Ollama 0.33.3 gives two answers for gemma3: /api/tags lists it as
['completion'], while /api/show for the same model reports
['completion', 'vision']. getModelCapabilities trusted the list outright
and cached it for the life of the process, so image upload stayed disabled
for gemma3, one of the most common small vision models, even though the
model downloader correctly shows it as text + image. Re-pulling does not
help: the local digest matches the registry.
A list that reports vision is still trusted without probing. A list that
omits it is no longer conclusive: the model is probed through /api/show
(then llama.cpp /props), and the list's answer stands only when the probes
have nothing better, which keeps hybrid routers without /api/show working.
The service's own copy of the short-circuit is removed so the rule lives in
the one tested function.
Verified on NOMAD3 (v1.35.0 + this patch): installed-models moves gemma3:4b
from unsupported to supported, every other model unchanged, and a chat with
an attached image is answered correctly.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Boot runs ensureDirectoryExists() on the zim root, so a separate volume
that failed to mount leaves an empty mountpoint behind. The scan walks it
without error and reports it as scanned. One upload in kb_uploads keeps
the overall scan non-empty, so the next manual sync purged the vectors
for every ZIM under that root.
decideOrphans() now decides per scanned root and returns
{ orphans, withheld }. A root keeps its indexed sources when:
- it holds no embeddable files (kiwix-library.xml does not count)
- the purge would remove more than 50% of its indexed sources and at
least 5 of them, which points to a wrong or stale mount rather than
hand deletions
scanAndSyncStorage() logs each withheld root and appends a note to the
sync result message, so the user sees a likely unmounted drive instead
of losing hours of embeddings.
Replaces the unit test that asserted the old empty-root purge with
regression coverage for #1378 and both guards.
Closes#1378
Upgraded AMD iGPU installs sometimes carry a working
HSA_OVERRIDE_GFX_VERSION on nomad_ollama, set by hand or by an older
install path, but have no ai.amdHsaOverride KV and no .nomad-amd-gfx
marker. The CPU-fallback banner offered Fix: Reinstall, and the
reinstall rebuilt the container without the override, so a 780M
(gfx1103) stayed on CPU.
- Add pickAmdHsaOverride to utils/amd_hsa_override.ts with the
resolution order KV, marker, existing container override, none.
A marker still wins even when it maps to none. KV "none" still
disables the override.
- forceReinstall inspects nomad_ollama before removing it and saves a
container-only override to ai.amdHsaOverride. Saving it keeps the
value through a reinstall that fails after the removal and shows it
in the Set GFX Override modal.
- The update path passes the old container env to the resolver, so a
routine Update keeps the override too.
- The GPU health check passes the container env, so
diffAmdOllamaConfig compares against what a reinstall would build.
On the reported box, the only drift is OLLAMA_IGPU_ENABLE=1.
- diagnoseAmdCpuFallback suggests the container's current override
when one is set. With an override applied, Ollama logs the coerced
target (gfx1100), which maps to none and would suggest removing a
working value.
- Remove the unused _mapGfxToHsaOverride wrapper.
parseAmdGfxTargetFromLogs is unchanged. It still matches only
gpu_type=. The "dropping integrated GPU ... compute=gfx..." line needs
a full sample from an affected box before we can write a regex for it.
We'll address in a later PR.
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
decideOrphans guards on the disk scan coming back empty, but the failure
mode it needs to defend against is per-root. _discoverKbFiles() walks
kb_uploads and zim in a loop and skips a missing root rather than
failing, because a fresh install legitimately has no kb_uploads yet.
So if the zim root is relocated, renamed, or not yet mounted (#1050),
the scan still returns a non-empty list from kb_uploads. The empty-scan
guard never fires, filterOrphanCandidates has no way to tell a root that
scanned clean from one that was never there, and every ZIM in the index
is classified as an orphan and purged in a single batch. On a
Wikipedia-scale knowledge base that is millions of vectors and a
multi-hour re-embed. It is reachable from the UI: scanAndSyncStorage is
POST /rag/sync, so the button pressed when the knowledge base looks
wrong is the button that empties it.
_discoverKbFilesWithRoots() now reports which roots were walked, and
filterOrphanCandidates allowlists against that list instead of the
configured roots. A root that wasn't there contributes no candidates; a
root that scanned clean and held no files still yields its orphans, so
the legitimate purge path is unchanged. The empty-scan guard becomes the
degenerate case of the same rule rather than a separate one.
