The Command Center header, settings sidebar, chat sidebar and README still
showed the old dotted "PROJECT N.O.M.A.D." badge with the retired backronym.
The earlier naming sweep removed the text strings but could not catch a
raster asset.
Swap in the vector primary badge from the brand kit (nomad-primary.svg) and
add object-contain so the hexagon keeps its true 0.866 aspect instead of
being stretched to fill the square boxes.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
GpuPassthroughRemediationProvider returned early unless the NVIDIA
runtime was registered with Docker. AMD doesn't register one, so the
log-based CPU-fallback detection added in v1.35.0-rc.1 never ran on
AMD boxes. On a Phoenix1 iGPU running ollama:rocm with /dev/kfd and
/dev/dri passed through, Ollama logged library=cpu while gpuHealth
reported status "ok".
The gpuHealth side had its own bug. hasNvidiaRuntime and
hasRocmRuntime were set only inside the lspci probe branch. When lspci
returned a plausible controller, the else branch reported "ok" without
probing and left both flags false. A blind reinstall would not have
helped either: gfx1103 needs HSA_OVERRIDE_GFX_VERSION=11.0.0, and
without the gfx marker or ai.amdHsaOverride a reinstall rebuilds the
same CPU-bound container.
- Add resolveExpectedGpuVendor(). It reads the nomad_ollama container
config first (nvidia DeviceRequest, ROCm image tag, /dev/kfd), then
the nvidia runtime, then the AMD GPU type when no container exists.
/dev/dri alone is not treated as AMD. A CPU container on an AMD box
is trusted as deliberate (#1232 fallback, acceleration disabled).
- Gate the provider on the expected vendor. NVIDIA auto-reinstall is
unchanged but now skips when the container requests a GPU with no
runtime registered. AMD is detect-only: the provider logs whether a
reinstall would change the container and never reinstalls itself.
- In gpuHealth, set the runtime flags up front and let Ollama's
startup log decide health whenever a GPU is expected, whatever lspci
returned. A CPU-only log now reports passthrough_failed and skips
the nvidia-smi exec. lspci stays the display source when clean.
- Parse the first GPU "inference compute" line instead of the last
line, which could be the CPU fallback device, and recognize Vulkan.
Move the startup-log reader into ollama_compute so both callers
share it.
- Report amdReinstallWouldChange, amdGfxTarget, currentHsaOverride and
suggestedHsaOverride on AMD passthrough_failed. The gfx target is
parsed from Ollama's "amdgpu is not supported" line (best-effort).
- Add GpuPassthroughAlert, shared by Settings > System and Settings >
Models. When a reinstall would rebuild the same AMD container, it
offers "Fix: Set GFX Override" instead of a reinstall. The dialog
saves ai.amdHsaOverride and then reinstalls.
- Expose ai.amdHsaOverride through the settings API. The value lands
in the container env, so only x.y.z, "none" or empty is accepted.
- Silence the HSA override resolver's logging on the gpuHealth poll.
The #1325 case where no GPU runtime is expected and lspci reports a
controller still returns "ok" unprobed.
Fixes#1344
Refs #1325, #1232
The post-rerank relevance floor rejects noise but passes coherent
off-topic questions, and it gets worse as the library grows. Adding
Gutenberg prose, the Python tutorial and MDN pages to the eval corpus
took the off-topic leak rate from 22% to 67% at the 0.62 floor.
Score cutoff does not fix it. The weakest correct top hit scores 0.666
while "write me a haiku about autumn leaves" pulls Walden at 0.705.
A cosine floor and a top-vs-median contrast test both cost recall
faster than they cut leaks.
- Add rag.relevanceCheck (default off). After the floor, the tasks
model, or the chat model when none is set, gives one grammar-constrained
on_topic verdict for the whole retrieved set. Off topic means no
context and no citations. Any failure keeps the chunks unjudged.
- Add a Settings > Models toggle recommending an 8B+ tasks model.
On llama3:8b the check cuts off-topic leaks from 67% to 6% for about
5 points of core recall@5 and ~0.6s per turn. On 3B models it rejects
most valid questions, which is why it is opt-in.
- Add 6 distractor documents and an off_topic suite (18 unanswerable
questions, 7 distractor controls) to the eval corpus.
- Report per-tag leak rates and leaked cases with top scores in
eval:retrieval. Add --judge-model to measure the check and --dump to
export pre-floor candidate pools for offline gate simulation.
- Pin the check off in eval:generation so a local setting cannot move
scores.
- Record the distractor sweep on RAG_MIN_FINAL_SCORE. The 0.62 default
stays: 0.65 halves leaks at no measured recall cost but leaves only
0.016 of margin.
The corpus fingerprint changes to b4ebe5dce8699f5d. Retrieval reports
from before this commit are not comparable, and a new baseline is
committed.
Refs #1341
planPrompt() returned the response reserve as num_predict, and the
reserve was clamped by MAX_RESPONSE_RESERVE = 1024. Chat answers
stopped at 1024 output tokens regardless of window size, often
mid-sentence, and the normalized stream chunks dropped Ollama's
done_reason, so neither the UI nor API clients could discern between
a cut-off answer and a finished one.
- Decouple the generation cap from the reserve. num_predict is now the
space left in the window after the prompt, less a 5% (min 64 token)
margin for estimator error, with the reserve as its floor. Raise
MAX_RESPONSE_RESERVE to 8192 so it only bounds prompt hold-back.
- Carry done_reason through all four OllamaService chat paths. Native
forwards Ollama's done_reason; compat maps OpenAI's finish_reason.
- Log length-limited stops in OllamaController with num_predict,
num_ctx and tokens generated.
- Show a truncation notice on cut-off answers, with a Continue button
on the latest one that sends a normal follow-up turn.
Generation evals before and after this change are not length
comparable.
Closes#1342
handleSendMessage awaited createChatSession before the optimistic render,
so on a slow request the message the user just sent did not appear at all,
with no spinner and nothing to retry. A failed session creation was worse:
a bare `return` left no message and no error, so the app looked like it had
ignored the user.
Render first, and surface a failure the same way a failed response is
surfaced. Completes #1211 alongside the stream-abort fix in #1220.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Chat sent num_ctx, num_predict and nothing else, so every turn decoded at
whatever the backend picked: temperature 0.8, top_p 0.9, no min_p. On a
heavily quantized 1-3B model that is the wandering, repetitive output people
read as "the local model is bad".
Adds `ai.responseStyle` with four profiles. min_p is the lever, not
temperature: it floors relative to the top token, so it truncates hard on a
confident distribution and barely at all on a flat one, which is where small
models start to wander. top_p stays at 1.0 rather than stacked on top of it.
repeat_penalty moves with the style, because a grounded answer legitimately
repeats a part number inside the 64-token window: `focused` relaxes it to
1.05, `creative` tightens it to 1.15.
