The standalone Python release used by libbackend does not publish a 3.11.18 artifact. Pin Whisper-Medusa to the available 3.11.13 build and cover the generated download URL.
Assisted-by: Codex:gpt-5 [systematic-debugging]
The post was written against the first draft of the release notes, when the
cycle stood at 214 PRs over thirteen days. It closed at 321 PRs over eighteen
days, and three of the larger user-facing changes landed after it was written.
- Correct the counts throughout: 321 PRs, eighteen days, 24 contributors
(11 first-time), gallery 1,221 to 1,505.
- Add sections for the three new capabilities: 3D generation as a modality
(Generate3D, FLAG_3D, /v1/3d/generations, trellis2cpp), audio.cpp serving
six audio endpoints from one process, and the operations bar becoming the
Activity page.
- Cover the two further hardening fixes (tar hardlink escape, cyclic $ref
stack overflow) alongside the TRL one.
- Note the Valkey store, systemd socket activation, persistent trace history,
in-place chat edits, the self-contained SYCL backend and the site split.
- Group the new-engine sections together rather than splitting them across
the operational ones.
Embeds the existing vllm-race and magpie clips, and adds a 3D generation clip
cut from the demo recording to the conventions in .agents/preparing-a-release.md
(no audio track, 14s, named for the feature). blog.css styled figure img but
not figure video, so a clip in a post rendered outside the card; both selectors
now share the rule.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
tests-qwen3-tts-cpp has been failing on master since 2026-07-31. The suite
loads every component fine and then stops: TTS() never returns from the
native call, so a job that takes ~5 minutes runs into the 20 minute Go test
timeout instead.
goroutine 74 [syscall, 19 minutes]:
github.com/ebitengine/purego.RegisterFunc.func4
qwen3-tts-cpp.(*Qwen3TtsCpp).TTS goqwen3ttscpp.go:154
qwen3-tts-cpp.init.func2.4 e2e_test.go:90
Not a flake: reproduced on master and again on an explicit re-run.
Bisected across this cycle's eight qwentts.cpp bumps by their own check:
10832, 10850, 10902, 10964, 11006, 11039 and 11127 all pass in ~5 minutes;
11241 (abab6b3) fails at 1h58m. That PR was merged with this check already
red, which is how the hang reached master.
35ebe537..abab6b3 is three upstream commits, and the only functional one is
26dd8adb, "predictor: unroll the frame into one cgraph and sample in standard
ops", which is consistent with a generation loop that never reaches its stop
condition.
Hold the pin at the last known-good commit. The bump entry is commented out
rather than left in place, because it tracks upstream master and would put
the hang straight back on the next nightly run. Both spots carry a pointer to
the other so the hold is discoverable, and restoring it is uncommenting four
lines once upstream is fixed.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Select the CPU_ALL_VARIANTS target for x86 GPU images so partial offload uses runtime-selected host kernels. Keep GPU arm64 builds on the portable fallback until their toolchains consistently provide gcc-14.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* ⬆️ Update ggml-org/llama.cpp
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(llama-cpp): drop merged MiniMax-M3 patch
The bumped llama.cpp revision includes the MiniMax-M3 parser and template detection, so the carried patch now rejects during backend preparation. Remove the obsolete patch while retaining the independent score-task patch.
Assisted-by: Codex:gpt-5 [systematic-debugging]
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Add the new 9B Fara computer-use model alongside its existing 27B sibling, with Q4_K_M and Q8_0 llama.cpp variants plus the required vision projector.
Assisted-by: Codex:gpt-5 [web]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Build the runtime CPU variant set alongside x86 GPU backends so partial offload uses the host's SIMD kernels instead of the scalar fallback. Keep arm64 GPU images on the portable binary until their builders consistently provide gcc-14.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(utils): reject tar hardlinks that escape the extraction root
ExtractArchive pre-scans archive members and rejects symlinks, but tar
hardlink entries carry a regular file mode and so pass that check.
Header.Linkname was never validated, so an archive could create a link
to a path outside the destination directory.
Validate Linkname with the same path check already applied to member
names. Hardlinks that resolve inside the extraction root still extract,
so ordinary archives are unaffected.
pkg/oci/image.go already resolves tar.TypeLink targets before using
them; this brings the archive extraction path in line with it.
Assisted-by: Claude:claude-opus-5
Signed-off-by: Zelys-DFKH <zelys@dfkhelper.com>
* test(utils): cover hardlink overwrite and in-root hardlinks
The existing hardlink test names a link target two levels above the
extraction root, so its final assertion checked a path the link never
resolved to and could not fail. Point the target one level up instead,
at the path that assertion already names.
Add two cases. The first uses a .tar.gz, where ExtractArchive binds a
Tar config with OverwriteExisting set, and follows the link entry with a
regular entry of the same name. Before the fix that pair linked to a
file outside the root and then truncated it through the link, which the
plain .tar case does not reach. The second extracts a hardlink whose
target is an earlier member of the same archive, covering the claim that
ordinary archives are unaffected.
Assisted-by: Claude:claude-opus-5
Signed-off-by: Zelys-DFKH <zelys@dfkhelper.com>
---------
Signed-off-by: Zelys-DFKH <zelys@dfkhelper.com>
Use the case-sensitive Hugging Face filenames and refresh the linked SHA256 values for both gallery variants.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Detect text-to-speech MLX repositories during model import and emit a TTS-ready mlx-audio configuration. Expose mlx-audio in the backend preference dropdown for repositories without complete metadata.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* feat(sycl): make the intel llama.cpp backend self-contained on any host
The SYCL backend shipped an incomplete oneAPI runtime AND relied on a
host-provided GPU driver, so it only ran inside the build container. On a
bare host it died with "libze_loader.so.1 / libdnnl.so.3: cannot open
shared object file", and even with the host's Intel driver installed it
SIGSEGV'd during SYCL init when the host driver was built against a newer
glibc than the backend's bundled loader (rolling-release distros).
package_intel_libs now bundles the complete, coherent oneAPI runtime
(the missing MKL ILP64 / sycl_blas / tbb_thread + oneDNN + the dlopen'd
UR adapters, plus a sweep of the backend binaries' own direct deps) and
the Intel GPU userspace driver (libze_intel_gpu + libigdrcl + IGC + gmm)
with its OpenCL ICD manifest, mirroring how package_vulkan_libs bundles
Mesa. run.sh points the Level Zero and OpenCL loaders at the bundled
driver, and install-base-deps.sh installs it in the SYCL build image.
Bundling the driver is safe across kernels because it talks to the host
i915/xe via the stable DRM UAPI (unlike NVIDIA's kernel-locked
userspace).
Validated on Arch (glibc 2.43, i915): the backend loads and runs on an
Iris Xe with no host Intel packages installed.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Dimitris Karakasilis <dimitris@karakasilis.me>
* fix(sycl): install a driver that exists, and let the user choose their own
The driver install added earlier in this branch asked apt for
intel-level-zero-gpu, which is not a package in Ubuntu 24.04. apt fails
outright on an unknown name, so neither driver was installed, nothing was there
to copy, and the images carried no driver at all.
It now comes from Intel's own repository, which has 25.18 for this Ubuntu
release, against 23.43 from late 2023 in the Ubuntu archive. The archive driver
does not know any card released since, so a machine with a recent Intel GPU
would end up carrying a driver that cannot drive it. Anything that goes wrong
during that install fails the build on purpose: an unreachable repository is a
passing problem that a retry fixes, while quietly carrying a different driver,
or none, is a difference nobody would notice until a user reports an idle GPU.
run.sh used to overwrite whatever driver the user had chosen. Level Zero uses
only the driver it is given, so on a machine with a card too new for the
carried driver, the GPU would go unused with no way back. Both that setting and
the OpenCL one are now left alone when already set, and the docs say how to
point a backend at the machine's own driver.
The OpenCL setting also used to be applied whenever the backend held a driver
list, even when the driver it named had not been copied, which leaves OpenCL
with nothing instead of falling back to the machine's own driver. It now
requires the copied driver to be present, and the packaging leaves out the list
entry of any driver it did not copy. The oneAPI images list a processor-only
OpenCL library, which was being carried with nothing behind it.
Two more corrections in the packaging. The scan for libraries a program is
linked against only looked at files named llama-cpp-*, so turboquant and bonsai,
which are also built for Intel GPUs, were left with the incomplete set of
libraries this branch set out to fix; it now looks at every program in the
directory. And a build that should carry a driver but ends up without one now
says so, which is what a stale prebuilt base image looks like: such a backend
still runs on a machine that has its own driver, so nothing fails and the only
other symptom is a user reporting an idle GPU.
Backends now also ask the driver to report how much graphics memory is free,
without which llama.cpp reads zero on an integrated GPU, since such a chip
shares the system memory instead of having its own. turboquant and bonsai get
the same run.sh handling as llama.cpp.
The driver is only carried by the builds that start through run.sh, because
run.sh is what points Level Zero and OpenCL at it. The Python backends for
Intel GPUs start differently and would never load it, so they keep using the
machine's own driver rather than carrying several hundred megabytes they cannot
use.
Checked in a container on Ubuntu 24.04: the install brings driver 25.18 with
the files where the packaging expects them, an unreachable repository fails the
build, and the copied set resolves on its own once the machine's Intel packages
are moved away.
Assisted-by: Claude:claude-opus-5
Signed-off-by: Dimitris Karakasilis <dimitris@karakasilis.me>
* fix(ci): rebuild every Linux backend when the GPU packaging script changes
scripts/build/package-gpu-libs.sh decides which GPU libraries end up inside an
image. The filter that builds the backend matrix listed it as an input of the
Python images only, so changing it rebuilt no Go and no C++ backend, even
though those run it from their own package.sh. A packaging fix aimed at the
Intel llama.cpp backend could merge and reach no image, which is the same
failure this rule was written to prevent.
Assisted-by: Claude:claude-opus-5
Signed-off-by: Dimitris Karakasilis <dimitris@karakasilis.me>
* fix(sycl): carry only the driver Level Zero uses, not the OpenCL one
llama.cpp reaches an Intel GPU through Level Zero, which hands the driver
programs that are already compiled and so needs only the back end of the
graphics compiler. The OpenCL driver can be handed source code instead, so it
needs the compiler's front end as well, and that arrives with its own copy of
clang. Carrying it cost about 139 MB in every backend built for Intel GPUs, and
took the carried set from 123 MB to 261 MB.
Nothing here takes that path. No LocalAI code selects an OpenCL device, each
backend image holds one backend, and the documentation never described OpenCL
as a way to run models: the only mentions are a stale clblas row in the
BUILD_TYPE table, for a llama.cpp backend that no longer exists and that no
build matrix entry uses, and the sycl-ls troubleshooting hint. Before this
branch the packaging carried the OpenCL loader and adapter but no driver, so
the path could not work in a released image either. There is nobody to keep
working.
The driver list that OpenCL reads is no longer carried, and run.sh no longer
sets OCL_ICD_VENDORS, so OpenCL inside a container keeps using whatever the
image provides rather than being pointed at a directory with no driver in it.
Checked in a container against the real 25.18 driver: the carried set is 123 MB
with nothing unresolved, and Level Zero still reports the GPU with the
machine's own Intel packages moved out of the way. Neither the Level Zero
driver nor the compiler back end names the front end or clang among the
libraries it opens by name, so the leaner set is complete for this path.
Assisted-by: Claude:claude-opus-5
Signed-off-by: Dimitris Karakasilis <dimitris@karakasilis.me>
---------
Signed-off-by: Dimitris Karakasilis <dimitris@karakasilis.me>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
* feat(chat): edit saved conversation messages
Add inline edit, save, and cancel controls for stored user and assistant messages without triggering inference. Preserve structured message attachments and cancel edits when streaming starts.
Assisted-by: Codex:gpt-5
* test(chat): preserve seeded conversation on reload
The saved-message edit test reloads the page to verify persistence, but its init script was replacing localStorage with the original fixture on every navigation. Seed only an empty store so reloads exercise the data written by the application.
Assisted-by: Codex:gpt-5 [Codex]
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Direct repository-root users to the supported make docs target and document the equivalent direct Hugo invocation from docs/.
Fixes#10062
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
The page reads as a list of features with nothing joining them, so two
things did not land.
The engines section never said these are the backends LocalAI loads. The
runtime section describes a core that pulls each engine in on demand, and
the engines section describes engines written from scratch, and nothing on
the page connected the two sentences. Readers were taking parakeet.cpp and
the rest for unrelated side projects by the same people. The lede now says
whose backends they are before it says anything else.
APEX was used as a known term on first appearance, in a section that opened
onto a benchmark table. Nothing said what it is or why it follows the
engines. It now opens by placing itself in the stack: the engine decides how
fast a model runs, the weights decide whether it runs at all, and APEX is
the second of those. Then the numbers.
Also drops "Most backends wrap somebody else's engine. These do not", which
is the machine-written antithesis shape, and fixes a list that broke its own
parallel halfway through.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5[1m]
The star, fork, contributor and release counts were typed into the templates
by hand, so they only moved when somebody remembered. They had already
drifted: stars read 48,042 against 48,067, forks 4,314 against 4,320, and
contributors 224 against 225.
They move to website/data/stats.yaml, which .github/ci/refresh-site-counters.sh
rewrites from the GitHub API, run weekly by a new workflow. The contributors
and releases endpoints never report a total, so the script asks for one item
per page and reads the count out of the Link header. It refuses to write a
zero or a non-number, which is what a rate-limited or failed call looks like,
and the workflow commits only when a number actually moved. The Discord count
has no API behind it, so the script reads the existing value back and carries
it through.
The engine count was wrong in a second way. The hero said 18, the section
heading said "Eighteen engines", the timeline said "Nineteen engines of our
own", and the /engines/ page derived 19 from the data file. All of them now
derive from that same file, so they cannot disagree again.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5[1m]
Add Q4_K_M and Q8_0 llama.cpp entries for the newly released Qwopus3.6-27B Fusion reasoning and coding merge, with MTP enabled.
Assisted-by: Codex:gpt-5 [Hugging Face API]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
The timeline set six 15rem columns in a flex row with overflow-x:auto, which
needs 90rem and so scrolled sideways on any normal laptop. It is a wrapping
grid now, and the rule that carries the dots moves from the container onto
each item so a wrapped row still gets a line above it. Column gap is zero and
the items carry their own right padding, so the rule stays continuous.
Integrations move from a card grid to a reel. Any single integration is a weak
signal and the whole moving line is the strong one, so the count is doing the
argument. It pauses on hover and on keyboard focus, since the names are links.
The list grows from 8 to 26: Open WebUI, Dify, LibreChat, RAGFlow, Continue,
big-AGI, Nextcloud, Frigate, promptfoo, Mods, TypingMind, baibot, k8sgpt-
operator and others. Each was admitted only after opening that project's own
repository or docs and reading the line that names LocalAI. The ones that
failed that test are listed in the data file so nobody re-adds them.
The blog cards were hand-written, which is how one of them came to advertise
"Porting vLLM to C++", a post that does not exist, and how all three linked to
the blog index instead of an article. They range over the posts now.
The section intro used the "a changelog tells you what moved, these posts show
you what it does" shape, which is the standard machine-written antithesis. It
states what the posts contain instead, including the perplexity regression
that APEX costs, because publishing the price is the actual claim.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5[1m]
The band led with three sentences of hedging and printed a commit count
next to each employer, so a one-commit entry beside a large name read as
weakness rather than as the modest, true claim it was. It now opens on the
contributor count, sets the employers as a sentence instead of a pill wall,
and keeps the caveat to one line. The counts stay in ecosystem.yaml, since
they are the provenance for the list and anyone re-checking it needs them.
Two "coverage" cards were not about this project. The modelslab.com piece
reviews Frikallo/parakeet.cpp, an unrelated project of the same name, and
the snailtext.app benchmark measures Parakeet through ONNX Runtime without
mentioning LocalAI at all. Both are removed, along with the contributor
card that duplicated the band's opening line.
Press was four posts from one vendor, which read as the whole of the
coverage rather than one enthusiastic outlet. SUSE collapses to a single
series entry, and Pulumi, Semaphore and Spectro Cloud join it. Each was
opened and checked against the project before being added. K8sGPT and
LlamaIndex join the integrations; both document LocalAI as a backend.
The quotes move above the lists so the section opens on its strongest
line, which is somebody else's. The hero gains a GitHub call to action,
the APEX collection link was returning 404 and is corrected, and the
footer no longer describes the site as a design mock.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5[1m]
Follow-up to 42541dd4f, which routed lint to arc-runner-set. Both of its
jobs failed there in one second (run 30637392862): the runner image has
git, curl, unzip, tar, ldd and python3, but not make, and build-scripts
additionally needs gcc because the packaging-script tests compile a
throwaway binary and inspect it with ldd.
golangci-lint needs make twice over: `make protogen-go` (which also wants
curl + unzip to fetch protoc) and `make lint` itself. So both jobs go back
to ubuntu-latest.
gh-pages.yml stays on arc-runner-set and is unaffected: it uses no make and
no C toolchain, and setup-go / actions-hugo fetch their own toolchains.
The preflight steps stay. They cost about a second on the hosted pool, and
they are what turned this into a one-second named failure instead of an
opaque one midway through a build. When the runner image gains make + gcc,
re-routing is one runs-on line per job. Any such re-route must stay
push-only: lint also runs on pull_request, and fork PRs execute untrusted
code that must not reach a persistent self-hosted runner.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5 [ClaudeCode]
The GitHub-hosted runner pool is shared per ACCOUNT, not per repo, so a
burst in one repo starves every other. On 2026-07-31 it reached zero
scheduled jobs for 35 consecutive minutes with 39 jobs queued, while
arc-runner-set completed 12 jobs without interruption across the same
window. Actions was healthy globally (other public repos were scheduling
normally), so this is an account-level throttle we cannot fix from inside
the workflows, only route around.
Site publishing and lint are small, run on nearly every commit, and gain
nothing from waiting behind a saturated hosted queue, so both move to
arc-runner-set, the label already proven in generate_intel_image.yaml.
lint.yml is routed for PUSH ONLY, and this is the important part: that
workflow also triggers on pull_request, and a fork PR executes untrusted
contributor code. Running that on a persistent self-hosted runner would be
a real compromise vector, so anything that is not a push to mudler/LocalAI
stays on the ephemeral hosted pool. gh-pages.yml needs no such clause: it
triggers only on push-to-master and workflow_dispatch, so it never runs
pull-request code. Both carry a repository guard so forks, which have no
such runner label, fall back to hosted instead of queueing forever.
Neither workflow uses sudo or apt, and both fetch their own toolchains via
setup-go / actions-hugo. A self-hosted image can still be leaner than the
hosted one, so each lint job opens with a preflight that names the missing
tool (curl/unzip/make for protoc and lint; gcc/ldd/python3 for the
packaging-script tests) rather than failing opaquely mid-build. Reverting
is one runs-on expression per job.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5 [ClaudeCode]
Signed backend verification performs separate registry requests for manifests and referrers. Reuse LocalAI's version-aware User-Agent there so the full install flow is attributable to LocalAI.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Adds the "who turns up around this project" section, split into three lists
because the evidence behind each one is a different strength and collapsing
them into a single logo wall would overclaim.
Contributors 21 companies whose engineers have commits here. Evidence is
the commit history plus the employer on that person's public
GitHub profile, so it is a claim about the person. Commit
counts are shown next to each name, including the ones that
are a single patch, because hiding that would be the whole
problem.
Integrations six projects that reference LocalAI in their own repository
or documentation, which anyone can verify without asking us.
Press four SUSE Communities articles about running LocalAI.
Names are set in type rather than fetched as logos. A logo reads as
endorsement, and a one-line typo fix from somebody who happens to work at a
large company does not support that, quite apart from what their trademark
policy says about it.
ADOPTERS.md is the mechanism for the stronger claim. An organisation that
wants to be listed as a user opens a pull request adding itself, which is both
the evidence and the permission, and is publicly auditable afterwards. The
file says plainly what the website does and does not claim, so the next person
to ask "can we add some big names" has the answer in the repository.
Assisted-by: Claude Code:claude-opus-5 [Bash] [Edit] [Write] [WebSearch]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(website): split the site, move docs to /docs, add a landing page
The Hugo docs site has always been localai.io itself, which left nowhere to
explain what LocalAI is or show what the team builds. This adds a separate
marketing site at the root and moves the documentation under /docs/.
Docs:
The existing site keeps its content tree and its Relearn theme, and now
builds with baseURL <root>/docs/. Its _index.md, which held a hand written
landing page, becomes a real documentation home.
Every previously published URL keeps working. GitHub Pages has no server
side rewrites, so .github/ci/gen-redirects.sh walks the built docs output
and leaves a meta refresh plus a canonical link at each old root path. It
covers bare .html files too, which is what keeps /gallery.html alive, and
it never overwrites a path the marketing site already owns.
Website:
A second Hugo site under website/ with its own layouts and no external
theme, so the marketing side does not have to fight Relearn's home rooted
menu and asset pipeline. CI builds both and merges them into one Pages
artifact.
The design is derived from the project logo rather than invented: the navy
of the triangle, the cyan of the llama, the purple of the speed bars. Those
offset bars became the motion signature. The background renders a real
depth-anything.cpp depth map as contour lines and switches to a
locate-anything.cpp style detection overlay over the engines section.
Also included: an /engines/ index driven entirely by data/engines.yaml, a
/blog/ section with five posts written from the release notes and the
engine benchmark suites, install.sh and a Kubernetes manifest since the
site advertises both, and a rule in .agents/ that release preparation now
includes a blog post and demo clips.
Every figure on the site is derived from the repository or the GitHub API,
not from memory. Correcting them against their sources found one error in
README.md: voxtral-tts.c is text to speech, not speech to text.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5 [Bash] [Edit] [Write] [Agent]
* feat(website): add a star history chart, rewrite the history post in first person
The history post read like a changelog written by a committee. It is now in
Ettore's voice, first person, with the admissions left in.
The numbers paragraph in particular read like a directory listing. It now says
what the figures mean rather than which file they came from.
Adds an interactive star history chart, built from the GitHub stargazers API
rather than embedded from a third party, so the page makes no external request
and cannot break when someone else's service is down. The four releases the
post is organised around are marked on the curve, and the labels stack into
rows because three of them land within two months of each other.
The API stops paginating at 40,000 items, so the curve is measured up to
December 2025 and the segment from there to today's total is drawn dashed,
labelled as an estimate in the caption and in the tooltip. It is a straight
line between two known points, and the chart says so rather than implying it
is data.
Also drops "marketing site" from the README heading and everywhere else it
appeared, and calls it the main site instead.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5 [Bash] [Edit] [Write]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
PR #11041 rewrote the testllama31inputResult1 fixture and un-escaped the
backslashes inside its Go raw-string literal, turning `[^"\\]` into
`[^"\]` and `["\\/bfnrt]` into `["\/bfnrt]`. The fixture is compared
line-by-line against the grammar built from PRIMITIVE_RULES in
bnf_rules.go, which is unchanged and still emits the doubled form, so
"generates a valid grammar from JSON schema" fails on every platform.
Restore the four fixture lines to their pre-#11041 form. The cyclic $ref
and depth specs added by that PR are untouched.
The regression reached master because only the DCO check ever reported
on #11041; its test runs were cancelled during the CI purge.
Assisted-by: Claude Code:claude-opus-5[1m] [Bash] [Edit]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Add the Qwen3.5-MoE POCKET-35B and Gemma 4 POCKET-26B releases with Q4, Q2, and compact IQ1 variants where available. Verify every artifact hash against its Hugging Face linked etag.