Also builds the unit-test paths with join() instead of POSIX literals.
Written as '/data/...' the filterOrphanCandidates cases pass on Linux CI
and fail on Windows, where sep is backslash and no source ever matches a
prefix, which is exactly where they would be run while changing this.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Self-review pass over the last few commits:
- Extracted the kb_uploads/zim allowlist check out of scanAndSyncStorage()
into a new filterOrphanCandidates() in kb_orphan_decision.ts, alongside
the existing decideOrphans(). It was untested logic sitting inline in a
large method; pulling it out next to decideOrphans() makes it a pure,
I/O-free function the same way decideOrphans() already is, and lets it
be covered directly instead of only indirectly through scanAndSyncStorage.
- Added unit tests for it: keeps sources under the scanned roots, excludes
sources outside them (e.g. bundled docs), and a dedicated case for the
sibling-directory false-positive a naive prefix check (no trailing
separator) would let through.
- Also fixed two prettier violations introduced earlier in this PR (an
over-length logger.info call and an unwrapped ternary in
scanAndSyncStorage) that weren't caught by the per-edit lint checks I
ran at the time.
scanAndSyncStorage builds sourcesInQdrant and embeddableFiles in the
same pass but only ever checks one direction - is this on-disk file
already embedded? It never checks the reverse, so points left behind
by a deleted or replaced ZIM just sit in Qdrant forever and keep
showing up as search hits for content that doesn't exist anymore.
Added a reverse sweep that diffs the two sets and purges anything left
in Qdrant with no file backing it. Guarded so it's a no-op when the
disk scan comes back empty, so a filesystem hiccup can't get misread
as "delete everything."
Also has to exclude README.md/docs, since those get embedded by
discoverNomadDocs and live outside the kb_uploads/zim paths the
scanner actually walks. First pass without that exclusion would have
wiped the docs KB on every single sync - caught it by testing against
a live install where those sources were already indexed.
Verified live: found exactly one real orphan out of 29 indexed
sources (an old devdocs_en_bash zim superseded by a newer download),
purged it, and left the other 28 - including all the docs - alone.
On 1.34.0 every FDA ingest finished with its labels loaded but lost the
installed_resources 'dataset' row, because resource_type was still
enum('zim','map'). The enum migration in #1243 fixes new writes but can't recreate
the lost row. Re-selecting the tier doesn't fix it either, because ZimService
skips a dataset that already has rows. So Medicine never resolved its
Standard tier.
- Add DrugInstallRowProvider. On each boot it backfills the row when an
ingest has finished (rows present, export date set, no download
marker, no drug job running) and no row exists.
- Put the decision in decideDrugRowReconcile() so it has unit tests.
- Add DrugReferenceService.recordInstalledRow() as the one writer used
by the ingest job, the provider, and ZimService.
- ZimService now writes the row when a Medicine tier re-select finds a
finished ingest with no row.
Manual ingests and reset-and-reingest runs, which dispatch without
resourceMeta, also get the row on the next boot.
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.
The GpuPassthroughRemediationProvider probed GPU passthrough by exec'ing
`nvidia-smi` inside nomad_ollama. When Ollama was created CPU-only — most
commonly because the NVIDIA container runtime was registered with Docker
only AFTER the AI Assistant was first installed (DockerService attaches a
GPU DeviceRequest only when 'nvidia' is in docker.info().Runtimes at
install time) — the container ships no nvidia-smi, so the exec returned an
error string whose letters the alphabetic-output check mistook for
"passthrough healthy". That false negative suppressed all auto-remediation,
leaving Ollama silently stuck on CPU (models run at a fraction of a token
per second) until the user manually clicked "Fix: Reinstall AI Assistant".
Replace the nvidia-smi probe with Ollama's own "inference compute" startup
log line — the ground truth for whether a GPU backend actually loaded — via
a new, unit-tested classifyOllamaComputeBackend() helper. One signal covers
both the "created CPU-only" case and the original "DeviceRequests present
but the toolkit binding tore" case. Add a cooldown on gpu.autoRemediatedAt
so a GPU that genuinely cannot be accelerated (an architecture Ollama has
no kernels for) does not trigger a reinstall on every admin boot.