`auto` is the only style that defers to the model. Plenty of library models
ship author-tuned samplers (qwen3 sets 0.6/0.95/20), so those win key by key
and NOMAD fills only the gap, which in practice is min_p. A style the user
picked by name overrides them, or it would silently do nothing on half
their models.
The compat transport drops min_p, so a profile carries a separate compatTopP.
Passing top_p 1.0 to a backend with no min_p behind it would sample the raw
distribution, which is worse than the 0.9 it replaced.
Resolved in the controller, so the grammar-constrained task calls keep their
temperature 0. An explicit temperature still outranks a profile's, which is
what keeps the eval harness deterministic.
`eval:generation --style` is new and load-bearing: temperature 0 makes min_p,
top_p and top_k inert, so a default run cannot see this change at all.
`--style=off` sends no samplers and no temperature, and is the control.
Verified against Ollama 0.32.9, min_p accepted. 22 unit tests.
Content Explorer hardcoded `lang: 'eng'`, so it could only ever show
about 1,300 of the catalog's ~10,900 books. Adds a language selector
sourced live from the catalog's own language feed, with book counts,
defaulting to English and remembered per browser.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
* feat(kb): add per-file active/inactive toggle for search inclusion
Implements the per-file toggle agreed on in #1119, in place of disabling
ZIM auto-discovery by default. Any indexed file (ZIM, upload, or other)
can now be excluded from RAG search results instantly, without deleting
or re-embedding its vectors.
- Vectors stay in Qdrant permanently; each point's payload carries an
active boolean. Toggling flips this payload in place, both directions,
with no re-embedding cost.
- Search filter is a denylist (must_not: active == false), not an
allowlist, so a point missing the field entirely is still found by
default -- search correctness never depends on backfill timing.
- embedAndStoreText() looks up a file's existing active state before
writing new points, so retries, force re-embeds, and replaced-content
reindexing never silently reactivate a file the user explicitly
toggled off.
- Applies uniformly to all non-admin_docs buckets (ZIM, uploads, other),
matching how the rest of this pipeline already treats buckets, rather
than special-casing ZIM.
New POST /api/rag/files/active endpoint and KB panel toggle switch,
following the existing updateFileCollection pattern.
Real vector deletion for genuinely deleted/replaced files remains
#1170's separate concern.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
* feat(kb): group personal KB uploads by collection with bulk toggle
Groups personal KB uploads into collapsible per-collection header
rows (with an "Uncategorized" bucket for files with no collection) to
reduce clutter in the file table. Each collection header also exposes
a bulk active/inactive toggle to flip every file in that collection at
once.
Also fixes three pre-existing bugs found in the collection-assignment
dropdown while building this: the popover was clipped by table cell
truncation, clipped again by the table wrapper's overflow, and the
combobox query was stale-filtering results on open.
Refs #1193
* fix(kb): widen the modal for the Active column and coerce active to a boolean
Both found by browser-verifying on NOMAD3.
The Active column adds ~57px, which put the table back over the modal width and
reintroduced the exact defect #1198 fixed: the Delete button falls off the right
edge at every viewport. Measured on the box at 1018px of table against 961px of
usable width at max-w-5xl. Widened to 6xl.
MySQL returns tinyint(1) as 0/1 rather than a boolean, and the raw 1 reached the
DOM as aria-checked="1". That is not a valid ARIA value, so a screen reader is
told nothing useful about whether the toggle is on. Coerced in the service so
every consumer sees a real boolean, with a !! guard in Switch as well.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
* fix(kb): validate the bulk collection toggle's input before sanitising
sanitizeCollectionName ran before the type check, so a form-encoded request
sending collection[] as an array reached .trim() on a non-string and produced
an uncaught TypeError, surfacing as a 500. The vision controller already
guards this the same way.
Also documents why requiring `active` to be a real boolean is load-bearing
rather than mere input hygiene: a cross-site HTML form can only send the string
"true", so that check is what keeps a bulk Qdrant write across every point in
the index out of reach of a form POST from another origin. Worth a comment,
because coercing it would look like a harmless usability fix.
Found in a security review of the release PRs.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
---------
Co-authored-by: John Cortright <jcortright@zscaler.com>
Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
The swatches reused the tile tint, which is 10% opacity. That reads well across
a 190px card and makes six 28px squares indistinguishable from one another, so
the picker looked like six empty outlines. Caught by looking at it.
Each color now carries a solid class alongside its tint: the picker shows the
color at full strength, the tile stays subtle. A test asserts the swatch class
is solid rather than an opacity variant, since reaching for the tint again is
the obvious mistake.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
"Address" was vague for a field that takes a URL. "No scheme? We'll default
to http://" named a concept most people do not have a word for, and it was not
needed: the live preview already shows http:// appearing the moment someone
types a bare address, which demonstrates the behaviour rather than describing
it. The preview stays, the sentence goes.
The two link tile validation messages follow the same wording. The custom URL
override message is left alone; it belongs to a different feature.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
"still tellable apart from" read badly; it is now "distinguishable from".
Also switches the spelling I had introduced to American, matching the rest of
the product and the existing schema and constants (custom_color, PIN_COLORS).
Limited to the files this branch adds; the two pre-existing benchmark
components that use the British form are left alone rather than churned.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
A link tile rendered on a flat surface colour, which read as a stark white card
against the filled green app tiles. Tiles now take one of six colours from the
brand palette, chosen when creating or editing one, and the card is tinted from
it.
Tiles stay visually distinct from managed apps regardless of colour: the dashed
border and the external-link marker carry that, not the hue, and the tint is
deliberately light so the distinction survives every option.
Class names are written out in full rather than interpolated, because Tailwind
scans source text for literal class strings and would silently drop a computed
one, leaving the tile untinted. A test asserts that.
Added as a separate migration from the one introducing is_link_tile, since that
has already run on the test box and editing it in place would leave fresh and
upgraded installs with different schemas.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Users want things they already run to appear on the dashboard: a NAS, a router
UI, a printer, a Pi, a container they started themselves. Adds a tile they
address themselves, with a name, one URL field, an optional description and an
icon from the curated set.
Chosen over adopting containers from the Docker daemon, which is what community
PR #1239 proposed. Adoption only reaches containers on this Docker host and has
to guess: it took the lowest published host port and assumed http, which picks
the wrong port for anything publishing several (Portainer 8000 against 9443,
Jellyfin 8096 against 8920) and breaks entirely for HTTPS. A tile the user
addresses has no guessing in it, covers the whole LAN rather than one Docker
host, and has no lifecycle that can break.
One URL field rather than separate host, port and path, because people paste
URLs and it gets https and sub-paths for free. A bare "192.168.1.50:8080" gains
http automatically, which is what most LAN devices need. normalizeCustomUrl and
getServiceLink already did exactly this work for the custom app URL override, so
both are reused rather than duplicated.
Stored as a service row with no container behind it: is_link_tile marks it,
custom_url carries the destination, and the service_name is namespaced
nomad_link_* so it can never collide with a curated entry. The seeder only
iterates its own DEFAULT_SERVICES and never prunes unknown rows, so a reseed
cannot touch or remove a tile.