Assisted-by: Codex:gpt-5 [web]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* refactor(ui): add layout/text primitives and per-page CSS blocks
The React UI already shipped a design system (tokens, form grids, data
tables, stat cards, callouts) that the pages largely bypassed: ~2,000
`style={{ ... }}` literals across src/pages and src/components. Each one is
a spacing or colour decision made locally, so no two pages share a rhythm,
which is the main reason the app reads as unfinished rather than as one
product.
Two additions, both to App.css:
- A small semantic primitive layer: .stack / .hstack for vertical and
horizontal rhythm, .text-note / .text-sub / .text-meta / .text-mono for
the text roles the pages kept re-deriving, .tone-* + .icon-chip for
semantically tinted icons, plus scale-locked spacing and size steps.
Deliberately short and semantic, not a utility framework: the size and
spacing classes exist mainly so that an OFF-scale value stays an inline
style and therefore stays visible.
- Named blocks for the shapes fifteen pages actually have (.p2p-diagram,
.usage-tile, .tr-code, .mw-badge, .set-rail, ...), so those shapes are
defined once instead of per call site.
Two findings worth recording. The type scale is xs 0.6875 / sm 0.8125 /
base 0.875, and 0.75rem was in use roughly 100 times without being on it
(along with 0.7, 0.85, 1.1 and 0.625rem); all now snap to the nearest step.
And there were thirteen distinct table column widths across the app where
three or four would do; they are pulled into .col-w-* so the ladder is
visible in one place, ready to normalise separately.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5 [Bash] [Edit] [Write]
* refactor(ui): move repeated inline styles onto shared classes
Six passes over src/pages and src/components, each matching a whole
`style={{ ... }}` attribute exactly so the swap is provably equivalent:
- the identical "waiting for the first response" wrapper, repeated
verbatim in 21 files
- text roles (size + colour combinations) onto .text-note / .text-meta /
.text-sub / .text-mono
- semantic colours, type-scale steps, .panel-title, .list-row
- spacing and weight steps, .stack / .hstack rows
- table column widths, small pills, chart legend swatches
- the remaining shapes appearing three or more times
One class of bug is worth calling out, because it is what a careless
style-to-class conversion produces and it is invisible to every check we
run. Adding `className="x"` to an element that already had a className
leaves TWO className attributes; JSX keeps the last and silently drops the
first, so `<i className={icon} className="text-xs" />` loses its icon while
passing eslint, `vite build` and the full Playwright suite. 112 of these
were introduced and repaired here. The gate added in a later commit fails
on them.
No visual change is intended beyond snapping off-scale font sizes onto the
type scale. Verified after every pass: eslint 0 errors, vite build passes,
Playwright page-render-smoke + navigation 22/22.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5 [Bash] [Edit] [Write]
* refactor(ui): convert fifteen pages onto named classes, add inline-style gate
Full per-page conversions, each one reading the page, naming the shapes it
actually has, and leaving inline only what is computed at runtime:
P2P 205->0 Traces 50->0 ConfigFieldRenderer 23->0 NodeDetail 29->1
ModelEditor 25->1 NodeInstallPicker 29->1 FineTune 175->2
Nodes 33->2 ImportModel 35->3 Talk 43->4 AgentJobDetails 27->4
Usage 97->6 Settings 24->6 Middleware 54->8 Backends 87->45
Every remainder is genuinely dynamic: a data-driven badge colour, a
`width: ${pct}%`, a tooltip's coordinates.
Naming the shapes made reuse fall out on its own. Nodes reuses the P2P
setup shapes (both present the same "no workers yet, here is how to add
one" flow) and Model Editor reuses the Settings section rail, which was
byte-identical. Two shared *style objects* also turned out to be classes
wearing a costume and were deleted: `monoCell` in Usage and `hintStyle` in
ImportModel.
Some fixes fell out of the conversion. The evaluation toggle on the
fine-tuning page was a hand-rolled div that rendered as a clipped circle;
it is the existing Toggle component now. That page's empty state pointed at
a "New Job" button that was scrolled off the top of the page, and now
carries its own call to action. And `.input--file` is added at the system
level rather than as a local hack, because ImageGen and VideoGen truncate
their file inputs the same way today.
scripts/inline-style-gate.mjs is the ratchet that keeps this from
regressing. It does not forbid inline styles; it fails when the total goes
UP (same discipline as the coverage baseline) and when an element carries
two className attributes. eslint would catch the latter via
react/jsx-props-no-duplicate-props, but that needs eslint-plugin-react,
which this project does not depend on, so the check lives next to the tool
that causes the problem.
npm run lint:inline-styles # check against baseline
npm run lint:inline-styles:report # per-file counts, worst first
npm run lint:inline-styles:write # refresh after converting
Net: 2,061 -> 611 inline styles. eslint 0 errors, vite build passes,
Playwright page-render-smoke + navigation 22/22, gate green on both checks.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5 [Bash] [Edit] [Write]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
refactor(backends): extract shared package-system-libs.sh from package.sh
The arch-detect-and-copy-system-libs block (Darwin rpath / x86_64 / aarch64
loader + libc/libstdc++/libgcc_s/libm/libgomp/libdl/librt/libpthread) was
inlined verbatim in 31 backend package.sh scripts. Extract it into a single
sourced scripts/build/package-system-libs.sh, the CPU-side counterpart to
scripts/build/package-gpu-libs.sh and its sourcing contract.
Consolidating the copies fixes three drift classes that had crept in:
- libgcc_s.so.1 and libstdc++.so.6 were listed twice in 9 backends
(acestep-cpp, crispasr, moss-tts-cpp, omnivoice-cpp, piper,
qwen3-tts-cpp, silero-vad, stablediffusion-ggml, whisper); the shared
script copies each once.
- libgomp.so.1 was omitted from opus. OpenMP consumers dlopen it rather
than link it, so the missing copy only failed at runtime; the shared
script always includes it.
- the Darwin @loader_path/lib rpath was applied only in piper and
silero-vad; both now pass their packaged binary to the shared script,
preserving that behavior. Every other backend passes an empty binary
path so no rpath is added, preserving its current behavior.
Each backend's pre/post packaging steps (binary copy, run.sh, ldd closure
walks, ggml variant bundling, espeak/OpenBLAS extras, the ds4 validate step)
are preserved verbatim; only the inline if/elif/else arch block is replaced
by a single source line.
Signed-off-by: supermario_leo <leo.stack@outlook.com>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
* fix(backends): fall back to copying links when the filesystem rejects symlinks (#10890)
Backend installation extracts the OCI image tar via containerd's
archive.Apply, which calls os.Symlink directly. On filesystems that do
not support symlinks (notably CIFS/SMB mounts, commonly used to back the
/backends volume) the syscall fails with "operation not supported" and
the whole install aborts, leaving an empty backend directory. The CUDA
llama.cpp image trips this on the libcublas.so -> libcublas.so.12.x
symlink.
When archive.Apply fails with a link-unsupported error, reset the
staging directory and re-extract with a pure-Go walker that still
attempts real symlinks/hardlinks first and degrades to copying the link
target's contents in place when the filesystem rejects them.
mutate.Extract already flattened the layers, so the tar carries no
whiteouts to interpret. Link copies are deferred to a second pass so
forward references resolve.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4.8 [Claude Code]
* fix(oci): check deferred Close in copyFilePreservingMode (errcheck)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4.8 [Claude Code]
* fix(oci): reject path-traversal tar entries in the link-copy fallback
safeJoin sanitized "../.." entries by clamping them under root instead of
rejecting them, so a malicious entry was silently redirected rather than
refused. Join without the leading-slash trick and reject any entry whose
cleaned path resolves outside root; absolute link targets are still mapped
under root (image-root relative) rather than escaping.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4.8 [Claude Code]
* fix(oci): silence gosec on the validated link-copy file ops
Use hdr.FileInfo().Mode() instead of converting the int64 tar mode to
os.FileMode (removes two G115 overflow findings), and annotate the tar
extraction file operations with justified #nosec comments: every path is
validated by safeJoin against the extraction root before use (G304/G305).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4.8 [Claude Code]
* fix(oci): build extraction image from downloaded layers
Avoid appending downloaded layers to the original remote-backed image, which duplicates the layer stack and reopens the source during extraction. Building from an empty image preserves the flattened whiteout semantics while keeping extraction local.
Assisted-by: Codex:gpt-5
* fix(oci): materialize chained links in dependency order
Retry deferred link copies until their targets exist so soname chains work on filesystems without symlink support. Document that copied links can increase backend storage usage on CIFS and SMB mounts.
Assisted-by: Codex:gpt-5
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* feat(api): add /v1/detokenize endpoint
Closes#1649.
Mirror of the existing /v1/tokenize path, requested by @benniekiss in
the issue thread for "complete API workflow" use cases that need to
turn token IDs back into text without local processing.
- Add Detokenize gRPC RPC with DetokenizeRequest{tokens} /
DetokenizeResponse{content} messages.
- Implement in the llama.cpp backend using common_token_to_piece, the
same primitive TokenizeString already uses internally.
- Other backends inherit the default Unimplemented from base.Base, in
line with how Detect, Rerank, etc. are gated per-backend.
- Wire up the Go gRPC interface, server, client, and in-process embed
wrapper alongside their TokenizeString counterparts.
- Add the schema types, ModelDetokenize wrapper, HTTP handler, route
registration, RouteFeatureRegistry entry (gated by FeatureTokenize so
no new feature flag is needed), and the discovery map entry under
ai_functions.
- Regenerated swagger reflects the new endpoint and types.
- Update authentication.md to list /v1/detokenize alongside /v1/tokenize.
Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com>
* test(e2e): add mock backend tests for /v1/detokenize
Add Detokenize to the mock gRPC backend and wire up two e2e tests in
the MockBackend suite: one that posts known token IDs and asserts a
non-empty content response, and a round-trip that tokenizes first then
detokenizes the returned IDs.
Addresses reviewer feedback on #9620.
Assisted-by: Claude:claude-sonnet-4-6
Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com>
* fix(kokoros): implement detokenize in the Rust backend service
The Detokenize RPC added in this PR grows the tonic-generated Backend
trait. Unlike the other languages there is nothing to inherit a default
from — Rust trait impls must list every method — so
backend/rust/kokoros failed to compile:
error[E0046]: not all trait items implemented, missing: `detokenize`
--> src/service.rs:72:1
72 | impl Backend for KokorosService {
Go backends pick up the Unimplemented default from base.Base, and the
generated C++/Python servicer bases default to UNIMPLEMENTED, which is
why the Rust backend was the only one that broke. kokoros is the sole
Rust crate in the tree, so this is the full extent of the fallout.
Return Status::unimplemented("Not supported"), matching how this same
file already gates tokenize_string and ~20 other unsupported RPCs.
Fixes the tests-kokoros and backend-jobs-singlearch-4 (-cpu-kokoros)
failures on the previous head.
Assisted-by: Claude:claude-opus-5 cargo
Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com>
---------
Signed-off-by: Adira Denis Muhando <dennisadira@gmail.com>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
On 2026-07-30, 12 of the 23 queued runs of this workflow were commits like "add
1 new model to gallery" or a docs fix, each rebuilding all 18 container images.
That was roughly 216 queued jobs producing byte-identical output, in a queue
holding 1071 jobs with an oldest entry two days old.
Verified against the shipped Dockerfile before assuming it: the final stage
copies only entrypoint.sh, healthcheck.sh and the local-ai binary, there is no
go:embed of gallery/ or docs/, and the gallery is fetched at runtime from
github:mudler/LocalAI/gallery/index.yaml@master. A gallery-only commit produces
an identical image, and the gallery change reaches users through GitHub whether
or not an image is rebuilt, so nothing is delayed by skipping.
Add a `changes` job that decides once whether the push can affect an image; the
other 11 jobs take `needs: changes` and an `if:` on its output.
A job gate rather than paths-ignore on the trigger, for two reasons that both
fail silently if got wrong:
- paths-ignore on `push` also applies to tag pushes, and a tag created on an
existing commit carries an empty commits list. That would skip the release
image build with no failure anywhere. The gate short-circuits to build for
refs/tags/*, and for a base commit that is missing, zero or unresolvable --
the same run-everything posture the backend matrix filter takes for a
truncated diff.
- the merge jobs use `if: ${{ !cancelled() && ... }}`, and !cancelled() is
true when a dependency is skipped, so they need the gate named explicitly
or they would try to merge manifest lists for images never built.
Checked the decision logic against real commits from the queue: the two
gallery/docs commits resolve to build=false, the two code commits to build=true,
and all three fallback paths (tag, zero base, unresolvable base) to build=true.
Assisted-by: Claude:opus-5 [claude-code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Document all stateful container paths, explain upgrade behavior and UnRAID mappings, and correct the obsolete troubleshooting mount target.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
docs: clarify reverse proxy bulk job guidance
Mention ingress controllers as another place to configure equivalent upstream response timeouts, and include an example private LocalAI URL for trusted bulk jobs.
Assisted-by: Hephaestus:openai/gpt-5.5 [opencode]
Signed-off-by: Owen Adirah <owenadira@gmail.com>
Stage the negative GPU-layer sentinels expected by the upstream argument parser, then restore LocalAI resolved values unless a passthrough flag explicitly overrides them. This avoids the parser assertion that terminated the backend for any generic option.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Version-pin bumps dominate PR volume: 48 update/* PRs in the week to
2026-07-30, from 16 pins, each a two-line diff. bump_deps.yaml runs a 28-entry
matrix daily and opens one PR per moved pin; CRISPASR and the gallery checksum
produced one every day, ik-llama-cpp six in seven days. Almost all of them edit
nothing but a single backend/*/<name>/Makefile.
Neither image-pr.yml nor build-test.yaml can observe such a change. `make build`
is `go build ./cmd/local-ai`, GoReleaser builds that plus ./cmd/launcher, and
the core image's final stage ships only entrypoint.sh, healthcheck.sh and the
binary. The per-backend trees are copied into the builder but nothing in them
reaches the output. That is 7 + 3 jobs per bump PR that cannot fail for a reason
the diff caused, roughly 410 jobs a week.
Add backend/{cpp,go,python}/** to the paths-ignore of those two workflows. The
inputs that do reach the binary are deliberately outside those prefixes and so
still trigger a full run: backend/backend.proto (protogen-go), go.mod/go.sum
(the go mod tidy before-hook), and backend/Dockerfile.* .
Not applied to the workflows that genuinely read that tree:
test.yml TEST_PATHS names ./backend/go/{cloud-proxy,local-store,
valkey-store}/...
lint.yml .golangci.yml carries backend/-scoped rules
tests-e2e.yml the e2e suite drives real backends over gRPC
backend_pr.yml its whole job is rebuilding the changed backend
Simulated against the change shapes that occur in this repo. Pin bumps and
python requirement bumps skip; backend.proto, go.mod, a core Go edit, a
backend/Dockerfile edit and any mixed diff all still run, since paths-ignore
skips only when every changed file matches.
Assisted-by: Claude:opus-5 [claude-code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
.agents/ci-caching.md stated that `cache-to: type=registry,mode=max` "exports
the cache mount data into the registry cache, so subsequent builds restore it".
BuildKit does not do that. A `--mount=type=cache` lives in the builder's local
state and is not part of a registry cache export, and every CI job gets a fresh
runner with a fresh builder, so /root/.ccache starts empty on every build.
The compile script already prints `ccache -s` after a `ccache -z`, so the
evidence was sitting in the logs:
job 89766266951 llama-cpp cublas-13 6369s 0 / 889 hits (and 0 / 1778)
job 89766267281 llama-cpp hipblas 8160s 0 / 537 hits
job 90210828110 llama-cpp cublas-12 5673s 0 / 813 hits
The first two are the control. Their commit, 90355cd44, changed exactly one
file: backend/go/magpie-tts-cpp/Makefile, nowhere near llama.cpp. The engine
source was byte-identical to the previous build, which is the case this section
claims ccache serves, and the hit rate was still 0.00%. A restored-but-stale
cache would show partial hits; 0-of-N is an empty cache.
So llama-cpp, ik-llama-cpp, turboquant, bonsai, ds4 and privacy-filter pay the
ccache wrapper overhead and get nothing back, and multi-hour C++ builds
recompile identical translation units every time.
Record this rather than silently extending it. Wiring the same mount into
Dockerfile.golang, which covers 215 of the 434 matrix entries, measured 18%
faster locally on a rebuild after a source edit with a 71.5% hit rate, but only
because that test reused a single builder across both builds. In CI it would be
a no-op. The note spells out what would actually work (ccache remote_storage or
sccache with a real backend, or round-tripping the cache dir through
actions/cache) and what each costs.
Also correct the composite-actions list, which still named test.yml as a
free-disk-space consumer after #11219 removed it.
Assisted-by: Claude:opus-5 [claude-code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Dockerfile.golang builds 215 of the 434 matrix entries: every ggml/C++ engine
wrapped in Go. Each of those Makefiles clones an upstream repo at a pinned SHA
and compiles it once per SIMD variant (depth-anything-cpp builds four: avx,
avx2, avx512, fallback), and those variant targets depend only on the clone.
They cannot observe a change anywhere else in the LocalAI tree.
The compile sat below `COPY . /LocalAI`, so any edit anywhere invalidated it and
recompiled C++ that had not changed. Move it above that COPY, behind a copy of
only the backend's own directory.
This lands the compile in the part of the image the registry cache already
restores. Measured on two real CI builds of this Dockerfile (jobs 90551029008
and 90551028904, both fresh runners): 13 of 17 layers CACHED from
quay.io/go-skynet/ci-cache. The uncached tail is exactly `COPY . /LocalAI`, the
git-config RUN and the build RUN. Putting the engine above the COPY moves it
from the uncached tail into the cached region.
Local measurement, depth-anything-cpp CPU, rebuild after editing a Go file
outside the backend:
master 78s, 216 C++ objects compiled
this change 25s, 0 C++ objects compiled (67% faster)
Note what this deliberately is not. An earlier attempt wired a
--mount=type=cache ccache into the same RUN. BuildKit does not export cache
mounts to a registry cache, so that measured well locally and is a no-op in CI
(see the ccache section of .agents/ci-caching.md). This change relies only on
ordinary layer caching, which the 13-of-17 figure above shows already works
here.
The layer copies the backend's whole directory rather than just the Makefile:
the CMake targets also need CMakeLists.txt and the file list differs per
backend. The cost is that editing a backend's own Go sources invalidates its
engine layer. The expensive cases are unaffected, since a shared-build-input or
backend.proto change, the weekly full-matrix cron and a tag push all rebuild
every backend while touching none of their directories.
Scoped to one backend for now: only depth-anything-cpp gains the `engine`
target. The other 27 fall through the `make -n engine` guard and build exactly
as before, verified against local-store and silero-vad. Rolling the target out
to the remaining 12 backends that define VARIANT_TARGETS is mechanical once this
is confirmed against the registry cache on master.
One caveat on merge: inserting layers shifts the cache keys, so the first build
of each entry after this lands is a full miss. It pays for itself on the second.
Assisted-by: Claude:opus-5 [claude-code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Measured over the week to 2026-07-30, 97% of CI wall-clock is queueing and 3%
is execution: a median 5-hour queue against a 4-20 minute median job. With the
queue saturated, throughput is concurrency divided by service time, so cutting
execution time raises the drain rate directly. Two steps stood out as paying
nothing for what they cost.
test.yml: drop the free-disk-space step (~3.1min per run, ~22 h/week). That
action exists to make room for docker buildx layers and this job runs no buildx
step. It was also sized for a `make test` that downloaded multi-GB GGUF/whisper
fixtures and built llama-cpp/whisper/stablediffusion-ggml; the test-suite reorg
moved all of that into tests/e2e-backends and tests/e2e-aio, as the Makefile
test target already records. Its tool-cache:true wipe was additionally deleting
/opt/hostedtoolcache, forcing setup-go and setup-node to re-download toolchains
that ship preinstalled on the runner.
build-test.yaml: build only the host target on pull_request. The three-platform
cross-compile (linux/amd64, linux/arm64, darwin/arm64) is the bulk of that job's
~6.6min median, ~47 h/week, and nothing consumes a PR's binaries. goreleaser's
--single-target still runs every before-hook (protogen-go, react-ui, go mod
tidy), so the "is the release build broken" signal is unchanged. master pushes
and tags keep building all three.
Also record why the Linux Go workflows pass cache: false to actions/setup-go,
since it reads as an oversight and is not. Set up Go has a median of 11 seconds
on those runners, so there is nothing to win, and the repo already sits at
GitHub's 10 GB Actions cache ceiling with 31 entries, where each setup-go entry
is 222-375 MB on Linux and up to 1.4 GB on macOS. Re-enabling it would evict
something that is earning its space.
Assisted-by: Claude:opus-5 [claude-code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(vllm): apply Options[] engine flags before engine init (#11130)
CLI-style flags in a model's `options:` array (`--quantization:gptq_marlin`,
`--enable-prefix-caching`, `--kv-cache-dtype:fp8_e5m2`) were discarded: the
backend only ever read `tool_parser`/`reasoning_parser` out of Options[], and
did so *after* `AsyncLLMEngine.from_engine_args()`, where nothing it set could
still reach the engine.
Map `--` prefixed options onto the AsyncEngineArgs dataclass before the engine
is constructed. Names are normalized the way vLLM's CLI spells them
(`--enable-prefix-caching` -> `enable_prefix_caching`), values are coerced to
the target field's type (bare flag -> True for booleans), and unknown or
uncoercible flags warn and are skipped instead of failing the load, since
Options[] is a bag shared with backend-level settings. Field types come from
the annotation's base so `Literal["auto", "float16"]` (vLLM's dtype) is not
mistaken for a float.
Precedence is typed proto fields -> `options:` -> `engine_args:`. The
production engine_args defaults seeded in hooks_vllm.go therefore skip any key
the user already set as an option, otherwise the later engine_args pass would
silently override it. Parser lookups now accept both spellings, so
`--reasoning-parser:qwen3` selects LocalAI's parser as well.
The helper's tests are stdlib-only and run in the lint workflow's
dependency-light job via `make test-python-helpers`.
Assisted-by: Claude:claude-opus-5 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
* backend(audio-cpp): add the native build scaffold
Links 0xShug0/audio.cpp engine_runtime through its public framework headers
and serves Health/Status. Model loading and the audio RPCs follow.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): keep the build-tree rpath at $ORIGIN
Upstream sets CMAKE_BUILD_WITH_INSTALL_RPATH in its own directory scope, so
CMake was appending its build-tree library dir to our target and baking an
absolute build-host path into the shipped binary. Set BUILD_WITH_INSTALL_RPATH
on the target so a package that forgets to bundle libggml*.so fails on the
build machine too, instead of only on a user's box.
Also document why EXCLUDE_FROM_ALL must stay on the add_subdirectory call,
correct the claim that Ubuntu ships no gRPC CMake config, stop the pin comment
from repeating the assignment token that bump_deps.sh rewrites, and make
test-engine fail rather than pass when no test is registered.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): parse namespaced model options
Splits option entries on the first colon so path values survive, and routes
load./session. prefixes to the upstream load and session option maps.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): reject out-of-range numeric model options
std::atoi is undefined once the digits exceed long and in practice wraps, so
device:2147483648 was accepted and handed the ggml backend selector a device
index of -2147483648 from a function whose error text promises a non-negative
integer. Parse with strtol and reject on ERANGE, on a value above INT_MAX, and
on any unconsumed trailing input. The error strings are unchanged.
Name the whole entry in the unknown-key error too: an entry like ':value' has
an empty key and left the user nothing to grep for in their YAML.
Tests look keys up through a helper instead of map::at, so a prefix off-by-one
fails one named check rather than aborting the binary and skipping the rest of
the suite, and cover the overflow, negative and non-numeric paths.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): route LocalAI RPCs onto audio.cpp tasks
Task-major resolution over the family's advertised capability set, with the
voice-reference and instructions signals selecting cloning and voice design,
and a streaming-to-offline fallback for server-streaming transcription only.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): use upstream's 'spk' task name and pin the preference order
The SpeakerRecognition short name was 'spkrec', which audio.cpp neither prints
nor parses; a name copied out of audio.cpp was rejected and a pinned 'spkrec'
would not survive the engine boundary. Emit 'spk', keep 'spkrec' as an
input-only alias, and correct the known-tasks lists.
