0f032fac2c65a2b55514cb0b8370dfdb7140c03d
149
Commits
| Author | SHA1 | Message | Date | |
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 vh
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7964d077de |
bronte-corpus: runbook — the five deviations and what the controls caught
Records the reproducible chain and, more usefully, why it diverges from the Yarros/Hemingway pipeline in five places, each forced by a measurement rather than a preference. Includes the control post-mortem, which is worth keeping because in three of four cases the CONTROL was wrong and the detector was right — the opposite of the reflex. Adele vs Adele-with-a-grave, Hollow at a 0.235 lowercase ratio, and Grace at 0.224 were all correct refusals. Blanche, at 0.0526 against a 0.05 bar, was the one real detector miss. |
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vh
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533cc0ce81 |
build_sft_pairs: reject beats that name characters the rename removed
A leak the corpus gate structurally cannot see, found on lv-bronte. The rename strips the author's names from the prose and leak_gate.py proves they are gone — 0 of 365 surviving on Brontë, both controls green. But the beat is written by an LLM that READ THE PASSAGE, and if it recognises the book it supplies the canonical names out of its own training. The beat is the INSTRUCTION half of the pair, so training on it re-teaches exactly the inventions the rename pipeline exists to remove, and the gate never looks at it: the gate reads the corpus and the renamed copies, never the generated beats. MEASURED on the first 714 Brontë pairs, before the filter existed: 13 beats (1.8%) named source characters — Rochester x6, Jane x3, Brocklehurst x2, Beck, Fairfax, Helen, Burns, Eyre, Reed, Rivers 0 of 714 RESPONSES did. The rename was perfect; the instruction side was not. One beat read "Saoirse confirms Rochester's flaws, then agrees in English to marry him" — a renamed name and a canonical one in the same sentence, which is the mechanism in miniature. Exposure scales with how well the generator knows the book, so it is WORST for public-domain classics and mildest for recent work. That is exactly why the Yarros and Hemingway runs came up clean and Brontë did not — their clean runs are NOT evidence this cannot happen to them, and both should be rebuilt with --source-entities if they are ever regenerated. Adds a `sourcename` reject to vet() plus --source-entities, which takes the UNRENAMED entity map and refuses any beat naming a surface from it. Firing at roughly 3% of attempts on Brontë. Also adds a `bronte` register. Brontë is the far end of the same axis from Hemingway and the register has to say so, or the beat-writer produces modern summary prose the passages never match. |
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vh
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fc834a8a23 |
bronte-corpus: gate lv-bronte for real — 0 of 365 with both controls green
The Brontë corpus's "0 of 203" was a HAND COUNT made before leak_gate.py
existed. On Yarros the automated instrument read 212 surviving where a hand
count said 86, so the hand count was never evidence. This runs the real gate,
and getting it to pass required fixing four defects the hand count could not
have seen.
CORPUS DEFECTS (repair_corpus_bronte.py, both measured):
- 1,922 words of publisher back matter inside Shirley's last unit — a
T. Nelson & Sons catalogue advertising Ainsworth, Marryat, Verne, Kingsley
and Dickens, plus a Gutenberg transcriber's punctuation list. Not Brontë,
and the source of the entity CHARLES. Same structural cause as the
Hemingway run: a splitter cuts on headings, nothing follows the final one.
- 1,368 Gutenberg italic spans. Two harms: they teach the adapter to emit
underscores, and the underscore is a word character, so the gate's
word-boundary scan cannot match inside an italicised name. An entity in
italics is invisible to the gate — the same never-renamed-AND-never-
reported shape as Yarros's possessive-only Afendra.
DETECTOR GAPS (phrase_map_bronte.json):
- Blanche is 19 capitalised against ONE lowercase — ratio 0.0526, over the
0.05 bar by a single token, so a named character with 19 mentions is
dropped by a hair.
- Grace (0.224) and Hollow (0.235) are refused correctly — both are common
nouns — but Grace Poole and Hollow's Mill are Brontë's. Sampling all 21
bare capitalised Grace found 20 are the character in direct address and
exactly one is the theological noun.
- Five compounds whose every component is non-renameable survive verbatim:
Moor House, Marsh End, Vale Hall, Bigben Close, Royd Lane. The other 77
audited phrases do not, because each has a renameable component.
GENDER (pin_known_gender.py): the inherited resolver put Jane MALE across 336
occurrences. Hemingway's base-rate resolver is strictly better here (1 wrong vs
4) but still fails on Jane, and the failure is structural, not tuning — Brontë's
three narrators are first-person, so their names appear almost only in dialogue
surrounded by other characters' pronouns. Ground truth is pinned separately from
the resolver's evaluation so the two are never conflated.
Also: min-cap lowered 8 to 3, which pulled Bertha, Ferndean, Rochesters and
Creemsvort in from below the old floor; corpus-scope rename so a name below
threshold in one novel is not printed verbatim there while renamed in another.
Gate: 0 of 365 surviving, positive control 365/365, negative control clean,
phrase audit 0 of 82. Floor stated: 3 capitals per work, 5 recurrences.
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 Vuong Hoang
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ebc4dac6d8 | grok-token-broker: hold a refreshable session credential behind a rotation-safety gate | ||
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Vuong Hoang
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6282833669 | pairs: fix the three construction defects and the abbreviation-truncation bug | ||
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Vuong Hoang
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03b4a3f62c | BabyHemingway D2+D3: entities, base-rate gender resolver, rename preset, leak gate passes | ||
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Vuong Hoang
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9598d0b4a7 | BabyHemingway D1: fiction-only corpus builder with measured exclusions | ||
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Vuong Hoang
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75051243ae | BabyYarros: amend the decision rule to gate on voice and non-memorization (operator-authorised) | ||
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Vuong Hoang
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efb734586b | BabyYarros: raw-surface scoring and a memorization check with both controls | ||
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Vuong Hoang
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713e83dd5e | BabyYarros: pre-register the pair-vs-rawtext decision rule before the arms are read | ||
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Vuong Hoang
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90ed506db3 | fix(pairs): apply_chat_template returns a BatchEncoding, and assert the mask boundary | ||
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Vuong Hoang
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9b3d3c80cb | BabyYarros Option C: instruction-pair builder and the assistant-masked pair trainer | ||
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vh
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687c6999f3 |
fix(esphome): actually disable remote-build — two switches, only one closes the port
ha-dev found the WS API and tested the read half; this runs the write. But the
command they identified is the wrong half, which is worth recording because the
naming actively misleads.
remote_build/set_offloader_settings {remote_builds_enabled: false}
the OUTBOUND half — this dashboard sending builds to peers.
Persists, reads back false, and leaves the receiver listening.
remote_build/set_settings {enabled: false}
the receiver-side master switch, per ReceiverController.set_settings's
own docstring. Tears the listener down live, no restart needed.
Set both. Verified across a restart: 6055 absent, zero peer-link bind lines,
zero mDNS advertisements, both switches read back false. Persisted at
_remote_build.enabled in /config/.device-builder.json — which did not exist
until the flag was first changed, so 'no on-disk representation' was true only
of the default state.
ESPHOME_REMOTE_BUILD_HOST=127.0.0.1 is KEPT as a backstop rather than removed.
The off state now lives in one JSON file whose in-code default is enabled:True
(controllers/remote_build/_state.py) and whose module's stores soft-recover to
an empty model on a malformed blob rather than erroring — so a lost or corrupt
settings file silently re-enables remote-build. With the env var set, that
regression binds loopback instead of 0.0.0.0.
Also finishes deploy-stack.sh properly. This was patched three times in one
session because -a is -rlptgoD and a non-root identity cannot apply owner,
group, permissions OR times to a root-owned directory; each patch fixed one
letter and the next deploy failed on the next one, every time exiting 23 AFTER
a successful transfer. The rule is now written into the script: the deploy
syncs content, the conventions own metadata. --no-o --no-g --no-perms
--omit-dir-times. Verified: clean run, destination keeps 2775 root:docker with
setgid intact.