The tile is deliberately styled differently from a managed app, outlined and
dashed with an external-link marker rather than filled, because if it looked the
same users would expect Start, Stop and Update and file bugs when those controls
are not there. Removing a tile arms a confirm first, since it is user-entered
data with no undo.
Icons come from a fixed 36 shared by the picker and the server-side validator,
so the two cannot disagree about what is selectable. DynamicIcon renders nothing
at all for a name it does not know, which would leave a silent hole in a tile.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Drops the condition examples from the dashboard tile. Also brings it in
line with the length and punctuation of the neighbouring tiles.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Deleting a pin was a single click on a trash icon with no confirmation and no
undo. Pin names are short and repetitive by nature ("Well", "Cache", "Fishing
bridge", "Fishing bridge west"), so the name in the row is not enough to tell
the user which place they are about to lose.
The trash icon now arms rather than deletes: it selects the pin and flies the
map to it, then the row offers Delete or Cancel. The user sees the actual
location before confirming.
Escape cancels. The armed state also clears if that pin stops being listed --
deleted from elsewhere, or filtered out by a search -- so a stray confirm can
never end up pointing at a different pin.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Dropping w-72 when the picker was rewritten left the absolutely positioned
popover to shrink-wrap its content. The six 1fr columns collapsed to a few
pixels each and the 18px glyphs overflowed and overlapped, so the grid rendered
as a smear. Restored the explicit width, added shrink-0 to the cells so a
narrow container can never squash them again, and centred them in their tracks.
Caught by looking at it. The DOM assertions I had run -- 36 buttons in a
grid-cols-6 -- all passed while the thing was visually broken, which is the
whole reason a frontend change needs eyes on it and not just a query.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Review changes from looking at the feature running on NOMAD3.
The icon picker offered every Tabler icon *and* every Font Awesome icon via
namespace imports: 160 pages, whose first page included the Amazon and Amazon
Pay logos, an "Ad" badge and text-alignment glyphs. It also took the maps chunk
from 864 kB to 5,774 kB. Replaced with a hand-written set of 36 map-relevant
icons in a 6x6 grid -- water, shelter, medical, power, comms, transport,
terrain, hazards -- with no search box or paging, because 36 fit on screen.
Maps chunk is back to 904 kB, +40 kB over dev rather than +4,910 kB, and the
react-icons dependency is gone entirely since Tabler was already present.
Icon resolution moved into marker_icons.ts so the panel and the pin share one
definition, with a caller-supplied fallback (the pin's inner glyph defaults to
a filled circle, the list to a map pin). An icon later removed from the set
still renders as the fallback rather than blanking the marker.
Dropped the tree view and the List/Tree band: grouping pins by hue or by icon
organises them by an attribute the user picked arbitrarily, and grouping by
first letter is worse than sorting. Search and sort cover the real need. "Hide
all" lived inside the tree view, so it moved up into the header where it
applies to whatever the list shows -- it is the one bulk control worth keeping.
The title bar now closes the panel, matching the "Pins" button that opens it;
clicking a title to open but having to hit a small X to close is an asymmetry
that makes the panel feel fiddly. The list also reclaims the height the removed
band was using.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Salvages @kennethbrewer3's work from #836, which had drifted onto a stale base
(GitHub showed 231 files; the real change is the map UI plus a migration).
Marker visibility (individually and Hide All), per-marker icon and custom hex
colour with contrast-adjusted icon colour, search, sorting and a tree view over
the marker list, coordinate search and fly-to with URL parameters
(?lat=&lng=&zoom=), creating a marker from typed coordinates, and markers
rendered as SVGs anchored to true coordinates rather than approximately.
Name, notes and preset colour already existed; the new columns are
custom_color, icon, icon_color and visible.
Dropped from the original as stale-base noise rather than his work: unrelated
duplicate changes to the Ollama, Docker, download, RAG and ZIM services, the
API reference and getting-started docs, README/FAQ/CONTRIBUTING, the installer
script, and a revert of AppLayout to a version predating the compact sidebar.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Closes#1176. Salvages @gabegraves's work from #1178, rebased onto the
RagPipelineService refactor that landed after it was written.
Adds JPEG/PNG/WebP attachments to chat over multipart, leaving text-only JSON
requests on their existing path. Images are normalized server-side to bounded
JPEG with metadata stripped, capped on count/size/pixels/output, and the
temporary uploads are cleaned up on every validation path. They are attached
only to the latest user message, are excluded from RAG, titles, logs and
persisted history, and are never written to storage.
Vision support is resolved per model from what the backend actually reports --
OpenAI-compatible /v1/models metadata, then Ollama /api/show, then llama.cpp
/props -- never inferred from a model name. A model that reports no vision
support has attachments disabled with a visible explanation; a backend that
reports nothing is allowed with a warning and its rejection is translated into
plain compatibility guidance rather than a raw error.
Changes from the original:
- Prompt assembly moved into RagPipelineService in the meantime, so the
controller half is rebuilt against the trace and the multipart-aware
collection filter is now the only one (dev's request.input() version would
have silently dropped the collection on every image request).
- Added a native-path converter. dev split chat into native and OpenAI-compat
paths after this was written; Ollama's native /api/chat does not take OpenAI
content parts, it takes a sibling `images` array of bare base64. Without this
every image request on a native Ollama backend would fail.
- Dropped the model-recommendation change (selectRecommendedModels and the
Qwen3-VL fallback entry). Displacing a recommended model at first-time setup
is a product decision and is being taken separately. The "Supports images"
label in Easy Setup is kept: it describes what is already on offer rather
than changing it.
- Dropped the DEFAULT_QUERY_REWRITE_MODEL download prompt his branch carried,
which dev deleted in d022c2d.
- Removed a duplicate checkModelHasThinking; kept dev's memoized getModelInfo
path, since thinking detection is not part of this feature.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
Closes#1179.
Surfaces the documents an answer was drawn from as a "Sources" list under the
assistant message, with the archive date where one is known, and persists it so
reopening a past conversation still shows what backed each answer.
Offline there is no second opinion to check an answer against, so provenance is
the only signal the user has that a claim came from a real document rather than
from the model. This is the other half of retrieval being allowed to decline:
one says when nothing relevant was found, this says what was found.
Citations are built from the chunks actually injected into the prompt, not from
everything retrieval returned. A chunk dropped by the budget planner never
reached the model, so citing it would credit the answer to a document it was
not based on -- the exact failure the list exists to prevent.
The archive title and date have been written into the vector payload by the ZIM
ingestion path all along and were simply never read back, so this works on
already-embedded content with no re-embed.
Rebased onto the RagPipelineService refactor, which landed after this was
written: the citation list now comes off the pipeline trace rather than the
inline retrieval block that used to live in the controller. Entries with
neither a path nor a title are skipped rather than shown as "Unknown source" --
a row the user cannot act on makes an answer look sourced when it is not.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
The history table rendered nomad_score for every row, so a v2 run showed its
legacy score while the Benchmark Details card directly above it showed the v2
one. The same run read as 65.0 in the table and 1036.1 in the card.