Three assertions were vacuous because their fixtures advertised a single task,
so reversing a preference order or dropping the RPC name and the attempted
pairs from the capability error all passed. Give them fixtures that can tell
the orderings apart.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): convert sample, time and PCM units
Integer nanosecond conversion so 44.1 kHz stays exact, float seconds for the
VAD and diarization messages, and saturating s16le encode so an overshooting
sample cannot wrap to the opposite sign.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): harden seconds_to_samples against NaN and overflow
seconds_to_samples is the one entry point fed by untrusted-shaped input: a
float-seconds timestamp off the wire, or a boundary from a model that diverged.
Its guard covered only the low side, so NaN and out-of-range values fell through
to an undefined double-to-int64 cast and came back as INT64_MIN. A hugely
negative sample index used later as an offset or a length is a wild pointer
rather than merely a wrong timestamp. Reject NaN with the !(x > 0) form and
saturate before the cast.
Also round instead of truncating there. These functions exist to cross the float
seconds boundary the VAD and diarize messages use, and truncation lost a sample
about half the time on the samples-to-seconds-and-back round trip, starting at
n=1.
Pin the decode scale at INT16_MIN, pin nanosecond truncation on a nonzero
fraction, and record why the clamp argument order in f32_to_s16le is
load-bearing for NaN.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): map NaN PCM samples to silence explicitly
f32_to_s16le relied on std::min argument order to keep a NaN sample away from
std::lround, whose result is unspecified for NaN. That was too subtle to rest on
a comment, and the comment was itself wrong: it warned against a spelling that
the outer std::max already catches, while three real spellings leak, including
std::clamp, which is the idiomatic C++17 way to write the same clamp and so the
likeliest future edit.
Divert NaN before the clamp and encode it as 0. A NaN sample rendered as a
full-scale click is worse audio than a dropped one, and this unit converts audio
that may have originated off the wire.
Pin it with an exact-value check rather than a range check, since all three
outcomes the plausible spellings produce are finite and inside full scale, plus
an invalid-operation check that fails unless the NaN is diverted before any
ordered comparison. That second check is what catches modernizing the clamp and
dropping the guard together.
Also bound the seconds round-trip comment, which claimed unconditionally what
holds only below roughly 2^23 samples, and document NaN, saturation and that
bound in the header.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): assemble transcripts from runtime spans
The top-level transcript text is TaskResult.text_output verbatim. audio.cpp
carries text nowhere else: speech_segments, speaker_turns and word_timestamps
hold spans and labels only, so deriving the text from them empties the
transcript for any producer that omits word timing, VibeVoice diarized ASR
included. Fixtures cover every observed producer shape.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): keep a nested speaker turn's own label
A segment sourced from speaker_turns re-derived its speaker by greatest
overlap. A turn's overlap with its own span is the largest possible, so a turn
nested inside another speaker's turn could only tie with the container, and the
tie went to whichever came first. sortformer_diar binarizes each speaker
independently and sorts by start sample, so the container always comes first
and the interjecting speaker was silently erased from DiarizeSegment.speaker.
choose_segment_spans now carries the label out with the span.
Also pins the nearest-segment fallback against measuring from either endpoint
or from segment position, which a trailing-only stray word could not do, and
exercises the empty-word guard in join_words. Two fixtures that pin a rule but
do not mirror any pinned family are relabelled defensive.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): serialize runs with a wedge-aware guard
audio.cpp sessions are not reentrant and a wedged CUDA call cannot be
cancelled, so a plain mutex would pile every worker thread behind a stuck GPU.
Callers waiting past the configured bound, or arriving while the holder has
already overrun it, fail fast instead.
A caller that queues behind a healthy run deliberately does not stamp the
clock: only the thread that takes the lock does. Stamping on arrival would
restart the wedge clock on every request and hide a stuck run from everyone
behind it, which is the pile-up this guard exists to prevent.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): serialize inference through an InferenceLane
One audio.cpp model is loaded per backend process and its sessions are not
reentrant, so concurrent gRPC handlers have to take turns. Serialization alone
is not enough: a wedged GPU call cannot be cancelled from userspace, so an
unbounded queue behind one stuck run would swallow every gRPC worker thread
until the process is useless.
InferenceLane gives handlers a lane with room for one runner. LaneEntry occupies
it for a scope and gives it back on every exit, including an exception, and is
the only way to take the lane at all: occupy/vacate are private with LaneEntry
as the sole friend, so a caller cannot acquire without holding something that
releases. LaneEntry is immovable on purpose, because a moved-from entry would
have to stop releasing while the lane still recorded it as occupied.
A caller either waits indefinitely or brings a millisecond budget. A bounded
caller that cannot get in fails instead of waiting on, and a bounded caller
whose budget is already shorter than the age of the run in the lane fails
immediately, which is what stops a queue forming behind a wedged run. The two
failures carry different text: one names the wait it exhausted, the other states
the measured age of the run without claiming to know why it is long, since a
short budget meeting a legitimately long run lands there too.
The run's age is stamped only after acquisition. A waiter that published itself
as holder would restart the measurement and hide a genuinely stuck holder from
every caller behind it.
Budget negotiation and the overrun decision are pure functions taking their
inputs explicitly, so both are covered without threads or sleeping. The
per-model ceiling arrives as an int of milliseconds; a request may tighten it
and may never loosen it.
Replaces the previous run_guard unit, which was a derivative of an
Apache-2.0 file upstream and could not stay in an MIT tree. Written from a
behaviour contract with no reference to the removed code.
Tests: 65 checks, standard library only, single translation unit, clean under
-Wall -Wextra. Mutation tested at 23/23 killed; two of those mutants exposed
missing coverage and the tests were extended until they died. ThreadSanitizer
clean.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): make the B10 test able to fail, and document LaneEntry
Review of the previous commit found the B10 test could not fail for the reason
it was named. It aged the in-flight run to about 120 ms and then tried two
budgets, 30 ms and 60 ms, both under that age, so both callers took the
fail-fast path. "The two failure modes do not share one message" was comparing
two fail-fast messages that differ only in the budget they print, and the
timeout path was never reached. The second budget is now 400 ms, well over the
run's age, so that caller queues and times out, and a new check asserts which
path each caller took instead of inferring it from inequality. A mutant that
makes the fail-fast path emit the timeout message previously died only on B4 and
B8 checks; it now also dies on B10.
Comment-only changes elsewhere. LaneEntry now says it is not reentrant and does
not detect reentrancy: a second entry on a thread that already holds the lane
surfaces as LaneUnavailable with a positive budget, but parks silently in
unbounded mode, which matters because a handler may hold one across a whole
stream. The immovability note now names the shapes that work, an optional
emplaced in place or a unique_ptr, rather than saying to hold the entry
indirectly without saying how; all three documented forms were compiled before
being written down, which is how the note came to say that an optional of an
immovable type cannot itself be returned.
The header's explanation of why fail-fast exists is reworded. Two clauses traced
back to a specification written after reading the Apache-2.0 upstream header,
and while that was judged de minimis, this unit was rewritten precisely to carry
no upstream expression at all.
The margin table in the report was also wrong about which wall-clock margins are
load-sensitive: there are four, not one, and the tightest is the B3 arrival
check, which is now flagged at the call site. No margin value changed and none
moved across 65 runs.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): gate model loading on the audio.cpp family
Refuses any GGUF without an audiocpp.model_spec.family key and any non-GGUF
path without an explicit family option, so the model loader's greedy backend
probe cannot bind an unrelated llama.cpp GGUF to this backend (#9287).
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): load models and cache sessions per task
Loads one ILoadedVoiceModel and creates an IVoiceTaskSession lazily per
(task, mode), so the same model serves both the unary and streaming RPCs.
LoadModel derives the family from GGUF metadata or an explicit option and
fails with INVALID_ARGUMENT otherwise, so a failed load is a gRPC error the
backend probe can see.
audiocpp_backend::Task mirrors engine::runtime::VoiceTaskKind positionally,
and drift there is silent: every unit still compiles and every test still
passes while the backend runs a different task. Two mechanisms pin it. The
static_asserts in loaded_model.cpp catch an insertion or a reorder, and
-Werror=switch on that one file turns an appended upstream enumerator into a
build failure rather than a warning in a 600 file log.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): stop aborting the process on SIGTERM
The signal handler called grpc::Server::Shutdown directly. Shutdown takes an
absl::Mutex, which is not async-signal-safe: the handler can interrupt a thread
already holding that mutex, and abseil's deadlock detector responds by aborting.
Every SIGTERM therefore ended in exit 134 and a 'dying due to potential
deadlock' stack rather than a drained shutdown.
The handler now sets a lock-free atomic and returns. Server::Wait moves to a
helper thread so the main thread can poll that flag and call Shutdown itself,
outside any signal context. A condition variable would not have helped, because
notifying one from a handler is not async-signal-safe either.
SIGTERM and SIGINT both exit 0 with no stack trace, where both previously
exited 134.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): correct the status, lifetime and state contracts of LoadedModel
An environment fault during session creation was reported as UNIMPLEMENTED. A
missing libggml-cpu-*.so surfaced to the client as 'family silero_vad advertises
vad/offline but refused to create the session: Failed to initialize CPU
backend', which tells LocalAI the model cannot do this and must never be
retried, and sends an operator hunting a capability bug instead of a packaging
one. A throw from create_task_session is now a plain runtime_error, so it maps
to INTERNAL. Only a null return, where the family genuinely declined, stays a
CapabilityError.
The model.'s task: option was parsed and then dropped: it lived in a local that
died at the end of LoadModel and had no route to RequestShape::pinned_task.
LoadedModel now keeps it and exposes pinned_task().
The global model becomes a shared_ptr reached through snapshot(). An audio RPC
runs for seconds and cannot hold g_model_mu for its duration, so under a
unique_ptr a Free arriving mid-request would destroy the model underneath it.
Handlers now take a counted reference and whichever finishes last does the
teardown, outside the lock.
session_for documents the streaming state contract rather than resetting the
session itself. Resetting on a cache hit was tried first and is not possible:
silero_vad throws 'session prepare() must be called before Silero VAD reset()',
so it would turn an ordinary second fetch into a hard error. start_stream's base
implementation is already a reset, so a caller that runs prepare then
start_stream per stream gets a clean session; a probe against the bundled
silero_vad confirms an identical replay when it does and a carried-over stream
when it does not.
Also: an unknown backend: name is rejected before the model loads rather than
after; MainGPU is parsed instead of passed through std::atoi, which turned
'gpu1' into device 0 silently; and device carries a device_set flag, because 0
is both the default and a real device index, so MainGPU was overriding an
explicit device:0 that the neighbouring threads: handling promises will win.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): serve the VAD and Diarize RPCs
Both emit float seconds, converted from the runtime's sample-index spans, and
both take a counted reference to the loaded model through snapshot() and hold it
for the whole call: a Free arriving mid-request drops only the global's
reference, so whichever request finishes last destroys the model instead of one
of them running on freed weights. An AddressSanitizer build reproduces exactly
that heap-use-after-free inside ggml_vec_dot_f32 when the handler keeps a raw
pointer instead, which is why the shape is what it is.
The inference lane is taken before session_for, not after. session_for reads and
writes an unsynchronised session cache and the offline run calls prepare(),
which mutates the session, so both belong inside the lane.
Diarize routes before it reads the input file, so a family that cannot diarize
at all says so rather than complaining about the audio first. Its per-segment
text stays empty because audio.cpp's SpeakerTurn carries a span and a speaker
label only, and nested or overlapping turns are passed through untouched: a
sortformer turn inside another speaker's turn is correct output for overlapped
speech, and LocalAI is overlap-tolerant downstream. Duration counts frames
rather than floats, so a stereo input does not report twice its length.
Verified end to end against upstream's bundled silero_vad, which needs no
download, using the bundled 16 kHz speech asset: a synthetic tone returns
nothing, correctly, because silero detects speech and a sine is not speech.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): enforce ModelIdentity on VAD and Diarize
audio-cpp was the only C++ backend without the model-identity guard, and no
later task in the plan added it. pkg/grpc/server.go enforces checkModelIdentity
on exactly these two RPCs, for the reason #10952 records: in distributed mode a
worker can recycle a stopped backend's gRPC port for another model's backend,
and the controller's liveness-only probe cannot tell a stale cached route from a
live one. Without this guard a stale route gets a different model's VAD or
diarization answer back with a 200.
The loaded identity lives on LoadedModel rather than in a separate global, which
is where this differs from llama-cpp. A handler holding the model through
snapshot() then necessarily judges against the identity that model was loaded
with, and a concurrent reload cannot swap one without the other. The refusal is
NOT_FOUND carrying the verbatim grpcerrors.ModelMismatchSentinel substring.
session_for and run_offline now take a const LaneEntry & proof-of-holding
parameter. The rule that both must run under the inference lane was prose, which
is exactly how the plan came to specify the inverted order; it is now a compile
error. Restoring the inverted order fails to build rather than racing on an
unsynchronised session map with a mutating prepare().
Diarize's speaker-hint comment claimed the dropped hints were "not a silent
failure". From the caller's side that is what they are, and backend.proto
documents num_speakers as forcing, so the comment now says plainly that the
forwarding is dead for sortformer and that the family which lands must either
honour num_speakers or refuse it. read_audio_file inspects the error_code from
exists(), so an unsearchable parent directory no longer reports as a missing
file. The VAD handler records the stimulus that actually works, since silero
correctly ignores synthetic tones and the next task would otherwise rediscover
that.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): make the lane and identity guards structural
Two hardenings ahead of the eleven handlers still to be written, both of which
get harder to retrofit later.
The lane proof-of-holding parameter was a const reference, which binds to a
temporary, so session_for(rpc, shape, model->acquire(0)) compiled. Each such
temporary dies at the end of its own full-expression, releasing the lane between
two calls that must share one: precisely the split the parameter exists to
prevent, and the form a future author is most likely to reach for because it
reads as tidy. A non-const reference requires an lvalue, so the temporary form
now fails to compile while the named-local handlers build unchanged. The header
comment no longer implies the check is total either: it proves a lane was taken,
not that it is this model's lane.
The identity check was two lines each handler had to remember, with nothing
failing if a new one forgot them and no C++ equivalent of
model_identity_modalities_test.go to notice. snapshot() becomes
snapshot_unchecked(), whose only legitimate caller is Status, since HealthMessage
carries no ModelIdentity. Handlers go through snapshot_for(), which takes the
counted reference, refuses when nothing is loaded, and runs the identity check
before anything can route. Every handler already has to call something to obtain
the model, so the guarded call is now the shortest path and skipping it means
deliberately typing snapshot_unchecked. A convention that has to be remembered
can rot; this cannot.
Verified: the temporary-argument and inverted-order forms each fail to compile
with the expected diagnostic, the real handlers build, and bypassing the guard in
Diarize alone turns the identity test red on that RPC while VAD stays green.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): serve the AudioTranscription RPC
Adds result_map, the engine-to-proto boundary, and wires the offline
transcription RPC.
The handler branches on the ROUTED task: for Asr the request's prompt is
whisper-style decoding context and becomes a request option, for Alignment
the same field IS the transcript to align and becomes the text input.
Routing has already decided which.
The result text is TaskResult.text_output verbatim and is never derived
from the segments. audio.cpp carries transcript text in text_output and
nowhere else, so deriving it returns an empty transcript for every
producer that reports segments without word timing. transcript_assembly
already enforces that; this commit's job is not to undo it at the proto
boundary, and result_map_ctest pins it there.
read_audio_file now takes the sample rate the caller needs. Both file-fed
speech handlers ask for 16 kHz mono, for two reasons: silero_vad and
sortformer_diar refuse anything else outright, which turned an ordinary
44.1 kHz upload into INTERNAL, and nemotron_asr emits word timestamps in
its own 16 kHz feature domain whatever the input was, so only a 16 kHz
buffer makes the emitted nanoseconds right. Zero keeps the file's native
rate and channels, which is what source separation will need.
LoadedModel::check_can_serve answers a capability refusal before the lane
is taken and before the input file is read. Routing is a pure read of the
immutable capabilities, so a model that cannot serve an RPC no longer
waits out somebody else's run to say so. VAD and Diarize use it too.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): stop linking sentencepiece's vendored protobuf
engine_runtime links sentencepiece, whose default SPM_PROTOBUF_PROVIDER
builds the protobuf-lite 3.14.0 sources it vendors. The generated
backend.pb.cc is built against the toolchain's protobuf 3.21.12. Both
ended up in the binary: 476 google::protobuf:: symbols came from the
archive, 278 of them also defined by libprotobuf.so, and the archive won,
because once ld pulls a member in for sentencepiece's own code every
reference binds to the definitions that member carries.
The visible symptom is one function.
ParseContext::ParseMessage(MessageLite*, const char*) is what a generated
_InternalParse calls for a submessage field and for nothing else, so flat
messages parsed and nested ones did not: a TranscriptResult carrying
segments serialized to correct bytes that the same process could not read
back, and TranscriptLiveRequest, a oneof of submessages, could not have
been parsed at all. Underneath that, 3.21 generated code was running 3.14
arena, ArenaStringPtr and ExtensionSet code.
-Wl,--exclude-libs does not fix it. It makes those symbols LOCAL in
.dynsym and the parse still fails, because the binding was decided at
static link time and no visibility flag revisits it.
Setting SPM_PROTOBUF_PROVIDER to "package" before add_subdirectory points
sentencepiece at the protobuf the generated code was already built
against. Zero google::protobuf:: definitions remain in the executable
afterwards, every nested message round trips, and citrinet_asr, which
parses a SentencePiece ModelProto at load time and would break first if
this were wrong, still tokenizes and transcribes correctly.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): fix the segment text a transcription response is built from
Segment text is not decoration. core/http/endpoints/openai/transcription.go
routes response_format text, srt, vtt and lrc through
schema.TranscriptionResponse, which builds the entire body out of
Segments[].Text and never reads the top-level text. So for those four
formats the segment text IS the response.
nemotron_asr emits one word_timestamp per SentencePiece token, and the
word boundary is carried as a LEADING SPACE on the piece ("So", "me",
" call"). join_words inserted a space unconditionally, so
response_format=text returned "So me call me na ture ," while the
correct sentence sat unread in the top-level field. The separator is now
chosen from the words themselves: whole words are space-joined, subword
pieces are concatenated, and one leading space anywhere selects the
latter. Concatenating the real nemotron pieces reproduces text_output
exactly, verified end to end.
This does not touch the top-level text, which is still text_output
verbatim. The rule that forbids deriving the transcript from the segments
is about the direction segments -> text; segment text has no source other
than its words.
Two smaller corrections in the same area:
timestamp_granularities ["word"] set only "word_timestamps", a key no
family in the pinned upstream reads. It now sets "return_timestamps",
which qwen3_asr does read and which both runs its forced aligner and
shortens its chunk window, so asking for word granularity no longer
silently returns nothing.
The request-option comment claimed more than it delivered. prompt,
translate and temperature are read by no ASR family, and are forwarded
only so a family adopting them works unchanged; the comment now says so
per key, and gives TranscriptRequest.diarize the same explicit treatment
threads already had.
Also: the shipping target now carries -Wall -Wextra -Wpedantic, which it
never did, so "the build is clean" starts meaning something; and
fill_transcript_result no longer swallows a null response pointer, since
answering OK with an empty transcript is the one failure mode this unit
exists to prevent.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): serve the AudioTransform RPC
Covers voice conversion, singing voice conversion, speech to speech and source
separation, the four tasks LocalAI's AudioTransform can represent.
AudioTransformResult carries one dst while htdemucs and mel_band_roformer
produce several named stems from a single run, so inference runs ONCE, every
stem is written as a sibling file <dst-stem>.<name>.<ext>, and params[stem]
selects which one dst receives, defaulting to vocals and falling back to the
first output. An unknown stem name is INVALID_ARGUMENT listing the real stem
names rather than a silent substitution, and the selection happens before the
first write so a refused request leaves no files behind. params[stem] is
consumed here and is not forwarded into the engine's request options.
The stem decision lives in stem_selection, which is stdlib only and therefore
tested by backend/cpp/run-unit-tests.sh. It also validates the names, because
they come from the model (htdemucs reads them from the GGUF's config.sources)
and each becomes a component of a path this backend writes: a name carrying a
path separator would escape the caller's output directory, and two stems
sharing a name would silently overwrite one another.
Both files are read at their native rate and channel count. Separation forces
it, since demucs and roformer refuse any rate but 44.1 kHz and lose the stereo
image that separates a centred vocal from a wide mix. The conversion families
all resample internally (seed_vc, vevo2, miocodec, chatterbox were each
checked), so passing the file through unchanged is also strictly better than
band limiting it to 16 kHz first.
Verified end to end against htdemucs f16 on a 44.1 kHz stereo mix: four stems
plus dst, dst byte identical to the selected stem, params[stem] selecting a
different one, an unknown stem refused with no files written, and mono input
preserved as mono output. Also against miocodec for the single output path,
where params[stem] is refused rather than ignored.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): refuse an impossible stem early, and stop blaming the caller for a failed write
Four fixes from the first review of the AudioTransform RPC.
check_can_serve now returns the resolved route, so params[stem] on a route that
is not source separation is refused from the route instead of after a full
inference: 11 ms rather than the 4.5 s a miocodec conversion costs, and far
worse on seed_vc or vevo2. The post-run refusal stays as the backstop for a
separation-routed family that returns no stems anyway. The typo'd-stem-name
case still needs the run, since no framework header publishes the stem names
before one.
Stem names carrying control bytes are refused. GGUF strings are length prefixed
and demucs reads its sources from JSON, so an embedded NUL survives to here:
two names differing only after the NUL are distinct std::strings, so the
duplicate check passes them, and then path::c_str() truncates both and they
open the same file. That is exactly the silent overwrite the duplicate check
exists to prevent, with the .wav lost as well.
A failed write is now INTERNAL rather than INVALID_ARGUMENT. The destination is
LocalAI's own generated-content directory, not anything the caller named, so a
full disk or a permission fault there is a server fault and is worth retrying,
which is the opposite of what INVALID_ARGUMENT tells a client. An empty output
path stays INVALID_ARGUMENT.
Two comment corrections and one clarification: the separators' required rate is
their checkpoint's declared samplerate rather than a hardcoded 44100, seed_vc
resamples with soxr and falls back to sinc-hann, and the "no files left behind"
guarantee covers a refused request, not a write that fails partway through the
loop.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(audio-transform): stop folding every upload to 16 kHz mono, and name the separation stems
Two defects that made source separation unusable through LocalAI's own API,
even though the backend served it correctly over gRPC.
/audio/transform normalized every upload to 16 kHz mono s16 through
utils.AudioToWav, with no way past it. htdemucs and mel_band_roformer refuse
any rate but their checkpoint's own and separate a centred vocal from a wide
mix using the stereo image, so every separation request through the HTTP API
died with "HTDemucs prepare() sample rate mismatch: expected 44100, got 16000"
while the same call over gRPC worked. The fold is not wrong, it is
backend-specific: LocalVQE's echo cancellation genuinely wants 16 kHz mono and
needs the reference in the same shape. So it becomes a declaration,
BackendCapability.AudioTransformInputMono16k, set for localvqe and for nothing
else. A backend that declares nothing gets its upload unchanged, which means no
backend has to opt in to work. utils.AudioToWavPreservingShape is the
non-folding conversion: a 16-bit PCM WAV passes through byte for byte at any
rate and channel count, anything else is transcoded to WAV with its rate and
channel layout kept.