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vh
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8073a6aed9 |
fix(esphome): bind the remote-build peer-link to loopback; finish the rsync fix
ha-dev asked for the Device Builder 1.0.0 remote-build receiver to be turned off: one instance, builds run locally, so the feature has no role, and it was binding 0.0.0.0:6055 with mDNS advertisement on a privileged host-network container that writes firmware to devices. Reading the source first changed the framing. controllers/remote_build/ _state.py declares 'remote_builds_enabled: bool = True', so nobody enabled it — it arrived on by default with the rewrite. And the flag has no on-disk representation until it is changed: neither .device-builder.json nor .device-builder-preferences.json carries it, and the only writer is the app's own command API behind the UI. Setting it from a playbook would mean inventing a schema for a model I have not read. So this binds ESPHOME_REMOTE_BUILD_HOST=127.0.0.1 — a documented env var, no entrypoint override — which removes the LAN reachability now and is verifiable (ss reports 127.0.0.1:6055, was 0.0.0.0:6055). It is explicitly NOT the off switch ha-dev asked for and the compose comment says so; the Settings toggle is one UI click and the line can go once someone flips it. Also completes yesterday's deploy-stack.sh fix, which was half a fix. --no-o --no-g stopped rsync chgrp-ing a root:docker destination as a non-root identity, but the very next deploy failed the same way one layer along — 'failed to set times on ...' — because a non-root identity cannot utime() a root-owned directory either. Same exit 23 after a successful transfer. Added --omit-dir-times. Fixing only the group half looked fixed until the next run, which is the whole reason this is worth a line in the script's comment. |
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vh
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d1769ed114 |
feat(esphome): pin 2026.8.2, relocate config into backup coverage, rotate creds
ha-dev requested all three on esh-docker-vm (operator-authorized); the stack had no canonical copy, so it is added to stacks/ rather than edited in place. Pinned ghcr.io/esphome/esphome:2026.8.2 — it was bare, which is exactly how it sat on 2025.8.2 for a year: docker pulled latest once at container creation (2026-04-20, from a layer cached 2025-08-29) and never re-pulled. Every current Everything Presence sensor failed config validation on that build. Verified after: esphome version reports 2026.8.2 and the vendor's own Pro package now validates clean (exit 0, 'Configuration is valid!'), which is the item that unblocks the six waiting sensors. Relocated /path/to/esphome/config (the upstream template placeholder, taken literally by docker) to /opt/docker/conf/esphome, matching the mosquitto pattern. Copied and checksum-verified all 5763 files before removing the original, with a tarball kept at /root/pre-change-archive/. Credentials moved off test/ChangeMe to the vaulted 32-char secret (esh-docker-vm/esphome-dashboard), passed via a host-only .env so nothing plaintext enters git. Three things the job surfaced that were not in the request: The directory is 538 MB, not the 3 KB reported — .esphome/platformio is 508 MB of PlatformIO toolchain and .esphome/build another 31 MB, both regenerable. Relocating as-asked would have inflated restic's /opt/docker source ~45x against its own ~12 MB budget, so both subtrees are excluded in /etc/restic/profiles.yaml. The 3 KB of actual config is now covered, which was the point. 2026.8.2 logs a DEPRECATION for the bare USERNAME/PASSWORD env names and says they will stop working in a future release — a silent auth loss on some later bump, on a privileged host-network container that can flash any ESP device on the LAN. Switched to ESPHOME_USERNAME/ESPHOME_PASSWORD; the warning is gone. Device Builder 1.0.0 opens a NEW listener on 0.0.0.0:6055 (remote-build peer-link) that 2025.8.2 did not have. Also fixes deploy-stack.sh: plain 'rsync -a' makes rsync chgrp the destination as the deploy identity, which since the 2026-09-14 root:docker normalisation is not root. It failed with 'Operation not permitted' and exit 23 AFTER transferring content — a loud error on a deploy that had succeeded. --no-o --no-g lets the setgid bit assign the group instead. |
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vh
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68fa80f44d |
feat(scripts): add kb — direct search over the personal Worldtree KB
The Worldtree HTTP API cannot answer a question about the operator's notes.
/search there searches conversation MESSAGES, so a note that plainly exists
comes back as a clean empty result with no error attached. On 2026-09-14 a
search for 'shrimp' returned 0 hits; searching for 'the' and 'a' also returned
0, which is the only reason the empty result was read as an empty ACCOUNT
rather than an empty KB. kb reads the markdown tree directly instead:
deterministic, ~0.9s for 7,634 files, no tokens.
Two measurements shaped the design rather than being assumed:
7,492 of 7,634 notes are INGESTED library material (4,155 fiction chapters,
3,287 book sections, 50 academic papers) and only ~142 are hand-written.
A flat relevance list buries the wanted note under a hundred chapters of
Austen, so NOTES and LIBRARY are ranked and reported separately.
Only 137 notes carry a frontmatter summary: key. Ingested notes use a
'## Summary' body heading instead and some have neither, so the description
falls back through all three shapes.
Two bugs caught by controls before shipping, both of which produced confident
wrong output rather than an error:
Deriving the word list from argv meant a quoted
NOTES — 40 matches, showing 12
Sous Vide Shrimp
ATLAS/Cooking/Sous Vide/Sous Vide Shrimp.md
Thawed shrimp should be sous vide at 135°F (57°C) for 30-40 minutes.
Beef Stew
ATLAS/Cooking/Sous Vide/Beef Stew.md
This note outlines sous vide cooking temperatures and times for stew meat
Pulled Pork
ATLAS/Cooking/Sous Vide/Pulled Pork.md
This note explains how to cook pulled pork sous vide: set the precision
Brisket Sous Vide
ATLAS/Cooking/Sous Vide/Brisket Sous Vide.md
Here''s a concise summary:
Ribs Sous Vide
ATLAS/Cooking/Sous Vide/Ribs Sous Vide.md
Here''s a concise summary:
Derusting Solution
ATLAS/Chemistry/Derusting Solution.md
This note details how to create an enhanced rust removal soak by adding specific
CNC with Raspberry Pi, USBIP & Camera
clippings/CNC with Raspberry Pi, USBIP & Camera.md
Here''s a concise summary of the note:
SF - Victor
ATLAS/Buy List/SF - Victor.md
This order confirmation details 7 separate shipments totaling $2,533.45,
Espresso Martini
ATLAS/Cooking/Espresso Martini.md
This note provides a recipe for a cocktail combining vodka, coffee liqueur,
Brazilian Cheese Bread - Pão de Queijo
ATLAS/Cooking/Brazilian Cheese Bread - Pão de Queijo.md
This note provides a recipe for Brazilian cheese bread (#brazilian #food
Congee Chao
ATLAS/Cooking/Congee Chao.md
This note provides the basic ratio (1 part rice to 7 parts water) for making
White Bread
ATLAS/Cooking/Baking/White Bread.md
Here''s a concise summary:
LIBRARY (ingested books, fiction, papers) — 635 matches, showing 12
Pride and Prejudice — CHAPTER XXI.
fiction/rex390-pnp/ch23.md
Following Mr. Collins’s proposal, Elizabeth encounters Wickham and learns that Jane has received a letter from Caroline Bingley announcing the party's immediate departure for London. While Jane interprets this move as definitive proof of Bingley’s indifference and permanent absence, Elizabeth remain
Pride and Prejudice — CHAPTER XXIV.
fiction/rex390-pnp/ch26.md
Following Bingley’s letter confirming his settlement in London and growing intimacy with Miss Darcy, Elizabeth doubts the sincerity of his attachment to Jane, while Jane remains optimistic that external influences rather than design are responsible for their separation. The sisters debate these diff
Pride and Prejudice — “On the Stairs.” CHAPTERXXVII.
fiction/rex390-pnp/ch29.md
Elizabeth reunites with Jane in London, where Mrs. Gardiner reveals that Jane suffers from periodic dejection despite her cheerful exterior, and the women debate whether Mr. Wickham’s pursuit of Miss King is motivated by mercenary or prudent reasons. Elizabeth then accepts an invitation from her aun
Pride and Prejudice — CHAPTER XXXII.
fiction/rex390-pnp/ch34.md
Mr. Darcy’s frequent visits to Hunsford Parsonage spark speculation among the locals, particularly Mrs. Collins, who suspects he is in love with Elizabeth despite her own dismissal of the idea. Their initial interactions reveal a clash of perspectives on social convenience and local attachment, whil
Pride and Prejudice — Chapter XLVI.
fiction/rex390-pnp/ch48.md
Following Lydia’s elopement with Wickham, Elizabeth Bennet informs Mr. Darcy of the scandal, reflecting that her earlier failure to reveal Wickham’s true character may have prevented the crisis and doubting their intent to marry due to their lack of funds. While Darcy offers sympathetic silence befo
Pride and Prejudice — CHAPTER XIII
fiction/rex390-pnp/ch15.md
Mr. Bennet announces that Mr. Collins, the heir to Longbourn, will visit on November 18th, prompting mixed reactions from his family regarding the entail and Collins’s pompous letter. Upon arrival, the tall and stately visitor formally compliments Mrs. Bennet’s daughters and praises the estate, thou
Pride and Prejudice — Covering a screen. CHAPTER VIII.
fiction/rex390-pnp/ch10.md
In Chapter VIII, Elizabeth endures the superficial sympathy and class-based mockery of the Bingley sisters while they criticize her muddy appearance and "low connections," even as Darcy defends her eyes and acknowledges her sisterly affection. The chapter highlights a clash of values when Darcy argu
Pride and Prejudice — “Conjecturing as to the date.” CHAPTER XLIII.
