:26:39 +02:00
rUv	5038e3c8e1	Merge pull request #911 from ruvnet/fix/ci-v1-api-mock-mode ci(v1-api): MOCK_POSE_DATA + declare psutil — green Performance Tests & API Docs	2026-06-02 06:20:21 -04:00
ruv	e239af3636	fix(deps): declare psutil in requirements.txt — green API Documentation CI The API Documentation job (and any env without locust) failed with `ModuleNotFoundError: No module named 'psutil'` when importing the app: psutil is imported by src/api/routers/health.py, services/metrics.py, commands/status.py, and tasks/monitoring.py, but was never declared as a dependency — it only happened to be present where locust (Performance Tests) pulled it in transitively. Declare it explicitly (psutil>=5.9.0). Verified locally: `from src.api.main import app; app.openapi()` (the exact docs-job operation) now succeeds.	2026-06-02 12:11:55 +02:00
ruv	4856afbd0c	ci(v1-api): run Performance Tests + API Docs with MOCK_POSE_DATA=true After the DensePoseHead startup fix (#910), the v1 API starts, but the Performance Tests load-hit the pose endpoints which error "requires real CSI data" (no hardware in CI, mock_pose_data defaults False), and the API-docs job imports the app the same way. Set MOCK_POSE_DATA=true on both jobs so they exercise the mock path. Verified: the env var maps to settings.mock_pose_data=True (pydantic, no env_prefix). (Note: Performance Tests is continue-on-error so this is cleanup, not a run-blocker; the run-level red on main has been transient Docker Hub pull timeouts on Tests/docker-build, which are infra flakes that pass on re-run.)	2026-06-02 12:04:58 +02:00
rUv	4d205a05c4	Merge pull request #910 from ruvnet/fix/v1-pose-service-densepose-config fix(v1-api): pass required config to DensePoseHead — green main CI	2026-06-02 05:50:25 -04:00
ruv	bc42ae7903	fix(v1-api): pass required config to DensePoseHead — green main CI The "Continuous Integration" workflow (Performance Tests + API Documentation jobs) has failed on every main commit since the API start path was exercised: pose_service._initialize_models() called `DensePoseHead()` with no args, but DensePoseHead.__init__ requires a config dict → "TypeError: DensePoseHead.__init__() missing 1 required positional argument: 'config'" → uvicorn "Application startup failed". Pass a config: input_channels=256 (matches the modality translator's output), num_body_parts=24 (DensePose standard), num_uv_coordinates=2. Both call sites (with/without pose_model_path) fixed. Verified locally: DensePoseHead(config) + ModalityTranslationNetwork(config) both construct + eval, clearing the startup TypeError.	2026-06-02 11:42:52 +02:00
rUv	b7b8c1109b	Merge pull request #908 from ruvnet/fix/893-release-bins-refresh release(firmware): refresh release_bins with the #893 CSI fix → v0.6.7	2026-06-02 05:35:34 -04:00
ruv	786e834dae	release(firmware): refresh release_bins with the #893 CSI fix → v0.6.7 The pre-built binaries in release_bins/ were v0.6.6 (May 21) and shipped the MGMT-only promiscuous filter, so display-less boards flashed from them got yield=0pps (#893/#866/#897 — the root cause of the "can't reproduce / it's fake" reports). Rebuilt every flashable variant from main (which has the #893 display-gated DATA-frame fix) and refreshed the binaries: - top-level ESP32-S3 8MB (sdkconfig.defaults) — esp32-csi-node.bin + bootloader (partition-table/ota_data unchanged — code-only fix) - esp32-csi-node-4mb.bin (ESP32-S3 4MB, sdkconfig.defaults.4mb) - c6-adr110/ (ESP32-C6, sdkconfig.defaults.esp32c6) — the exact firmware hardware-verified on COM6 (CSI yield 0→27 pps, presence/motion alive, no #396 crash) - s3-adr110/ (same production S3 8MB config) Left untouched: s3-fair-adr110/ (a non-production size-comparison build, features stripped — not a board anyone flashes for sensing). version.txt → 0.6.7; SHA256SUMS regenerated for the changed variant dirs. Display boards keep MGMT-only (preserves the #396 crash protection); display-less boards now capture DATA frames and stream CSI. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-02 11:18:03 +02:00
dependabot[bot]	1d41e81ac6	chore(deps-dev): bump @vitejs/plugin-react Bumps [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/tree/HEAD/packages/plugin-react) from 4.7.0 to 6.0.2. - [Release notes](https://github.com/vitejs/vite-plugin-react/releases) - [Changelog](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react/CHANGELOG.md) - [Commits](https://github.com/vitejs/vite-plugin-react/commits/plugin-react@6.0.2/packages/plugin-react) --- updated-dependencies: - dependency-name: "@vitejs/plugin-react" dependency-version: 6.0.2 dependency-type: direct:development update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] <support@github.com>	2026-05-20 01:14:14 +00:00