Rows predating v2 have no v2 score and can only show the legacy number, so the
two scales necessarily share a column. They differ by more than 10x, and
without the scale on screen a v2 run sitting above older runs reads as a
collapse rather than a rescale. Legacy rows now carry a "/ 100" suffix, which
names the scale in place and reuses the wording the details card already uses
("Legacy scale: X / 100").
This compounds the re-run guidance in the release notes: someone re-runs on
1.34 as asked, gets a real v2 score, and their own history then shows the old
number as though the machine got slower.
Frontend only. getAllResults() already returns full rows, so nomad_score_v2
was in the payload the whole time.
Verified on the NOMAD2 dev environment with a seeded history matching a real
mixed case (one v2 run at 1036.1 plus two pre-v2 runs): the v2 row shows
1036.1 with no suffix and agrees with the details card, and the legacy rows
show 71.1 / 100 and 86.5 / 100. Inertia typecheck shows the same 30
pre-existing errors as dev with none in this file.
There was one cutoff, Qdrant's score_threshold at 0.3, and nomic scores
unrelated text well above it, so every question retrieved *something*
(nonEmptyRateOnRefusal 1.0) and rag_context wasted four lines asking a 3B
model to "silently judge" relevance. That is a classification a number
should decide, not a micro model.
Adds `RAG_MIN_FINAL_SCORE`, a floor on the post-rerank score, applied before
source diversity. The floor judges relevance, the 0.85^n penalty judges
redundancy. Nothing clears it and nothing is injected. `score_threshold` stays
at 0.3 as the candidate net. Exposed as `rag.minRelevance` with a module-
scoped TTL cache invalidated from `updateSetting`.
The floor is calibrated and the harness was describing the wrong number:
aggregate() bucketed semanticScore, so its percentiles measured raw cosine
while the new knob filters the reranked score. Both axes now, and the gap
matters: recall falls at 0.60 on the semantic axis, 0.66 on the final one.
floor recall@5 precision@5 emptyOnAnswerable nonEmptyOnRefusal
0.00 0.991 0.221 0% 100%
0.62 0.991 0.524 0% 60%
0.66 0.991 0.695 0% 60%
0.67 0.972 0.704 1% 60%
Default 0.62, not the last-lossless 0.66: the refusal win is complete at
0.62 and 28 documents is a thin basis for spending margin. 0.60 is the
honest floor. Three of five refusal goldens are near-corpus by
construction, where declining is the generation tier's job.
Both eval tiers pin the floor to the constant and ignore the setting, for
the same reason the harness never sets skipRetrieval.
4 metrics improved against baseline, no regressions.
Chat was run through Ollama's OpenAI-compatible /v1 endpoint, which has no
context-size field, so the num_ctx we sent was silently discarded and the
entire NUM_CTX_LADDER was dead code. Every conversation ran at the backend
default and was truncated from the middle (where history and
retrieved context actually sit). Measured with identical ~7k-token prompts:
2,060 tokens processed against 7,049 on the native endpoint, and with the
needed fact in the discarded middle the old path hallucinated a plausible
wrong number.
Transport: add a native /api/chat path using the already-installed ollama
package, sending a real options object (num_ctx, num_predict, temperature,
seed) plus keep_alive. The OpenAI path is still used for LM Studio and llama.cpp,
minus the ineffective num_ctx and with include_usage so both paths return
prompt token counts. /api/show is now read for trained context, parameter
size, quantization and any modelfile num_ctx. The <think> stream normalizer
moves to app/utils/think_stream.ts so both transports share it; it gains a
flush() that fixes a dangling partial tag being dropped at end of stream.
Token accounting: replace chars/N with a structural segmenter scaled by a
per-model factor learned by EWMA from the prompt_eval_count every response
already returned and threw away. End-to-end estimator error is 4.6% against
18-20% for a fixed divisor — qwen2.5 converges to k=1.26 where llama3 sits
at 1.00, so no single global constant serves both.
Context window: resolved once per model from trained context, the exact KV
cost derived from GGUF metadata (head_count_kv, not head_count — GQA makes
them differ 4x), and available VRAM, then memoized. Memoization is
load-bearing: asking for a different num_ctx makes Ollama unload and reload
the model, stalling the turn and discarding the KV cache. The floor never
overrides the model's trained ceiling — tinyllama trains to 2048, and a
blind 4096 floor pushes RoPE past anything the weights saw.
Prompt budget: planPrompt allocates explicitly instead of delegating
overflow to silent backend truncation — response reserve, then fixed blocks
(system and current query, never dropped), then RAG chunks whole and
best-first, then history in whole user+assistant turns, evicted newest-first
in blocks with an elision marker. Block eviction keeps the prefix stable for
several turns rather than shifting on every one.
KV-cache ordering: the per-turn retrieved block moves behind history to the
tail, so the stable prefix stays byte-identical turn to turn. At turn 14 of
a long conversation, prefill is 231ms at the tail against 539ms at the front
(~1ms/turn growth against ~25ms). The win is conditional — with a large
retrieved block and short history the two measure the same — so both
orderings ship behind RAG_PLACEMENT. The per-turn query rewrite also moves
to the tasks model; on a single-slot Ollama it was evicting the chat model's
cached prefix on every single turn.
Also: OLLAMA_CONTEXT_LENGTH and OLLAMA_KV_CACHE_TYPE=q8_0 on the container
(q8_0 is treated as headroom, never as a budgeting assumption, since
unsupported architectures fall back to f16 silently), a Context Window
setting in Settings > Models, and budget fields on PipelineTrace.
Eval: golden suites (--suite) so the new long_context goldens cannot move
the aggregates the committed baselines were recorded against, plus budget
and estimator-error metrics through the report path. Retrieval is unchanged
and eval:compare reports no metric outside the tolerance band; the
long_context suite scores correctness 1.000 with historyElided 0.500 (the
two eviction cases, by design). Unit tests 337 -> 386 passing, same 7
pre-existing failures.
Ingest-side CHAR_TO_TOKEN_RATIO is deliberately untouched: changing it
re-chunks the corpus and invalidates retrieval baselines, which belongs in
its own measured change.
Allows users to optionally specify a model to use for ancillary tasks (chat suggestions, chat titles, etc.) instead of strictly using the last used model. This means aesthetic/non-critical work can be passed to a small, lightweight model instead of a heavy reasoning model used for chats.
If a model is not selected in the AI Assistant settings (`/settings/models`), the existing behavior of using the last used model is retained.
Two layout defects in the Knowledge Base modal, both found during
v1.34.0-rc.4 QA.
