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Clean up suites, one runner per suite and the kBench site #3

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kleb merged 10 commits from benchmark/cleanup-benchs-20261030 into main

2026-10-30 22:47:21 +01:00

kleb commented

2026-10-30 22:31:26 +01:00

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Data: suites live under benchs/ with one dataset each (Synthetic EN-DE-PL) and only the newest run per configuration from October. Engines are fixed to hosts: CPU and iGPU on the kEmbed nodes, GPU on root-PC. The four i7-12700K CPU runs are removed; every model already has a 12600H run, so nothing needed recovering.
Code: split into packages/web, packages/shared (benchlib, result schemas) and packages/runners. One entrypoint per suite: python -m embedding, python -m ocr, python -m review, with the backend as a flag. Public datasets, private replay and the archived judge scorer are gone.
Monitoring: every run prints progress lines with counts, rate, ETA and a status text (OCR and review did not report before). The lane runner keeps the latest line, prints changes and detects stalls, with a limit stretched to the observed rate. Matrix lanes are hosts (kembed01, kembed02, rootpc).
Site (kBench): one ranked metric at a time per engine, CPU first, all models selected, exclusive engine choice. No methods text and no repository link. Columns size to their content and the available width; the sidebar lists only models with runs on the selected engine.
Docs: outdated docs removed; AGENTS.md records the host rule, one script per suite and the progress contract.

Not run on real hardware: no inference was allowed on the agent host, so the new runners are proven by mocked tests only. The first lane on each host is the real test. New GPU runs are labelled NVIDIA GeForce RTX 4070 Ti GPU, without the old "(concurrent lane)".

Proven by 274 Python tests, bun tests, typecheck, validate and build (30 results verified), and by checking all four pages in a browser from 2560 to 390 px for overflow and cut-off text.

The repository had grown messy: many test groups and datasets per suite, old runs, suites spread across the root, CPU results from a host that should not run them, one script per backend, and a busy site with methods text. This cleans it up end to end. - **Data:** suites live under `benchs/` with one dataset each (Synthetic EN-DE-PL) and only the newest run per configuration from October. Engines are fixed to hosts: CPU and iGPU on the kEmbed nodes, GPU on root-PC. The four i7-12700K CPU runs are removed; every model already has a 12600H run, so nothing needed recovering. - **Code:** split into `packages/web`, `packages/shared` (benchlib, result schemas) and `packages/runners`. One entrypoint per suite: `python -m embedding`, `python -m ocr`, `python -m review`, with the backend as a flag. Public datasets, private replay and the archived judge scorer are gone. - **Monitoring:** every run prints progress lines with counts, rate, ETA and a status text (OCR and review did not report before). The lane runner keeps the latest line, prints changes and detects stalls, with a limit stretched to the observed rate. Matrix lanes are hosts (`kembed01`, `kembed02`, `rootpc`). - **Site (kBench):** one ranked metric at a time per engine, CPU first, all models selected, exclusive engine choice. No methods text and no repository link. Columns size to their content and the available width; the sidebar lists only models with runs on the selected engine. - **Docs:** outdated docs removed; AGENTS.md records the host rule, one script per suite and the progress contract. ![embedding-desktop.png](https://git.kleb.sh/attachments/1f9e0c9f-7c51-4a43-8002-8c89fbf47358) ![embedding-1100.png](https://git.kleb.sh/attachments/3b3757dd-495f-4fe6-9fcd-6c1451a1060b) ![embedding-mobile.png](https://git.kleb.sh/attachments/7559d06f-e4db-4f64-bf68-51e9bb98fec8) ![ocr-desktop.png](https://git.kleb.sh/attachments/609da671-f656-4425-97c6-d90c3ae3fcb7) Not run on real hardware: no inference was allowed on the agent host, so the new runners are proven by mocked tests only. The first lane on each host is the real test. New GPU runs are labelled `NVIDIA GeForce RTX 4070 Ti GPU`, without the old "(concurrent lane)". Proven by 274 Python tests, bun tests, typecheck, validate and build (30 results verified), and by checking all four pages in a browser from 2560 to 390 px for overflow and cut-off text.