The other defect is that the run-once stem design bought nothing. A separation
backend writes every stem beside dst from one inference, but AudioTransformResult
carried only dst, so the other three were files no caller could find and a
caller wanting all four had to run four separations. AudioTransformResult grows
a repeated AudioTransformStem, the backend fills it, core/backend validates that
each path really is inside the generated-content directory it handed over, and
the endpoint publishes them as an X-Audio-Stems JSON header beside the existing
X-Audio-Input-Url. JSON because a stem name is the model's own string and could
contain any separator a hand-rolled format would use.
Verified end to end through the HTTP endpoint with htdemucs f16 on a 44.1 kHz
stereo file: 200 with a 44.1 kHz stereo body, all four stems named and fetchable
through /generated-audio/, body byte identical to the selected stem, and
params[stem]=drums returning a different one. The same upload sent to a model
whose backend is localvqe still reaches the backend as 16 kHz mono, confirmed
both by the engine's own rate refusal and by the persisted input file.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(audio-transform): reject extensible WAV from the passthrough, escape stem URLs, convert stems with dst
Four fixes from the second review, plus one bug they made visible.
isPCM16Wav tested only the bit depth, and go-audio's IsValidFile never looks at
the format tag, so a 16-bit WAVE_FORMAT_EXTENSIBLE (0xFFFE) upload was passed
through untouched where the old fold would have transcoded it. audio.cpp's WAV
reader accepts 16-bit only when the tag is 1, so such a file died with
"unsupported WAV encoding". Extensible is what many DAWs and Windows tools
write and music files are this endpoint's new headline input, so it is a
first-contact failure rather than a corner. The check now requires tag 1, with a
spec that fails against the old implementation.
Stem URLs are percent-escaped. A stem name is the model's own string and legally
contains a space, a '#', a '?' or a '%'; an unescaped '#' truncates the URL
before the request is even sent. The name field keeps the raw name.
sample_rate and response_format are applied to the stems as well as to dst.
Applying beat documenting: dst IS one of those stems, so leaving them alone
broke the "dst duplicates the selected stem" invariant the whole design rests
on, and both conversions are no-ops when unset. A stem whose conversion fails is
dropped from the header rather than advertised in the wrong shape.
Verifying that turned up why it had never been noticed: the two fields were
never bound at all. The request arrives as multipart/form-data and echo's binder
falls back to the FIELD NAME without a form tag, matching only
case-insensitively, so "SampleRate" never matched "sample_rate" and "Format"
never matched "response_format". Both were documented in the endpoint table and
silently ignored. Two form tags fix it, and with them the conversion is
observable end to end.
Docs: audio-transform.md now documents what LocalAI does to an upload before the
backend sees it, which backend gets the 16 kHz mono fold and why, params[stem],
and the X-Audio-Stems header with a worked example.
Also records the known limitation that the fold lookup is on the bare backend
name, so pinned variants (vulkan-localvqe) do not match, and points at
IsLlamaCppBackend as the suffix-tolerant precedent.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): serve the TTS and SoundGeneration RPCs
TTSRequest.voice is treated as a speaker reference clip when it names an
existing regular file, which makes routing prefer VoiceCloning, and as a named
preset otherwise, in which case it travels as VoiceReference::cached_voice_id.
Both the clip and SoundGenerationRequest.src are read at the file's own rate and
channel count: upstream's own CLI and server do exactly that, every consuming
family resamples internally and mostly with a better resampler than ours, and
ace_step and stable_audio resample their input per channel, so a downmix here
would delete the stereo image they are built to consume.
The request builders live in their own unit rather than in grpc-server.cpp's
anonymous namespace so they can be tested; grpc-server.cpp has a main() and
cannot be linked into a test binary. The option keys are the whole point of
these functions, so each one was grepped against the pinned upstream and the
accounting is written down beside it. instructions maps to "instruct", which is
what upstream's own server maps the OpenAI field to and what qwen3_tts and
omnivoice read, and to "caption" for irodori_tts; the style tag is spelled
"instruct" too, because "instructions" is looked up nowhere. duration maps to
"duration_seconds", read by all three generation families, with the proto's own
name kept only as a forward-tolerant alias. Keys that no family reads say so.
Both handlers answer a capability refusal before taking the lane and before any
file read, so a model that cannot synthesise does not queue behind somebody
else's run to be told no.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): stop emitting an empty style language, and name the missing clip
StyleCondition::language was set whenever has_language() was true, with no
!empty() guard, while the language option twelve lines below had one.
core/backend/tts.go sets Language unconditionally, so has_language() is true on
every request LocalAI sends and carries "" when the caller named none. An
engaged-but-empty style language is worse than an absent one: supertonic reads
text_input->language behind its own !empty() guard and then overrides it from
style->language with no guard at all, so "" replaced its "en" default and its
tokenizer threw "invalid Supertonic language: ". Every /v1/audio/speech request
that set instructions and no language would have been an INTERNAL against a
supertonic model. A plain request never saw it, because the style condition only
exists when instructions are non-empty, which is why the chatterbox end to end
run did not catch it.
TTS also stops discarding the Route that check_can_serve already returns. A
family routed to voice cloning without a reference clip used to be refused from
inside its own prepare(), which meant an INTERNAL naming neither the RPC nor the
field to set; chatterbox advertises clon and no tts, so that was every
preset-only request to it. It is now an INVALID_ARGUMENT naming
TTSRequest.voice, answered in about 4 ms, and it cannot misfire because
has_voice_reference is what selected cloning in the first place. Reading
CapabilitySet::supports_speaker_reference to generalise this stays a follow-up.
The src read carries a written caveat rather than a family blocklist, because
ace_step's editing routes legitimately need src: setting src on a stable_audio
model corrupts the heap and aborts the process in the pinned upstream, and the
only thing keeping that off the network is that
schema.ElevenLabsSoundGenerationRequest has no field for it. Nobody reading that
Go schema would know why, so the reason is recorded where the field is read.
build_tts_shape is extracted so TTSStream cannot describe the same request
differently, and it arrived untested: two mutations of it survived until a
test_tts_shape case was added.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): serve the TTSStream and AudioTranscriptionStream RPCs
TTSStream leads with a streaming WAV header carrying 0xFFFFFFFF sizes, matching
the convention backend/go/vibevoice-cpp established, so an HTTP client can start
playback before the full PCM exists. Its chunks are read from
StreamEvent::named_audio_outputs and not audio_output: supertonic, omnivoice and
voxcpm2 all put their streamed audio there and leave audio_output empty until
the very end, so reading the obvious field yields a stream with no audio in it.
The finish_stream result is the family's own merged whole rather than a tail, so
it is emitted only when nothing was streamed.
Streaming transcription sends incremental deltas and degrades to a single delta
plus the final result on families that offer no streaming ASR, which is the same
message sequence with fewer deltas. The four streaming ASR families disagree on
what partial_text means: nemotron_asr, vibevoice_asr and higgs_audio_stt report
incremental fragments while voxtral_realtime reports the whole hypothesis and
reports it twice, so the reconciliation lives in one tested unit rather than in
the handler. nemotron_asr reports only through the stream event sink, and only
from inside finalize, so the audio driver installs one and clears it again
before returning: the session is cached and a sink left holding the caller's
frame is a use after free waiting for the next stream.
begin_stream is now the only implementation of the streaming state obligation,
prepare then start_stream. Streaming sessions are cached, and what clears the
previous stream is start_stream's reset; a family override that dropped it would
break every call site with no compile error, so there is one call site.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): keep streaming deltas on UTF-8 boundaries, refuse dtypes that abort
TranscriptStreamResponse.delta is a proto3 string, whose wire format requires
valid UTF-8. voxtral_realtime reports its hypothesis as a concatenation of raw
token BYTES (tokenizer_text.cpp:171-183), so the cumulative difference between
two consecutive reports is eventually a lone continuation byte, and the C++
runtime serializes that with only a logged warning while the Go runtime refuses
to unmarshal it: the client loses the remaining deltas AND the final_result.
Measured on a trace of a non-ASCII sentence, 11 of 31 messages failed to
unmarshal and every accented character was lost. TranscriptDeltaTracker now
holds back an incomplete trailing sequence and merges it into the next fragment;
reconcile flushes it, which it always can because the final text is complete.
The same trace now unmarshals in full with zero failures.
A streaming buffer whose float count is not a whole number of frames is refused
rather than truncated. The integer division dropped the tail floats from the fed
audio and therefore from the transcript, with no diagnostic; vibevoice_asr
refuses the same thing from the other side of the call.
A supertonic GGUF whose weights are not f32 is refused at load. It reaches
ggml_concat with mismatched operand types and ggml_abort takes the whole backend
process down on the first request, so nothing downstream can report it: the
model loads, then every request kills the process. Attributed rather than
assumed, the unary TTS path aborts identically, and upstream records that
package as untested. The refusal names the orig package and says what to run
before deleting the guard.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): stop a repeated lead byte from orphaning the next delta
The first UTF-8 fix closed the cumulative half only. Rule 2 discards a fragment
the known text already starts with, and when that fragment is the LEAD BYTE of a
new character it looks exactly like a repeat of an older character beginning
with the same byte. It was discarded rather than held, its continuation bytes
then arrived alone and began the next delta, and utf8_complete_prefix_length
only ever inspected the trailing sequence, so a delta invalid at the FRONT went
out whole. Through a real Go proto.Unmarshal the review's four-character repro
gave 3 deltas, 2 unmarshal failures and a lost transcript.
Reachable from the incremental families, not only from voxtral: nemotron_asr's
decoder cuts at a byte offset and vibevoice_asr's common_prefix_size compares
bytes, so both split characters. Measured over 30,000 randomized incremental
traces, 53.28% of Japanese traces and 9.52% of French ones carried at least one
delta the Go runtime refuses.
Two changes. Rule 2 no longer judges a fragment that ends mid-character, so the
lead byte is held instead of swallowed and the character survives intact; the
cost is a few duplicated bytes in a shrinking cumulative report, which no pinned
family produces. release() additionally drops leading orphan continuation bytes,
so no delta can begin mid-character whatever the rules above it decide. Losing a
byte keeps the stream alive; emitting one ends the RPC and takes the
final_result with it.
Post-fix all 60,000 traces produce zero unmarshal failures, and the cumulative
streams plus both pure-ASCII incremental streams are byte-identical to the
previous commit, so nothing changed for the families already working.
The weight-dtype allow list moves to family_gate, where it is stdlib-only and
pinned by a test rather than only by a comment. Two comment citations corrected.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): read only an exact repeat as a repeat, not any prefix
Rule 2 discarded any partial the known text merely started with. For a cumulative
family that is a duplicate; for an incremental family it is an ordinary short
fragment that happens to coincide with the start of the transcript, and it was
dropped, silently corrupting the text. Pure ASCII, no multi-byte character
anywhere: the fragments "pure ", "ascii ", "trans", "c", "ri", "p", "t" left the
client holding "pure ascii transcrit". Over 5,000 randomized traces per
transcript, 9.50% of pure-ASCII and 29.12% of French traces ended with the client
holding something other than final_result.text, with a 200 and no diagnostic.
Both incremental families emit fragments that small routinely, since nemotron_asr
cuts at a byte offset and vibevoice_asr at a common prefix.
Narrowing rule 2 to an exact repeat drives that to zero on all six transcripts
and changes no cumulative stream at all: 30,000 randomized cumulative traces are
byte-identical to the previous commit.
What rule 2 guarded was established from upstream rather than from its own
comment. The only duplicate any pinned family produces is voxtral_realtime's,
where process_available_stream_chunks feeds each event to the sink from inside
its loop and returns the last of the batch, so that event arrives twice with
byte-equal text. A duplicate is an exact repeat, so equality still covers it. The
case given up is a cumulative report that SHRINKS, which no pinned family can
produce: voxtral decodes a token vector that is only push_back'ed and cleared by
reset(), so within a stream it can only grow.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): serve the AudioTranscriptionLive RPC
The one bidirectional stream this backend serves. The client sends a
TranscriptLiveConfig, then TranscriptLiveAudio frames; the server acknowledges
with ready, emits deltas as the audio arrives, and sends final_result once the
read side closes. There is no offline fallback: live transcription has to
consume audio incrementally, so a family with no streaming ASR is refused
rather than served a batch run, which is what this RPC's Streaming-only
mode_candidates list already says.
The driver is a new sibling of run_streaming_audio, run_streaming_live, because
the audio does not exist yet: instead of slicing a buffer it pulls frames from
the caller until the read side closes. It installs the same ScopedStreamSink in
the same order, which is not optional, since nemotron_asr returns a bare event
from process_audio_chunk and reports every partial through the sink from inside
finalize(). It buffers the wire's frames up to the family's own preferred window
rather than feeding whatever size the client's audio callback produced, and it
does not call finish_stream at all when no audio arrived, because nemotron_asr
throws "finalize requires streamed audio" and an empty transcript is the
truthful answer to transcribing nothing.
Three things the handler had to get right and one it cannot:
- The audio contract. A live request carries no samples, but nemotron_asr's
streaming prepare() throws without an audio contract, and
build_preparation_request derives it from TaskRequest::audio_input, so that
field is an EMPTY buffer holding only the rate and the channel count.
- 16 kHz or a refusal. The families express their spans in their own 16 kHz
feature domain whatever the input was, and live frames cannot be resampled
on the way in the way a file can, so an 8 kHz session would return
timestamps 2x off with a 200. core/backend hardcodes 16000 anyway.
- A mid-stream Config is refused. backend.proto calls it a decoder reset, but
deltas already on the wire cannot be retracted, so a reset would leave the
final text contradicting the transcript the client assembled. Ignoring the
message would hand a client that believes it reset the decoder a transcript
that silently continues the audio it thought it discarded.
- The stale-route identity check cannot run here: TranscriptLiveRequest
carries no ModelIdentity in either arm of its oneof, so snapshot_for does
not instantiate for it. snapshot_unchecked's comment now names that as a
second legitimate class of caller and says the fix is a proto change.
eou and eob stay false. They exist for cache-aware models that emit
end-of-utterance and end-of-backchannel tokens; audio.cpp's StreamEvent has no
equivalent signal, and a client uses eou to decide the speaker yielded the turn,
so a guess inferred from silence cuts people off mid-sentence.
The lane is held for the whole stream, which is as long as the user keeps
talking: the streaming session is stateful and cached, so a concurrent run would
interleave two callers' audio and corrupt both transcripts.
Verified against nemotron_asr over a real connection with a 14 s WAV in
512-sample frames: ready first, 59 incremental deltas with no repeated prefix,
concat(deltas) equal to final_result.text, word timestamps in nanoseconds, eou
and eob false. citrinet_asr answers UNIMPLEMENTED naming the family and listing
asr/offline. A config followed by a close returns an empty final_result rather
than hanging, and a first message that is not a config is INVALID_ARGUMENT. Two
concurrent streams both return the complete transcript.
Two cleanups on lines Task 12 touched, folded in. The DtypeAllowList terminator
is now asserted at compile time: the reported out-of-bounds read did not exist,
the single entry does terminate, but the loops have no other bound and any edit
that widened an entry would walk off the end. And the dtype guard now
short-circuits on "is there a table entry" through a new predicate rather than
on the emptiness of the description string, which would have skipped the check
on an entry with an empty allow list, i.e. on precisely the entry that refuses
every dtype.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): bound the lane a live stream can hold
AudioTranscriptionLive holds the model's inference lane for the whole stream,
which is correct (the streaming session is stateful and a concurrent run would
interleave two callers' audio) and newly dangerous. Every other RPC holds the
lane across compute, or across a write to a slow reader, and both of those
terminate on their own. A live stream instead blocks in a client-driven read,
and a peer that goes silent WITHOUT closing the stream never terminates
anything: the lane stays taken and every other request against that model queues
behind a client that stopped speaking.
live_watchdog is a one-shot idle timer that ends the stream when no frame has
arrived inside a window. It is standard library only, so it is unit tested
without an engine. gRPC's synchronous Read has no timeout and cannot be given
one, so the only way to unblock it is ServerContext::TryCancel, which decides
the wire status itself: the client sees CANCELLED rather than the
DEADLINE_EXCEEDED the handler returns, the reason is logged, and the lane coming
back is the point. When it fires the read loop throws rather than reporting
end-of-input, so the driver does not go on to finalize a decode nobody is
waiting for.
It is armed only after the lane is taken and disarmed as soon as the read side
closes, and both ends matter. Arming earlier would cover acquire(), which
legitimately blocks while another live stream runs, so a queued caller would be
cancelled for waiting its turn. Disarming later would cover our own decode,
where a window overrun is not a peer going quiet and cancelling would throw away
the transcript the client is waiting for.
The window is the new live_idle_timeout_ms option, 30 s by default, 0 meaning no
limit. core/http/endpoints/openai/realtime.go drives a 300 ms ticker and feeds
every tick that produced new audio while a turn is open, so 30 s of silence is a
hundred ticks that delivered nothing. It is also longer than any pause a speaker
takes mid-utterance, which is the case that must never be cut off, and
backend.proto lets one stream span many utterances, so a client that pauses
longer between them raises the option rather than discovering it.
Two smaller corrections in the same handler:
- check_can_serve now runs BEFORE the sample rate check.
pkg/grpc/grpcerrors/errors.go degrades to the file path on UNIMPLEMENTED and
on nothing else, so a live-incapable model asked at a wrong rate was
answering INVALID_ARGUMENT and costing the caller its fallback.
- a negative sample rate is refused instead of silently becoming 16000. Zero
still means 16000, which is what the proto documents; -1 is malformed rather
than absent and gets the same refusal every other bad rate gets.
And one thing recorded rather than changed, at the handler: "live" here means
incremental INPUT, not low latency, and with the pinned families it does not yet
mean incremental OUTPUT either. nemotron_asr's process_audio_chunk only appends
to its buffer, so its whole decode and every delta happen inside finalize(),
after the client closes its send side. The policy-window buffering is inert for
that family and matters only for vibevoice_asr and higgs_audio_stt.
Verified on the wire with live_idle_timeout_ms:3000. A silent client acked at
371 ms and was cancelled at 3.371 s; a second live stream opened one second
later received its ack 2.37 s in, i.e. at the instant the first was cancelled,
and then transcribed successfully on the same cached session. Without the
watchdog it would still be waiting. Re-ran the live transcription (ready first,
59 incremental deltas, concat equal to the final text, word timestamps in
nanoseconds, eou and eob false), the citrinet refusal at both a right and a
wrong rate (UNIMPLEMENTED either way now), and Task 12's AudioTranscriptionStream
on nemotron_asr, which is unchanged.
Mutation testing the watchdog found a weakness in its own test: the destructor
test slept past the window inside the watched scope, so a destructor that
DETACHED the thread instead of joining it passed unnoticed. The test now uses a
window longer than the scope, which kills that mutant, and says why.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): refuse the unsupported RPCs with a reason
AudioEncode, AudioDecode, AudioTransformStream, AudioToAudioStream and
VoiceEmbed have no counterpart in audio.cpp's VoiceTaskKind. Each now returns
UNIMPLEMENTED naming the loaded family, what that family does support, and the
upstream limitation, instead of the generated base class's bare status. The
reasons live in a table in capability_routing.cpp so they are data rather than
literals copied into five handlers, and so a test can assert every one of them.
The five claims this was planned against were re-read at the pinned upstream
e800d435d130dc776baf6f3e6129bb62b1495c89, and one did not hold. "audio.cpp
streams tts and asr only" is false: silero_vad advertises vad with
RunMode::Streaming. The refusal stands on the narrower claim that survives, that
no family advertises streaming for any task AudioTransform routes to, and a test
asserts the refuted wording does not come back.
VoiceEmbed is the one refusal whose request carries a ModelIdentity, so it runs
the #10952 check before answering: a stale route must get NOT_FOUND and the
router's sentinel, not "audio.cpp cannot embed speakers" about a model that is
not loaded here. It cannot use snapshot_for, whose no-model branch would tell
the caller to load a model when no model can help, so it takes the reference
through snapshot_unchecked and checks identity itself. That function's comment
now names three classes of caller instead of two.
The two bidirectional surfaces refuse without reading their stream, verified
with a client that writes a config and eight frames first and gets the status
rather than hanging.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): correct the vevo2 clause, and assert the absences
Review found a false clause in the AudioToAudioStream refusal. It said s2s is
"offline voice conversion ... which converts one clip into another speaker's
voice", which is true of miocodec and false of vevo2: vevo2's s2s route is
`editing` and only `editing` (default_route_for_task and route_matches_task in
src/models/vevo2/session.cpp), documented as "Edit source speech into new target
text while using the target voice" and requiring --target-text, so it rewrites
what was said. vevo2's voice conversion is its separate vc task. It now reads
"offline clip-to-clip processing against a target voice, declared only by
miocodec (voice conversion) and vevo2 (speech editing)", and a test asserts the
miscast cannot come back. The conclusion is unchanged: neither family converses.
That defect was undetectable on the wire, since vevo2 does not load here, which
is the argument for upstream_absence_ctest.cpp. It links engine_runtime purely
to interrogate make_default_registry() and asserts the five premises the refusal
reasons rest on: no codec task kind, no family advertising spk, no streaming for
sep/vc/svc/s2s, miocodec advertising exactly vc and s2s, and s2s advertised by
exactly miocodec and vevo2. The last two are exact sets, so an addition fails
here rather than leaving a message stale. A positive control proves the registry
is populated and the query works before any absence is believed, and every
assertion has a reproduced negative control. This turns an AUDIO_CPP_VERSION
bump from "remember to re-read five prose paragraphs" into a test failure.
unsupported_surface now switches over UnsupportedRpc with no default label, so
-Wswitch reports a sixth enumerator added without a row at build time; the
runtime bounds guard it replaces is deleted.
The AudioTransformStream reason had a true premise and an overreaching
conclusion: an offline sep family could be buffered into a stream, as other
LocalAI backends do. It now says this backend declines to offer a buffered
offline call in disguise, rather than implying impossibility.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): make the missing-switch-case diagnostic fatal
unsupported_surface() switches UnsupportedRpc onto the table row that explains
it, with no default label, so -Wswitch reports an enumerator nobody handled. As
a warning that is not enough: adding a sixth enumerator and building the shipping
target gives exit 0, a binary and one warning, and the trailing
`return surfaces[0];` then answers the new RPC with AudioEncode's codec reason.
That is a confident, specific and false statement about audio.cpp on the wire, on
the one code path whose entire job is to be truthful about what this backend
cannot do, and it is worse than the runtime fallback it replaced, which at least
named itself as a bug in this file.
capability_routing.cpp therefore joins loaded_model.cpp on the existing
-Werror=switch pin, whose comment already made this argument for the engine enum.
The comment now covers both files. The pin stays per-file rather than
project-wide because upstream's own ace_step/vae_decoder.cpp has unhandled
-Wswitch cases of its own.
Verified: a sixth enumerator now fails `make grpc-server` with exit 2 and no
binary; appending a 14th VoiceTaskKind upstream still fails loaded_model.cpp, so
the two pins fire independently; both reverted clean.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): package the backend image
Bundles the dependency closure for the from-scratch image, the dlopened ggml
CPU-variant shared objects that ldd cannot see, and upstream's bundled
silero_vad and marblenet_vad assets so VAD works with no download.
The bundled loader sits in the package ROOT rather than at lib/ld.so. run.sh
execs it, which makes /proc/self/exe name the loader, and this backend has two
consumers of that path: ggml discovers the libggml-cpu-*.so by listing
dirname(/proc/self/exe), and resolve_model_path expands bundled:<name> under the
same directory. Rooting the loader makes the binary, the ggml objects and
assets/ share the one directory all three resolution mechanisms agree on.
llama-cpp's lib/ld.so layout would need assets/ moved into lib/ as well.