fiction/rex390-pnp/ch45.md
Elizabeth’s visit to Pemberley fundamentally shifts her perception of Mr. Darcy, as the estate’s elegance and Mrs. Reynolds’ glowing testimony reveal his true character as a kind master and brother. This admiration deepens into gratitude upon seeing his portrait, softening her view of his past pride
Pride and Prejudice — CHAPTER LVI.
fiction/rex390-pnp/ch58.md
Lady Catherine de Bourgh arrives at Longbourn to confront Elizabeth Bennet, demanding she promise never to accept Mr. Darcy’s hand based on claims of superior lineage and the scandal surrounding the Bennet family. She argues that Elizabeth’s inferior birth and lack of fortune constitute a disgracefu
Pride and Prejudice — PRIDE. and PREJUDICE
fiction/rex390-pnp/ch02.md
Jane Austen’s *Pride and Prejudice* is presented as her most perfect work, distinguished by its structural regularity where every incident drives the plot toward a denouement strictly connected to earlier events. The novel’s supreme merit lies in its masterpieces of humor and character creation, whi
Pride and Prejudice — A note for Miss Bennet. CHAPTER VII.
fiction/rex390-pnp/ch09.md
Mr. Bennet’s estate entailed on a distant relation leaves his daughters with limited financial security, yet the family’s attention is dominated by the arrival of the militia in Meryton rather than Mr. Bingley’s fortune. Mrs. Bennet successfully engineers Jane’s stay at Netherfield by sending her ou
Pride and Prejudice — CHAPTER XVI.
fiction/rex390-pnp/ch18.md
In Chapter XVI, Mr. Collins and the Bennet cousins visit Meryton, where Mr. Wickham captivates the room and initiates a conversation with Elizabeth regarding Mr. Darcy’s character. Wickham claims that Darcy unjustly withheld a valuable living promised by his father, attributing this act to jealousy
arrived as ONE element and became a single three-word pattern. The phrase
never appears in a note titled 'Sous Vide Shrimp', so the tool reported
'no match' for a note it had just found for the bare word 'shrimp'. The
needle is now split on whitespace.
Resolving the payload from dirname $0 broke the moment it was symlinked onto
PATH. Now readlink -f.
cat refuses any path resolving outside the KB root — the remote half runs as
root because the volume is root-owned.
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vh
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dfa91a8eaf |
docs(fv-ml1): add curated LLM seat catalog (lineage/provenance/cards/speed) + bench script
Adds docs/pfi/llm-seat-catalog.md, the durable hand-curated record of what each seat IS -- lineage, provenance, model-card facts, quantization, speculative decoding, licenses, and measured warm tok/s + deep-prefill depth results with their harness and date. It complements the auto-generated fv-ml1-gpu-seat-inventory.md (live placement/KV/concurrency): the two split by volatility, and the catalog defers to the inventory for any live number. Adds scripts/seat-bench.py so the catalog's speed/depth numbers are reproducible (warm decode tok/s, n=3, conc=1, median; deep prefill at ~0.97x max-model-len with an allocator-log OOM scan). Serial by design -- concurrent deep prefills would confound both OOM and tok/s. Captures the 2026-09-14 measurements: all six generative seats prefill to ~255K (coder ~16K) with zero OOM/CUBLAS/illegal-memory; warm decode 62.7-337.3 tok/s; per-seat VRAM. seat-inventory.py now cross-links the catalog in its footer. |
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vh
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c2a70c13db |
feat(fv-ml1): daily drift alarm for the seat inventory
Wires scripts/seat-inventory.py --check to a user systemd timer on nh3-dev (09:15 daily, Persistent=true so a missed run fires on next boot) that posts to althing when the committed document stops matching the live box. Alarms rather than auto-committing. A drift means something changed on the HOST, which deserves a human look -- silently regenerating the doc would erase the evidence of when the change happened and why, which is how the char-rp substitution went unnoticed for three weeks. The alarm includes the changed table rows, not just the fact of divergence, so it does not send the reader hunting. ⚠ The post goes --to infra-ops, which is the fleet ops handle the reading session also runs as. That is the documented exception -- a memo from cron to a future session, the same pattern as the Beszel alerts -- so the message says so in its first line, to stop a future session triaging its own alarm as peer mail and trying to reply to it. SuccessExitStatus=0 1 because a detected drift is a deliberate non-zero exit, not a unit failure. |
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vh
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a91b841d86 |
feat(fv-ml1): generate the seat inventory from the live box instead of maintaining it by hand
The seat documentation must stay current, and a hand-written document cannot. The LiteLLM config described char-rp as a 31B model on a host and GPU it had not been on since 2026-08-24 -- three weeks of silent drift in a file that read as authoritative, and the reason a seat spent that period serving a model nobody intended. Anything typed here drifts the same way; anything read off the running containers cannot. scripts/seat-inventory.py derives the whole document from the host: - placement and VRAM from nvidia-smi compute-apps, mapped to containers through /proc/<pid>/cgroup -- nvidia-smi reports the vLLM engine child while docker reports the container pid, so matching them directly silently yields nothing - weights and KV tokens parsed from each engine's own startup log, not derived arithmetically, with concurrency computed as KV tokens over context - architecture, layer and expert counts, and the exact quantization group scheme (W4A4 vs W4A16 distinguished) from each model's config.json - speculative-decoding method and k from the container argv, which is how the three incompatible methods on this box became visible - lineage from the .PROVENANCE.txt SIBLING files -- they sit beside the model directory, not inside it, which is why an earlier pass wrongly reported two fully-documented seats as having no provenance - gateway aliases resolved from the LiteLLM config on ana-docker --check compares the committed document against the live box and exits non-zero when they diverge, ignoring only the generation timestamp. Suitable for CI or a scheduled drift alarm; read-only throughout, safe against production. Also commits the KV_CACHE_BYTES override added to the MTP campaign runner, which asserts the flag exists in the derived argv and aborts rather than running a campaign that silently ignored it. |
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vh
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3132a16ca0 |
fv-ml1: finish the renumber the cutover missed -- 16 dead dashboard links
Every fv-ml1 link on the Homepage dashboard was broken. Measured against the
live dashboard API before the fix: 16 entries pointing at the dead 10.250.50.54
and zero at the live 10.251.50.54, covering gen, M.O.G.-SEC, Scriberr, Embed,
Rerank, Reward, Coder, Dockge and six dormant seats.
The miss was structural, not careless. fv-ml1-rename-sweep.sh works from an
allowlist assembled from files that mention the HOST, and a homepage.href label
mentions only an IP -- so every stack whose sole stale reference was a label
fell outside it. The allowlist now covers those 24 files, and records how to
derive the list next time (grep the old address, subtract history) rather than
enumerating from memory.
History is still untouched, and the exclusions are now written down with the
reason each one keeps the old address: recorded benchmark results, whose
base_url is part of a measurement's provenance; the one LiteLLM comment
preserving a retired hand-test endpoint; and the cutover runbooks, where the old
address is the subject matter.
Two bugs found while applying it, both fixed here:
- deploy-stack.sh rejected any stack name containing a dot, so qwen3.5-122b,
qwopus3.5-122b and mistral-medium-3.5 could not be deployed by the script at
all. The check exists to stop path traversal, which means rejecting ".." and
"/" -- not every dot. Traversal is now rejected explicitly and tested.
- stacks/scriberr/.env.example allowed CORS only from the dead IP and from
scriberr.ana.internal, which no longer resolves; the box is at the fv site
and DNS already carries scriberr.fv.internal. The live .env had both stale
origins, i.e. an allowlist with nothing reachable in it.
Host side, applied separately: canonical pushed for the 16 stacks whose only
difference from the host was this renumber, and an in-place address-only fix for
the nine whose host copy has genuinely drifted or has no canonical copy, so that
drift survives for a deliberate reconciliation instead of being clobbered. Every
compose.yaml on fv-ml1 now reads 10.251.50.54. The labels themselves only take
effect at container creation, so the running containers still need recreating.