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embedding-1100.png

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kleb added 9 commits

2026-10-30 22:31:26 +01:00

Move suites under benchs and keep one dataset with newest runs 3c5c8a7108

Each suite now lives in benchs/{embedding,ocr,review,ui}. Embedding keeps
the newest October run per configuration on Synthetic EN-DE-PL retrieval v1
at 512 tokens (29 runs), OCR the 5 Synthetic EN-DE-PL print OCR v1 runs,
review its most complete run, and the kReview catalogue its October run.
Superseded results, unreferenced evidence, campaign bookkeeping and run
logs are removed. Retained results and evidence move unchanged.

The site drops test-group selection and shows one table per suite. The
loader rejects a suite that mixes datasets or accuracy measures. Evidence
paths resolve against benchs/, and UI captures are served from benchs/ui.

Split code into web, shared and runners packages 8dcb894da2

benchs/ now holds only benchmark data and definitions. Code moves to
packages/: web (Astro site, build checks, packaging, deploy), shared
(benchlib plus the TS result and catalogue schemas) and runners (embedding
and OCR runners, review and matrix scripts, Python tests).

Python uses a uv workspace with benchlib and runners as editable members,
so runners run as `python -m embedding.run` again; third-party pins stay
in the root and uv.lock only gains the two members. Bun uses workspaces
with unchanged resolutions; root scripts forward to the web package.
Runners read manifests from benchs/ and the site finds the repository
root by locating benchs/.

Rank results per metric and engine as kBench 73c7a7b8d4

The embedding and OCR pages replace the chart, stats and table with one
ranked list per metric: bars from zero, a dot plot on a zoomed axis for
accuracy, tied values sharing a rank, and an all-runs or best-per-model
toggle. The engine filter is exclusive and opens on CPU, falling back to
the first engine a suite has. All models start selected and keep a fixed
color per model family. The site is renamed to kBench.

Remove method sections from the site 13f60605cb

The Embedding, OCR, UI and Code review pages, their detail drawers and the
glossary no longer carry method text. Speed and token terms now point to
each run's evidence for counting and timing rules.

Keep only kEmbed CPU and iGPU and root-PC GPU runs 2373c93a39

Drop the four i7-12700K CPU embedding runs; every model has a 12600H run.

One entrypoint per suite with live progress for stall monitoring 1c6441623a

- python -m embedding: torch, gguf and openvino are --backend flags of one
  runner; synthetic set only (public datasets and private replay removed).
- python -m ocr: all OCR backends including GLM-OCR GGUF in one runner.
- python -m review: prepare, audit, run and score stages; archived judge
  scorer removed.
- Progress lines carry counts, rate, ETA and a status text; OCR and review
  runs now report too. The lane runner keeps the latest line in its state,
  prints changes, and stretches the stall limit to the observed rate.
- Matrix lanes are hosts (kembed01, kembed02, rootpc) with engines fixed to
  them; the llama.cpp server moved to benchlib.
- Remove outdated docs and the unused data extra.

Size site columns to their content and the available width a75ee9ff06

Board columns are shared across rows: labels and values take what they
need, bars the rest. The sidebar and chart side panels fit their content,
stats fill the row, table text wraps before scrolling, and view tabs move
to a second header row instead of being cut off. Also drop a stale render
of the removed review notes that threw on load.

List only models with runs on the selected engine; drop the repository link 9ac4779bb4

Keep the model dot with its name when board labels wrap 2225de263f

kAgent commented

2026-10-30 22:31:53 +01:00

First-time contributor

kReview review

Verdict: 2 High, 1 Medium

Partial review: This review did not cover 1790 of 3855 changed files in full. See the files and code sections below.

Review found 3 findings: 2 high, 1 medium. Highest priority: Restore the embedding fixture checksum.

