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chore(ci): bump codecov/codecov-action from 4 to 6 - #2

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chore(ci): bump codecov/codecov-action from 4 to 6#2
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Bumps codecov/codecov-action from 4 to 6.

Release notes

Sourced from codecov/codecov-action's releases.

v6.0.0

⚠️ This version introduces support for node24 which make cause breaking changes for systems that do not currently support node24. ⚠️

What's Changed

Full Changelog: codecov/codecov-action@v5.5.4...v6.0.0

v5.5.4

This is a mirror of v5.5.2. v6 will be released which requires node24

What's Changed

Full Changelog: codecov/codecov-action@v5.5.3...v5.5.4

v5.5.3

What's Changed

Full Changelog: codecov/codecov-action@v5.5.2...v5.5.3

v5.5.2

What's Changed

New Contributors

Full Changelog: codecov/codecov-action@v5.5.1...v5.5.2

v5.5.1

What's Changed

... (truncated)

Changelog

Sourced from codecov/codecov-action's changelog.

v5.5.2

What's Changed

Full Changelog: https://github.com/codecov/codecov-action/compare/v5.5.1..v5.5.2

v5.5.1

What's Changed

Full Changelog: https://github.com/codecov/codecov-action/compare/v5.5.0..v5.5.1

v5.5.0

What's Changed

Full Changelog: https://github.com/codecov/codecov-action/compare/v5.4.3..v5.5.0

v5.4.3

What's Changed

Full Changelog: https://github.com/codecov/codecov-action/compare/v5.4.2..v5.4.3

v5.4.2

... (truncated)

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Bumps [codecov/codecov-action](https://github.com/codecov/codecov-action) from 4 to 6.
- [Release notes](https://github.com/codecov/codecov-action/releases)
- [Changelog](https://github.com/codecov/codecov-action/blob/main/CHANGELOG.md)
- [Commits](codecov/codecov-action@v4...v6)

---
updated-dependencies:
- dependency-name: codecov/codecov-action
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <[email protected]>
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abailey81 added a commit that referenced this pull request Apr 27, 2026
…fy two-number framing, add re-runnable verifier

The phase-21 honesty audit caught me quoting the project's
*conservative-stress-test* perplexity (1725) as if it were the
headline number, when the *training-time response-only* perplexity
is **~ 147** (from `best_eval_loss = 4.987` in the checkpoint blob).
Both numbers are real and measure different things; only the second
should be the demo-cheat-sheet headline.

DOCUMENT FIXES
- docs/huawei/PRESENTER_CHEAT_SHEET.md  ("What this prototype is NOT"
  section): replaced the bare "perplexity ~ 1725" claim with the
  two-number framing — 147 as the apples-to-apples comparable to
  published SLMs, 1725 as the stress-test on broader distribution
  with history-token loss included.
- docs/huawei/open_problems.md  (#2 — full-corpus SLM retrain):
  documented BOTH numbers in the background, and split the acceptance
  criteria into "training-time held-out below 80" and
  "stress-test below 600".  Previously claimed only 1725 → 600,
  which made the success bar artificially harsh.
- reports/slm_v2_eval.md: added a "Read this before quoting any
  number" preamble at the top explaining the two metrics with a
  one-line "use this number when…" guide.  The stress-test 1725 is
  now annotated inline ("← stress-test number, not the headline").
  Added a "Headline number" subsection at the bottom citing
  best_eval_loss = 4.987 and exp(4.987) ≈ 146.6 with the source.
  Architecture line updated to disclose the 204.4 M unique vs
  229.4 M state_dict spread (the difference is the tied-weight
  LM-head + a few biases the model's `.num_parameters` dedupes).

NEW TOOLING — scripts/verify_numbers.py
- A re-runnable audit that loads each artefact on disk and asserts
  every recruiter-facing claim matches.  Caches no data; just
  reads the live checkpoint, the live ONNX, the live KG, the live
  corpus.  Prints PASS / FAIL per claim, exits non-zero on drift.
- Current run: 22 / 22 claims verify.  Specifically:
    SLM v2 architecture (d_model 768, 12L, 12H, vocab 32 k)
    SLM v2 step (18 000), eval_loss (4.987), ppl (~ 147)
    SLM v2 params (~ 204 M unique, 229 M state_dict)
    Qwen LoRA (rank 16, alpha 32, DoRA, 4 545/252, 1 704 steps × 3 epochs,
        best_val_loss 5.36e-06, wall 9 656 s)
    Encoder ONNX (FP32 441 KB, INT8 162 KB, 63 % reduction, parity
        MAE 0.0006)
    KG subjects (31), corpus pairs (974 k)
- Run anytime with: .venv/Scripts/python.exe scripts/verify_numbers.py

Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>
abailey81 added a commit that referenced this pull request Apr 29, 2026
Iter 58 — the user reported the dashboard's 'Typing rhythm' tile
still reading 0 ms after iter 41 + restart, even though composition
cadence (1.29 s avg) was being recorded correctly on the same turn.

Root cause: the iter 41 fix correctly routed JS-format ``iki_ms``
into the keystroke_buffer, but the buffer's first sampled keystroke
event always has ``iki_ms = 0`` (no preceding keystroke).  When a
short message produced exactly ONE keystroke event (every 3rd
keystroke is sampled — so a 3-key message lands on event #3 with
keyTimings.length=2 → iki_ms is the gap between #2 and #3, OK; but
when the very first sampled event is the only one, the buffer has
[0]).  The pre-fix server passed ``[0]`` straight to
``Pipeline._iki_stats``, which filtered the zero out and returned
mean=0 — even though composition_metrics.keystroke_timings had real
data right there.

Three-level fallback:
  1. server-side keystroke_buffer (filter to non-zero entries)
  2. composition_metrics.keystroke_timings array
  3. composition_metrics.mean_iki scalar (last resort: synthesize a
     single timing from the JS-precomputed mean)

The dashboard's 'Typing rhythm' tile now never reads 0 ms when the
JS client has any meaningful inter-key data — even on edge-case
messages where the per-event sampler captured only zero-IKI entries.
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