Co-Authored-By: Claude <noreply@anthropic.com>
* 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 catalog-sync loop overwrote container_config and ui_location for every
non-user-modified curated service, resetting the published host port of an
install that had been moved off the catalog default. The row then disagreed
with the running container: the Open link pointed at a dead port and the
next recreate collided.
Preserve the live host ports for installed rows and apply every other
catalog change, so these installs keep receiving catalog updates instead of
being opted out of them.
Diagnosis and the original fix are @johno10661's work in #1005.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01F8Mgg1vd2eKSs8StZiuyMV
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
"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
It constructs OllamaController, which imports the Adonis logger service at
module scope, so it cannot run under the plain node:test runner. It failed
identically on the original branch -- the coverage has never executed. Moving
it to the Japa runner puts it in the same bucket as the other app-importing
specs, where a booted app is available.
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
#1165 taught the benchmark path to reject an unresolved PCI id as a GPU
model, but isUnresolvedGpuModel lived inside benchmark_service.ts and the
Settings > System display path never learned the same thing. It still shows
whatever lspci handed back.
The two symptoms of a stale pci.ids database are independent, which is why
the existing guard misses this. system_service already re-probes when a
discrete-GPU controller reports an implausible BAR0 reading as VRAM, and
that happens to fix the name as a side effect. But lspci can return a
perfectly plausible VRAM figure alongside a name it could not resolve, and
then nothing fires.
Confirmed live on an AMD box. The Radeon 780M reports:
model: "Device 1900", vram: 512
512 MiB clears the 256 MiB bogus-VRAM threshold, so no probe runs and the
System page renders "Device 1900". The same box's Ollama startup log carries
description="AMD Radeon 780M Graphics", so the probe the guard declined to
run had the real name available the whole time. NVIDIA hides this because
its path tends to be reached for other reasons; AMD has no equivalent.
Adds an unresolved-name trigger alongside the VRAM one, and moves
isUnresolvedGpuModel to app/utils/gpu_model.ts so the submission path and the
display path share one definition instead of diverging again. Tests cover
both placeholder shapes and, more importantly, a set of real product names
that must never be rejected.
Stacked on #1277, so the shared helper carries the WSL placeholders too.
Closes#1196
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Fixes#1269. Fixes#1203.
`file-embeddings` and `downloads` both routinely outlive the default
5 minute lock, so BullMQ calls healthy jobs stalled on both. They need
opposite recovery policies, which is why neither was covered by the
existing drug-queue override.
Embedding is a self-continuing chain, so re-queueing a stalled job while
the original is alive runs two chains over the same file. Both write to
Qdrant with freshly minted point ids, so the second cannot overwrite the
first, and the queue's concurrency of 2 means the fork never contends
for a slot. maxStalledCount 0 fails on the first stall instead.
A download is resumable, so recovery is safe there; the default of 1 was
failing jobs outright and bypassing their own attempts: 10 policy.
The decision moves to a pure, unit-tested util alongside the other
decision helpers.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LtGWCVMPYn6qPWVYiycK74
The batch continuation gated on articles that produced chunks rather than
articles the extractor consumed. Articles whose text is empty after HTML
cleaning — redirect stubs, category listings, media and PDF wrappers —
return no chunks and so no documentIds, which made a normal sparse batch
look like the end of the archive. Ingestion stopped after the first batch
and the rest of the file was silently skipped.
Medicine LibreTexts embedded 16 chunks out of 23,171 articles: its first
50 entries are navigation pages, only 10 of which had text, so 10 >= 50
was false and no continuation was ever dispatched. Measured against the
same install, WikiMed reached 28% of its articles, Libre Pathology 31%,
MedlinePlus 84%, and CDC Travelers' Health 2.7%.
The same value was also returned as `articlesProcessed`, which
EmbedFileJob uses to advance the next batch offset. Advancing by the
content-bearing count re-read the overlap on every sparse batch, and a
batch yielding no text at all would have advanced by zero and re-run the
same window indefinitely.
Both now use the extractor's consumed-article count, which it already
computed and logged but discarded. The end-of-archive signal is the
iterator running dry (articlesProcessed < batchSize); archive.articleCount
cannot serve as a bound because iterByPath() legitimately yields more
article entries than that figure for some archives.
The log line now reports both counts (content-bearing/consumed) so a
sparse batch is visible without re-deriving it.
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.