High (2)

Restore the embedding fixture checksum · packages/runners/embedding/run.py:48
Every embedding run fails before loading a model because benchs/embedding/fixtures.sha256 is absent from the reviewed head. main calls load_fixtures at line 296, and this read raises FileNotFoundError. The directory listing confirms that the checksum file is missing.
Suggested fix: Add benchs/embedding/fixtures.sha256 with the checksum of the committed fixture manifest.
Restore the BGE-Code requirements file · packages/runners/embedding/torch_backend.py:74
BGE-Code torch runs fail before they publish results because benchs/embedding/bge-code-requirements.txt is absent from the reviewed head. The BGE-Code model has runtimeProfile set to bge-code-upstream-v1 in benchs/embedding/models.json lines 72–76, so this call tries to hash the missing file. The directory listing confirms that the file is missing.
Suggested fix: Add the pinned BGE-Code requirements file at benchs/embedding/bge-code-requirements.txt.

Medium (1)

Read the current release after acquiring the deployment lock · packages/web/deploy/release.sh:12
A failed deployment can roll the site back past the most recent successful release. If another deployment activates after this line but releases the lock before this deployment acquires it, previous still points to the older release. The recovery copy and rollback then use that stale path.
Suggested fix: Acquire the deployment lock before reading and validating current.

Partially reviewed

This review checked only parts of these files:

1771 partially reviewed files

benchs/embedding/evidence/r20261026-01a17710-igpu1-e-voyage-syn-512.json
benchs/embedding/evidence/r20261026-01a17710-igpu2-e-gemma-syn-512.json
benchs/embedding/evidence/r20261026-01a17710-igpu2-e-qwen-syn-512.json
benchs/embedding/evidence/r576206b9fb9146af-gpu-e-gemma-syn-512.json
benchs/embedding/evidence/r576206b9fb9146af-gpu-e-voyage-syn-512.json
benchs/embedding/evidence/r61e4a984dee14aaa-gpu-e-jina-syn-512.json
benchs/embedding/evidence/r7664b33260f94780-cpu1-e-qwen3-syn-512.json
benchs/embedding/evidence/r7664b33260f94780-cpu2-e-e5-syn-512.json
benchs/embedding/evidence/r7664b33260f94780-cpu2-e-jina-syn-512.json
benchs/embedding/evidence/r7664b33260f94780-cpu2-e-m3-syn-512.json
benchs/embedding/evidence/r7664b33260f94780-cpu2-e-voyage-syn-512.json
benchs/embedding/evidence/r8b0a09f2e357-gpu-e-bge-syn-512.json
benchs/embedding/evidence/r8f42bbbe50e94347-cpu1-r7664b33260f94780-cpu1-e-bge-syn-512.json
benchs/embedding/evidence/r9974465f7ebb4a68-igpu2-e-jina-syn-512.json
benchs/embedding/evidence/rb0809b96837946b0-gpu-e-m3-syn-512.json
benchs/embedding/evidence/rc71de2e680b24561-cpu1-e-gemma-syn-512.json
benchs/embedding/evidence/rd130878c3d3446df-igpu1-e-jina-syn-512-pfx.json
benchs/embedding/evidence/rdfce37f57e154325-gpu-e-e5-syn-512.json
benchs/embedding/evidence/rffb2d0bb736243b1-igpu1-e-bge-syn-512.json
benchs/embedding/evidence/rffb2d0bb736243b1-igpu1-e-e5-syn-512.json
benchs/embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-syn-512-pfx.json
benchs/embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-syn-512-pfx.json
benchs/embedding/evidence/rffb2d0bb736243b1-igpu2-e-m3-syn-512.json
benchs/embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-syn-512-pfx.json
benchs/review/evidence/review-51a87b3360a74fcc97b67840dad79434.json
benchs/review/fixtures/public-prs-v1.json
embedding/completions/baseline-20261029.json
embedding/completions/baseline-recovered-20261030.json
embedding/completions/igpu-setup-checkpoint-20261029-a2964fcbc678.json
embedding/completions/igpu-setup-checkpoint-20261029-d8577014171c.json
embedding/completions/jina-cpu-20261029.json
embedding/continuations/igpu-setup-recovery-20261029-ffb2d0bb7362.json
embedding/continuations/igpu2-hang-restart-20261029-80d0175f7d26.json
embedding/continuations/rootpc-reboot-e0d42f67497a467ab0f97be1ff584a82.json
embedding/datasets.py
embedding/evidence/artifact-20261020-public-root-pc.json
embedding/evidence/r1cd1a574e5074c87-cpu1-e-qwen3-contest-512.json
embedding/evidence/r1e044ec73acd455c-gpu-e-qwen3-dl-512.json
embedding/evidence/r1e044ec73acd455c-gpu-e-qwen3-sci-2048.json
embedding/evidence/r1e044ec73acd455c-gpu-e-qwen3-sci-512.json
embedding/evidence/r1e044ec73acd455c-gpu-e-qwen3-syn-2048.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-code-512-screen-dense-1024d-67bfc8871499.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-code-512-screen-dense-2048d-aecd3fe20769.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-code-512-screen-dense-256d-c379569eed25.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-code-512-screen-dense-512d-48ef93dac4d3.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-contest-2048.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-contest-512.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-dl-2048.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-mem-512-screen-dense-1024d-d68cfe5e068d.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-mem-512-screen-dense-2048d-a92fba4821ed.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-mem-512-screen-dense-256d-3a4d1733ba09.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-mem-512-screen-dense-512d-a4609a388fac.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-dense-1024d-e58e6dcc3575.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-dense-2048d-8636183e8a38.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-dense-256d-555950d1c71c.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-dense-512d-15f6eb1ec69a.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-hybrid-1024d-4bf04eea2505.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-hybrid-2048d-02a26a1767e3.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-hybrid-256d-0ac2493b96b2.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-hybrid-512d-beefee93f8e0.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-lexical-1024d-797675478b7c.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-lexical-2048d-13b7abd9c247.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-lexical-256d-f50a82ccb30b.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-changed-references-lexical-512d-736952dc2821.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-dense-1024d-2bc70c4a394f.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-dense-2048d-65198d8b994b.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-dense-256d-41141277f7fe.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-dense-512d-1a0759e44bbd.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-hybrid-1024d-a17e5fe0bf52.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-hybrid-2048d-5e065a0cc761.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-hybrid-256d-72936684bd26.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-hybrid-512d-0a9406b2ac22.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-lexical-1024d-2aaf7709c0b6.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-lexical-2048d-b2e76da27ac3.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-lexical-256d-c0b4ae20779f.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-code-lexical-512d-0f785e10129d.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-combined-native-index-bf8cca9e5ae0.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-latency-change-ebab5da262b5.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-latency-short-c863331755c8.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-memory-new-dense-1024d-c88aa09fcdf8.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-memory-new-dense-2048d-2bc50ac42c6c.json
embedding/evidence/r1e044ec73acd455c-gpu-e-voyage-val-2048-memory-new-dense-256d-dbbe3adfc267.json
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embedding/evidence/r20261026-01a17710-cpu-e-e5-code-512-screen-dense-384d-2c1bf9620451.json
embedding/evidence/r20261026-01a17710-cpu-e-e5-contest-512.json
embedding/evidence/r20261026-01a17710-cpu-e-e5-dl-512.json
embedding/evidence/r20261026-01a17710-cpu-e-e5-mem-512-screen-dense-384d-99f7034dc9dc.json
embedding/evidence/r20261026-01a17710-cpu-e-e5-sci-512.json
embedding/evidence/r20261026-01a17710-cpu-e-e5-syn-512.json
embedding/evidence/r20261026-01a17710-cpu-e-gemma-dl-512.json
embedding/evidence/r20261026-01a17710-cpu-e-gemma-sci-2048.json
embedding/evidence/r20261026-01a17710-cpu-e-gemma-sci-512.json
embedding/evidence/r20261026-01a17710-cpu-e-gemma-syn-2048.json