The image builds against apt gRPC and protobuf, like Dockerfile.ds4 and unlike
Dockerfile.privacy-filter. The from-source gRPC that install-base-deps.sh and
the base-grpc-* images supply vendors protobuf 26, which pulls abseil into
message_lite.h; with SPM_PROTOBUF_PROVIDER=package that collides with
sentencepiece's vendored mini-abseil and every absl::internal reference becomes
ambiguous. Noble's protobuf 3.21.12 predates the abseil dependency and is the
pair every earlier verification of this backend ran against.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): exempt the driver libraries from the packaging gate
package.sh already left libcuda.so* and libnvidia-* to the host when copying,
because the driver has to match the kernel module on whatever host runs the
image, but the validation gate had no matching exemption. With BUILD_TYPE=cublas
ggml is static and links CUDA::cuda_driver, so grpc-server carries DT_NEEDED
libcuda.so.1 and the gate would have rejected the very absence the copy loop
created, failing every cublas build in CI. One regex now feeds both.
Building a control for that found a second defect: ld.so --list refuses to trace
an object with an unresolvable dependency at all, exiting 127 without emitting a
per-library line, so the "=> not found" rule was dead code and no exemption could
have applied to it. The gate now traces with LD_TRACE_LOADED_OBJECTS and
LD_LIBRARY_PATH, which reports the missing name and exits 0, and which is also
what run.sh does at run time.
Adds a layout assertion so a future move of the loader into lib/ fails the build
instead of shipping a package that resolves bundled: models into lib/assets and
finds no ggml CPU backend, and records for Task 16 that the Darwin script must
not be a straight copy of privacy-filter-darwin.sh, which never calls package.sh
and would silently drop assets/.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): register the backend with CI and the gallery
Adds the five Linux matrix entries (cpu amd64/arm64 sharing a tag-suffix so the
manifest merge fires, cuda 12, cuda 13, vulkan), the path-filter case that keeps
later PRs touching backend/cpp/audio-cpp/ from getting zero CI jobs, the
bump-bot entry pointing at the AUDIO_CPP_VERSION pin in the backend Makefile,
the gallery meta plus its -development variant and the image entries for every
variant, and the Makefile docker-build wiring.
The matrix entries carry base-image only, with no builder-base-image, unlike
the llama-cpp and privacy-filter blocks they sit next to. The prebuilt
quay.io/go-skynet/ci-cache:base-grpc-* images ship a from-source gRPC whose
protobuf v26 depends on abseil, and this backend's sentencepiece is built with
SPM_PROTOBUF_PROVIDER=package, so it sees real abseil's absl::lts_20240116::
internal alongside its own vendored plain absl::internal and every
absl::internal:: reference becomes ambiguous. Building against base-grpc-amd64
fails at sentencepiece-static.dir/error.cc.o with "reference to 'internal' is
ambiguous". Dockerfile.audio-cpp installs apt's gRPC/protobuf 3.21.12 itself,
which is also the pair every unit and end-to-end run of this backend has been
verified against, and the CUDA toolkit therefore has to come from base-image.
No Darwin matrix entry and no metal gallery entries: the Metal build needs
scripts/build/audio-cpp-darwin.sh, a backends/audio-cpp-darwin make target and
a routing step in backend_build_darwin.yml, none of which exist yet, so an
entry added now would be routed to build-darwin-go-backend and look for
backend/go/audio-cpp/. The inferBackendPathDarwin case and the
DARWIN_BESPOKE_BUILDERS membership are in place, inert, so that adding the
entry later is a one-line change that cannot be claimed by the generic Go path.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): pin the CUDA architectures, drop the vulkan variant
Upstream sets CUDA_ARCHITECTURES to `native` on the engine_runtime target
whenever CMAKE_CUDA_ARCHITECTURES is unset at root scope, and docs/build/
linux.md says so outright. ggml's own default does not rescue it: it
list(APPEND)s in the ggml subdirectory scope, which never reaches the root
scope where the engine_runtime property is decided. No CI runner has a GPU for
`native` to enumerate, so both cublas entries would have gone red on the very
commit that first turns a CUDA build on.
Pin the list in backend/cpp/audio-cpp/Makefile, selected by CUDA_MAJOR_VERSION,
which Dockerfile.audio-cpp now forwards from the CI build-arg it was previously
discarding. The values are copied from ggml's own version guards rather than
invented, so engine_runtime and ggml compile for the same set: CUDA 12 keeps the
Maxwell/Pascal/Volta virtual archs and stops at 120a-real, CUDA 13 drops them
and adds 121a-real. The `a` suffix is used rather than `f` because the latter
needs CMake 3.31.8 and Ubuntu Noble ships 3.28.3. Verified by driving CMake
3.28.3's own CUDA architecture validator over both lists, with 120f-virtual as
the rejected control.
Drop the vulkan matrix entry, its two gallery entries, the vulkan capability
key on both metas and the Vulkan tag. Every other vulkan backend gets its Mesa
ICD drivers from .docker/install-base-deps.sh, which package-gpu-libs.sh then
bundles; Dockerfile.audio-cpp calls neither and installs only libvulkan-dev and
glslc, so the image would ship a Vulkan loader that finds no GPU. No CI job runs
a vulkan image against real hardware, so that would have passed green and failed
in users' hands. BUILD_TYPE=vulkan stays supported for local builds.
Also note on the cublas entries that cuda-major-version now selects the
architecture list and that cuda-minor-version and the base-image tag encode the
same toolkit, and correct the stale entry counts on matrixEntryKey.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): build for Darwin Metal
Bespoke C++ Darwin path like ds4 and privacy-filter: an includeDarwin matrix
entry, a backends/audio-cpp-darwin make target, a gated workflow step, and the
metal image entries plus metal/metal-darwin-arm64 capability keys in the
backend gallery.
The build script deliberately does NOT reassemble the package the way
privacy-filter-darwin.sh does. It runs the backend's own `make package` and
copies the result, so the Darwin package keeps the root-level layout the Linux
one has: grpc-server, run.sh, the ggml objects and assets/ in one directory,
with lib/ for the dylib closure. Hand-assembling would drop assets/, and
assets/ is what makes the bundled: model paths resolve with nothing downloaded.
The dylib walk is a full transitive closure rather than the single level ds4
and llama-cpp do, because Homebrew's grpc++ pulls libgrpc, abseil, upb, cares
and OpenSSL that grpc-server does not link itself, and a level-1 walk ships a
package that only works on a machine that already has Homebrew grpc.
Two fixes folded in, both in the backend Makefile:
- an EMPTY CUDA_MAJOR_VERSION fell through to the CUDA 12 architecture list,
which contains 120a-real and so needs nvcc >= 12.8. A local
BUILD_TYPE=cublas build on a 12.0-12.7 host failed to compile where
upstream's documented default (native) worked. EMPTY now maps to native,
12 and 13 keep their lists, and any other non-empty value is an error on
cublas builds. CI always passes a major, so CI is unaffected.
- the Darwin branch now points CMake at Homebrew's keg-only libomp. AppleClang
ships no OpenMP runtime and nothing is symlinked into /opt/homebrew, so
FindOpenMP finds neither the library nor the header, and audio.cpp calls
find_package(OpenMP REQUIRED) whenever ENGINE_ENABLE_OPENMP is on. Without
the hint the macOS build would have died at configure time. If the keg is
absent the build disables OpenMP instead of failing.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): make the Darwin fallbacks loud and the rpath walk complete
Review follow-up on the Darwin Metal build.
The OpenMP fallback was silent. If brew --prefix libomp ever comes back empty,
CI produced a green Metal package with 108 #pragma omp directives across ~30
files compiled out, and clang says nothing about an ignored omp pragma without
-Wsource-uses-openmp, so the only trace was one absent flag inside a set -x
cmake line. That regression would have been blamed on Metal. It now warns.
The @rpath arm of the dylib walk had no live candidate when it was written, on
the reasoning that a Metal build links ggml statically. The OpenMP fix in the
same commit made libomp.dylib one, and whether Homebrew records it as an
absolute opt path or as @rpath/libomp.dylib is not observable from Linux. The
walk now expands @rpath, @loader_path and @executable_path against the object's
own LC_RPATH entries, and only fails when nothing on disk answers, printing the
rpath list with the error so a failure on a machine nobody can attach to
explains itself.
Also: ADDITIONAL_LIBS now go through the closure rather than a bare cp, so they
are deduplicated and their own dependencies bundled; build/darwin/lib is
created explicitly instead of relying on package.sh pre-creating it; the libomp
probe uses nested ifneq rather than $(and ...), which needs GNU make 3.81 and
would otherwise expand empty and take the OFF branch on an older make; and
-DOpenMP_ROOT is quoted like its CUDA sibling.
Verified with a Linux harness that runs the script verbatim against a stubbed
otool: a level-2 transitive dep, an @rpath dep reachable only through LC_RPATH,
and an ADDITIONAL_LIBS dep are all bundled, a dependency cycle terminates,
system libraries are skipped, the packaged tree has assets/ at the root beside
grpc-server with the dylibs in lib/, and both failure paths exit non-zero.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): make bundled: reachable from a model YAML
resolve_model_path() tested the bundled: prefix on `candidate`, which prefers
ModelFile and falls back to Model. LocalAI fills ModelFile by joining ModelPath
onto the configured model string (pkg/model/loader.go, LoadModelWithFile), and
only sets it from a managed artifact otherwise, so a model YAML saying
`model: bundled:silero_vad` arrives as ModelFile "/models/bundled:silero_vad"
and Model "bundled:silero_vad". The prefix therefore never matched through the
normal load path: it matched only for a hand-written LoadModel call that left
ModelFile empty, which is exactly how task 15 verified it, and every model YAML
using the form failed with "model path does not exist:
/models/bundled:silero_vad".
Both fields are now checked, Model first, so the zero-download VAD path the
package ships assets for is reachable the way it is documented. A caller that
puts the form in ModelFile still works, so task 15's verification stands.
Compiled clean; the runtime check could not run on this host, whose system
libprotobuf/libre2 have gone missing (the pre-existing grpc-server binary no
longer resolves its libraries either), so it wants a container run.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): advertise the backend and document its options
Registers audio-cpp as preference-only in /backends/known: the family lives in
GGUF metadata that an importer cannot read from a remote repo, and one repo
hosts thirty families, so there is no honest auto-detect signal. Modality is a
single string and the import form chips on a fixed key set, so it registers as
tts with the other modalities named in the description rather than under an
invented key the UI would bucket as "other".
Adds a features page covering the option namespacing, the routing table per
endpoint, the RPCs this backend declines and why, the bundled VAD path, the
separation stem behaviour, and the family gotchas (supertonic needs the orig
package; chatterbox advertises cloning and no plain tts; nemotron_asr defers
its whole decode to finalize so live transcription emits nothing until the
client half-closes, unlike higgs_audio_stt and voxtral_realtime). Every option
name and family capability in it was read off the pinned upstream checkout.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(audio-cpp): test resolve_model_path, and correct the family names
The bundled: fix in 842443cd7 shipped without a test, which is how the bug got
there: task 15 verified the form with a hand-written LoadModel that left
ModelFile empty, and that is the one shape the server never produces. Four cases
in streaming_driver_ctest, which already links loaded_model.cpp, pin the
PRODUCTION shapes instead. The first fails against the pre-fix source (returns
the joined /models/bundled:silero_vad); the other three are the branches the
bundled: lookup now runs in front of and must fall through for.
Three family names in the docs were the source directory rather than the
registered family, on pages whose whole argument is that these names cannot be
guessed: demucs is htdemucs (demucs/loader.cpp:22), roformer is
mel_band_roformer (roformer/assets.h:15), and moss is TWO families,
moss_tts_local and moss_tts_nano. The hyphenated ASR names are underscored to
match, here and in the compatibility table.
The supertonic dtype note claimed more than the evidence carries. The f16 abort
is a local observation, identical through TTS and TTSStream; upstream's
docs/gguf.md leaves the 16-bit column untested and records q8_0 as "No
(unsupported weight dtype)", which says unusable rather than fatal. Both are
still refused, because the allow list is what the family can run. Corrected in
family_gate.h, family_gate.cpp and the docs together, since the docs inherited
the wording from the code.
The importers tripwire says in the file that it is a tripwire: it exercises no
audio-cpp behaviour, and the registration assertion lives in backend_test.go.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* gallery: add audio.cpp models covering every served RPC
One representative model per RPC group of the audio-cpp backend, plus the two
bundled VAD models, which need no download at all because the assets ship
inside the backend package.
Every hash was computed with sha256sum on the downloaded file. Quantizations
come from upstream's tested-status table in docs/gguf.md rather than a default
of q8_0: supertonic ships the orig package (its q8_0 is recorded as an
unsupported weight dtype and its f16 aborts in ggml_concat), and nemotron_asr
and htdemucs ship f16 because their q8_0 builds are recorded with drift while
16-bit is a clean pass.
Diarization and separation use the diarization and audio_transform usecases,
not transcript: /v1/audio/diarization and /audio/transform filter the default
model on FLAG_DIARIZATION and FLAG_AUDIO_TRANSFORM respectively, so a
transcript flag would have hidden both models from their own endpoints. The
forced aligner sets parameters.language, which the transcription endpoint uses
as the fallback when no language form field is sent, because the family
requires both a transcript and a language.
All ten entries were run twice: once against the raw gRPC server, and once
installed with local-ai models install and called through the HTTP endpoint.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* gallery: correct the audio.cpp entries' licenses
Swept all ten entries against the real upstream named in audio.cpp's
tools/model_manager.py rather than against the audio.cpp repo's own license.
Three were wrong:
supertonic apache-2.0 -> openrail weights come from
mlx-community/supertonic-3-mlx, and
both it and Supertone/supertonic are
openrail
citrinet apache-2.0 -> other pulled from NGC
nvidia/nemo/stt_en_citrinet_256,
governed by the NGC Terms of Use
sortformer other -> cc-by-nc-4.0 nvidia/diar_sortformer_4spk-v1 is
CC BY-NC 4.0, and the gallery already
uses that exact string, so there is no
reason to obscure a non-commercial bar
The license field is one word, so citrinet and sortformer also gained a
sentence saying why they are restricted. The other seven were confirmed
correct against their sources.
Also drops an unverified claim from the nemotron description. It said the
model drives the realtime transcription session; that endpoint actually calls
TranscribeStream, and the live RPC reaches LocalAI only through
realtime_semantic_vad.go. Neither path was exercised here, so the description
now states only the two calls that were.
MarbleNet gains the NeMo upstream under urls: for parity with silero.
No sha256, quantization, usecase or model choice changed.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(audio-transform): bound sample_rate, keep same-named uploads apart
Four defects the whole-branch review found on the Go side, plus two comment
corrections.
sample_rate is a disk-exhaustion hazard. The branch added the `form:` tag that
makes the field bind for the first time, so the resample path went from dead to
live, and utils.AudioResample interpolates the int straight into ffmpeg's -ar
with no bound. Measured with ffmpeg 7: -ar 999999999 on a 0.01 s clip writes
20 MB and exits 0, which scales linearly to the reported 3.9 GB for one second,
into a GeneratedContentDir nothing sweeps, and convertStems repeats it once per
separation stem. Clamped to 8000..192000 in the handler, before the temp dir and
before the model is touched, and rejected with a 400 outside it.
The low end was reported as "a 0-byte file". It is not: -ar 1 writes a 78-byte
header with no audio behind it, whose declared data size still claims 70 bytes,
so go-audio parses it as a 35 SECOND file and a size check does not see it. The
guard therefore compares the declared data chunk against the bytes actually on
disk, and AudioResample now fails rather than returning a WAV carrying nothing.
Both parts of a transform request land in one temp dir, and the raw copy was
named only after the client's basename, so `-F audio=@mic/clip.wav
-F reference=@loopback/clip.wav` wrote "raw-clip.wav" twice. Since
AudioToWavPreservingShape hardlinks an already-PCM16 WAV rather than copying it,
the reference part's os.Create truncated the inode audio.wav pointed at: mic and
reference came out identical, which makes an echo canceller null everything and
return near-silence with a 200. The raw copy now carries the form field name.
audio-cpp had no BackendCapabilities entry, so VoiceCloningForModel returned nil
before it ever consulted the model's tts.voice_cloning override and every
`voice: "profile:<id>"` request was refused with a 400, on a backend that ships
audio-cpp-chatterbox whose family serves cloning and not plain TTS. Registered
with its RPCs, usecases and the reference-audio contract, and deliberately
without the 16 kHz mono fold, which its separation families cannot survive.
GetBackendCapability was exact-match only, so every pinned gallery variant read
as an unknown backend: vulkan-localvqe lost the 16 kHz mono fold that used to be
unconditional and started failing inside LocalVQE, and the usecase gate does not
stand in for it because BuildFilteredFirstAvailableDefaultModel returns early
once the client names a model. Lookup now falls back to the meta name by
stripping the gallery's hardware prefix and release-channel suffix, exact match
first so nothing can be shadowed. Same class as #10945.
Also corrected: the AudioTransformRequest comment claimed echo's binder falls
back to the field name, which it does not in either direction (bindData binds
ONLY tagged fields and `continue`s otherwise; `model` arrives from
setModelNameFromRequest's c.FormValue). And the stable_audio `src` heap
corruption caveat now lives on ElevenLabsSoundGenerationRequest, where the Go
developer who would add the field can see it, instead of only in C++.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(audio-cpp): refuse a task pin the RPC cannot serve, and stop empty frames holding the lane
The model's `task:` option is copied into the request shape by all nine
handlers, which is correct, but resolve_route then replaced the RPC's candidate
list with the pin WHOLESALE and never asked whether the pin was something that
RPC routes to. One pin therefore bled across all nine surfaces, and because the
family still supported the pinned task the result was a wrong 200 rather than an
error. Reproduced live: nemotron with task:asr made Vad return 200 with zero
segments after a full ASR decode, so 14 seconds of speech was reported as
silence, and Diarize did the same; silero_vad with task:vad made
AudioTranscription return 200 with empty text and four segments whose spans were
VAD segments, which combined with response_format in {text,srt,vtt,lrc} building
the body solely from Segments[].Text yields a well formed SRT of four timed
EMPTY cues. It also contradicted the documented contract, that a family which
cannot serve a request is refused rather than rerouted.
A pin is now checked against the RPC's admissible task set before it is adopted,
and the refusal names both the pin and the RPC. The set is derived from
task_candidates with every shape flag set rather than restated, so a task added
to an RPC's candidates cannot become inadmissible by omission. Every legitimate
pin survives, and the test asserts all fifteen of them alongside the eight
crossings that must not.
The live watchdog was defeated by empty frames. idle.touch() ran on ANY message,
before the has_audio and pcm.empty() filters, so a peer writing unset-oneof or
zero-length frames faster than the window held the lane indefinitely while
feeding the decoder nothing. There is one lane per model and one model per
process, so that is a single client denying the whole backend, which is what the
watchdog exists to prevent, and the thrown text already said "no audio frame
arrived". The touch moved below the filters, which are now a named predicate so
the distinction is testable rather than a call order nobody can see.
Three comments corrected against measurement rather than reasoning:
- CMakeLists claimed zero google::protobuf:: definitions remain in the
executable. nm -C --defined-only reports 2515, and that is expected: they are
generated code, sentencepiece::ModelProto's own _InternalParse among them. The
claim that holds, and the one the ABI fix is actually about, is that no
vendored protobuf RUNTIME is linked and ParseContext::ParseMessage is
UNDEFINED in the executable, resolving to libprotobuf.so.
- refuse_cloning_without_a_clip's "cannot misfire" paragraph had its reasoning
backwards. Routing picks VoiceCloning as the FALLBACK when there is no clip,
which is the case being caught; chatterbox, which ships in the gallery,
advertises clon and no tts at all, so every voice-less request lands there.
- audio_units read "2.1 min at 96 kHz" for index 11289602, which is 1.96 min.
2.1 min is 96 kHz's OWN first failure at 12288002. Both were remeasured and
the note is now a per-rate table.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* build(audio-cpp): exclude the upstream checkout from the C++ gate, harden the darwin walk
run-unit-tests.sh pruned */llama.cpp/* but not */audio.cpp/*. It is safe today
only by luck: upstream's 44 tests all put "test" at the FRONT of the filename
(17 test-*.cpp, 27 test_*.cpp, zero *_test.cpp), so the glob misses every one of
them, and nothing enforces that. This gate runs on every PR for every backend
and compiles each match as a standalone translation unit with nothing but
nlohmann/json on the include path, so the day upstream adds or renames one test
the gate goes red repo-wide on an Apache-2.0 file nobody here wrote.
audio-cpp-darwin.sh now logs the raw otool -L output and the parsed LC_RPATH
list unconditionally, before the walk. Both awk filters in that script assume a
column layout nobody working on this can observe, since it runs only on the CI
Mac, and a green first Darwin run proves nothing about the assumption: an awk
that silently matched nothing yields an empty dependency list, which reads
exactly like "no non-system dependencies" and packages happily. Both filters
otherwise feed process substitutions, so their input never reached the log.
It also lists every symlink in the package and fails on one that cannot resolve
inside the image. A dangling link does not fail anything else here, because
every assertion tests with -e, which follows links; it fails at dlopen on a
user's Mac. Links are NOT banned outright, which the review suggested but which
would break the libggml.dylib -> libggml.0.dylib chain the `cp -a` above exists
to preserve. What is banned is a link that resolves on the build host and will
not resolve in the image: a broken one, or an absolute one pointing outside the
package.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* style(audio-cpp): drop em dashes from the audio-cpp capability entry
Follow-up to a84b3c4b9, no behaviour change.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(config): key the voice-cloning model rule on the resolved backend
Making GetBackendCapability strip the gallery hardware prefix and release
channel fixed pinned variants of /audio/transform, but VoiceCloningForModel
kept keying its per-backend switch on the caller's spelling. A pinned name
therefore resolved the capability by stripping and then missed every case in
the switch, falling through to the permissive default: cuda12-vibevoice-cpp
advertised voice cloning for the realtime 0.5B model, metal-coqui for
tacotron2, cuda12-crispasr for a pure ASR model, cpu-qwen3-tts-cpp for
CustomVoice. Each of those is a model that cannot clone, so /v1/audio/speech
accepted a profile: voice it had to fail on inside the backend rather than
rejecting it with a 400, and the UI advertised the capability too.
resolveBackendCapability now returns the key the entry was found under, and
callers that branch on backend identity use that key instead of the name they
were handed. The exact-match-first order is unchanged, so a backend genuinely
registered under a variant-looking name still keys on its own name.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* gallery(audio-cpp): declare audio_transform on the chatterbox entry
Chatterbox advertises VoiceCloning AND VoiceConversion
(src/models/chatterbox), and the entry's own description already said so, but
known_usecases listed only tts. /audio/transform selects its default model by
FLAG_AUDIO_TRANSFORM, so voice conversion was reachable only by naming the
model explicitly and was invisible to every usecase-driven surface. It is the
one audio.cpp task with a shipped gallery model and no way to find it.
Verified against the real model rather than inferred from the capability list:
AudioTransform with chatterbox-q8_0, speech as audio_path and a speaker clip
as reference_path, returns a 5.08 s 24 kHz mono WAV at -25.5 dB mean and zero
stems, which is the single-output shape voice conversion should have.
The description now says which endpoint reaches that half and warns that
installing this next to a source-separation model gives /audio/transform two
candidates, so the model should be named rather than defaulted.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* gallery(audio-cpp): add voice-design and singing-voice-conversion entries
Two of the three audio.cpp task kinds that had no gallery model now have one.