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8400f3aef5 | scripts: pre-script the ana-ml2->fv-ml1 rename sweep (scoped, dry-run default, history-safe) | ||
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vh
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5558d9c7d3 |
R49/BabyYarros: voice + beat evaluation tooling and the seat-free delta_cb
Adds the Yarros-side evaluation the training exists to justify: does the adapter move arbitrary prose toward Yarros, and can the instruct arm still expand a beat to a paragraph on direction. Yarros-flavoured voice prompts (modern/neutral/ romantasy tiers so any Yarros voice in the modern tier is adapter-attributable, not prompt-supplied) and a Yarros-register beat SYS on the chat generator. voice_distance.py is the honest slice of adjudication that needs no seat: Burrows's Delta over character bigrams against held-out Yarros. Its first cut mis-framed the noise floor — it used the same-author distance (held-out vs itself) as the between-arm significance threshold, which is the target, not the threshold. Fixed to the measured floor: the within-arm seed spread, which is this metric's sampling variance at this sample size, computed from the two seeds already generated rather than assumed. Result on the built corpus, ordering base-125-tuned < instruct-tuned < base-unadapted, both adapters clearing the 0.046 measured floor (base +0.157, instruct +0.076), and the ordering corroborating the independent held-out loss ordering (Base below Instruct). One seed-pair per arm, so it corroborates rather than settles; the full frozen adjudication still needs a romantasy control panel, a second seed, and the gen seat for the beat-incumbent leg. |
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vh
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38eb40ace4 |
BabyYarros: stage the 4B-Base comparison arm, both concurrent and chained
One arm is not a comparison. On the Brontë corpus Base won held-out loss (2.814 against the instruct arm's 2.908) while instruct won instruction-following, and that trade is the open question for Skaldsong. It has to be re-measured on this corpus rather than carried over: BabyYarros is 12% larger and contemporary. Two entry points because the right one depends on a measurement rather than an argument. The box has 98 GiB free against an 18.4 GiB training footprint, so VRAM is not the constraint -- but VRAM was never the binding constraint on a GB10 that onboarding measured at 6x slower than ana-ml2 where compute predicts 2.7x, and where batching was not a throughput lever. If the box is already at its bandwidth roofline, a second job splits the same bandwidth and buys nothing. So: launch-yarros-4b-base.sh takes an explicit --allow-shared-gpu that bypasses the GPU-clear guard, and chain-yarros-4b-base.sh waits on the instruct run and refuses if it produced no adapter. The bypass is an argument and never a default, because the guard's normal job -- stopping a chain from firing into a live run -- is what keeps one lost run from becoming two. A shared-GPU launch stamps its own log with a warning that its s/it is not comparable to a solo run, since the harness is part of the number. Both carry the same gate guard as the instruct arm: refuse to start unless the leak gate report on disk says PASSED. |
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7b0580dcbe |
BabyYarros: the leak gate passes, and it found three defects nobody was looking for
The gate is new. There was no committed instrument for "does any of the author's own proper nouns survive the rename" -- the Brontë number was produced by hand -- so leak_gate.py is now that instrument, and it runs both directions every time: the same scan over the unrenamed source as a positive control, and a nonce string as a negative one. A detector that only ever sees renamed text cannot distinguish absent from blind. Run against BabyYarros as built it reported 212 surviving entities, not the 86 recorded earlier, because it scans the whole corpus rather than each work separately and it counts the sub-threshold entities rename never looked at. Three findings came out of closing that. The corpus had a typography defect of its own. The D1 notes correctly say no unwrap was needed; a different defect was there instead. The Empyrean books set their chapter epigraphs in small caps and the extractor rendered the run as uppercase while leaving the large initial as a separate token, so the corpus carried "M AJOR A FENDRA'S G UIDE TO THE R IDERS Q UADRANT" -- 106 lines, ~700 splits -- plus 52 drop caps like "T he flight field". That is where the entities called IDERS, UADRANT, NAUTHORIZED and seventeen bare single letters came from. A split initial next to an uppercased run is enough to recover the original mixed case, so the restore is exact rather than approximate: a word with a split initial was capitalised, an all-caps word without one was lowercase. Back matter was inside the prose. The builder splits on chapter headings and nothing follows the last one, so every work carried its acknowledgments, newsletter pitches and cover-artist credits -- 4,555 words naming the author's agent, editors and children, in a corpus whose entire purpose is that no identifiable name survives. And the gate passed at 0 of 314 while Afendra was still in every copy. The name never appears unpossessed, so it keyed as an apostrophe form, and rename and the gate both skip those as contractions -- unrenamed and unreported at once, which is the worst failure shape available. Baxter escaped a different way: wilder renders an in-book news article entirely in lowercase, putting the cap/lowercase ratio at 0.13 against a 0.05 bar. Then a second class the unigram scan structurally cannot see. Riders Quadrant, Flame Section, War Games and Fourth Wing -- the book's own title -- are built from ordinary words the detector correctly refuses to call names. The gate now audits recurring capitalised 2-3grams against an explicit allow list, and rename applies a phrase map after the entity pass. Every new detector flag is opt-in and off by default, and the Brontë entity map was re-derived after each change and confirmed identical in keys, surfaces and every field. The stoplist was built by reading each surface in context, which is why it is short: Violence is Xaden's nickname for Violet, and Continent, Presentation, Barrens, Originals, Montserrat, Athena, Aura, Curator and Sage are all in-world. A plausible-looking guess would have excluded most of them. Final: 0 of 325 entities and 0 of 91 audited phrases survive in any of 30 copy files, both controls passing. The sensitivity floor is stated in the gate's own output -- 3 occurrences for a name, 5 for a phrase -- because a negative without one is unfalsifiable. |
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6dba912324 |
BabyYarros: corpus built, gender resolution fixed, rename blocked on leak gate
Located the source: five Rebecca Yarros works in the Kvasir licensed library, with rights recorded as gated. Built D1 at 208 chapters and 780,744 words, which is 15% larger than the Brontë corpus. No unwrap step was needed because Kvasir's cleaner already emits flowing paragraphs, so the hard-wrap defect that cost a re-cut on Brontë does not exist here. The alphabet was re-derived rather than inherited: 23 non-ASCII letters across three forms, against F02's 4 on a smaller sample. Same ASCII-fold conclusion from a different measurement, which is the reason to re-derive per corpus. The interesting finding is a new pathology. In a rotating first-person POV corpus, every book's narrator gets the wrong gender. Measured against six names verified in the text, the pronoun resolver called Violet male, Leah male and Landon female -- three of eighteen wrong, and all three are the narrator of the book where they were misgendered. A narrator is "I" in her own book, so her name appears mostly inside the other lead's dialogue surrounded by his pronouns. This is Brontë's "Jane called male" amplified by rotating POV. Title-first resolution, which fixed it for Brontë, is nearly blind here because contemporary romance uses given names rather than honorifics. What works is the POV header: resolve each name from the chapters it does not narrate. Validated at 9 correct, 9 held, 0 wrong against the previous 7, 8 and 3 wrong, and the instrument refuses to write unless it beats what it replaces. Re-pointing rename.py surfaced three bugs, two of which would have silently corrupted the corpus. Gender came only from honorifics and the entities file's gender field was ignored, so the POV fix had no effect until wired through; that took wilder from 1 gendered entity to 13. The pool labels were hardcoded in a print statement, so any non-Brontë preset crashed. And the collision-filter log claimed it dropped names colliding with Brontë entities regardless of which corpus it filtered against -- the logic was right but the message named the wrong corpus, which is how a reader later concludes the filter ran on the wrong thing. D3 is blocked and nothing has been trained. The leak gate shows 86 of 232 renameable source entities surviving where the Brontë run reached 0 of 203. It decomposes into detector false positives that need a stopword filter rather than renaming, genuine misses among worldbuilding proper nouns, and a third class whose cause is not yet established. Training before the gate passes means fitting in-copyright text with 86 identifiable source entities intact, in a corpus F02 already flagged as small enough for leak to be a real concern. |
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e15c5ee5ea |
Instruct probe: voice and instruction-following coexist
Trained the same corpus onto Qwen3-4B instruct rather than -Base, with seed, steps and token count held so the carrier is the only variable. The chain picked checkpoint-150 by loss automatically, applying the lesson that cost a re-cut on 4B-Base. The central risk did not materialise. The assistant prior did not block the voice: curly quotes land at 16 of 18, identical to the 4B-Base tuned arm, against 1 of 18 on the unadapted control, and task-leak is 0 of 18 where the base carrier leaked 4. Instruction-following also survived raw-text training -- 10 of 10 on-beat through the chat template, the same as the untuned control. The cost is length discipline rather than comprehension. In-band dropped from 10 of 10 to 6 of 10 and the median went from 124 to 140 words. Training on Victorian prose made it wordier, which is a soft degradation and not a break. Held-out sits at 2.908 against 4B-Base's 2.814, and it plateaus without turning where the base carrier overfit at step 75. The assistant prior competes for capacity, so the instruct carrier absorbs less rather than overfitting more. What raw-continuation training does not fix is the plot furniture. The tuned instruct arm renders the beat and then drags the referent -- "He licked her clean... my master thus, my husband thus", turning the dog into a man, because the corpus is about masters and husbands. Another beat ran to 247 words and gave the narrator a list of duties. That is precisely what instruction-pair training addresses, since pairs teach render-this-and-stop where continuation teaches keep-writing. The probe de-risks the instruction-pair path without substituting for it. One metric note against future misreading: ran_on reports 10 of 10 on both arms and is uninformative on this job, because a single paragraph contains no blank line for it to find. |