embedding/evidence/r20261026-01a17710-cpu-e-gemma-syn-512.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-code-512-screen-dense-1536d-86eef28ff84f.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-contest-2048.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-contest-512.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-dl-2048.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-dl-512.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-mem-512-screen-dense-1536d-1176f102ee8a.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-sci-2048.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-sci-512.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-syn-2048.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-syn-512.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-code-changed-references-dense-1536d-d3731ecfdd24.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-code-changed-references-hybrid-1536d-b10e6ae49fde.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-code-changed-references-lexical-1536d-a4049b65d8f0.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-code-dense-1536d-cbe38ed074c7.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-code-hybrid-1536d-33fdb1c8cc65.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-code-lexical-1536d-49b5383f266f.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-combined-native-index-cc067b722474.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-latency-change-e906845d30e2.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-latency-short-436f75710be7.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-memory-new-dense-1536d-01fb1b5c8ac7.json
embedding/evidence/r20261026-01a17710-gpu-e-bge-val-2048-memory-original-dense-1536d-0fc18a1c4229.json
embedding/evidence/r20261026-01a17710-gpu-e-e5-code-512-screen-dense-384d-e7a0c172849b.json
embedding/evidence/r20261026-01a17710-gpu-e-e5-contest-512.json
embedding/evidence/r20261026-01a17710-gpu-e-e5-dl-512.json
embedding/evidence/r20261026-01a17710-gpu-e-e5-mem-512-screen-dense-384d-a1ce282e9b08.json
embedding/evidence/r20261026-01a17710-gpu-e-e5-sci-512.json
embedding/evidence/r20261026-01a17710-gpu-e-e5-syn-512.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-code-512-screen-dense-128d-fddcefbfeb55.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-code-512-screen-dense-256d-9b66b34741f3.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-code-512-screen-dense-512d-53b6694f6222.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-code-512-screen-dense-768d-b7945e6b0c2b.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-contest-2048.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-contest-512.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-dl-2048.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-dl-512.json
embedding/evidence/r20261026-01a17710-gpu-e-gemma-mem-512-screen-dense-128d-e456f06f056b.json
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embedding/evidence/rffb2d0bb736243b1-igpu1-e-bge-val-2048-memory-new-dense-1536d-8f89ae95811d.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-bge-val-2048-memory-original-dense-1536d-d19147640f59.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-e5-code-512-screen-dense-384d-70d0081d7a21.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-e5-contest-512.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-e5-dl-512.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-e5-mem-512-screen-dense-384d-631d579f29b6.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-e5-sci-512.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-contest-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-contest-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-dl-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-dl-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-sci-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-sci-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-syn-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-contest-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-contest-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-dl-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-dl-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-sci-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-sci-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-syn-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-m3-dl-512.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-m3-sci-2048.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-m3-sci-512.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-m3-syn-2048.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-contest-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-contest-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-dl-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-dl-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-sci-2048-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-sci-512-pfx.json
embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-syn-2048-pfx.json
embedding/evidence/v6-i2-j-code-512-screen-dense-128d-d54df36ed72a.json
embedding/evidence/v6-i2-j-code-512-screen-dense-256d-fc5ba6c78fa3.json
embedding/evidence/v6-i2-j-code-512-screen-dense-512d-91a0bc267a0b.json
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embedding/evidence/v6-i2-j-mem-512-screen-dense-128d-d97ecd8732da.json
embedding/evidence/v6-i2-j-mem-512-screen-dense-256d-ad6c0ec4b1d6.json
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embedding/evidence/v6-i2-j-mem-512-screen-dense-896d-620c157eaad8.json
embedding/evidence/v6-i2-j-sci-512.json
embedding/evidence/v6-i2-q-code-512-screen-dense-1024d-bf10943ffb7f.json
embedding/evidence/v6-i2-q-code-512-screen-dense-128d-e992f955554c.json
embedding/evidence/v6-i2-q-code-512-screen-dense-256d-3066e4168497.json
embedding/evidence/v6-i2-q-code-512-screen-dense-32d-111fc46d9e2e.json
embedding/evidence/v6-i2-q-code-512-screen-dense-512d-a91e5e80c4f0.json
embedding/evidence/v6-i2-q-code-512-screen-dense-64d-f7907ec27801.json
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embedding/evidence/v6-i2-q-mem-512-screen-dense-128d-2e64afc4016a.json
embedding/evidence/v6-i2-q-mem-512-screen-dense-256d-92de9bdbafbf.json
embedding/evidence/v6-i2-q-mem-512-screen-dense-32d-e75fdca2bccc.json
embedding/evidence/v6-i2-q-mem-512-screen-dense-512d-63eda1b13106.json
embedding/evidence/v6-i2-q-mem-512-screen-dense-64d-41fc808fb6b4.json
embedding/evidence/v6-i2-q-sci-512.json
embedding/gguf.py
embedding/legacy.py
embedding/preflights/bge-bounded-highram-20261030-abc19ffaf2b6.json
embedding/preflights/bge-hang-investigation-20261030-d130878c3d34.json
embedding/preflights/bge-static-sequence-20261030-89345c27bc04.json
embedding/preflights/bge-validation-node1-20261030-f72fd0c782d5.json
embedding/preflights/igpu-setup-20261029-node1.json
review/evidence/review-719a9b63fed04a0e84a7cdd4c9de31b7.json