Both were driven end to end against the real weights through the backend
before being written, not inferred from the capability tables.
audio-cpp-irodori-voicedesign covers vdes. TTS carrying `instructions` routes
to the vdes task, so the voice is described in words rather than supplied as a
clip. Verified: "a calm elderly woman speaking slowly with a warm, gentle
tone" over an 8.76 s 48 kHz mono render at -16.8 dB mean, and a closed-loop
citrinet pass recovers the sentence with the accent drift expected from a
Japanese-first model read by an English recogniser.
audio-cpp-seedvc-singing covers svc, and pins task:svc because nothing else
can reach it. seed_vc advertises svc and ordinary voice conversion, no request
signal means "this input is singing", and auto-routing resolves the tie to
voice conversion every time. Verified with the pin: 5.04 s 44.1 kHz output
whose closed-loop citrinet transcription is exact.
s2s deliberately has no entry, and the reason is not effort. miocodec is the
only upstream family whose speech-to-speech route needs no text, and it
returned audio with correct duration and level but no recoverable speech in
four independent attempts: the stale build, v2 q8_0, v2 orig (the variant
upstream records as a clean Pass), both tasks, and matched 44.1 kHz inputs on
both sides. vevo2's route refuses with "Vevo2 text/prosody route requires
text_input or target_text", and session.cpp:897 fills target_text only from
request.text_input, which AudioTransform has no field to carry. The same
vevo2 weights convert voice correctly through the default route with an exact
ASR round trip, so the model and the plumbing are both healthy; it is the s2s
route specifically that this RPC cannot express.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* backend(audio-cpp): carry transform text through params, add the s2s entry
AudioTransform is audio-in / audio-out and its proto message has no text
field, but not every task it routes to is audio-only. vevo2's speech-to-speech
route is a text and prosody route: session.cpp:897 fills refs.target_text from
request.text_input and nowhere else, and the run refuses without one with
"Vevo2 text/prosody route requires text_input or target_text". The params map
is the only channel this RPC has that reaches the engine, so the text travels
through it and apply_transform_text_input unpacks it after the params have
been copied into task.options.
Before this, s2s was not awkward to reach through /audio/transform, it was
unreachable, and it was the last audio.cpp task kind with a real model and no
way to get to it.
target_text is canonical and text is its alias, the order vevo2's own option
table declares them in, so a request setting both gets the canonical one
rather than whichever the map happened to store first. An empty value falls
through to the next candidate instead of ending the search. language rides
along only when a text was found: on its own it conditions nothing, and
manufacturing a text_input for it would route a plain separation request
carrying a language hint through the text path. The keys are left in
task.options rather than erased, because vevo2's loader advertises target_text
as a request option and a family reading it there keeps working.
Nine tests, all confirmed failing on behaviour against a stub that returned
false before the implementation was written. Verified end to end afterwards:
vevo2-q8_0 with task:s2s and params[text] returns a 5.12 s 24 kHz output whose
closed-loop citrinet transcription is exact, and htdemucs separation with no
text param still returns its four stems, with and without params[stem].
audio-cpp-vevo2-speech-to-speech ships that route. Every audio.cpp task kind
with a loadable family now has a gallery entry; spk remains the only gap and
has no family upstream at all.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* docs(audio-cpp): document params[text] and the pinned transform tasks
The text channel and the two task pins are both invisible from the endpoint
contract alone: nothing in the AudioTransform form tells a reader that a
speech-to-speech model needs the line it is resynthesising, and nothing says
that asking for singing voice conversion without task:svc silently gets plain
voice conversion instead. Both are the kind of thing a user only discovers
from a refusal or, worse, from output that looks right and is not.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(utils): annotate the two G304 sites this branch introduced
gosec flags os.Open on a variable path, and both new call sites in ffmpeg.go
are its alerts on this PR. Neither is reachable by an outside caller: isPCM16Wav
opens the exact path it is about to hand ffmpeg as input, which in the upload
path is a server-created temp file named from path.Base of the client name so
no traversal survives, and wavAudioBytes opens AudioResample's own dst, a name
this package derives from src and has just had ffmpeg write.
Annotated in the repo's existing style rather than restructured, with the
reason spelled out, because a bare suppression is worth nothing to the next
reader. The three other G304 sites in this file, in passthroughWAV and
isTargetWav, predate the branch and are left untouched.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(audio-cpp): build arm64 with gcc-14 for the armv9.2 SME variants
The arm64 CPU image failed to build:
cc1: error: invalid feature modifier 'sme' in
'-march=armv9.2-a+dotprod+fp16+sve+i8mm+sve2+sme'
ggml's CPU_ALL_VARIANTS table includes armv9.2 variants compiled with +sme, and
Ubuntu Noble's default gcc-13 rejects that feature modifier. Every entry in the
table has to compile even though a host only ever dlopens the one its own CPU
supports, so a single unbuildable variant fails the whole image. gcc-14 accepts
it, which is exactly the fix llama-cpp already carries in
.docker/llama-cpp-compile.sh; this is the same problem reached by a different
Dockerfile.
Applied to every arm64 BUILD_TYPE rather than to the CPU one alone, and that
differs from llama-cpp on purpose. llama-cpp needs it only for its pure-CPU
image because its GPU builds run llama-cpp-fallback, which builds no variant
table. This backend's Makefile turns ENGINE_ENABLE_CPU_ALL_VARIANTS on for
every non-Darwin build, GPU included, so an arm64 GPU image would hit the
identical error. The matrix has no arm64 GPU entry today, which is precisely
why gating on an empty BUILD_TYPE would leave the trap armed for whoever adds
the first one.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(model): deterministic, file-type-filtered backend auto-detect (#9287)
When a model config declares no explicit `backend:`, Load() fell into a
trial loop built by ranging the external-backends Go map (random order)
with no filtering, returning the first backend whose gRPC LoadModel
succeeded. An unrelated installed backend - e.g. the "opus" audio codec -
could therefore win a GGUF/LLM model load, so a model that should run on
llama.cpp wrongly tried to use opus.
Extract the candidate selection into a pure, testable function
SelectAutoLoadBackends that:
- sorts the candidate list deterministically (no more map-order
nondeterminism), and
- for a `.gguf` model, filters to LLM-capable backends (via
core/config.BackendCapabilities) and puts llama-cpp first, so an
incompatible audio/codec/image backend can never win the trial loop.
If filtering would leave zero candidates, the full sorted set is returned
unchanged, so a previously-loadable model is never made unloadable.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(model): break core/config <-> pkg/model import cycle in backend auto-detect
The #9287 auto-detect change made pkg/model/autoload.go import core/config
for the backend capability table. core/config already imports pkg/model
(runtime_settings_registry.go uses model.DefaultWatchdogInterval), so this
closed a core/config -> pkg/model -> core/config import cycle and broke the
build and golangci-lint.
Invert the dependency so the lower-level pkg/model no longer imports the
higher-level core/config. pkg/model exposes RegisterLLMCapableBackendFunc and
uses the registered predicate; core/config (which owns the capability table)
registers it from an init(). The deterministic, GGUF-type-filtered selection
behaviour is unchanged. When the predicate is unwired the GGUF filter is
skipped, preserving the existing zero-candidate fallback.
The unit test now injects a fake capability predicate so SelectAutoLoadBackends
is exercised independently of the core/config table.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4.8 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
* fix(grammars): reject cyclic $ref in JSON-schema grammar to prevent stack-overflow crash
JSONSchemaConverter.visit resolved $ref entries by recursively calling
itself with no cycle detection. A client-supplied grammar_json_functions
schema whose $defs contains a self- or mutually-referential $ref (e.g.
{"A": {"$ref": "#/$defs/A"}}) made visit recurse until the goroutine
stack was exhausted, producing a fatal "stack overflow" that kills the
whole process rather than failing the single request. The schema is
converted synchronously in the /v1/chat/completions handler before any
backend call, so this is an unauthenticated remote crash. Fixes#11020.
Track the $ref targets currently on the recursion stack and error out
when one is re-entered, while popping after each descent so sibling
(non-cyclic) reuse of the same $ref is still allowed.
Signed-off-by: Tai An <antai12232931@outlook.com>
* fix(grammars): add a bounded recursion depth and cover llama31 $ref cycles
Addresses the review on #11041. The stack-set approach catches cyclic
$ref chains, but a deeply nested yet acyclic client schema (thousands of
nested arrays/objects) can still recurse through visit until the
goroutine stack is exhausted, which is the same unauthenticated remote
crash surface as #11020.
- Add a bounded depth counter to JSONSchemaConverter.visit (incremented
with a defer-based cleanup, capped at maxSchemaDepth = 256, far above
any realistic schema) so an over-deep schema fails the request with an
ordinary error instead of crashing the process.
- Apply the same cyclic-$ref guard and depth bound to
LLama31SchemaConverter.visit, the other production grammar entry point
named in #11020, which previously had no cycle detection at all.
- Regression tests: a deeply nested acyclic schema is rejected while a
moderately nested one still builds, plus direct/indirect $ref cycle
and depth tests for the llama31 converter.
Signed-off-by: Tai An <antai12232931@outlook.com>
* test(grammars): make llama31 cycle fixtures valid function-call shapes
The two new llama31 $ref-cycle specs asserted on "cyclic $ref" but the
converter requires each top-level oneOf alternative to carry its
function-name property before descending, so both fixtures failed
earlier with "no function name found in the schema" and never reached
the cycle guard.
Give each fixture a valid llama31 shape: construct the converter with
NewLLama31SchemaConverter("function"), put "function": {"const": "test"}
on the top-level alternative, and hang the cyclic $ref under an
arguments property, so all 29 grammar specs pass and the assertions
genuinely observe the cyclic $ref error.
Signed-off-by: Tai An <antai12232931@outlook.com>
---------
Signed-off-by: Tai An <antai12232931@outlook.com>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
backend_pr.yml and test-extra.yml already filter themselves, so a gallery-only
or docs-only PR costs them about one job each. The image and Go workflows had no
filter of any kind, so a one-line gallery/index.yaml edit queued 20 jobs: 7
container image builds, 3 GoReleaser/darwin launcher builds, 3 unit test jobs, 2
golangci-lint, 1 e2e, 1 yamllint, plus the 3 that correctly stop after their
detect step. A docs-only PR queued the same.
This matters more than the job count suggests. Measured over the week to
2026-07-30, 97% of CI wall-clock is queueing and 3% is execution: a median
5-hour queue against a 4-20 minute median job. Cutting job count is the only
lever that shortens feedback time. The volume is there to cut, too: 13
gallery-only PRs merged that week with 10 open at once, and 78 of the 137 PRs
opened were bot-generated.
Add paths-ignore for gallery/**, docs/**, examples/** and **/*.md to the
pull_request trigger of image-pr.yml, build-test.yaml and tests-e2e.yml, and
add gallery/** to lint.yml, which already excluded the rest. That drops 13 of
the 20 jobs. None of the four can observe such a diff: gallery metadata is
parsed at runtime and never copied into an image, docs and markdown never enter
one at all, GoReleaser and the launcher take no such input, the e2e suite drives
backends over gRPC directly, and golangci-lint runs new-from-merge-base so a
diff with no touched Go lines is a no-op. The build-test exclusion also frees
macOS capacity, which is the scarcest runner class.
The two checks that do validate the gallery are deliberately left alone.
test.yml still runs core/gallery/variants_lint_test.go, which reads the real
gallery/index.yaml and asserts the index invariants, and yaml-check.yml still
lints the syntax.
paths-ignore skips a run only when every changed file matches, so a PR touching
the gallery and Go code still runs everything. master carries no branch
protection and no rulesets, so a skipped workflow reports no status and nothing
waits on it; .agents/ci-caching.md records that constraint for whenever required
status checks are introduced.
image.yml on master push is left unfiltered on purpose: skipping it would stop
the master and latest tags being republished for a gallery commit, which is a
publishing decision rather than a cost one.
Assisted-by: Claude:opus-5 [claude-code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* gallery: add Nanbeige4.2 3B GGUF variants
Add Q4_K_M and Q8_0 builds of the compact Nanbeige4.2 agentic and reasoning model, grouped as install-time variants.
Assisted-by: Codex:gpt-5
* gallery: simplify Nanbeige4.2 model name
Apply the maintainer-requested canonical model name while retaining the quantization variants under the entry.\n\nAssisted-by: Codex:gpt-5
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Add the official Q4_K_M build and seven APEX quality and size variants for llama.cpp.
Assisted-by: Codex:gpt-5 [Hugging Face API]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
GenerateImage hardcoded TilingParamsSetEnabled(vaep, false), so tiled VAE
decoding was unreachable from a model config even though all four upstream
setters were already bound in main.go.
Sampling runs in latent space, but the final VAE decode expands to full
resolution and needs one large compute buffer. At 1024x1024 that buffer
exceeds 8GB, which fails on two kinds of device: cards without the VRAM
for a full-frame decode, and drivers that cap a single allocation
regardless of how much memory is free. Mesa RADV reports a 4GiB
maxMemoryAllocationSize, so a Radeon 8060S with 74GiB of device-local
heap still cannot serve that decode:
[INFO ] sampling completed, taking 251.82s
[INFO ] decoding 1 latents
ggml_vulkan: Requested buffer size exceeds device buffer size limit:
ErrorOutOfDeviceMemory
[ERROR] vae: failed to allocate the compute buffer
[ERROR] decode_first_stage failed for latent 1
Every sampling step completes and then the run is discarded at the last
stage, so the whole generation is wasted.
Add three options, parsed in Load and applied per generation:
vae_tiling:true enable tiled decoding (bare flag also works)
vae_tile_size:512 tile size, or 512x384 for a rectangle
vae_tile_overlap:0.25 overlap between tiles
Tiling stays off unless requested, so existing models are unaffected. Tile
size and overlap only reach the library when the operator set them, which
keeps upstream's defaults rather than pushing a zero, and an unparseable
value is treated as absent for the same reason.
Truthy spellings match what load_model already accepts for its own bool
options, and the bare-flag form matches diffusion_model, so no new
convention is introduced.
Signed-off-by: Dimitris Karakasilis <dimitris@karakasilis.me>
Add the CAJAL GGUF gallery template and gallery index entry for local llama-cpp installs.
Assisted-by: Codex:gpt-5
Signed-off-by: Ching Kao <0980124jim@gmail.com>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
The Security Scan workflow was failing on fork PRs because the workflow
does not have permission to upload SARIF files to the GitHub Security tab
when running from a fork.
This change adds '!github.repository.fork' checks to all steps
to prevent the workflow from running on fork repositories.
This fix should be applied to the main repository so that
all forks inherit the correct configuration.
Fixes#10322, #10318, #10320, #10321
Co-authored-by: ghshhf <ghshhf@users.noreply.github.com>
fix(chatterbox): pin cublas12 torch/transformers and setuptools so the backend loads
The cuda12-chatterbox gallery backend fails to load on a fresh install
because several deps in requirements-cublas12.txt are unpinned:
- torch/torchaudio: unlike requirements-cublas13.txt and
requirements-cpu.txt, this file has no --extra-index-url, so pip pulls
a wheel whose CUDA runtime (cu130) is newer than the host driver
supports ("NVIDIA driver on your system is too old"). Add the cu124
index and pin torch/torchaudio 2.6.0+cu124.
- transformers: resolves to 5.x, which dropped LlamaConfig.rope_theta
that chatterbox-tts 0.3.1's T3 config still reads. Cap to <5.
- setuptools: 81+ dropped pkg_resources, which perth imports under a
bare try/except and silently sets PerthImplicitWatermarker=None,
making ChatterboxTTS.__init__ raise 'NoneType' object is not callable.
Cap to <81 in requirements.txt.
Fixes#11070
Signed-off-by: Tai An <antai12232931@anaiguo.com>
Co-authored-by: Tai An <antai12232931@anaiguo.com>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
response.create accepts a metadata map and ResponseCreateParams has carried
the field all along, but triggerResponse never copied it onto the Response it
emits, so both terminals went out with metadata omitted.
That field is the only thing tying a terminal event back to the
response.create that asked for it. Our own doc comment on ResponseCreateEvent
says so — "the metadata field is a good way to disambiguate multiple
simultaneous Responses" — and it is what makes an out-of-band response
(conversation: "none") usable at all: a client running one alongside the
spoken conversation has no way to tell its own answer from the conversation's,
so it waits for a reply it already received and gave away.
Found from the client side: a headless text turn injected into a live session
was answered correctly in about a second, and the caller still blocked until
its own two-minute timeout because it could not recognise the answer.
Carry the map on liveResponse so all three terminals (in_progress, cancelled,
completed) report it, and leave it omitted when response.create sent none.
Assisted-by: Claude:claude-opus-5 gofmt
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat: add Valkey Search vector store backend
Add a new built-in Go gRPC store backend 'valkey-store' that implements the
four Stores RPCs (Set/Get/Delete/Find) against the Valkey Search module (FT.*)
using the pure-Go github.com/valkey-io/valkey-go client. It is selected via the
existing per-request 'backend' field on /stores, so there is no proto or HTTP
API change, and it mirrors the in-memory local-store while adding persistence
across restarts and opt-in HNSW.
Each vector is a Valkey HASH keyed by hex(little-endian float32); the index is
created lazily on first Set (FLAT+COSINE by default), cosine similarity is
derived as 1-distance, and namespaces get a collision-resistant token. Includes
unit tests (valkey-go mock) and env-gated integration tests against
valkey/valkey-bundle, plus build/matrix/gallery wiring and docs.
Assisted-by: Kiro:claude-opus-4.8 golangci-lint
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* Address review feedback: recover persisted index dimension, harden Find
- Load now recovers the persisted vector DIM from FT.INFO (not just index
existence), so a post-restart Set/Find validates against the real DIM
instead of silently re-learning a wrong one and dropping mismatched
vectors from the index. This also restores Find's dimension check after
a restart.
- StoresFind treats a dropped/missing index as an empty store (empty
result, no error) and clears the stale indexCreated flag, matching
local-store's empty-store behaviour.
- StoresSet reuses checkDims for its per-key length check so the four RPCs
share one dimension-guard implementation.
- Add unit tests for FT.INFO dimension recovery, loadIndexState, and the
dropped-index Find path.
Assisted-by: Kiro:claude-opus-4.8
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* Address review feedback: TLS ServerName/CA, Find nil-check, config fail-fast
Addresses external review comments on the valkey-store backend:
- StoresFind now rejects a nil/empty query Key before dereferencing it,
so a malformed gRPC request can no longer panic the backend.
- TLS: derive ServerName (SNI) from the VALKEY_ADDR host so certificate
verification works for IP-addressed endpoints, and add VALKEY_TLS_CA_CERT
(custom CA bundle) and VALKEY_TLS_SKIP_VERIFY (testing-only) knobs.
- Config integer parsing now fails fast on a malformed value (e.g.
VALKEY_HNSW_M=1x6) instead of silently defaulting, matching the
fail-fast behaviour of the index-algo/distance-metric validation.
- Add VALKEY_DB (SELECT n) support for logical-DB isolation.
- Cap the human-readable part of a namespace token at 64 chars so a very
long model name cannot produce an unbounded key prefix / index name
(the appended short hash keeps distinct namespaces collision-free).
- Document the KNN-query injection-safety invariant (fields are constants)
and why StoresGet uses a single aggregate DoMulti deadline for reads.
- Unit tests for the Find nil/empty-key guard, fail-fast HNSW parsing,
and VALKEY_DB parsing/validation; docs + .env updated for the new vars.
Assisted-by: Kiro:claude-opus-4.8 golangci-lint
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* Address review feedback: configure valkey-store via model config
richiejp asked that the valkey-store backend take its configuration from
a model config rather than process-wide VALKEY_* environment variables,
so multiple stores can each have their own Valkey config within one
LocalAI process. This removes every env access from the backend and
routes config through the model-config seam every other backend uses.
- config.go: loadConfig(opts *pb.ModelOptions) now parses the model
config `options:` list (key:value strings, split on the first ':')
instead of os.Getenv. Option keys mirror the old VALKEY_* names without
the prefix (addr, index_algo, distance_metric, ...). Defaults, fail-fast
validation and the mandatory client name are unchanged.
- store.go: Load threads opts into loadConfig; TLS comments/errors renamed
off the VALKEY_* names.
- core/backend/stores.go: StoreBackend and NewVectorStore take a
*config.ModelConfigLoader, resolve the per-store ModelConfig by store
name, and pass its Options (and Backend when unset) to the backend via
WithLoadGRPCLoadModelOpts. No config -> default backend + built-in
defaults, preserving the zero-config experience.
- Endpoints/routes/application: thread the config loader to StoreBackend.
- Unit + integration tests: configure via options; the integration test
passes addr through the model-config path (VALKEY_ADDR is now only the
test harness locating the server).
- docs + .env: document the model-config options, drop the env var table.
Assisted-by: Kiro:claude-opus-4.8
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* Remove valkey-store informational comment from .env The backend is configured via model config, not env vars — the comment was unnecessary noise in .env. The configuration is already documented in docs/content/features/stores.md.
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* feat(valkey-store): gate Load on NamespacePrefix to refuse autoload probing Mirror local-store's pattern: reject model names without store.NamespacePrefix so the model loader's greedy autoload probe cannot bind an arbitrary model name to the vector store backend (the #9287 failure mode). Also adds unit tests for the gate covering: prefixed namespace, prefix alone, unprefixed model name, empty model, and nil opts.
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* feat(valkey-store): add username_env/password_env credential indirection Add support for resolving Valkey credentials from environment variables named in the model config, mirroring cloud-proxy's api_key_env pattern. This keeps secrets out of model YAML files and lets distinct store configs each reference their own credentials. Options: username_env / password_env name the env var holding the value. The direct username / password options still work and take precedence when both are set (backward compatible). Includes 5 unit tests and updated stores.md documentation.
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* fix: correct rebase artifacts in backend-matrix.yml and Makefile Fix two issues introduced by the conflict-resolution script during the rebase onto master: 1. .github/backend-matrix.yml: valkey-store entries were merged INTO the cloud-proxy entries (duplicate keys in same YAML map items) instead of being separate list items. This broke cloud-proxy Linux builds and the cloud-proxy darwin entry lost its build-type/lang. Fixed by making them standalone entries and restoring cloud-proxy exactly as on master. 2. Makefile: duplicated .NOTPARALLEL and docker-build-backends lines. Collapsed to single lines that are master's current content plus the valkey-store additions. Also adds the three optional pickups from #10801: - /valkey-store in .gitignore (the built binary) - valkey-store row in docs/content/reference/compatibility-table.md - valkey-store line in backend/README.md
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
---------
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
Co-authored-by: Daria Korenieva <daric2612@gmail.com>
* docs(gpu): add gfx1151 / ROCm 7.x and fix ROCm section
- Fix typo: "deditated" → "dedicated", "ROCm6" → "ROCm"
- Add ROCm 7.x to requirements (alongside ROCm 6.x)
- Add Ubuntu 24.04 to tested OS list
- Add AMD Strix Halo / gfx1151 section with kernel params,
required env vars (HSA_OVERRIDE_GFX_VERSION, ROCBLAS_USE_HIPBLASLT),
and Docker Compose example
- Add gfx1151 to the list of compiled GPU targets
- Add ROCm version column to verified devices table
- Add gfx1151 / Radeon 8060S (ROCm 7.11.0) as verified device
* fix(docs/gpu): correct gfx1151 section — env vars, image tag, safety warning
- Add all 4 required env vars (HSA_OVERRIDE_GFX_VERSION, ROCBLAS_USE_HIPBLASLT,
HSA_XNACK=1, HSA_ENABLE_SDMA=0) with descriptions in a table
- Fix Docker Compose example to use the ROCm 7.x image tag (-gpu-hipblas-rocm7),
not the ROCm 6.x image
- Add explicit warning: GGML_CUDA_ENABLE_UNIFIED_MEMORY must NOT be set
(even =0 activates hipMallocManaged due to getenv != nullptr check)
- Add --force-recreate note (docker restart does not update container env)
- Add tested hardware note (Geekom A9 Mega / Ryzen AI MAX+ 395)
* docs(gpu): single ROCm image — drop -rocm7 tag suffix
Per maintainer feedback on PR #9229: there is only one ROCm/hipblas
main image, and it ships with ROCm 7.x by default — no separate
-rocm7 tag.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Document the reverse-proxy settings needed for long-running and multimodal requests, and distinguish edge-generated 504 responses from the optional LocalAI busy watchdog.