The collection combobox list was clipped to a single row's height on
every row of the table. The cause is not stacking order - StyledTable
gives each cell `truncate` (overflow:hidden) plus `relative`, so an
absolutely-positioned child cannot escape the cell box. No z-index can
win against a clip. The modal body is also an `overflow-y-auto`
scroller, so simply opting the cell out of `truncate` still left rows
lower down clipped by the scroller instead.
Render the list in a portal with fixed positioning instead, measured
from the input's rect and flipped above when it would run off the
bottom of the viewport. Reposition on scroll and resize (capture
listener, so any ancestor scroller counts). The click-outside handler
now also checks the portaled list, otherwise mousedown on an option
would close it before the click landed.
Separately, the modal was capped at max-w-4xl (896px) while its table
needs 906px, so the Delete button lost its right edge for everyone
regardless of monitor size. max-w-5xl gives the table room with none to
spare wasted.
Verified against a real build on a test appliance.
The banner shipped with two highlights while the 1.34 line delivered 21
features, so it undersold the release. Adds the three with the widest
user-facing surface: Score v2, NOMAD.md and Knowledge Base collections.
Also converts the two existing bullets from em dashes to spaced hyphens
to match project copy convention.
Kept to five bullets - this is a dashboard alert, not release notes.
The chat modal's pop-out button called window.open('/chat', '_blank').
/chat is served by the admin app itself, so this spawned a second browser
window for a same-origin internal route.
That breaks anyone running NOMAD as an installed web app or in kiosk mode:
clicking it leaves a stray window they then have to get back out of, which
is exactly the complaint in #1123.
Navigate with router.visit instead, and relabel the button from "Open in
New Tab" to "Open Full Chat" so it describes what now happens. IconMessage
isn't in the DynamicIcon registry (deliberately curated for tree-shaking),
so use the already-registered IconArrowRight.
Refs #1123
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
* feat(drug-reference): compact header + single dashboard tile
Phase 1 of the drug-reference redesign:
- AppLayout gains an opt-in `compact` prop (small inline logo+title) so tool
pages reclaim the ~230px the full branding block costs; drug-reference/index
opts in.
- Consolidate the two dashboard tiles (Drug Reference + When to use what) into a
single Drug Reference tile with a broadened description (/conditions already
redirects to /drug-reference).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(drug-reference): tabbed redesign — search-by-drug + by-situation + FDA data
- Split /drug-reference into three tabs (Headless UI TabGroup): 'Search by
drug', 'By situation', 'FDA data'. Each tab runs only its own direction,
which removes the two-overlapping-sections confusion.
- Search by drug: results grouped by active ingredient (IngredientGroup,
single-ingredient groups first, combos after), drug-first result rows, and a
collapsible de-jargoned filter drawer (Over-the-counter / Prescription, Form,
Sort) that auto-collapses once results land.
- By situation: multi-select symptom chips → an 'Treats all N selected'
intersection section pinned on top (computed client-side from each
situation's result set) + one union group per situation.
- FDA data: the download/ingest control + status moved behind its own tab
(the pre-ingest empty state stays the prominent download prompt).
- DrugResultRow now leads with the active ingredient (drug-first) by default,
or the brand when rendered inside an ingredient group.
- Rename 'Compare interactions' → 'Compare label warnings' to match what it does.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(drug-reference): rank situation matches single-ingredient-first
The raw FDA indication match floods a situation (e.g. Headache) with
many-ingredient homeopathic products, burying real OTC drugs and leaving the
cross-situation intersection empty. Pull a wider result set (200) and sort by
active-ingredient count ascending — not a medical judgement, the same
'single-ingredient first' principle as the drug-search grouping. Now real
drugs (acetaminophen, ibuprofen) surface on top and the 'Treats all N selected'
intersection actually finds the shared OTC options. Per-situation cards cap the
display to the top 25 (ranked), intersection uses the full set.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(drug-reference): first-open disclaimer gate + first-group-expanded
- Add a required disclaimer modal on first open of the Drug Reference (Jake's
mechanism): comprehensive not-medical-advice notice the user must acknowledge;
acceptance is saved to the browser's localStorage (versioned key) so it isn't
shown again on that browser, while new browsers/devices see it on first open.
Non-dismissible (no backdrop/Escape) — only the acknowledge button closes it.
- Search-by-drug: expand the first ingredient group by default, collapse all
subsequent groups (IngredientGroup gains an explicit defaultOpen prop,
replacing the size heuristic).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(drug-reference): intersection-first multi-select
Multiple situations now lead with the 'Treats all N selected' intersection and
only break out per-situation sections when the intersection is empty (nothing
treats all) — with a 'No single option treats all N of these' explainer. Keeps
the view combined when there's a shared answer, and only fragments as a fallback.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(drug-reference): compact header on detail/interactions/conditions pages
Apply the compact AppLayout header to the drug detail, interactions, and
condition pages so they match the redesigned index instead of the full-height
branding block.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(drug-reference): rename interactions heading to 'Compare label warnings'
Match the page heading + title to the button label, so the name reflects what
the view does (each drug's own FDA-labeled warnings side by side, not a
cross-drug interaction checker).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(drug-reference): offline FDA drug labels, conditions, and remedies
Adds an offline medical-reference feature with three coupled layers:
- Drug Reference: full-text search over openFDA drug-label indications,
a detail page per label, and a side-by-side single-drug comparison view.
A two-phase background pipeline downloads the openFDA label parts to the
storage volume (resumable) and ingests them into the search table.
- Conditions ("When to use what"): a curated spine of first-aid situations
that maps each situation to matching OTC drugs, each linking back to its
Drug Reference detail page.
- Curated remedies: hand-authored natural and home-remedy entries drawn from
US-government public-domain sources (NCCIH, CDC, MedlinePlus, FDA), shown
with their source links and the same safety disclaimers as the rest of the
feature.
The drug-reference and conditions layers are intentionally coupled: the drug
detail page shows the situations a drug treats, and the conditions controller
reads the same drug_labels table.
Safety surfaces ship as written. The amber SafetyBanner ("informational only,
not medical advice, not an FDA endorsement, not a drug-interaction checker, in
an emergency call emergency services") renders on the condition pages and the
search page; the detail and comparison pages carry their own "not a cross-drug
interaction checker" callout; and every page carries the openFDA CC0 source
citation and no-FDA-affiliation footer.
Wiring on this branch:
- start/routes.ts: the /drug-reference and /conditions page GETs plus their
/api/* groups.
- commands/queue/work.ts: the drug-download and drug-ingest queues, both at
concurrency 1. The two drug queues get a per-queue stall override
(lockDuration 1_800_000, maxStalledCount 3) because each part is one long
stream; every other queue keeps the existing 300000 default.
- inertia/pages/home.tsx: Drug Reference and "When to use what" tiles. The
icon and display_order are a starting point, open to change.
- types/kv_store.ts: the two drugReference.* keys the pipeline reads and writes.
- package.json: yauzl and stream-json (plus their @types), used by the ingest
job to stream the label JSON out of the downloaded zips.