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This review did not check these files:

19 skipped files

review/evidence/review-afd4546db574450e9c7b9b4f14d17353.json
review/remaining/queue-cleared-4d122b5380394b7c9acb9c70429406c5.json
review/results/review-719a9b63fed04a0e84a7cdd4c9de31b7.json
review/results/review-86fe816019fd47e0a6156b22c2ff202c.json
review/results/review-9633caf326724169a49f9f5e6dda37f4.json
review/results/review-afd4546db574450e9c7b9b4f14d17353.json
scripts/build-matrix.py
scripts/import-history.py
scripts/prepare-private.py
scripts/score-review-models.py
src/components/Workbench.astro
src/data/code-review.json
src/lib/compare.ts
src/scripts/workbench.ts
tests/test_cli.py
tests/test_datasets.py
tests/test_legacy.py
tests/test_ocr_datasets.py
tests/test_review_scoring.py

This review did not check generated or vendored files: bun.lock, uv.lock.

kReview checked only the PR diff, metadata, and supplied repository context at 001bd61ffa. It reports only issues supported by this material.

Estimated cost: ~$21.82 total (23.2M in / 13.8k out); this run ~$11.12 (11.6M in / 7.5k out) / gpt-6.1-terra.

Run time: 13:32 total; this run 2:20.