Assisted-by: Codex:gpt-5 [Codex]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* feat(3d): add Generate3D RPC, FLAG_3D capability, and /v1/3d/generations endpoint
Adds the plumbing for image-conditioned 3D asset generation (binary
glTF / GLB output), modeled on the video generation path:
- backend.proto: Generate3D RPC + Generate3DRequest (staged image src,
glb dst, seed/step/cfg_scale/texture_steps, quality and background
enums, params map for backend-specific extras)
- pkg/grpc: thread Generate3D through client, server, embed, base and
the backend interfaces; connection-evicting and distributed-node
wrappers (in-flight tracking + file staging) included
- core/config: FLAG_3D usecase (guessed only for the trellis2cpp
backend), '3d' canonical usecase string mapped to the Generate3D
method, and a '3d' output modality
- REST: POST /v1/3d/generations (+ unversioned alias) returning
OpenAIResponse with a /generated-3d URL or b64_json; conditioning
image accepted as URL, base64, or data URI; quality/background
validated at the edge; .glb served as model/gltf-binary
- auth: '3d' route feature (default ON); /api/instructions entry
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(trellis2cpp): add the trellis2.cpp image-to-3D backend
Wraps localai-org/trellis2cpp (C++/GGML port of Microsoft TRELLIS.2,
pbr-textures branch) as a Go+purego backend, following the
stablediffusion-ggml pattern:
- backend/go/trellis2cpp: purego bindings to the flat C ABI (v9,
asserted at startup), eager pipeline load with model-set validation
(refuses non-trellis GGUFs; degrades coarse/geometry-only/textured
exactly like the upstream demo), Generate3D via t2_generate +
t2_bake_glb writing a binary glTF to dst. Weight-free unit tests
cover resolution/validation/param mapping — CI never downloads the
multi-GB GGUF set or runs inference.
- CPU SIMD variants build into per-variant directories (the shared
libggml sonames collide across variants, unlike sd-ggml's flat
renamed-.so scheme); run.sh picks one via /proc/cpuinfo.
- CI wiring: backend-matrix entries (cpu, cuda12/13, vulkan
amd64+arm64, l4t, l4t-cuda13, darwin metal), index.yaml meta +
latest/master image entries, bump_deps tracking of the pbr-textures
branch, changed-backends.js mapping, top-level Makefile targets.
- Importer: auto-detects trellis GGUF repos/URIs (registered before
llama-cpp so the .gguf match isn't stolen) and expands any trellis
URI to the full 10-file component set spanning the three LocalAI-io
HF repos.
- Gallery: trellis2-4b (full PBR + 1024 cascade) and
trellis2-4b-geometry (512 untextured) with verified sha256s.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(ui): 3D generation page with native GLB viewer and IndexedDB history
Adds a Studio tab + /app/3d page for the new image-to-3D endpoint:
- GlbViewer ports the trellis2cpp demo's dependency-free WebGL2
renderer (quaternion trackball, metallic-roughness PBR, ACES,
hidden-line wireframe with a bounded index budget) and pairs it with
a minimal GLB parser for the two forms t2_bake_glb emits — dense
vertex-PBR (linear COLOR_0 + _METALLIC_ROUGHNESS, uploaded as
normalized integers) and the opt-in UV-atlas textured form. Parsing
happens before any GL so stats and errors render without WebGL2.
- use3DHistory stores past generations (params, input thumbnail, and
the GLB blob itself) in IndexedDB with keep-newest-20 eviction —
GLBs are multi-MB binaries localStorage can't hold — and the page
offers a download button for the active GLB.
- Wiring: CAP_3D capability constant (FLAG_3D — the exact string
/api/models/capabilities serves), threeDApi, router entries, Studio
tab, vite dev proxy, en locale keys.
- e2e: render-smoke entry plus a focused spec that feeds a real
one-triangle vertex-PBR GLB through the parser/viewer and exercises
IndexedDB persistence, selection, deletion, and API errors.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(3d): address API correctness and UX issues
Keep 3D generation on the LocalAI-specific /3d/generations route and ensure authentication and permissions cover it.
Propagate distributed transfer failures, publish a portable ARM64 backend image, honor importer overrides, and align discovery, upload validation, and touch controls.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(3d): add previewable print remeshing
Add a single-detail CGAL Alpha Wrap workflow for existing Trellis GLBs, including PBR reprojection, API documentation, tracing, and an in-browser preview before download.
Allow the remesh route to enforce its 512 MiB upload cap independently of the smaller global default so generated high-resolution meshes can be processed.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* build(trellis2cpp): centralize remesh dependency pins
Assisted-by: Codex:GPT-5 [apply_patch] [exec_command]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(kokoros): implement Generate3D stub for new proto RPC
The Generate3D RPC added to backend.proto for the trellis2cpp backend
made tonic's generated Backend trait require generate3_d, breaking the
kokoros-grpc build. Return unimplemented like the other unsupported
modalities.
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
backend/backend.proto is consumed by every language, so its SHARED_BUILD_INPUTS
rule could only ever be always/always: 417 Linux plus 56 Darwin builds. It fires
on ~1.3% of commits (10 of 767 over six months), which made it the single
largest CI cost driver in the repo.
On 2026-07-29 the queue reached 2178 jobs against 8 concurrent runners. Four
runs totalling 935 of those jobs were triggered by nothing but a proto edit. The
largest, 378 jobs on master, came from PR #11158, whose entire proto diff was
six lines adding `bool cache_prompt = 8;` to one message. No backend that does
not read that field behaves any differently for it.
Make the rule content-aware. changed-backends.js resolves backend.proto at the
base revision (the contents-API pattern already used for backend-matrix.yml) and
hands both texts to protoChangeIsAdditive(), which compares them structurally so
a comment reflow, reindent or field reorder does not read as a change. An
additive-only edit (new field with an unused number, new message, new enum
value, new RPC) suppresses the rule and rebuilds nothing; a removed, renumbered,
retyped or renamed field, a dropped RPC or a changed option still rebuilds
everything, as does an unresolvable base revision.
Every other matched rule is untouched, so a PR that edits the proto and
scripts/build/ is still a full rebuild, and the weekly full-matrix cron remains
the backstop for stale wheels.
Verified against all ten proto commits of the preceding six months: the nine
with a resolvable parent all classify as additive, and controls covering a
retyped-and-renumbered field, a deleted RPC, identical revisions and a
reindent-plus-comment-reflow all classify correctly.
Assisted-by: Claude:opus-5 [claude-code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(llama-cpp): route Score through the slot loop
Score previously bypassed the slot loop with a direct llama_decode: a
conflict guard aborted the whole process if scoring raced generation, the
config validator had to reject score alongside chat/completion/embeddings,
and every candidate re-decoded the full shared prompt.
Add SERVER_TASK_TYPE_SCORE to the (patched) upstream server so score tasks
are scheduled like any other slot work: generation and scoring serialize
naturally, the shared prompt is decoded once per call, and the slot's
prompt cache carries the conversation prefix across calls. Context
checkpoints at the score boundary and at the cache-divergence point keep
SWA/hybrid/recurrent models (e.g. LFM2.5) from re-prefilling the whole
prompt per candidate: warm-turn scoring on a 6-option set drops from ~8s
to ~0.5s on a desktop CPU.
The conflict guard and the validation split are removed; declaring score
with generation usecases on one config is now supported and shares the
slot cache.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): classifier wire types and pipeline config
Wire types and YAML config for realtime classifier mode: sessions carry a
localai_classifier extension (options with canned replies/tool calls,
softmax threshold, normalization, history trimming, fallback modes, and a
deterministic wake-word address gate), mirrored by pipeline.classifier in
the model YAML and surfaced in the config-meta registry. The
localai.classifier.result server event reports the full score distribution
per turn.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): classifier response flow
Classifier-mode responses: instead of autoregressive generation, each user
turn is prefill-scored against the option list (router.ScoreClassifier
prompt/candidate shapes over the Score primitive) and the winning option's
canned reply and tool call are emitted through the existing response
machinery. Below-threshold turns take the configured fallback (none /
canned reply / generate); empty transcripts and unaddressed turns (wake
word not mentioned) skip scoring entirely. The scoring probe defaults to
the latest user message only — small scorers echo canned replies from
prior turns back as the top option otherwise.
Built for hardware that can afford prompt processing but not decode: with
slot-based Score the option list stays KV-cached across turns, so a turn
costs roughly one forward pass over the new words.
session_update_error events now carry the validation cause instead of a
generic message.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(realtime): bound the VAD tick's scan window and buffer retention
The VAD tick loop re-scanned the entire input buffer every 300ms and only
trimmed it on zero-segment ticks or commits. Audio that keeps producing
segments without a committing pause (steady noise a mic pipeline lets
through, music, continuous speech) grew the buffer toward the 100MB cap
with each tick rescanning all of it — O(n^2), measured at ~3.3ms of silero
per buffered second: past ~90s retained, ticks run back to back and pin
~4 cores until the stream stops.
Silero's recurrent state only carries a few hundred ms of context, so
rescanning old audio buys nothing. Clip the slice handed to the VAD to the
largest silence the commit test can need to measure (server_vad silence
window or the semantic eagerness fallback) plus a warm-up margin, and
rebase the returned segment times so every downstream consumer keeps
whole-buffer coordinates. An open turn whose clipped window is all silence
now commits (the silence outran the window) instead of being discarded as
no-speech. Independently, retain at most 90s of raw buffer, rebasing the
live-feed and EOU cursors on trim — this also bounds the previously
unbounded VAD-error path. Turn boundaries are otherwise unchanged: no
forced commits, no new coordinator states.
pipeline.turn_detection.vad_window_sec can widen the scan window; values
below the automatic floor are ignored. The tick body is extracted into
vadTick so specs can drive turn detection synchronously (same shape as
classifySoundWindow); the babble reproduction that pinned 4 cores now
plateaus under 10% of one core.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(backend): let per-model threads override the global default
ModelOptions overrode a set per-model threads value with the app-level
--threads whenever the latter was non-zero — and WithThreads defaults it
to the physical core count, so it always was. The YAML threads: knob has
been dead config: a tiny VAD model could never opt down from the global
pool size.
SetDefaults already fills an unset per-model value from the app config,
which is the intended precedence; resolve threads through a helper that
honors it (explicit threads: 0 still means unset).
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(gallery): single-thread the silero VAD
Silero is a ~2MB recurrent model with no exploitable graph parallelism:
measured per-call latency is identical at 1 and 10 ORT threads, while
every extra pool thread just spin-waits between the realtime loop's
frequent tiny inferences.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* docs(realtime): classifier mode, VAD scan window, threads precedence
Document the realtime classifier mode (options, threshold guidance,
wake-word address gate, empty-transcript handling), the VAD scan window
and 90s buffer retention (pipeline.turn_detection.vad_window_sec), the
per-model threads precedence, and the M3 classifier note in the realtime
state-machine design doc.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* perf(llama-cpp): score all candidates in one batched decode
One scoring call is now a single SERVER_TASK_TYPE_SCORE task: the slot
decodes the shared prefix (prompt + longest common candidate token
prefix) once, then forks one sequence per candidate off it
(metadata-only for the unified KV cache, copy-on-write for recurrent
state) and decodes every candidate's unique tail in one llama_decode.
Previously each candidate was its own task that restored the boundary
checkpoint and re-decoded its full tail sequentially, paying
per-candidate task and decode overhead.
The context reserves SERVER_SCORE_FORK_SEQS extra sequence ids (and
recurrent-state cells) beyond the parallel slots via the new
common_params::n_seq_score_forks. Forking requires the unified KV cache
(already this backend's default) since per-sequence streams would shrink
n_ctx_seq; an explicit kv_unified:false disables forking and Score calls
that need it fail cleanly. Candidates beyond the fork/output budget
decode in successive chunks.
Wire contract and scores are unchanged: per-token logprobs are stitched
from the shared region and the forked tails. Verified bitwise
deterministic call-to-call and independent of candidate order (no
cross-fork leakage via equal-length candidate swap); ranking matches the
per-candidate implementation on the drone battery (winner softmax
0.99996 vs 0.99997), and >16-candidate chunking, prefix-of-another and
empty candidates all pass.
Measured on a desktop CPU: warm /api/score calls 0.52s -> 0.23s; warm
realtime classifier turns 196-303ms. The 9-candidate drone turn decodes
~17 unique tail tokens in one batch instead of nine sequential ~220ms
checkpoint-restore tasks.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(realtime): gate scoring capacity by model usecase
Reserve llama.cpp scoring slots only for models that explicitly declare the score usecase, while allowing score to coexist with chat and completion. Reject incompatible unified-KV settings and classifier activation on models without scoring capacity.
Propagate application defaults when resolving realtime and preload pipeline stages so unset thread counts are resolved consistently without overriding explicit model settings.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(ci): honor APT mirrors in the prebuilt llama-cpp compile step
The builder-prebuilt path installs gcc-14 with apt directly and ignored
the APT_MIRROR/APT_PORTS_MIRROR build args the from-source path already
honors, so an ubuntu mirror outage broke every arm64 backend build. Pass
the args into the stage and run apt-mirror.sh (already in the build
context via COPY . /LocalAI) before the apt step.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): classifier argument slots via constrained completion
Hybrid classify-then-complete: a classifier option's canned tool call can
declare typed argument slots (number | enum | string, with defaults and
prompt hints) referenced as "{{name}}" in the arguments template. When
the option wins, the slots are filled by a short grammar-constrained
completion that continues the exact scoring prompt — rendered by the same
cached ScoreClassifier, so the llama.cpp prompt cache is already warm —
with the chosen route JSON re-opened at the first slot field. A GBNF
grammar pins the field skeleton and frees only the values; temperature 0,
a couple dozen tokens at most (~300ms on a desktop CPU for two slots).
Slot declarations and hints ride the option descriptions in the shared
system prompt, informing scoring and the fill alike at no per-turn token
cost. The localai.classifier.result event carries the final arguments and
a fill_latency_ms. On inference failure the slots' defaults apply; a slot
without a default fails the response (or falls through with
fallback.mode: generate). Slot filling requires completion alongside
score in the scoring model's known_usecases.
Verified end-to-end on the Pi drone demo: "fly forward three meters" in
distance mode classifies forward and infers {"distance": 3, "units":
"meters"} in ~310ms, and the drone flies exactly 3 units.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): splice filled slot values into classifier replies
A classifier option's spoken reply can now reference its tool's argument
slots ("Going forward {{distance}} {{units}}."): the values inferred by
the slot-fill completion — or the recovery defaults — are spliced into
the reply as plain text before it is emitted, so what the assistant says
confirms what it actually inferred. Placeholders without a value stay
literal, and options without slots are untouched.
FillToolArguments now returns the raw slot values alongside the spliced
arguments JSON to make the reply templating possible.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(realtime): harden classifier slot completion
Reserve context for constrained slot filling, size completions from their encoded output, and encode enum grammar literals as valid JSON. Reject empty enum values and cover the failure modes with regression tests.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): prewarm the classifier scoring prompt on registration
Swapping a session's classifier option list (a voice-switched command
mode, for instance) made the next turns pay a full re-prefill of the new
option-list prompt — measured 2.4s vs 0.3s warm on a desktop CPU, and
worse: on hybrid-memory models like LFM2.5, whose state cannot be
partially rewound (llama.cpp can only restore checkpoints), *every*
probe change re-prefilled from scratch whenever the last checkpoint
missed the probe boundary, so even same-list turns intermittently cost
full prefills.
Registering an option list (pipeline seed or session.update) now fires a
best-effort background prewarm: two throwaway scores with distinct
probes. The first prefills the new option-list prompt; the second,
diverging exactly where per-turn probe text starts, plants the backend's
rewind point (KV checkpoint) at the stable-prefix boundary that every
real turn reuses. The prewarm hides behind the canned mode-switch reply
— by the time it finishes speaking, the cache is warm. Idempotent per
option set, detached from the registering request's lifetime.
Measured on the drone demo (LFM2.5-1.2B, desktop CPU): first turn after
a mode switch 2374ms -> 340ms; intermittent same-list full prefills
(1.3-2.1s) all -> under 0.5s. For clients that swap lists frequently,
options: [parallel:2] on the scoring model additionally keeps one slot
per list via prefix-similarity routing (+26MB RSS, unified KV).
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* perf(llama-cpp): checkpoint scoring at the caller-declared stable prefix
Hybrid-memory models (LFM2.5 shortconv, Qwen3.5 deltanet — where new
small models are headed) cannot rewind their state, so any prompt-cache
reuse that needs a rewind falls back to a full re-prefill. For classifier
scoring that meant every probe change re-processed the whole option-list
prompt: the server's checkpoints were placed reactively (at wherever the
previous task happened to diverge), so a checkpoint past the next
divergence was erased rather than restored — measured as intermittent
2-10s turns on prompts with a 95%+ common prefix.
The classifier now computes the probe-invariant prompt prefix once (the
byte-wise common prefix of two synthetic probe renders) and declares its
length with every Score request; the server maps it to a token boundary
and forces a KV checkpoint exactly there on each score prefill. That
checkpoint sits at or before every future divergence under the same
option list, so it always survives and always restores — repeat scoring
costs probe+candidates regardless of how the probe changes.
Also:
- prewarm reruns on every option-list registration instead of memoizing
per list: with boundary checkpoints a redundant rewarm costs two
probe-sized decodes, while skipping one after a slot eviction (three
lists sharing fewer slots evict in LRU cascades) silently moves a full
re-prefill onto the user's next turn
- new llama.cpp backend option rs_seq:N exposes bounded recurrent-state
rollback outside speculative decoding; measured impractical for
deltanet-scale states (65GB for 64 snapshots on Qwen3.5-4B) but cheap
insurance for small-state models
- docs: the multi-list recipe (parallel:N + sps:0.5 — the default slot
similarity threshold funnels distinct lists onto one slot)
Measured on the drone demo (LFM2.5-1.2B scorer, desktop CPU), steady
state: every turn 285-421ms including mode switches, vs 2.4s post-switch
and intermittent 1.3-2.9s re-prefills before.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(realtime): align classifier cache guidance
Document the single-score prewarm behavior and clean the vendored score patch formatting.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(llama-cpp): guard score task for fork backends
TurboQuant and Bonsai reuse the primary gRPC server against llama.cpp forks that do not carry LocalAI's slot-based Score patches. Compile the Score integration only for the patched primary backend and return UNIMPLEMENTED from fork builds instead of referencing absent task types and common_params fields.
Assisted-by: Codex:gpt-5 [gh]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(dev): generate gRPC code before commit lint
The coverage phase regenerates ignored protobuf bindings, but lint runs first and can fail against missing or stale output. Generate the pinned bindings before lint so the gate always type-checks the current schema.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
Add the official Q4_K_M and Q8_0 builds plus the DFlash speculative-decoding pairing for llama.cpp.
Assisted-by: Codex:gpt-5 [Hugging Face API]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(sglang): keep nvidia-modelopt on a stable release
Every cublas sglang image currently fails to build:
Failed to build `nvidia-modelopt==0.46.0rc0`
Call to `wheel_stub.buildapi.build_wheel` failed
ModuleNotFoundError: No module named 'wheel_stub'
sglang[all] pulls nvidia-modelopt in through its `diffusion` extra with no
version bound of its own, and install.sh adds a GLOBAL --prerelease=allow so
that flash-attn-4, which only ships 4.0.0b* wheels, can resolve. Unbounded plus
prereleases-allowed picks 0.46.0rc0, whose build backend imports wheel_stub
without declaring it in build-system.requires. EXTRA_PIP_INSTALL_FLAGS also
starts with --no-build-isolation, so nothing installs wheel_stub and the build
dies. Latest stable is 0.45.0 and resolves cleanly.
Bounding this one package rather than dropping the global flag, because the
flag is load-bearing for flash-attn-4 and this is the narrower change with the
smaller blast radius. Raise the bound when 0.46.0 final ships.
This is invisible on master because the backend build is path-filtered: sglang
is only rebuilt when sglang changes. It surfaces on any PR touching a shared
build input such as backend/backend.proto, which rebuilds the whole matrix.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(nemo): build the darwin venv on Python 3.12
The darwin nemo image fails to build:
ModuleNotFoundError: No module named 'maturin'
nemo_toolkit pulls in text2num, a Rust extension built with maturin, whose
macOS arm64 wheels start at cp311: 3.0.2 publishes cp311, cp312, cp313 and
cp314 and no cp310. libbackend.sh defaults PYTHON_VERSION to 3.10, so pip finds
no wheel, falls back to the sdist, and dies in the PEP 517 hook because
EXTRA_PIP_INSTALL_FLAGS carries --no-build-isolation and nothing installs the
build backend. Taking the prebuilt wheel avoids the source build entirely, so
the runner needs no Rust toolchain.
Darwin only, deliberately: the Linux profiles resolve a cp310 manylinux wheel
for the same package and have no reason to move. The override is set after
libbackend.sh is sourced and before installRequirements, the same shape
sglang's install.sh already uses for its l4t13 profile.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(nemo): pin the darwin portable-Python patch level too
The 3.12 bump alone traded one failure for another:
curl: (56) The requested URL returned error: 404
make[1]: *** [nemo-asr] Error 56
libbackend builds the portable-Python URL from
cpython-${PYTHON_VERSION}.${PYTHON_PATCH}+${PY_STANDALONE_TAG}, and
PYTHON_PATCH defaults to 18 because the default interpreter is 3.10.18. Setting
only PYTHON_VERSION asked for a 3.12.18 that was never released.
Patch 11, not the 12 that sglang/install.sh pairs with 3.12 for l4t13: at the
20250818 tag python-build-standalone published 3.12.12 for linux aarch64 but
not for aarch64-apple-darwin, where 3.12.11 is the newest. Both URLs were
checked against the release assets rather than assumed to match.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
* feat(cli): support systemd socket activation
Serve the API from a single stream listener inherited through the systemd activation protocol while retaining the existing address bind path when no listener is provided. Validate activation metadata, preserve the public-bind safety check, and document an on-demand systemd setup.
Assisted-by: Codex:gpt-5
* fix(cli): satisfy listener cleanup lint
Make the best-effort close explicit so errcheck accepts the deferred systemd listener cleanup.
Assisted-by: Codex:gpt-5 [golangci-lint]
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Some Transformers processors used by MLX-VLM, including Qwen vision models, import both PyTorch and Torchvision. Include them in the Metal backend environment so model loading does not fail with missing-library errors.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
The Anthropic translate provider builds the upstream request from scratch and
never emitted cache_control, so prompt caching was impossible for OpenAI-format
clients routed through cloud-proxy — even though the entire system prompt + tools
prefix is re-sent on every agentic turn.
Add an opt-in cache_prompt flag (ProxyOptions.cache_prompt; model YAML
proxy.cache_prompt: true). On a translate+anthropic model, buildAnthropicRequest
injects cache_control:{type:ephemeral} on the stable prefix — the system block,
the last tool, and the last message block (at most 3 of Anthropic's 4 allowed
breakpoints). Anthropic then serves the repeated prefix at the cache-read rate
(0.1x input) on subsequent calls, cutting cost on multi-turn/agentic workloads.
No effect in passthrough mode, for non-Anthropic providers, or when unset.
System is widened to any so it can carry the block form required to attach
cache_control, while still marshalling as a bare string when caching is off.
Adds a unit test asserting exactly three breakpoints when on and none when off,
and documents the option in docs/content/operations/cloud-proxy.md.