The app reads the conditions and remedy data from the compiled TS constants in
app/data/; the repo-root collections/*.json files are the browseable mirrors.
The natural-remedies standalone test reads collections/natural_remedies.json to
assert the two stay in sync, so that file is also a test fixture.
The four standalone tests pass (drug_interactions, drug_ingest_status,
conditions, natural_remedies). tsc reports no errors in the feature code.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* chore(drug-reference): drop a fork-internal comment reference
* fix(drug-reference): address review — defer FULLTEXT, fallback remedies prop, strip fork refs
- migration: wrap the FULLTEXT ALTER in this.defer so it runs after the
deferred createTable (was silently swallowed, index never created)
- controller: add remedies:[] to the index() error fallback (required prop)
- strip fork-internal issue/spec references from ported comments
- tsconfig: exclude tests/standalone (node --experimental-strip-types only)
- correct the varchar(768) byte-math comment; extend remedy-spine test
* fix(drug-reference): make the interaction comparison readable at five drugs
The comparison view laid its columns out on an equal-fraction CSS grid
(repeat(N, minmax(0, 1fr))), so each added drug shrank every column; at the
five-drug maximum the FDA interaction text was squeezed into unreadable slivers.
Lay the columns out with flex instead: full-width and stacked on phones, then
fixed-width columns that scroll sideways from the sm: breakpoint up, so they
never shrink below a readable width. Theme the columns with the same palette as
the rest of the page (they were on stock gray), and give the headers a fixed
min-height so columns line up when drug names wrap.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* feat(collections): route a 'dataset' tier resource to the drug pipeline
Add an optional `type` discriminator to SpecResource ('zim' | 'dataset',
absent == 'zim'), so the tier installer can carry a DB-ingested resource
alongside ZIM files. ZimService.downloadCategoryTier branches on it: a
'dataset' resource dispatches the existing FDA download+ingest pipeline
instead of RunDownloadJob, guarded against duplicate dispatch by the drug
ingest status. Every existing manifest entry has no `type` and keeps the
exact ZIM path.
Widen InstalledResource.resource_type to include 'dataset' and exclude
dataset rows from the ZIM/map catalog-update scan (datasets aren't
filename-versioned; their freshness path is separate). No dataset rows are
written yet: the InstalledResource 'dataset' row on ingest-ready, the
manifest entry, install-gating, and the downloads-aggregator integration
are follow-up commits.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* feat(drug-reference): rework into an opt-in medicine-standard tier dataset
Reshapes the offline FDA drug reference from a built-in feature into curated
content installed by selecting the Medicine / Standard tier, per maintainer
direction.
- install-state: the ingest writes an installed_resources 'dataset' row on
ready (version = the openFDA export_date), threaded installer to download to
ingest; the tier-status math and the home-tile gate read it. Manual ingests
write no row, so install-state stays tied to the curated path.
- manifest: declare the dataset in the medicine-standard tier (runtime fetches
the remote manifest, so this also needs to land upstream).
- install-gating: the drug-reference home tiles render only when installed.
- uninstall: DrugReferenceService.uninstall() stops the two drug queues, deletes
the on-disk parts, truncates drug_labels (schema kept), clears the KV markers,
and drops the install row. Best-effort, logged, scoped to drug data only.
- downloads: the download phase reports the canonical {percent, downloadedBytes,
totalBytes} shape as one drug-data card in the Active Downloads aggregator with
cancel/remove; the heavy ingest stays in the IngestStatus surface with an
Indexing handoff on the card.
- auto-update: a daily DrugAutoUpdateJob compares the manifest export_date and
re-downloads when newer, gated on installed + no active job.
typecheck clean; the drug standalone suites pass. Three points are flagged in
code for the maintainer: the InstalledResource 'dataset' approach, the tier
home, and the export_date string format.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* fix(downloads): keep the drug download card live across all parts
The Active Downloads card filtered to the deterministic jobId, but the
download's continuations run under auto-generated jobIds (only part 0 uses the
deterministic one). So the card tracked part 0 and then vanished while parts
2..N kept downloading. The queue is concurrency 1, so collapse to whichever
single part is in flight and report the deterministic jobId: one card tracks
aggregate progress through the whole download and cancel/remove still routes.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* feat(drug-reference): co-locate a persistent safety note with affirmative remedy guidance
Add RemedySafetyNote at the head of every natural-remedy section — the two on
Drug Reference and the one on "When to use what" — so the "informational only,
not medical advice, seek real medical care in an emergency" framing appears with
the guidance itself, not only in the page-top banner. Replaces the terse
per-section caveat with the same amber alert language as SafetyBanner.
Addresses the upstream #1040 review request that the disclaimer be unmistakable
and present wherever affirmative self-care guidance appears, not a one-time banner.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* fix(drug-reference): fold dataset freshness into the content-auto-update path
The drug dataset auto-updated on its own daily cron that ignored the
contentAutoUpdate.* master switch, so it would refresh even with content
auto-update turned off, and it didn't ride the content-update path the way
ZIMs and maps do.
Move the export_date freshness/apply orchestration onto
DrugReferenceService.attemptAutoUpdate(), add
ContentAutoUpdateService.attemptDrugDataset() gated on the same enabled +
window config, and have the hourly ContentAutoUpdateJob drive both. Retire
the standalone DrugAutoUpdateJob. The ZIM/map attempt() path is unchanged.
Addresses the upstream #1040 request to wire the openFDA export_date check
into the content updater so the dataset updates alongside ZIMs and maps.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* feat(drug-reference): strengthen the remedy note to consult a clinician before combining with meds
Widen the affirmative-remedy safety note from "talk to a clinician before use"
to explicitly cover using a remedy AND combining one with a medication the user
already takes — the interaction case is the higher-risk path for an off-grid
user self-treating.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* feat(drug-reference): gate affirmative remedy content behind an off-by-default flag
Add drugReference.remediesEnabled (default off), independent of the tier
install. When off, the server emits no remedy data at any boundary — the
drug-reference page prop, conditions show, and the /api/conditions/drugs
situation search — and the "Natural" filter is hidden, so installing the
medicine-standard tier lights up the verbatim FDA label search and the
condition-to-OTC matching but not the hand-authored self-care and herbal
sections. No user-facing toggle: it is flipped on after a clinician content-pass.
Implements the upstream #1040 split-by-risk request: the regulated label content
ships with the tier; the authored remedy guidance stays gated until sign-off.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: Jake Turner <52841588+jakeaturner@users.noreply.github.com>
Shows a dismissible dashboard banner to users who submitted a benchmark under
v1 scoring but don't yet have a Score v2 result, nudging them to re-run so the
community leaderboard gets their v2 number.
- Show logic (benchmark_service.shouldShowRerunBanner): has a result with
submitted_to_repository=true AND no result with nomad_score_v2 AND the
dismiss KV isn't set. Self-clears two ways — dismiss sets the KV, and any v2
run gives a result a nomad_score_v2 so the condition flips off on its own.