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d9cf486004 |
Settle the Skaldsong architecture question with a ten-format negative result
Skaldsong's requirement is beat-sentence in, paragraph out, stitchable. That is narrower than free-form continuation and it fails differently, so it was tested directly rather than assumed from the earlier prompt work. The adapted 4B carrier cannot do it. Ten prompt formats across three seeds each -- bare, paragraph-break, labelled, epigraph, one-shot, one-shot unlabelled, three-shot, "it happened in this way", "I remember the whole of it", and the letter prompt's label-and-begin move applied to a beat -- produced thirty samples and not one that reliably renders the beat. They drift, they frame, or they truncate. The cause is structural rather than a shortfall of the adapter: "write a paragraph about this sentence" is an instruction, and a completion model has no mechanism for "about". It continues the text it is handed. Two formats failed worse than drifting and leaked pretraining task data. The paragraph-break format emitted an NLI multiple-choice item, and label-begin emitted a grammar-correction exercise. A standalone sentence followed by a blank line looks exactly like a dataset entry, and style adaptation does not remove base-model task artifacts. The same five beats through the gen seat with a style instruction and no adapter landed all ten samples inside the requested 90 to 140 word band, every one on its beat, with no drift into a following scene. The voice, however, is generic literary pastiche -- abstract-noun-heavy, fond of aphoristic openers, and over-written -- rather than Brontë. Voice without direction against direction without voice. The product needs both, which makes rebuilding the corpus as instruction-response pairs on an instruct carrier the evidence-backed option rather than more prompt cleverness. This applies to Yarros identically, because the carrier question is orthogonal to the author, so the next corpus should not re-run this experiment. Stitching also has its own failure mode, shown in the booth's third panel: the paragraphs were generated independently and the point of view slides between them, so by the fourth beat the narrator is both watching the girl carry the animals and carrying them herself. A real stitcher has to feed prior paragraphs back as context, which means the instruction-pair corpus wants multi-paragraph continuity examples and not only isolated beat-to-paragraph pairs. |
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8787daf04f |
Find the prompt recipe that works on a completion carrier
Two operator prompts settled the question the handoff prompt opened. The winner labels the artifact and then begins it: "This is the letter I wrote verbatim, my two short paragraphs, detailing the time I saw the mangy gray dog meet and then lovingly and tenderly lick a calico kitten: Auntie, You'll never believe what I saw--". Two of three seeds delivered the actual event in first person, and one is the strongest output of the sweep -- the dog following her to the mill, the kitten caught in a hedge, the dog carrying it out and laying it in her lap before licking it. Coherent arc, correct subject, no gloom-override, no meta-frame. It also reproduced the Gutenberg underscore-italics convention. It works where the handoff failed for a specific reason. The handoff could be satisfied by narrating compliance, because the letter did not yet exist. Naming the artifact and starting it leaves nothing to narrate around, so the only continuation is the artifact. The chapter-heading prompt refuted a hypothesis of mine. I predicted that rendering the title in the corpus's own conventions would make it land harder than the operator's inline form. It did the opposite: both corpus-form seeds ignored the title and opened unrelated scenes, while the inline form at least finished the heading and wrote a chapter about the story. Corpus chapter titles are short and decorative, so a long descriptive one in that slot reads as decoration to skip. A label only instructs if the model treats that slot as load-bearing. That prompt also surfaced an unnoticed consequence of the D2/D3 rename pipeline: given "Alice", the adapter produced "Alexander the Alexander, as he was known in Little London". The corpus was entity-renamed from a French/English pool, so the adapter learned that character names come from that pool and rewrites outside names into it. Callers cannot reliably name their own characters at prompt time. That is not a defect of the rename, which exists to prevent memorising Brontë's cast, but it is a usability constraint worth stating. |
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e47295d2ce |
Re-cut the 4B arms from checkpoint-75 and test an in-fiction instruction
The 4B tuned arms now come from checkpoint-75, the actual loss minimum at 2.813826 confirmed from loss-series.json rather than from reading the training log. Only the tuned arms needed re-cutting; the base arm never touches the adapter. One surprise in the comparison: step-75 and end-of-run differ on typography rather than voice. Curly quotes read 16 of 18 against 17, collapse is 0 either way, but the hard-wrap ratio is 0.33 at step-75 against 0.12 at the end. Further training washes the residual line-break habit out while held-out loss gets worse, so best loss and best typography are different checkpoints. Neither is near the original 0.85 defect and the corpus's own residual from preserved verse is 0.25. The operator's second prompt embeds the instruction inside the fiction: Abernathy tells the tale badly and then asks the narrator to retell it in a few short paragraphs. Across six seeds the model acknowledged the handoff every time and never once performed it. It wrote "I told it, briefly, to his satisfaction", and "So I wrote it out, and kept it in my pocket-book", and one seed negotiated the brief in character, objecting that it could not condense the story into a few short paragraphs because there were too many points to touch. The reason is structural rather than a failure of the adapter. In a novel, "she retold the story" is an ordinary sentence, so the likeliest continuation of a request is narration of compliance rather than compliance. A trailing paragraph break did shift the behaviour -- one seed opened in the narrator's own quoted speech -- so typography is a real lever, just not a sufficient one. That is direct evidence on the instruct question raised earlier: if the product is asking for a scene and getting the scene, no amount of in-fiction framing substitutes for a post-trained instruction-follower, which favours rebuilding the corpus as instruction pairs over more prompt cleverness. |
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25eb65e23b |
Complete the R49 carrier sweep: 4B closes the continuity gap and overfits
The three rungs now sit on the same unwrapped corpus, seed, step count and token count, so carrier size is the only variable. Held-out loss reads 3.329 at 0.6B, 3.018 at 1.7B and 2.814 at 4B -- deltas of 0.311 and then 0.204, diminishing but still real. 4B answers the question the rung existed for. Scene-level continuity holds: on the office-kitchen prompt it produces a named character with motivated dialogue, a spatial layout the narrator navigates, and a physical description, all in one passage, where 1.7B wrote pretty but eventless prose about opening doors and looking at stars. On the letter prompt it opens the letter, promises to quote it, and then quotes it across a paragraph break. Voice saturation is also the best of any rung: curly quotes 17 of 18 against its own base arm's 1 of 18, and collapse 0 of 18 against 4 of 18. Two findings that change earlier conclusions. 4B is the first rung to overfit inside one epoch. Its series runs 2.832, 2.816, 2.814, 2.820, 2.824, 2.825, 2.825 -- a minimum around step 75 and then a turn. Both smaller rungs plateaued without turning, so the optimal epoch count shrinks as the carrier grows and my earlier "one epoch is right for this corpus" holds only for the small end. The consequence is operational: the adapter directory holds the end-of-run weights at 2.825 rather than the step-75 best at 2.814, and it exists as a recoverable checkpoint only because save_steps was set. The voice arms were cut from the end-of-run adapter, so the booth understates 4B slightly. The tone-override also appears to close. On the operator's frame prompt asking for a wonderful story, 1.7B held the frame on every seed but killed the animals on two of four; 4B kept them alive on both seeds, and one of them had the narrator doubt the story he was told and supply a parallel childhood memory to explain the doubt. That is a narrator with an interior position on the tale. Two samples per arm, so directionally right rather than established. |
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4cee4b179d |
Launch the 4B rung and record that voice transfer carries subject matter
Rung 3 of the sweep is training: Qwen3-4B-Base, one epoch, seed 4919, the same unwrapped corpus, 159 steps at roughly 37.8 s/it for about 100 minutes. Carrier size remains the only variable across the three rungs. A two-arm voice test is chained behind it, gated on the adapter existing, so the rung is readable when it lands rather than needing a second round trip to become informative. The finding worth keeping came from an operator prompt rather than from my test set. Asked for a wonderful story about a stray dog licking a calico kitten, framed as reported speech, the 1.7B adapter held the frame across all four seeds and was unmistakably Victorian throughout -- and two of the four turned the premise into animal death, with the cat licking the puppy to death and the narrator's interlocutor answering that he wished they were all dead. That is not a coherence failure. It is Charlotte Brontë's preoccupations arriving alongside her sentences: Jane Eyre opens on a beaten child, Helen Burns dies, and Villette is saturated with grief. Train 680k words of that into a small carrier and a request for something wholesome reaches for mortality. My nine test prompts were all emotionally neutral and structurally could not have surfaced this. The operator's prompt found it on the first try, which is worth recording as a property of the test set rather than of the adapter. The implication for the regime is that "voice transfer" includes tone and subject, so wanting the voice without the gloom is a corpus-selection or prompt-framing problem rather than a training-length one. Also observed: one seed closed its anecdote and began "CHAPTER XIX. THE CHILD'S CLOSET", having learned book structure unprompted. The base control on the same prompt went modern and essayistic, so the shift is the adapter rather than the carrier. |