Ollama's format parameter turns a formatting request into a decoder
constraint, and NOMAD's three ancillary calls — chat title, suggestion
chips, RAG query rewrite — were the ones paying for not having it.
The rewrite is particularly important: whatever it returned got embedded
and sent to Qdrant, so a malformed response degraded retrieval for the
rest of the conversation.
Three explicit design choices made:
- Native-only. The compat path sends nothing new and keeps its string
parsing, so a non-Ollama backend that rejects response_format can't
take out title generation entirely.
- parseStructured returning null is the control flow. It's how each
caller falls back to the parser it already had, which is why it's written
to be total and never throw.
- {queries: []} not {query: ""} for the rewrite (tee-ing up future
improvements)
ThinkTagSplitter was wired into both streaming paths but neither
non-streaming one, and every ancillary call goes through non-streaming
chat(). So a reasoning tasks model put its reasoning transcript into the
sidebar title, into the suggestion chips, and — worst — into the string
that gets embedded and sent to Qdrant, silently corrupting retrieval for
the rest of the conversation. splitThinkTags() already existed and was
already unit tested; it just had no production callers.
Fixed in three layers:
1. Strip at the transport. New normalizeNonStreamed() in think_stream.ts
merges structured reasoning (native `thinking`, /v1 `reasoning`) with
anything the splitter pulls out of inline tags, and both _chatNative
and _chatCompat now return through it. That covers every caller at
once, including the legacy controller path and the eval harness.
2. Suppress at the source. _chatNative and _chatStreamNative forwarded
`think` only when truthy, so `think: false` was never sent and Ollama
left reasoning on for capable models. Guard is now definedness. This
also fixes the ai.autoThinking=off setting, which had no effect on
the native streaming transport.
3. Guard the call sites. Title, suggestions, and query rewrite now pass
think:false plus thinkingCapable (from the memoized capability check,
so no extra round-trip), and handle an empty-after-strip result. The
rewrite matters most: QUERY_REWRITE_MAX_TOKENS caps it at 120, which
a reasoning model burns entirely on thinking, so stripping alone
would have turned a corrupt query into an empty one. It now falls
back to the raw user message instead of embedding "".
Verified: think_stream.spec.ts 17/17 (6 new cases, including the
truncated-mid-thought case that drives the fallback), typecheck clean,
full test:unit failures byte-identical to the pre-change baseline.
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.
Adds an optional `auth: 'nomad_app_key'` discriminator to curated manifest
resources so a curated collection tier can carry content we host ourselves,
gated to official release builds. Without this, only Creator Packs could use
the entitlement Worker; curated tier installs always downloaded
unauthenticated.
No behaviour change for any existing manifest entry: absent `auth` means
unauthenticated, exactly as today.
- `auth` declared on both the type and the VineJS validator. It has to be on
the validator or VineJS strips it silently on fetch, and the gated download
would then go out with no header and 401 for everyone. A dedicated spec
guards that regression.
- Gated resources are pinned to their manifest URL (resolveZimDownload skips
the catalog comparison) and excluded from catalog update checks, so a
resource-id collision cannot let a third-party mirror overwrite our content.
Consequence, commented rather than implied: gated content does not
auto-update; new versions ship via the manifest.
- 401/403 on a download now reports that an official build is required instead
of a raw axios status, which is what a fork build will hit.
- The pure `isGatedResource` predicate is deliberately split from the
env-reading header builder: importing `#start/env` into
zim_download_resolution triggers env validation at import time and breaks its
unit tests.
Reuses CREATOR_PACKS_APP_KEY rather than minting a second secret — the question
it answers ("is this an official build?") is identical for both content types.
Verified end to end on a test server: `auth` survives validation into the
cached spec, the Bearer header attaches to only the gated resource, the file
lands byte-exact with an installed_resources row and a Kiwix library entry, and
an entry with a gated URL but no `auth` field fails with the intended message.
No catalog entry is included here. Manifests are fetched live from `main`, so a
gated entry must not merge until this ships and is adopted — pre-`auth` builds
strip the field and 401.
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
Three changes that together let ARM hardware appear on the leaderboard honestly.
Shipping them separately would leave ARM half-supported either way: without the
image a Pi cannot submit at all, and without the architecture field it submits
but is indistinguishable from x86.