## kReview review **Verdict:** 2 High, 1 Medium > **Partial review:** This review did not cover 1790 of 3855 changed files in full. See the files and code sections below. Review found 3 findings: 2 high, 1 medium. Highest priority: Restore the embedding fixture checksum. ### High (2) - **Restore the embedding fixture checksum** · [`packages/runners/embedding/run.py:48`](https://git.kleb.sh/kleb/benchmark/src/commit/001bd61ffa57742084074c5f2359cd7f8fb13a06/packages/runners/embedding/run.py#L48) Every embedding run fails before loading a model because `benchs/embedding/fixtures.sha256` is absent from the reviewed head. `main` calls `load_fixtures` at line 296, and this read raises `FileNotFoundError`. The directory listing confirms that the checksum file is missing. Suggested fix: Add `benchs/embedding/fixtures.sha256` with the checksum of the committed fixture manifest. - **Restore the BGE-Code requirements file** · [`packages/runners/embedding/torch_backend.py:74`](https://git.kleb.sh/kleb/benchmark/src/commit/001bd61ffa57742084074c5f2359cd7f8fb13a06/packages/runners/embedding/torch_backend.py#L74) BGE-Code torch runs fail before they publish results because `benchs/embedding/bge-code-requirements.txt` is absent from the reviewed head. The BGE-Code model has `runtimeProfile` set to `bge-code-upstream-v1` in `benchs/embedding/models.json` lines 72–76, so this call tries to hash the missing file. The directory listing confirms that the file is missing. Suggested fix: Add the pinned BGE-Code requirements file at `benchs/embedding/bge-code-requirements.txt`. ### Medium (1) - **Read the current release after acquiring the deployment lock** · [`packages/web/deploy/release.sh:12`](https://git.kleb.sh/kleb/benchmark/src/commit/001bd61ffa57742084074c5f2359cd7f8fb13a06/packages/web/deploy/release.sh#L12) A failed deployment can roll the site back past the most recent successful release. If another deployment activates after this line but releases the lock before this deployment acquires it, `previous` still points to the older release. The recovery copy and rollback then use that stale path. Suggested fix: Acquire the deployment lock before reading and validating `current`. ### Partially reviewed This review checked only parts of these files: <details> <summary>1771 partially reviewed files</summary> - `benchs/embedding/evidence/r20261026-01a17710-igpu1-e-voyage-syn-512.json` - `benchs/embedding/evidence/r20261026-01a17710-igpu2-e-gemma-syn-512.json` - `benchs/embedding/evidence/r20261026-01a17710-igpu2-e-qwen-syn-512.json` - `benchs/embedding/evidence/r576206b9fb9146af-gpu-e-gemma-syn-512.json` - `benchs/embedding/evidence/r576206b9fb9146af-gpu-e-voyage-syn-512.json` - `benchs/embedding/evidence/r61e4a984dee14aaa-gpu-e-jina-syn-512.json` - `benchs/embedding/evidence/r7664b33260f94780-cpu1-e-qwen3-syn-512.json` - `benchs/embedding/evidence/r7664b33260f94780-cpu2-e-e5-syn-512.json` - `benchs/embedding/evidence/r7664b33260f94780-cpu2-e-jina-syn-512.json` - `benchs/embedding/evidence/r7664b33260f94780-cpu2-e-m3-syn-512.json` - `benchs/embedding/evidence/r7664b33260f94780-cpu2-e-voyage-syn-512.json` - `benchs/embedding/evidence/r8b0a09f2e357-gpu-e-bge-syn-512.json` - `benchs/embedding/evidence/r8f42bbbe50e94347-cpu1-r7664b33260f94780-cpu1-e-bge-syn-512.json` - `benchs/embedding/evidence/r9974465f7ebb4a68-igpu2-e-jina-syn-512.json` - `benchs/embedding/evidence/rb0809b96837946b0-gpu-e-m3-syn-512.json` - `benchs/embedding/evidence/rc71de2e680b24561-cpu1-e-gemma-syn-512.json` - `benchs/embedding/evidence/rd130878c3d3446df-igpu1-e-jina-syn-512-pfx.json` - `benchs/embedding/evidence/rdfce37f57e154325-gpu-e-e5-syn-512.json` - `benchs/embedding/evidence/rffb2d0bb736243b1-igpu1-e-bge-syn-512.json` - `benchs/embedding/evidence/rffb2d0bb736243b1-igpu1-e-e5-syn-512.json` - `benchs/embedding/evidence/rffb2d0bb736243b1-igpu1-e-gemma-syn-512-pfx.json` - `benchs/embedding/evidence/rffb2d0bb736243b1-igpu1-e-qwen-syn-512-pfx.json` - `benchs/embedding/evidence/rffb2d0bb736243b1-igpu2-e-m3-syn-512.json` - `benchs/embedding/evidence/rffb2d0bb736243b1-igpu2-e-voyage-syn-512-pfx.json` - `benchs/review/evidence/review-51a87b3360a74fcc97b67840dad79434.json` - `benchs/review/fixtures/public-prs-v1.json` - `embedding/completions/baseline-20261029.json` - `embedding/completions/baseline-recovered-20261030.json` - `embedding/completions/igpu-setup-checkpoint-20261029-a2964fcbc678.json` - `embedding/completions/igpu-setup-checkpoint-20261029-d8577014171c.json` - `embedding/completions/jina-cpu-20261029.json` - `embedding/continuations/igpu-setup-recovery-20261029-ffb2d0bb7362.json` - `embedding/continuations/igpu2-hang-restart-20261029-80d0175f7d26.json` - `embedding/continuations/rootpc-reboot-e0d42f67497a467ab0f97be1ff584a82.json` - `embedding/datasets.py` - `embedding/evidence/artifact-20261020-public-root-pc.json` - `embedding/evidence/r1cd1a574e5074c87-cpu1-e-qwen3-contest-512.json` - `embedding/evidence/r1e044ec73acd455c-gpu-e-qwen3-dl-512.json` - `embedding/evidence/r1e044ec73acd455c-gpu-e-qwen3-sci-2048.json` - `embedding/evidence/r1e044ec73acd455c-gpu-e-qwen3-sci-512.json` - `embedding/evidence/r1e044ec73acd455c-gpu-e-qwen3-syn-2048.json` - 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It reports only issues supported by this material._ _Estimated cost: ~$21.82 total (23.2M in / 13.8k out); this run ~$11.12 (11.6M in / 7.5k out) / gpt-6.1-terra._ _Run time: 13:32 total; this run 2:20._