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9e18fd58ec |
Complete R49 rung 2 and booth the three-way voice comparison
Both rungs now sit on the same unwrapped corpus with seed, steps and token count held, so carrier size is the only difference and the effect is attributable: held-out 3.329 at 0.6B against 3.018 at 1.7B, a gap of 0.311 nats. The chained 0.6B rerun closed the confound the unwrap opened. Two things in those numbers need stating or they will be misread. First, the original wrapped-corpus 0.6B reached 3.172, which looks better than the unwrapped 0.6B's 3.329 and is not. Different corpus means a different held-out set, and the wrapped version's 5.7% newline tokens are near-deterministic after a 70-character line, so they deflate the loss with cheap wins. Removing them removed the easy tokens. It is a measurement artifact, not a regression. Second, a correction to my own earlier claim: I twice described the 0.6B run as still descending and undertrained at 3.172. Its series reads 3.176, 3.173, 3.172, 3.172 -- it flattened. All three runs plateau, so one epoch is about right for this corpus rather than short. The three-way booth puts 1.7B base, 1.7B tuned and 0.6B tuned side by side on the same nine prompts and seeds. The base arm is the control that matters: curly quotes go 0 of 18 on 1.7B base to 15 of 18 on 1.7B tuned, and worksheet-or- explainer collapse goes 3 of 18 to 0 of 18, so the shift is the adapter rather than the larger carrier. Hard-wrapping fell from 0.85 to 0.18, confirming the corpus unwrap carried through into the adapter. Sense partially returned. The 1.7B arm produces locally coherent sequential Victorian prose where the 0.6B produced word salad, but scene-level continuity still breaks mid-passage. One observation held loosely: curly quotes are slightly lower at 1.7B than 0.6B, which would fit a bigger model's stronger priors resisting the adapter at the same rank. That is untested and is not offered as established. |
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935b35ac2e |
Unwrap the Brontë corpus and launch the 1.7B rung
Operator: "start the 1.7b training." The 0.6B adapter learned the Gutenberg transcription's ~70-character line breaks along with the prose -- its output wrapped at a mid-length-line ratio of 0.85 against the base model's 0.00. That is typography rather than style, and every further rung would have inherited it, so the corpus is reflowed before rung 2 rather than after the sweep. The reflow joins 57,430 of 85,380 paragraph blocks and keeps 27,950. Verse is the hazard a blind join would destroy, so the decision is per block by median line length: blocks whose lines cluster near the wrap width are flowed prose, blocks of consistently short lines keep their breaks. Every kept multi-line block in the sample was genuinely verse with its lineation intact. No line ended in a lone hyphen, so the space-join could not split a word across lines. The acceptance check is content identity -- " ".join(text.split()) byte-identical before and after -- and it passed on all 852 records, proving only whitespace changed. Concrete cost of the old defect: 5.7% of the training budget was newline tokens. The same words pack to 5,210,112 tokens unwrapped against 5,525,504 wrapped. The 1.7B run is live at 159 steps and roughly 18.7 s/it. Everything but the carrier and the corpus is held from the 0.6B run: seed 4919, rank 32, lr 1e-4, seq 4096, batch 1 by accum 8, one epoch, eval and save every 25 steps so the minimum is located rather than assumed. That corpus change is a second variable and it is named as one. A 0.6B-vs-1.7B comparison is descriptive, not attributable, until the chained 0.6B rerun on the same unwrapped corpus lands behind it -- gated on the 1.7B actually producing an adapter, because a chain that fires on failure turns one lost run into two. "Did sense come back at 1.7B" is a within-arm reading and survives the confound; any between-rung delta does not. The original wrapped corpus is untouched, so the 0.6B run's pinned corpus sha 3959036cf851bf62 stays reproducible. |
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b8dbe71a1c |
memory: snapshot — R49 1-epoch pilot complete and awaiting adjudication; MeroMero A4B quantized, v2 blocked; althing 3.6.2 rolled
Ships the two pending code changes alongside the memory that describes them: train_voice_lora.py gains --eval-steps/--save-steps (the 3-epoch pilot overfit with per-epoch eval and save_strategy="no", so the minimum was neither visible nor recoverable), and the althing post-office compose is pinned to 3.6.2. Index rewritten: in-flight compressed from 176 lines to the live state, three detail files added for R49 D1-D3, the MeroMero four-failure chain, and the althing rollout. Seven closed pre-08-27 entries archived; the guards held back the rest because they carry open deferred pointers. |
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eb75713c1b | Wire Beszel fleet filesystems, GPU telemetry, dashboard and alerts | ||
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20bbb95113 |
fix(r49): loss-series collector silently dropped every eval record
The LossLog callback filtered on `"loss" in logs`. Trainer emits eval under `eval_loss` with no `loss` key, so every eval record was discarded and loss-series.json showed zero eval points while the log a metre away carried `eval_loss: 3.198`. An artefact that omits data which demonstrably exists reads as "no eval was run" rather than "the collector dropped it", which is the failure mode that costs someone a re-run. Collector now accepts either key. Seed 2 gets it from launch; seed 1 is already running with the old code, so recover_eval_series.py parses the eval records back out of its log -- the data was printed, not lost -- and the chain runs that recovery before cutting the generation arms, so the artefact is complete before anything reads it. The two seeds therefore differ in logging code but not in training math: the callback only affects what is recorded, never what is computed, so the weight trajectories remain comparable. Noting it because a difference between the two arms whose spread sets the decision threshold is worth stating even when it is provably inert. |
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8fff722f2c |
feat(r49): incumbent arm generated against the concrete gen seat, not the stale H02 name
brokkr-smithy corrected H02's incumbent naming: qwen3.6-35-a3b-heretic was retired from the gateway roster on 2026-08-15 and is not what Skaldsong would call today. Verified against the gateway and the seat itself -- alias `gen` resolves to hosted_vllm/qwen3.8-27b-uncensored on ana-ml2:8015, container vllm-gen, 262,144 ctx. The arm targets that. 24 records, style-prompted on the same prompts and sampler as the other arms. Alias resolved at run start AND end and confirmed stable across the run, per the fleet rule that an artefact records the backing model rather than the alias. Two things recorded rather than glossed: The harness is NOT matched to the other arms and the artefact says so. Base and adapted arms are local transformers on gx10; the incumbent is a served NVFP4 27B reached over the gateway, and it is an instruct model receiving a style instruction where the others are base models receiving none. That asymmetry is the comparison H02 asks for -- prompted imitation against trained voice -- but it must not be reported as if the harnesses were identical. The gateway echoes the ALIAS in each response's `model` field, so a row read on its own would have recorded "gen" as provenance -- the same class of mistake that inflated an exposure count 4.7x on this fleet. Rows now carry alias_echoed_by_gateway beside backing_model_resolved and its date, and the generator was fixed at source rather than only in the emitted file. Sanity: median 392 completion tokens, zero records opening with markdown or meta-commentary, output reads as continuation prose. The style prompt was written to be a fair incumbent rather than a strawman, since this arm is what the adapter must beat. |
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375244ad05 |
feat(r49): D2/D3 complete and the H02 pilot is training on gx10
Entity resolution, deterministic rename augmentation, packing and the pilot trainer. Qwen3-0.6B-Base is training now: 507 steps, 11.2 s/it, ~1h35m. D2 -- gender resolution is TITLE-FIRST, and that is a change from F02's method rather than a port of it. F02 used pronoun proximity and recorded that it is structurally blind to the first-person narrator, whose name appears mainly in dialogue surrounded by other people's pronouns. Measured here, proximity called JANE MALE -- the narrator of Jane Eyre and the single worst entity to get wrong. Titles have no such blind spot: Miss Eyre, Mrs. Fairfax, Mr. Rochester, Madame Beck, M. Paul, and a 19th-century novel is saturated with them. Measured: 16 entities resolved, zero wrong, every ambiguous case landing on HELD -- shared family surnames like Helstone and Pelet genuinely belong to both a man and a woman and hold as they should. Held means ungendered, not unrenamed. A HELD entity is still renamed, from the gender-neutral surname pool, because the operator's Yarros directive was "rename all proper nouns" and holding a place leaks it -- Thornfield appears 100 times in Jane Eyre and is as author-specific as Riders Quadrant was. Substituting a neutral token makes no gender claim, so no gender claim can be wrong. D3 -- pool is French + English per the operator, weighted per work by setting: Brussels novels 60% French, Yorkshire novels 25%. Locales restricted to fr_FR/fr_BE/en_GB/en_IE; en_US and en_AU carry modern surnames that are wrong register for the 1840s. The pool is filtered against Brontë's own 75-letter alphabet, so French accents stay and Czech/Latvian marks do not. Two collision defects found by running the leak gate rather than trusting it: `Burns` and `Marie` were drawn as replacements while being Brontë characters -- F02's collision filter was built against Yarros and does not carry -- and then `Pierre-Yves` passed a whole-string filter while `Pierre` (Mademoiselle St. Pierre) is a Villette character. The filter now compares by COMPONENT. Final gate: 0 of 203 source entities survive in any of 24 copy-files. Trainer records what the run RESOLVED to rather than what it requested -- attention implementation, dtype, device, corpus sha and harness cleanliness are read back off the live objects. transformers 5.x has dropped warmup_ratio, caught by reading the signature after the first launch failed on it; the 3% warmup is computed into warmup_steps instead. |
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ba8dac2c80 |
feat(r49): D1 corpus built and green — Charlotte Brontë, 680k words, 951k tokens
scripts/r49-corpus/{build_corpus,verify_corpus}.py; corpus staged at
gx10:~/r49-corpus/. Catalogue ids verified against gutenberg.org's own search
rather than recalled. Charlotte only -- the Bell poems are co-authored and the
Gaskell biography is a different hand, so neither belongs in a single-voice corpus.