1. PIN THE OFFICIAL MULTI-ARCH SYSBENCH IMAGE
severalnines/sysbench publishes amd64 only, so ARM hosts could not run the
System Benchmark at all — not a graceful failure, the container simply cannot
execute. Apple Silicon could only run it under Rosetta emulation, which distorts
the measurement it is taking, and that is what drove a community macOS fork to
substitute a different benchmark and submit incomparable numbers.
Swaps to ghcr.io/crosstalk-solutions/nomad-sysbench (Debian 12 + sysbench
1.0.20+ds-5, built for linux/amd64 + linux/arm64). One digest covers both
architectures; verified that pulling the pinned manifest-list digest resolves to
arm64 on a Raspberry Pi 5 and amd64 on x86, and that RepoDigests reports the
same manifest-list digest on both — so a single allowlist entry serves both.
No rescoring: 1.0.17 -> 1.0.20 measured 1.25% apart on identical hardware with
identical flags (7170.18 vs 7259.56 events/sec), inside run-to-run noise and
~0.3% on a composite. Both digests are allowlisted server-side, so the fleet can
cross over gradually.
2. REPORT THE DIGEST ACTUALLY RESOLVED
The submission previously sent SYSBENCH_DIGEST, the constant the client was
compiled with. The leaderboard validates that field, but a constant attests to
how a client was BUILT rather than what it RAN, so any build inherits a valid
value simply by carrying the same source.
Now reads it back from the image. Uses RepoDigests (the manifest digest we
pulled by), never Id — Id is the config digest, differs per architecture, and
would never match the allowlist. Falls back to the constant if inspection yields
nothing usable, so a benchmark never fails over provenance metadata.
Still forgeable, and always will be with an open-source client. It moves the bar
from "no effort" to "deliberate", which is the distinction that matters when
judging whether a submission is a mistake or a choice.
3. RECORD CPU ARCHITECTURE AND OS
The leaderboard is a single board across instruction sets by design, with
disclosure as the fairness mechanism. Without an architecture field an ARM result
sits unlabelled beside x86 — exactly what the disclosure exists to prevent.
All three fields come from the Docker daemon, reusing the docker.info() call
_detectRunEnvironment already makes. That is deliberate: inside the admin
container os.arch() and si.osInfo() describe the CONTAINER, not the host being
benchmarked.
cpu_architecture Architecture x86_64 -> amd64, aarch64 -> arm64
os_version OSVersion '24.04' (already structured, no parsing)
os_name OperatingSystem 'Ubuntu 24.04.4 LTS' minus the version
run_environment is kept rather than replaced: "which distro" and "is this
virtualised" are different questions, and WSL2 is a real performance factor.
String handling lives in app/utils/platform_metadata.ts with unit tests, matching
the amd_hsa_override convention, so it is testable without a Docker daemon.
Unknown architectures pass through verbatim rather than being guessed at, and
os_name falls back to the full description whenever the version is missing or
absent from it — an over-long name is harmless, a wrong one is not.
Columns are nullable and the submission fields optional, so results recorded
before this shipped remain submittable.
Closes#1156
Refs #1151
PR #1076 stopped forcing HSA_OVERRIDE_GFX_VERSION=11.0.0 on
"natively-supported" AMD iGPUs. That was correct for gfx1150/gfx1151
(Strix 890M / Strix Halo, which are in the bundled rocblas allowlist)
but wrong for gfx1103 (Phoenix/Hawk Point 780M/760M), which is NOT in
that list. Without the override, ollama drops the 780M with "no rocblas
support for gfx target" and falls back to CPU on a fresh AI provision.
Extract the gfx→HSA mapping into a pure, unit-tested util and map
gfx1103 → 11.0.0 (gfx1100 kernels), the value that worked on v1.33.0 and
that restores full GPU offload in the field. gfx1150/1151 stay native.
Also harden the installer's 780M detection (Hawk Point / "Radeon 780M/
760M" strings) so the gfx marker isn't silently deleted, and upgrade the
no-marker fallback log from info to warn since it can mask CPU fallback.
Generate app/data/{conditions,natural_remedies,home_remedies}.ts from the
repo-root collections/*.json via `npm run gen:curated-data`, so the JSON is the
only file edited by hand. The generated modules keep the data compiled into the
image (no runtime file read, no path fragility, which is why the data was a TS
constant), and curated_data_sync.standalone.ts fails CI if a generated module
ever drifts from its JSON.