- New GET /api/benchmark/rerun-banner + useBenchmarkRerunBanner hook (mirrors
useUpdateAvailable), rendered as a dismissible Alert on the dashboard with a
"Re-run benchmark" CTA to /settings/benchmark.
- New KV key benchmark.rerunBannerDismissed (boolean) in both KV_STORE_SCHEMA
and the SETTINGS_KEYS whitelist (the PATCH /system/settings validator enum);
dismiss writes it via the existing updateSetting endpoint + invalidates the
query.
Sibling to the Score v2 app client (#1094); stacked on it for the
nomad_score_v2 column. Browser-verified on the NOMAD3 dev env: show/dismiss/
reload-persist/self-clear-on-v2 all correct.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Phase 4 of the NOMAD Score v2 effort (stacked on #1089). Captures the raw
channel values the leaderboard scores from, computes the uncapped v2 score
in-app (byte-matching the leaderboard's server-side recompute), submits the
v2 payload, and surfaces it in the benchmark UI.
- Capture raws: per-channel sysbench values + O_DIRECT disk (W4), single/multi
thread CPU + memory, W6 consistency companions, and run-environment metadata
(run_environment, storage_path_type, gpu_compute_detected, #1016).
- AI hardening: reference model llama3.1:8b, num_predict=256, VRAM eviction
before the run + unload own model after, pre-flight disk check (~6.5GB, only
when the model is uncached), median-of-3 run (W7).
- Score: _calculateNomadScoreV2 (uncapped, reference->1000) byte-matches the
leaderboard recompute. nomad_score_v2 stays null unless a full run with AI.
- Payload: submitToRepository sends the v2 raws + score alongside legacy v1.
- UI: v2 headline score, legacy v1 as secondary, raws/env in details.
- Migration: 13 nullable columns; double (not knex float(8,2)) so millions-scale
raws keep full precision and don't break the leaderboard byte-match.
Reference constant REFERENCE_SCORES_V2.ai_tokens_per_second is still the stale
40.5 placeholder (TODO in source); locking it to the measured 13.2 is a
follow-up gated on the AMD iGPU fix (#1074). Live prod v2 submit is separately
blocked by the leaderboard TTFT floor (tracked in the leaderboard follow-up).
Verified on NOMAD3 (RTX 5060) dev env: migration applies, raws recorded,
v2 score computed, backend + benchmark.tsx typecheck clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
An install that never went online while visiting /maps never provisions
world.pmtiles (it is lazily extracted from the internet), leaving the map
blank/grey offline outside any downloaded regional extracts.
Detect the world basemap's presence on disk and surface it to the UI so:
- /maps shows a clear notice explaining the base map isn't downloaded and
how to fix it, instead of a silent grey screen.
- /settings/maps offers an explicit "Download Base Map" action (~15 MB) to
provision it deliberately while online.
Adds MapService.checkWorldBasemapExists() / provisionWorldBasemap(), a
POST /maps/setup-world-basemap endpoint, and threads worldBasemapExists
through the maps page props.
Refs #1030
Co-authored-by: Cursor <cursoragent@cursor.com>
* feat(AI): per-model thinking toggle with global default (off)
Stop forcing thinking on for every capable model. Adds a global default
(ai.autoThinking, ships OFF) and a per-model override in the chat window,
shown only for thinking-capable models and remembered client-side.
The /v1 (OpenAI-compat) endpoint ignores `think`; reasoning_effort is the
real lever. The controller resolves per-request preference -> global default
-> OFF (gated on capability), and the service maps that to reasoning_effort
('none' to suppress on a capable model, 'medium' for gpt-oss, unset to let a
capable model default thinking on). A new thinkingCapable flag keeps
non-Ollama backends from ever receiving reasoning_effort.
installed-models is enriched with a `thinking` flag (checkModelHasThinking,
now memoized) so the picker knows which models get the toggle.
Stacks on #1078 (reasoning-field read + client-disconnect abort).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(AI): thinking toggle as NOMAD Switch + info tooltip
Address review feedback on the per-model thinking control:
- Use the shared Switch component (matches AI Assistant settings) instead
of a raw checkbox.
- Label "Thinking:" with a colon to match the adjacent "Model:" label.
- Add an InfoTooltip explaining what thinking does and where the default
lives. Extend InfoTooltip with optional `position` ('top'|'bottom') and
`align` ('center'|'right') so it opens downward and expands leftward from
the right-edge header slot instead of being clipped/crushed against the
viewport edge. Defaults preserve existing (benchmark page) behavior.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(creator-packs): backend rail for gated creator content packs
Phase 1 of Creator Packs: the app-side download rail for per-creator
video ZIMs served from the private R2 bucket behind the entitlement
Worker. No UI yet (Phase 2).
- Thread optional requestHeaders through the download util + job so the
ZIM fetch can carry `Authorization: Bearer <APP_KEY>` on both the HEAD
probe and the GET stream (Worker streams the ZIM directly, gated).
- Add resourceMetadata.skip_embedding and gate the RAG/EmbedFileJob
branch on it so video ZIMs are never sent to the knowledge base.
- New creator_packs ManifestType + creatorPacksSpecSchema (display
metadata only, no url) + CollectionManifestService wiring and
getCreatorPacksWithStatus() status join.
- collections/creator-packs.json catalog with the two seed packs.
- CreatorPackService.installPack: ensure Kiwix (auto-install if absent),
resolve the stable Worker URL, dispatch the gated download with
skip_embedding. Typed result codes.
- CreatorPacksController + GET/POST /api/creator-packs routes.
- CREATOR_PACKS_APP_KEY / CREATOR_PACKS_WORKER_BASE env (release-injected
key; app degrades to a clear not_configured error when unset).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(creator-packs): Phase 2 UI — Content Explorer, settings page, wizard step
Adds the three user-facing surfaces for Creator Packs on top of the Phase 1
backend rail. All surfaces HIDE entirely on builds without the release-injected
key (configured=false) so a fork never shows a broken install button.
- Backend: CreatorPackService.isConfigured() + `configured` flag on the
GET /api/creator-packs response; /settings/creator-packs route + controller
action.
- api client + useCreatorPacks hook (shared cached source of configured/packs/
downloads for every surface) + CreatorPackCard (status badges, art fallback,
update pill) + CreatorPacksSection (install-on-click grid + confirm modal with
the license note), reused by the Content Explorer block and settings page.
- Content Explorer: Creator Packs section before Additional Content.
- Settings: new /settings/creator-packs manage page + conditional nav item.
- Easy Setup wizard: new Creator Packs step after Content. Replaces the fragile
hardcoded AI-skip math with a computed activeSteps list so the two optional
steps (Creator Packs + AI) navigate correctly in every on/off combination;
selection state, storage projection, review summary, and finish-install wired.