Jane Eyre 1260 · Villette 9182 · Shirley 30486 · The Professor 1028
680,291 words · 142 chapters · 950,974 Qwen3 tokens (1.40 tok/word)
alphabet 75 letters, 23 non-ASCII · round-trip lossless · 0 byte-fallback
All 11 acceptance checks pass, including both tokenizer legs run against the pilot
carrier itself. With a real denominator the projections tighten: at 6 rename copies
x 3 epochs = 17.1M tokens, the 0.6B pilot is 1.98 h.
THE ALPHABET INVERTS THE YARROS RESULT. Brontë writes French constantly -- Villette
is set in a French-speaking city, Jane Eyre has Adèle, The Professor is set in
Brussels -- so the corpus carries é 432, è 237, à 93, ê 79, ô 48 plus œ and æ. F02
measured Yarros at 0.0002% non-ASCII and derived an ASCII-fold for the name pool.
Under F02's own subset rule the Brontë pool may keep FRENCH accents and must still
exclude the Czech/Latvian/Slovak/Hungarian marks that never appear here. The fold is
per-work, and this is the first corpus where deriving it changes the answer.
Typography was inconsistent across works and it was the transcriber, not the author:
Shirley uses straight quotes and `--` with zero em-dashes while Jane Eyre and
Villette use curly and em-dash. Normalised toward what the text means.
Three defects, each found by running something rather than reasoning about it:
`Produced by` matched Brontë's own prose four times, which is the adjective-"minor"
shape again and is fixed by anchoring boilerplate patterns to line start; asserting
open/close quote counts must be equal is wrong, because 19th-century multi-paragraph
speech legitimately runs a surplus of opens, so the real error signature is that no
paragraph may begin with a closing quote; and The Professor's table of contents puts
two chapter names per line, so a bare regex returns 38 headings for a 25-chapter
novel and a minimum-gap filter still leaks its tail -- the rule that works is that
the body's "CHAPTER I" is the last one in the file.
Records the operator's pilot ruling: trial on Qwen3-0.6B-Base first, move up only if
it produces something useful.
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04950c2881 |
feat(training-probes): re-measure the R49 name pool under the Qwen3 tokenizer
brokkr-smithy flagged that R49 F02's name-pool token splits were measured with the Qwen3.5-2B tokenizer, so the dense-Qwen3 carrier ruling invalidates them. Measured rather than left on their critical path; handed over as input to their re-check, since the dictionary and the adjudication are theirs. The multi-token property strengthens on the chosen carrier: pool multi-token 88.0% -> 90.3%, mean tokens 2.33 -> 2.46. A smaller vocabulary fragments more, so Qwen3's 151,936 splits names into more pieces than Qwen3.5's 248,320. The operator's requirement that names be multi-token, so the drafter reconstructs them from the prefix instead of recalling one embedding, is better served after the ruling. Positive control: the Qwen3.5 column reproduces F02's published figure on the same pool and tokenizer (F02 89% / mean 2.35; here 88.0% / 2.33), so the instrument recovers a known-true value before being asked about an unknown one. The pool is deduped across locales, which reconciles male_given and female_given exactly against the dictionary's own totals block. |
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36f1b70a88 |
chore(erp-tune): purge intermediate checkpoints (~74 GB); R49 carrier settled on dense Qwen3
Two operator rulings, 2026-09-09.
"purge intermediate checkpoints" -- seven checkpoints/ directories removed with
literal paths, one rm per line, after confirming none was a symlink and that
every run's final adapter/ is an independent real directory:
pfi-gx10 run-03c 11G run-04 16G run-05 9.2G run-06 9.2G = 45 GB
ana-ml2 run-01 12G run-02 12G run-03 5.9G = 29 GB
gx10 419G->374G used, 496 GB free. /tank/erp-tune 392G->363G with zfs list -t
snapshot empty, so the space is genuinely returned rather than snapshot-held. All
eight adapters re-verified by sha256 after the deletion, matching the values
recorded during the mirror. Merged artifacts deliberately untouched -- they are
not checkpoints, and the ~550 GB of superseded merges stays a separate call.
"use dense qwen3" -- the R49 H02 carrier sweep becomes Qwen3-{0.6,1.7,4}B-Base,
which overrides the Qwen3.5 arms H02 names; brokkr-smithy owns that file and was
told directly. Qwen3-4B-Base staged and benched to complete the family:
Qwen3-0.6B-Base 0.616 B 1.707 s/step 2,399 tok/s spread 0.6%
Qwen3-1.7B-Base 1.755 B 2.895 s/step 1,415 tok/s spread 0.8%
Qwen3-4B-Base 4.089 B 5.714 s/step 717 tok/s spread 0.3%
The dense 4.089 B carrier still trains 33% faster than the hybrid 0.765 B one.
Projected per voice 2.7 / 4.6 / 9.1 h; the three-arm sweep at two seeds is ~33 h
of GPU, ~10 h if H03's corpus floor holds. The three Qwen3.5 checkpoints stay
staged so the decision is reversible behind an fla install.
Also recorded: verified at 22:45-22:48 PT that nothing is training on gx10,
ana-ml2, nh3-dev or irv-ml1, and that brokkr's own run07-gate close states
"Nothing is owed. No battery to run." Run 7 has no servable artifact left. And a
correction to a standing lesson -- the bracketed-class trick does not defeat a
wrapper's argv, since the invoking shell's command line carries the literal
pattern; observe the artifact instead.