kleb added 1 commit

2026-10-30 22:43:22 +01:00

Install workspace packages in the BGE-Code environment; keep slow rates nonzero 001bd61ffa

kleb commented

2026-10-30 22:43:36 +01:00

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Owner

Dismissed "Restore the BGE-Code requirements file" (packages/runners/embedding/torch_backend.py): the file exists at the reviewed head. git ls-tree 2225de2 benchs/embedding/ lists bge-code-requirements.txt (blob d056e16), and test_bge_requirements_match_profile_without_changing_model_pin reads it and passes. It was likely in the partially reviewed part of this large diff.

Dismissed "Restore the BGE-Code requirements file" (`packages/runners/embedding/torch_backend.py`): the file exists at the reviewed head. `git ls-tree 2225de2 benchs/embedding/` lists `bge-code-requirements.txt` (blob d056e16), and `test_bge_requirements_match_profile_without_changing_model_pin` reads it and passes. It was likely in the partially reviewed part of this large diff.

kleb commented

2026-10-30 22:46:00 +01:00

Author

Owner

Dismissed "Restore the embedding fixture checksum" (packages/runners/embedding/run.py): benchs/embedding/fixtures.sha256 exists at 001bd61 (blob 3e899d2), and test_fixture_integrity_and_languages loads it and passes.

Won't fix here: "Read the current release after acquiring the deployment lock" (packages/web/deploy/release.sh). The file is only moved in this PR (100% similarity rename from deploy/release.sh); the race predates it. Kept as a follow-up.

Dismissed "Restore the embedding fixture checksum" (`packages/runners/embedding/run.py`): `benchs/embedding/fixtures.sha256` exists at 001bd61 (blob 3e899d2), and `test_fixture_integrity_and_languages` loads it and passes. Won't fix here: "Read the current release after acquiring the deployment lock" (`packages/web/deploy/release.sh`). The file is only moved in this PR (100% similarity rename from `deploy/release.sh`); the race predates it. Kept as a follow-up.

kleb merged commit 85a463b58d into main

2026-10-30 22:47:21 +01:00

kleb deleted branch benchmark/cleanup-benchs-20261030

2026-10-30 22:47:22 +01:00

kleb referenced this pull request from a commit

2026-10-30 22:47:23 +01:00

Merge pull request 'Clean up suites, one runner per suite and the kBench site' (#3) from benchmark/cleanup-benchs-20261030 into main