Browser-tested on NOMAD3 across all surfaces (configured + fork paths), incl.
live install→download→cancel and AI-on/off wizard renumbering.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(creator-packs): use branded pack banners on the cards
Replace the generic colored-block cards with the branded 1060x175 banners we
build into each pack ZIM, shown on both the settings page and the Easy Setup
wizard step (and the Content Explorer block, via the shared card).
- Bundle the seed-pack banners as local webp under admin/public/creator-packs/
so they render offline (no external image dependency, matching the existing
/rogue-support-banner.webp convention).
- CreatorPackCard is now banner-forward: the banner is the hero, with a compact
status/metadata footer (videos · size, Installed/Downloading/Selected/Install,
update pill). Falls back to a simple header if an image is ever missing.
- Prefer an optional catalog `banner_url` (future remote creators) over the
bundled-by-id path; add banner_url to the CreatorPack type + validator.
- Widen the card grids to 1–2 columns since banners are wide.
Browser-tested on NOMAD3: banners render on the settings page and wizard step;
selection/installed/downloading states and storage projection still correct.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(creator-packs): Phase 3 — uninstall, license, release key-injection
Completes the Creator Packs feature.
- Uninstall: CreatorPackService.uninstallPack reuses ZimService.delete (removes
the ZIM, drops it from the Kiwix library, clears the InstalledResource) behind
DELETE /api/creator-packs/:id. A trash control on installed cards appears only
on the settings "manage" surface (allowUninstall) — never on the Content
Explorer block or the wizard — with a danger confirm modal.
- License: draft "Project NOMAD Creator Pack License v1.0" at
collections/creator-pack-license.md (marked DRAFT — pending legal review;
personal-use, no-redistribution, official-channel-only, creators retain
copyright). The install modal links to it ("View license").
- Release key-injection: Dockerfile ARG/ENV CREATOR_PACKS_APP_KEY in the runtime
stage (empty default → source/CI builds ship unconfigured and hide the UI) +
build-primary-image.yml passes it from the CREATOR_PACKS_APP_KEY CI secret.
NOTE FOR JAKE: add that repo secret = the entitlement Worker's key.
- Update flow was already functional (installed-with-update cards → "Update
pack"); verified.
Browser-tested on NOMAD3: uninstall round-trip (file + DB row + kiwix library
cleaned, then reinstalled), settings-only uninstall control, install-modal
license link, and the "Update available" pill via a temporary catalog bump.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(downloads): clean up header merge logic
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: jakeaturner <jturner@cosmistack.com>
* feat(rag): add subject/collection organization to knowledge base
- Add nullable collection field to KbIngestState, propagated through the
embed job, RAG service, and Qdrant point payloads (indexed for filtering)
- Add upload-time category selection and per-file collection reassignment
in the Knowledge Base modal, with a filterable Stored Files table
- Add a 'Search in' collection filter to the chat interface, threaded
through to searchSimilarDocuments as an optional Qdrant filter
- Fix .docx extraction: previously routed through raw-text extraction
(garbage output for a ZIP-based XML format); adds a proper mammoth-based
extractor and a dedicated 'docx' file-type case
* feat(rag): support dynamic KB collection creation, rename, and removal
Extends collection organization with a Manage Collections UI: collections
are created on the fly when a file is assigned to a new name, can be
renamed (bulk-updates every tagged file and Qdrant point), and can be
removed (reassigns tagged files back to Uncategorized rather than
deleting anything).
* fix(rag): use dynamic collections query in chat search filter
chat/index.tsx still imported the static KB_COLLECTIONS constant for its
'Search in' dropdown, inconsistent with KnowledgeBaseModal.tsx which already
uses the live getKnowledgeCollections() query. Renamed/added collections
via the new Manage Collections UI weren't reflected in the chat filter.
* feat(rag): broaden preset tags and add creatable collection combobox
Replaces the survival-specific preset list with general-purpose starter
tags (recipes, diy, health, technology, finance, travel, hobbies,
reference, survival, energy) so the Knowledge Base reads well for
home-lab/reference use, not just prepping.
Adds sanitizeCollectionName() (trim, lowercase, length cap) applied on
every write path server-side, and a dependency-free CollectionCombobox
component replacing the plain <select> + window.prompt pattern for
tagging — autocompletes against presets + tags already in use, with a
'+ Create' option for anything new.
* chore(rag): remove .docx fix from this branch, split into #1100
Per review feedback, the .docx extraction fix is unrelated to the
collections feature and can merge independently. Moved to a standalone
PR (Crosstalk-Solutions/project-nomad#1100) off dev.
* chore: remove unrelated diff noise (lockfile, comments, indentation)
---------
Co-authored-by: John Cortright <jcortright@zscaler.com>
A System-Only or AI-Only run is a partial result, not the NOMAD Score
(which is the full-benchmark composite). Two problems addressed:
1. Scoring bug: AI-only runs were NOT renormalized. _calculateNomadScore
always added the system weights (0.60) to the denominator even for an
AI-only run (default-zero system scores), so an excellent AI-only run
scored ~39.8 -- scaled against the full NOMAD 100 where AI is only 40%
-- while system-only already renormalized correctly. Fix: pass
systemScores only when the system benchmarks actually ran, so AI-only
renormalizes to its own 0-100 (39.8 -> ~99.7). Full and System-only
scores are unchanged.
2. Presentation: partial runs were shown with the full "NOMAD Score"
label + big gauge, outweighing the small "Partial" notice. Now partial
runs are relabelled "System Score" / "AI Score" with a PARTIAL badge,
a muted (neutral) gauge + number, and a "run a Full Benchmark for your
NOMAD Score" CTA -- applied to both the persistent score section and
the Phase 3 ScoreReveal via a shared getScoreDisplay() helper. Adds a
`muted` prop to CircularGauge.
Browser-validated on NOMAD3: AI-only now shows "AI Score" + PARTIAL,
muted gauge, 99.7 (was 39.8); Full still shows "NOMAD Score" green.
Implements the display-layer fix from the Score v2 red-team's W2; the
AI-ceiling saturation (W1) remains v2 work.
Part of #1082.
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Phase 3 of the live benchmark run experience.
- ScoreReveal: replaces the abrupt run-view unmount with a deliberate
end-of-run "REPORT" card -- animated NOMAD score gauge + odometer
count-up number, sub-score gauges cascading in, Continue button +
5s auto-dismiss. Takes score scale as a prop so it survives Score v2.
- GPU-util overlay (NVIDIA): during the AI stage, a ~1Hz nvidia-smi poll
inside the Ollama container feeds live GPU utilization + VRAM into the
telemetry frames; shown in the AI hero, hidden when absent (AMD/none).
Poller is side-effect-only and cleared in a finally -- scored numbers
unchanged.
- Disk polish: reset in-test buffers on stage transition so the write
stage no longer briefly shows the carried disk-read value.
Browser-validated on NOMAD3 (RTX 5060): GPU overlay live (1% util,
0.2/8.0 GB VRAM during model load); reveal cascade + count-up; AI-only
score 39.8 (scored path unchanged).
Part of #1082 (tracker stays open).
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