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7db6c44bcd |
feat(r49-prep): author-voice LoRA regime prep on gx10 — carriers staged, throughput measured, adapters secured
Prep for the BabyBronte / brokkr-smithy R49 author-voice adapter regime, plus the operator's "keep the adapter" ruling made durable. Measured on pfi-gx10 (GB10, sm_121), n=10 per arm after 3 warmup steps, seq 4096, LoRA r=32 on q/k/v/o + MLP, bf16, sdpa, grad-checkpointing on: Qwen3-0.6B-Base dense 0.616 B 1.707 s/step 2,399 tok/s Qwen3-1.7B-Base dense 1.755 B 2.895 s/step 1,415 tok/s Qwen3.5-0.8B-Base hybrid 0.765 B 7.581 s/step 540 tok/s The dense 1.755 B carrier trains 2.6x faster than the hybrid 0.765 B one on 2.3x the parameters (~6x per parameter), with more LoRA modules adapted (196 vs 96). Spreads of 0.6-2.6% put instrument noise an order of magnitude below the effect. Cause: Qwen3.5 is 18 linear-attention (SSM) layers to 6 attention, and no fused linear-attention kernel is installed on the box. Grad checkpointing is not the culprit (19%, and saves 2.6x memory). Batching is not the lever for either family -- both sit at this box's roofline at batch 1. Projected per voice on a Brontë-scale corpus: dense 0.6B 2.7 h, dense 1.7B 4.6 h, hybrid 0.8B 12 h. The hybrid would take longer than the 7 h 26B-A4B tune the regime exists to replace, so the carrier family is now an open decision with a recommendation for the dense Qwen3 line -- the design doc's original pin. Two further Qwen3.5 findings, both measured rather than read off the config: the Base checkpoints ship a vision tower (153/297 model.visual.* Linear tensors that target_modules="all-linear" would train on text) and an MTP head, both dropped for free by loading through AutoModelForCausalLM -- which renames modules relative to the vLLM serving path, so adapter binding needs the sampled-target-changed check on the serving side; and cross-document packing is unsafe because SSM state ignores the attention mask, breaking the per-copy name-consistency invariant the design doc calls sacred. Neither exists on dense. Adapter disposition, per the operator's ruling: all five gx10-resident ERP adapters (run-03c/04/05/06/07) mirrored to ana-ml2:/tank/erp-tune/run-<N>/adapter matching the layout runs 01-03 already used, byte-totals identical both sides and sha256 matching on every adapter_model.safetensors. /tank/* is deliberately excluded from ana-ml2's restic sources, so the profile gains one documented carve-out for /tank/erp-tune/run-*/adapter, verified by resticprofile --dry-run to expand to exactly those eight paths. Nothing is training and nothing is queued. |
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9b9f0625c9 |
fix(refresh): refuse to promote an empty capture over a good snapshot
ssh exiting 0 is not proof the capture is usable — the inspect script can emit nothing and both refresh scripts would mv that over a good system-details.txt and report 'ok (0 bytes)'. Every reader tests the snapshot with -s, so the writer was producing an artifact its own readers call invalid: a guard whose test disagrees with its writer's contract has quietly stopped guarding. Prompted by brokkr-smithy-dev hitting the same shape from the other side (a -s test against a sentinel written with touch, a precondition that could never pass). - empty capture -> refused, previous snapshot kept, host counted as failed (exit 1) - capture under 1/4 of the previous -> promoted but flagged, since a host can legitimately shed services and the script should not guess - header + CLAUDE.md contract lines corrected to say what is actually guaranteed - verified red (empty inspect -> FAIL, snapshot intact, rc=1) then green (real host -> ok 6727 bytes) |
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a34a72fc09 | feat(erp-tune): run 7 launched on pfi-gx10 (opening-split slot + mask union) — config, launcher, builder, runbook; erp-seat: pin vLLM nightly 311b3513 (forced tool_choice 1/9 -> 6/9, round trip clean), README on the gemma4-parser design limit | ||
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14dd9ab90c |
feat(egress): fleet SOCKS5 residential egress on nh3-scale (100.64.0.1:1080), successor to the retired nh3-dev danted; yt-voice-clipper repointed and back up
- scripts/setup-nh3-scale-socks-egress.sh: dante-server on CT107, mesh+fleet ACL only, After=tailscaled + Restart=on-failure; run via pct push/exec on nh3-pve - YTVC_PROXY on irv-ml1 -> socks5h://100.64.0.1:1080 (override, untracked); worker recreated; end-to-end job verified with proxied/direct controls - YTVC Homepage href/siteMonitor -> irv-ml1.nh3.internal:8000 (was the dead wg0 IP) |
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3fec668bf2 |
feat(erp-tune): run 6 on pfi-gx10 — jenerallee78 ARA-abliterated base (index 33c59654) pulled + byte-verified, run-5 recipe byte-held, launched under operator-2026-09-08-rnd-run6
- scripts/erp-tune-gx10/pull-verify-jenerallee78.sh + base-pin-jenerallee78-shards.txt: revision-pinned root-shard pull, 32/32 sha256+size vs brokkr-smithy pins, index set-equal to stock, STOCK tokenizer set installed over the repo's (which bakes in a 256-token truncation); repo originals kept as *.repo - scripts/erp-tune-gx10/run-06-gx10.json + launch-run-06.sh: run-05 config with the base swapped, recipe-r6, survivors-r5 verbatim, stock template path - docs/runbooks/gx10-run-06.md: pull/verify record, free-check result (encode reproduces run 5 exactly), hf download --include gotcha, gate naming (erp-seat-base-ara / erp-tune-v6) |
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265357efb2 |
ops(erp-tune): stage + launch R47 ERP-seat SFT run 5 on pfi-gx10
Run 5 = the dependency-forcing corpus arm: airoboros-3.2 OUT of the 20% slot, govreport/clean-v1 (496) + qmsum/clean-v1 (97) IN, at run 4's lr 2e-04 with everything else held. kvasir byte-identical (survivors-r5 = survivors-r4 minus airoboros plus the two new roots whole). Operator authorized the launch to infra-ops directly; grant operator-2026-09-07-rnd-run5. Canonical copies of the config, launcher and survivors builder; runbook docs/runbooks/gx10-run-05.md. Launch gates all passed (7/7 root shas + shard hashes, survivor join 8,212 = recipe, holdout disjoint, window_count==1 on all 593 slot rows, realized [mix] slot loss 3.46% vs preregistered 3.4%). 524 steps. persistent-memory current-state updated: run 5 LAUNCHED + training. |
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dae77ee118 |
feat(pfi-gx10): stage ERP-seat SFT run 3c — verified, not launched
Rehome run 3c from ana-ml2 to pfi-gx10 unchanged: same corpus, base,
recipe and hyperparameters, different host. Slower (~13.3 h vs ~2.5 h)
and correct — an Anaheim breaker trip costs a 40-minute drive each way
and 13 hosts down, three of them SureFire client machines, while the
GX10 is a ~240 W appliance at NH3 that can take nothing else down.
Verified rather than assumed, because ana-ml2 ran transformers 5.15.1
on x86-64 and this box runs 5.16.1 on aarch64 — the silent
backend-delta class that has already voided conclusions here:
- both 49 GB base shards sha256-match ana-ml2's (size equality is a
weaker claim and was already true)
- a full encode was run into a throwaway dir and the encoded corpus
compared byte-for-byte: 197,360,233 B, sha256 c08bb1fe2ecb0be3,
identical. Every aggregate matched too. That verified artifact is
what the run will train on — it is seeded into run-03c/encode-cache
- the harness's own suite: 122 passed on aarch64
- the config generator asserts key-by-key that no non-path value
differs from run-03c.json
The encode-cache filename differs by design (base_model_path is part of
the key) — an input hash, not an output hash. Documented so it is not
misread as drift, or "fixed" by faking /tank on this box.
Corpus is copied to local NVMe; the box mounts no NFS. nh3-nas is now on
the same subnet, which makes mounting it tempting and still wrong under
a 13 h unattended run.
The launcher refuses on a live pidfile rather than a pgrep: `pgrep -f
erp_sft_harness` invoked over ssh matches the invoking shell's own argv.
That self-match cost a shell during staging.
Not launched. 13.3 h is the operator's call.
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0f748ea54e |
feat(searxng): move to nh3-docker, update, and expose as an MCP tool
The ana-docker instance was returning zero results for every query while reporting healthy — 4.5 months stale (2026.4.17 against a current 2026.9.3), its engine scrapers rotted against sites that had changed. /healthz proves the web app answers and says nothing about whether search works, so seven days of green sat on top of a search box that found nothing. Moved to nh3-docker rather than updated in place, because the colo egress is the other half of the problem: 38.120.12.42 is a datacenter address that DuckDuckGo and Startpage CAPTCHA, while nh3-docker egresses residentially at 70.230.226.88. Same reasoning as the fleet's residential proxy for yt-dlp, applied at the source instead of around it. Config corrected along the way: base_url said searxng.pfi.local, a name retired on 2026-08-19, while the environment said something else — the env won so nothing broke and the file quietly lied. The karmasearch.videos removal key never matched, because the engine's real name has a space. scripts/searxng-health.sh asserts results > 0 across three unrelated queries. That is the check that would have caught this, and the only kind that can: the mechanism was healthy throughout. services/searxng-mcp exposes it as `web_search` at user scope, so every Claude Code session has it. Zero results raise rather than returning an empty list — an empty list is indistinguishable from a broken aggregator, which is precisely how this hid. Old instance stopped and removed; DNS alias repointed to searxng.nh3.internal. |
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6ca455a15f |
feat(scripts): provision-mac-dsh.sh — one script for a Mac, end to end
Three Macs and six accounts were done by hand, and the fourth would have repeated every mistake the first three taught. This script carries them. Each guard is something a hand-run got wrong first: - an account may not own its own home. A `sudo mkdir` before sysadminctl leaves /Users/<account> root-owned; the account then authenticates, gets a shell, has a correct $HOME and cannot write to it. Surfaced on the Studio as a bare "Permission denied" hours after the account looked fine. - `sudo -u` keeps the CALLER's $HOME. Without -H the install's rm -rf aims at the wrong account — it did, at a working install, and only permissions stopped it. The remote half refuses to run unless $HOME matches the target. - the provider ships a hard-coded model catalog that the web GUI reads INDEPENDENTLY of agent-default-model, so a correct default still showed DeepSeek models in the picker. `models:` replaces it. - reasoningEffort / maxTokens / defaultContextWindow are all measured against the seat; the harness defaults fail on every one. - the key is scoped per machine and the scope is VERIFIED (200 on gen-reasoning, 403 on gen), not trusted from the mint. The first run found two more: it named the vault item after the IP (`mac-10-0-10-10/`, unreadable beside esh-mac-studio) and its config check used grep -A3 where the block needs -A4, so it printed an empty model and passed anyway. Both fixed, and verification now asserts the model rather than only the answer token — a check that cannot fail is not a check. Run twice against the same account to confirm idempotence, then against vhpfi. docs/runbooks/mac-provisioning.md carries the operator-run stage and the traps that are not the script's to solve. |