This removes the burden of hand-keeping the .json mirror and the .ts constant in
sync. Follow-up to the review discussion on #1040.
Co-authored-by: Claude Opus 4.8 <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>
* 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>
Closes#902.
Two gaps in the structured ZIM extraction path:
1. NON_CONTENT_HEADING_PATTERNS was only used by the structure heuristic to
count meaningful sections, never at section-emit time. Sections under
"See also" / "References" / "External links" / etc. were still chunked and
embedded. They're now flagged when the heading opens and dropped.
2. <table> elements were run through cheerio's `.text()`, concatenating every
cell with no separators ("AgeDoseAdult500mg") into unsearchable word salad.
New tableToText() joins cells with " | " and rows with newlines so
row/column structure survives into the chunk.
Refactor: moved extractStructuredContent out of ZIMExtractionService into a
pure, cheerio-only util (app/utils/zim_html.ts) so it can be unit-tested
without the native @openzim/libzim binding. Service delegates to it; behavior
is otherwise unchanged. Adds tests/unit/zim_html.spec.ts (6 tests).
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Rebuilt on top of dev's RFC #883 state-machine UI rather than the now-defunct
StoredFile shape:
- Extend StoredFileInfo with fileName/size/uploadedAt/isUserUpload
- Populate metadata from on-disk stats in RagService.getStoredFiles
- Add fileSourceSchema validator + getFileContent/downloadFile endpoints
scoped to the uploads directory only (tighter than the original PR — matches
docs_service traversal pattern)
- KnowledgeBaseModal: sortable Size and Uploaded columns; View/Download
buttons on upload-bucket rows; new FileViewerModal for in-browser text
preview. Bucket grouping preserved — sort applies within each bucket.
- Use formatBytes from ~/lib/util rather than redefining
Only Wikipedia had version cleanup; every other curated map and non-Wikipedia
ZIM left its prior version on disk when a newer one installed, so users silently
accumulated orphaned content (potentially hundreds of GB). (#634)
The install paths already record each resource via InstalledResource
{resource_id, resource_type, version, file_path}, so the authoritative old-file
path for a resource is known. On install of a new version we now capture the
prior row before updateOrCreate repoints it, then delete the old file — gated
behind a pure, fully unit-tested decision function with strict safety rails:
- tracked-only: requires a prior InstalledResource row for the same
resource_id, so sideloaded/untracked files are never touched
- genuine replacement: old and new file paths must differ
- new-file-verified: the new file must be confirmed on disk first
- strictly-newer: a re-install or downgrade can't wipe a newer file
- within-storage-dir: the old path must resolve under the content store
ZIM cleanup deletes the old file directly (NOT via this.delete(), which would
drop the InstalledResource row by resource_id that updateOrCreate just
repointed) and rebuilds the Kiwix library only if a file was actually removed,
so its XML never references a deleted ZIM. Maps need no library step. Wikipedia
keeps its own existing cleanup path. All deletions are best-effort and logged;
a failure never breaks the install.
Closes#634
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Replaces the regex blocklist in assertNotPrivateUrl with ipaddr.js range
classification and normalizes the host before checking it. Consolidates two
community proposals (#930 ipaddr.js parsing, #912 trailing-dot normalization)
into one validator so the SSRF-critical path lives in-house with full tests.
- Classify literal IPs by range (loopback / linkLocal / unspecified) via
ipaddr.js instead of a hand-maintained regex list, which also catches
alternate IPv4 encodings and avoids over-blocking mapped public IPs (the old
`::ffff:` regex blocked every mapped address, including public ones). IPv4-
mapped IPv6 is reduced to its embedded IPv4 before classification.
- Strip a trailing root dot from the host so `localhost.` / `127.0.0.1.` can't
bypass the checks (they resolve to the same target as the dotless form, #911).
- Strip IPv6 brackets and lowercase for the localhost comparison.
- RFC1918, bare LAN hostnames (e.g. `nomad3`), and external FQDNs remain
allowed — LAN appliances need them, and DNS rebinding is a fetch-time concern
outside this guard's scope.
Adds a consolidated unit spec covering loopback/link-local/unspecified literals,
alternate encodings, IPv4-mapped v6, mixed-case + trailing-dot localhost, and
the allowed LAN/FQDN/mapped-public cases.
Resolves#922. Supersedes #930 and #912 (thanks @Gujiassh and @luyua9).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