Assisted-by: Claude:opus-4.8
Signed-off-by: stefanwalcz <stefan.walcz@walcz.de>
* feat(ui): record finished gallery operations in a bounded history ring
The operations panel drops an operation the moment it succeeds, so a user
who steps away cannot tell whether an install finished, failed or was never
started. OpCache now keeps the last 50 terminal operations, recorded from
the point where an op leaves the cache.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(ui): pin the history ring's dedupe, outcome order and start stamp
Review of the history ring found four gaps. The dedupe guard and the
bounded seen set were unreachable through the exported API and so had no
coverage; an in-package spec file now drives opHistory directly. The
outcome switch claimed an ordering was load bearing that nothing pinned,
so an errored op that never reached Processed now has a spec.
Two behaviour fixes come with it. StartedAt was the zero time for ops
recovered from the store or replicated from a peer, since neither path
stamps a start time, which would have rendered as a two-millennia
duration; it now falls back to the finish time. Reusing a cache key with
a fresh job ID orphaned the previous stamp, so Set and SetBackend now
drop it.
The comment on the outcome switch described a state the code cannot be
in: CancelOperation sets Cancelled and Processed synchronously before the
handler removes the entry, so status.Cancelled already covers the cancel
endpoint. The !Processed clause stays for the dismiss endpoint firing on
an in-flight op, and the comments now say so.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): record operations that end on a peer replica
The NATS end event is the only signal a replica gets for an install another
replica ran. Record from applyEnd too, deduped by job ID so the originating
replica does not record its own broadcast twice.
Three start-stamp defects in the same path go with it. applyEnd now drops the
stamp unconditionally, since recordTerminal only cleans up on the path where it
found a cache key and an end event can overtake the local Set. applyStart drops
the stamp of the job whose cache key it replaces, which a peer-driven retry
previously stranded. And recordTerminal reads the stamp once instead of testing
Exists and then reading, so a concurrent record for the same job can no longer
delete the stamp between the two and let the zero time overwrite the
finish-time fallback, which the Activity page would render as a two-millennia
run.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): do not guess the outcome of a peer operation with no local status
A replica that restarts mid-operation hydrates its OpCache keys from
PostgreSQL, but gallery statuses are in-memory only and come back empty. The
end broadcast then landed on recordTerminal's nil-status branch, which reads a
missing status as queued-and-removed and filed a successful install as
cancelled. That reading is right locally and wrong on the peer path, where a
missing status means the outcome was never held here.
recordTerminal now takes the source of the terminal event and records nothing
when the peer path finds no status, restoring what the replica did before the
end event started recording. The local path is unchanged.
Also move the ApplyEndForTest seam to the conventional export_test.go, and stop
the dedupe spec from claiming to guard the ring's seen set: the local delete
removes the status keys, so the broadcast that follows returns before reaching
it. An in-package spec that calls recordTerminal twice does the pinning.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(api): add GET and DELETE /api/operations/history
Admin gated like the rest of the operations API. The live /api/operations
payload is unchanged so the one second poll stays small.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): expose operation history through OperationsContext
Fetched on demand and when the live list shrinks, never on the one second
poll interval.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): detect operation departure by identity and ignore committing ops in the ETA gate
Refetching history on a shrinking live count missed a completion that
coincided with a start, which is the common case during a batch install.
Track the live job IDs instead, so any departure triggers the refetch
regardless of how the count moved.
An operation that has finished downloading stays live at
currentBytes == totalBytes for the whole commit and install phase and can
never produce an estimate, so counting it in the all-or-nothing gate blanked
every other operation's time remaining for as long as it lasted. Only
operations still moving bytes get a vote.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): let only downloading operations gate the time remaining estimate
Verifying pins an operation flat below its total for the whole sha256 pass:
the AfterDownload hook reports completedBytes plus the finished file against
a total summed over every file, then hashes synchronously without emitting
progress. Files download sequentially, so a 15 shard model enters that
window 14 times, and a byte comparison cannot see it because the counter is
genuinely below the total throughout.
Gating on phase closes resolving, verifying, committing and persisting in
one predicate, so a quiet neighbour no longer blanks every other
operation's estimate for minutes at a time. The byte clauses stay: a
producer can report downloading with bytes already at the total.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): collapse the operations bar to a single line
Four concurrent installs used to take four rows above every page. The strip
now shows one operation, failure first, with a counter linking to Activity.
The close button hides the strip and no longer cancels an install.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): keep the operations strip from widening the page and from muting a failure
A long install error made the strip report a 1600px minimum width, which sized
main-content to fit and gave every page under it a horizontal scrollbar.
Inline-size containment plus shrinkable detail and bytes cells keep it inside
the viewport.
Hiding is no longer able to swallow the hidden job's own failure, a completed
removal or staging says so instead of claiming an install, a cancelling
operation renders as cancelling, and the live region no longer covers the
per-second percentage.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): shrink main-content instead of containing the strip, and expose progress
min-width on .main-content is what actually lets a long install error shrink,
and unlike inline-size containment it has no browser support floor and no
latent collapse if the strip ever lands in a shrink-to-fit context. It matches
what .app-layout-chat .main-content already does, and it clears pre-existing
horizontal overflow on narrow viewports as a side effect.
The progress track is now a labelled progressbar, so assistive tech can read
the value on demand rather than losing it to the aria-hidden that stopped the
live region re-announcing every poll.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): add the live operation card for the Activity page
Carries the detail the one-line strip has to drop: phase, bytes, the per-node
breakdown for cluster installs, and a labelled Cancel button. Cancelling is
destructive, so it gets a labelled button rather than a glyph.
A cancelling operation drops its progress bar and its time estimate, the same
call the strip makes: a percentage still climbing under "Cancelling" reads as
the cancel not having taken.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): give the operation card a verb, live node disclosure and its per-node detail
The card carried no verb, so an install, a removal and a staging op rendered as
spinner plus name plus kind tag and were indistinguishable. It now runs the same
verb and icon chain as the one-line strip, which is what stops the page that is
meant to carry more detail from carrying less.
The auto-expand default was evaluated once at mount. An operation is listed as
soon as it is admitted but its nodes are filled in only when the fan-out starts
reporting, so a card mounted at creation latched on the empty list and stayed
collapsed. The default is a live expression now, and state holds only an
explicit choice.
Also: an optional onRetry gates a Retry button, so the page can own the install
reconstruction without the card ever showing a control with nothing behind it;
the disclosure moved above the region it controls and gained aria-controls; the
toggle is gated at more than one node so the count is never "1 nodes"; an
unmapped node status is passed through instead of being relabelled "Queued";
error text is clamped with the full string in the title; and file_name plus the
per-node progress bar are rendered again, reviving three CSS rules that had gone
dead along with the detail they styled.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): add the Activity page
Live operations, unacknowledged failures and the record of what finished, at
/app/activity in the Operate console. Cancelling an install now lives here
behind a labelled button rather than on the strip, and a failed install can be
retried: the retry dismisses the failure first so it still reaches the record,
then reissues the model, backend or node-scoped backend install.
The sidebar Operate entry carries the operation count. The console rail is only
rendered on an Operate route and can be collapsed, so a badge there could
vanish while operations were still running.
Two follow-ups from review fold in here: a failed removal or staging job no
longer reports a failed install on either the card or the strip, and the card's
error text can shrink so one unbroken token cannot widen the card.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): dismiss operations by job, and stop the Activity page contradicting itself
Dismissing resolved the job by display id, but /api/operations strips the
"node:<nodeID>:" prefix before emitting, so a local install and a node-scoped
install of one backend arrive as two jobs sharing one id. Dismissing by id
retired whichever came first. That defeated the guarantee retry was built
around: with the wrong job dismissed, the reinstall overwrote the acted-on
failure's opcache entry in place, bypassing recordTerminal, while an unrelated
failure vanished from Needs attention. dismissFailedOp, the card's dismiss
control and the strip now all pass the jobID, which is what the endpoint takes.
A filter matching nothing rendered the "nothing has ever run" empty state while
the header counted the records the filter had hidden. The empty state is now
gated on the All chip and a narrowed view gets its own message plus a way back;
the header counts the instance rather than the chip, so selecting Backends no
longer reports "Nothing running" over running model installs.
Also: the summary drops a zero clause instead of rendering "0 needs attention"
on the happy path and pluralises both counts; a record duration is floored at
"< 1s" and rejected above a day, so a zero-value start stamp cannot render a
span of millennia and a zero span cannot render "installed in" with nothing
after it; a deletion cancelled mid-flight reports the cancellation rather than
claiming it was removed; and the retry variant comment names the fix instead of
calling the gap closed.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: document the Activity page and the operations history endpoints
Adds an Activity page under Operations covering the one-line operations
strip, the /app/activity sections and filters, per-operation cancel,
retry and dismiss, the in-memory 50-entry record, and the sidebar count.
Documents GET and DELETE /api/operations/history, and fills the gap in
the admin-only endpoint list, which also omitted the pre-existing
POST /api/operations/:jobID/dismiss.
Corrects the distributed-mode install-watching section: the per-node
breakdown now lives on the Activity page rather than on the strip, which
rolls a fan-out up into a single phrase.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: correct nine details in the Activity page documentation
The operations strip never renders a file name: its detail line is the
error, the node roll-up, the target node, the phase or the queued note.
Drops the stale clause in the distributed-mode section, where the
per-node bullet is now the only place a file name is described.
Scopes the phase vocabulary to artifact-backed gallery models, since a
plain GGUF install emits no phase. Corrects the per-node list: the
toggle exists for any fan-out of two or more workers and the four-node
threshold only governs whether it starts open, while the N nodes tag
needs more than one node. Notes that a cancelled operation can sit in
the live section reading Cancelling, that cluster staging never reaches
the record, and that Clear history appears only when the record has
something in it.
Names the operations response envelope, with a JSON example, so callers
do not index a bare array, and stops describing the icon-only dismiss
control as a labelled button.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: drop the unreachable Cancelling state and scope the byte claims
An operation can only report isCancelled while it is unprocessed, but
every writer of Cancelled sets Processed in the same breath, on the peer
path as much as the local one, and the cache evicts cancelled entries
before the handler sees them. The state cannot reach the page, so the
live section is described again as running or queued operations.
Byte counts come from the artifact bridge alone, the same producer as
the phase, so a plain GGUF install, a removal and a backend install
report none. Scopes both to artifact-backed gallery models and leaves
the verb, the name and the percentage as what every operation shows. A
worker backend install reports its bytes through fields the operations
payload does not carry, so the distributed section now describes the
percentage and the node roll-up, with per-file counts pointed at the
per-node detail.
Also: staging jobs carry no error, so they never reach Needs attention
and Retry never had a staging case to exclude; an install that involves
workers is no longer called node-scoped, which this page uses for
node-targeted installs; and the record timestamps carry nanoseconds.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: state only the verb and the name as unconditional on the strip
The percentage is as conditional as the bytes were: it renders only for
a running operation that has reported progress, so a queued operation, a
failed one and a removal never carry it. A removal in particular sits at
progress zero for its whole visible life, since the delete path reports
none and its completion is filtered out. Both the strip and the card
paragraphs now lead with what always shows and list the rest as
conditions.
The Cluster chip matches on a node list that finished operations do not
carry, so a fan-out install leaves the chip once it reaches the record.
Scoped that claim to the live sections.
Two more of the same shape, found by re-reading each clause alone: the
strip also appears for a failure, which is not running, and the
four-second hold only applies when nothing replaces the operation that
just finished.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): stop reporting a cancelled install as installed, and make queued real
Three defects that all trace to one root cause: `isCancelled: true` is
unreachable from /api/operations. Every writer of Cancelled=true also sets
Processed=true, the handler skips Processed && Cancelled, and OpCache.GetStatus
evicts a cancelled op before the handler iterates it.
Cancelling the last running operation put a green "Installed model X" on the
strip for four seconds: the completion hold was guarded by
`!previous.isCancelled`, which is dead. A cancellation deletes the operation
server side, so the strip sees exactly what it sees on a completion, and
nothing in the payload separates the two. The signal now comes from the side
that issued the cancel: the operations context remembers the job IDs it
cancelled (pruned after a minute) and the strip asks before it holds anything.
A cancelled operation goes as soon as it stops; the record already reports it
as cancelled.
isQueued was set only when the gallery status was missing, but markQueued
publishes a "queued" status at admission, so a queued op has a status for its
whole queued life and the state was unreachable outside a microsecond window.
Every operation waiting behind a running install rendered as "Installing model
X" with a spinner. The queued phase is now the signal, via an exported
PhaseQueued and a nil-safe OpStatus.IsQueued() next to the writer.
With those two fixed, the Cancelling state has no way to be entered: cancelling
is instantaneous from the API's point of view. Its branches, CSS, locale key
and the isCancelled field itself are removed rather than left for a future
reader to assume they work.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): keep a removal a removal, and say what an install is doing
OpStatus.Deletion was set once, at admission, and lost on the next status
write: UpdateStatus replaces the whole status and only carried Nodes
forward. Every later writer (the worker's first write, the progress
ticks, the failure path) leaves the field at its zero value, so the flag
survived only the queued window, and both surfaces test isQueued first.
The reachable consequence is that a failed removal reported itself as a
failed install, which is exactly the shape the Activity page offers Retry
for, and Retry installs: pressing it on a removal that failed
re-downloaded the model. A running delete also rendered as "Installing
model X" with a spinner, and a successful one as "Installed model X".
Carry Deletion forward the way Nodes already is. A job is a delete or an
install for its whole life; an unset flag means "no new information", not
"this is an install". Pinned by Go specs on both the service and
/api/operations: the existing Playwright specs were green only because
they stubbed a payload the server could not emit.
Also restore the operation's own status message on the Activity card.
Phases and byte counters exist only on the managed-artifact path, so a
legacy files: gallery model and every backend install rendered a sub-row
with nothing in it but the verb. The strip stays terse on purpose.
And give the strip's name a min-width floor: overflow: hidden zeroes its
automatic minimum, so a long error squeezed the name down to "mod…" and
the identity of the thing that broke was the first thing lost.
primaryOperation is made module-private: its comment claimed the Activity
page selected the same operation, but that page shows all of them,
partitioned into failed and running, and never imported it.
Assisted-by: Claude Code:Opus 5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(activity): read the operations record from PostgreSQL
The Activity page's record of finished installs and removals was a 50-entry
in-memory ring per frontend replica. In distributed mode that is the wrong
place for it: each replica keeps its own copy, a replica added by a scale-out
or a rolling deploy starts empty and never backfills, and "Clear history"
clears only the replica that served the request, so the record reappears on
the next poll routed elsewhere.
The data is already in gallery_operations. Read it from there.
GalleryStore gains ListTerminal and ClearTerminal, sharing a lifted
terminalStatuses set with CleanOld so there is one definition of "finished".
ListTerminal orders by updated_at, when the operation reached its terminal
status, because the record reports what finished and when.
OpCache.History and ClearHistory dispatch on whether a store is wired, so the
HTTP handlers and the OpRecord JSON shape are unchanged and the page needed no
change. A failed store read falls back to the local ring rather than blanking
the page, and ClearHistory empties the ring as well so a database blip cannot
resurrect a record the admin just cleared.
The name derivation in recordTerminal is lifted into operationDisplayName and
used by both paths, so the ring and the store cannot name the same operation
differently.
Also fixes a pre-existing bug the store path made visible: the backend channel
hardcoded op_type "backend_install" even for a removal, while the model channel
derives model_install/model_delete from op.Delete. Both channels carry the same
ManagementOp, whose Delete field the backend handler already branches on, so
the backend channel now derives backend_delete the same way.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(activity): keep a cancelled operation cancelled, and report a failed clear
Review follow-up on the store-backed Activity record.
A cancelled install was recorded as a failure. The cancel handler persists
"cancelled" synchronously, then the handler goroutine unwinds with the context
error and Start hands that to updateError unconditionally, which overwrote the
row with "failed: context canceled". The page rendered a cancelled install as a
red failure card offering Retry, with a raw context error as the reason.
Fixed in GalleryStore rather than in Start, because an operation finishes once
and the paths that retire one are not mutually exclusive: UpdateStatus now
refuses to rewrite a row that already reached a terminal status. That also pins
updated_at to when the operation really finished, which is the key the record is
ordered by, and Create's upsert now freezes the same columns so a worker
dequeuing an operation the admin cancelled while it was queued cannot reopen it
as pending.
ClearHistory returned nothing, so a failed delete logged a warning while the
handler still answered 200. The admin watched the record clear and come back on
the next fetch with nothing said about why. It now returns the error, the DELETE
handler answers 500, and the store is cleared before the local ring so a failure
leaves the fallback record intact rather than faking an empty one.
Hydrate is the only reader that decides from op_type whether an operation is a
removal, and it tested for "model_delete" exactly, so the backend_delete added
in the previous commit hydrated as an install: a replica restarting during a
backend removal rendered "Installing backend X". Both discriminations now go
through IsDeleteOpType/IsBackendOpType so a fifth op_type cannot silently read
as an install in whichever consumer was missed.
Also: the backend channel now persists Cancellable as !op.Delete, matching the
model channel; IsBackend falls back to the op_type prefix, since is_backend_op
is only written by UpsertCacheKey and the rows needing the name fallback were
reporting backend operations as models; and an unrecognized terminal status is
logged rather than quietly filed as a success, which is what the comment already
claimed.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(activity): keep a reaped operation correctable by its real outcome
The terminal-status freeze added in the previous commit was too wide. It froze
"failed" alongside "completed" and "cancelled", and the stale reaper writes
"failed" onto operations that are still going to run.
The gallery worker is a single goroutine consuming both channels serially, so
an operation queued behind a large download sits in "pending" with nothing
bumping updated_at, and ReapStaleOperations gives up on it after 30 minutes.
That used to be self-healing: the worker dequeued it, Create reset the row to
"pending", and the operation reported its real outcome. With the freeze the row
stayed "failed" forever while the install ran and succeeded underneath it: a red
failure card offering Retry for a model that is installed, omitted from
ListActive so no replica hydrates it, and no longer deduped cluster-wide by
FindDuplicate.
Freeze on ("completed", "cancelled") instead. That is all the cancelled-install
fix ever needed, and it leaves a failure correctable by what actually happened.
The set is separate from terminalStatuses, which ListTerminal, ClearTerminal and
CleanOld all still want in full, because the two mean different things: a
failure can be superseded by a real outcome, a completion or a cancellation is
the real outcome.
UpdateStatus now writes the error column unconditionally, so a corrected
outcome drops the previous attempt's reason rather than being recorded as
completed while still carrying "stale operation reaped" as its error.
Also adds the route-level spec for the 500 branch of DELETE
/api/operations/history, and trims a comment that credited the persisted
cancellable column with more than it survives long enough to do.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(activity): offer Cancel in the phase that can honour it
The cancellable flag was set at both ends of an operation's life and was wrong
at both, in opposite directions.
A queued operation is cancellable whatever it is. EnqueueModelOp and
EnqueueBackendOp select on the operation context, so cancelling one that is
still waiting releases the delivery goroutine and abandonQueued retires it: the
worker never sees it, nothing is downloaded, nothing is deleted. markQueued
nevertheless wrote Cancellable: !deletion, so a queued removal reported
cancellable: false and the UI hid the Cancel button in the one window where
pressing it both works and leaves no trace. A removal queued behind a large
install was stuck there until the install finished.
A running removal is not cancellable at all. DeleteModel and DeleteBackend take
no context, and modelHandler only checks the operation context after the call
returns, so a "cancelled" verdict would land after the model was already gone.
Both handlers nevertheless wrote Cancellable: true unconditionally at entry,
ahead of the op.Delete branch, offering a Cancel button the server cannot
honour.
So the queued phase is more cancellable than the running phase, which is the
reverse of the usual shape. markQueued now reports true unconditionally, and
the handler-entry writes report !op.Delete. Both sites carry a comment saying
why, because reading either one alone suggests the other is a bug.
GalleryStore.Create keeps !op.Delete: it runs at dequeue, so its value already
describes the running phase. Its comment now says so.
Specs cover queued removal, queued install, running removal and running install
through the handlers, plus the queued-removal case through /api/operations
where the flag is consumed, plus the behaviour the whole asymmetry rests on: a
removal cancelled while queued never reaches the worker and deletes nothing.
No existing spec asserted the old values.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(activity): clamp the installer message, and add a real-binary e2e spec
Running the page against a real local-ai showed the legacy installer message
wrapping to three lines and dominating the card: it embeds an absolute file
path, so it is both long and a single unbreakable token. One line, ellipsised,
full text in the title, matching what the error string already does.
The spec that found it runs with no route stubbing at all. Every other spec
here stubs /api/operations, which is how a payload the server cannot emit
(isDeletion true on a live operation) stayed green through a full review while
the UI rendered a removal as an install. It is skipped unless
LOCALAI_REAL_BINARY is set, so CI is unaffected.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Publish the existing Kokoro CPU profile for amd64 and arm64 and use it as the default gallery capability so Vulkan-only and CPU hosts can install the backend.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
sherpa-onnx links onnxruntime's CUDA execution provider, and
libonnxruntime_providers_cuda.so carries cuDNN as a hard DT_NEEDED. The
onnxruntime GPU tarball ships no cuDNN of its own, and Dockerfile.golang
only installs libcudnn9 on the arm64 + CUDA 13 branch, so the amd64 CUDA
builders have none at all.
Since #10946 added the packaging guard, that combination is fatal rather
than silent: package-gpu-libs.sh reports 'cuDNN: venv=absent system=absent
-> bundle=detect', correctly detects the reference, finds nothing to copy
and refuses to emit the package. Both -gpu-nvidia-cuda-12-sherpa-onnx and
-gpu-nvidia-cuda-13-sherpa-onnx have failed to build since 2026-07-19, so
neither image has been published. Before the guard existed they shipped
without cuDNN and failed at load time instead.
Install the runtime package for this backend only. The auto-detection
bundles solely what a package references, so no other backend would grow,
but every Go CUDA builder would pay ~1.1 GB of layer and registry cache
for a library ggml never calls.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
RecordBackendTrace does a non-blocking send onto a 100-slot channel and
drops when it is full, so tracing never stalls inference. The payload
bounding specs pushed all 200 traces in one tight loop, which overruns
that channel on a loaded machine: entries are dropped for good and the
Eventually waiting for 200 can never be satisfied, no matter the timeout.
CI hit this on master at 0a8a7fbb, settling at 158/200.
Feed the traces in chunks of 50, draining after each, so the channel is
never overrun and the count stays exact. Reproduced with 60 busy loops on
a 20-core box at GOMAXPROCS=2: 0/12 runs passed before, 12/12 after.
Assisted-by: Claude Code:claude-opus-5 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(tts): forward the OpenAI speed field to the backend (#11097)
/v1/audio/speech accepted the documented OpenAI `speed` field and then
dropped it: schema.TTSRequest had no Speed member, so the value never
reached proto.TTSRequest and the request returned 200 with an unchanged
playback rate.
Accept speed and normalise it into the existing per-request params map,
which core/backend forwards verbatim to the backend. An explicit
params["speed"] still wins, and a value outside the documented 0.25-4.0
range is now rejected with 400 instead of being silently ignored.
Signed-off-by: Anai-Guo <antai12232931@outlook.com>
* fix(tts): distinguish explicit speed=0 from an omitted field
Make TTSRequest.Speed a *float32 so an explicit `"speed": 0` (invalid,
below the documented 0.25 minimum) is rejected with 400 instead of being
treated as unset and silently defaulted. An omitted field stays nil and
leaves the backend default untouched.
Add a request-boundary regression that distinguishes an omitted speed from
an explicit zero, addressing review feedback.
Signed-off-by: Anai-Guo <antai12232931@outlook.com>
* docs: drop the speed field from the TTS docs
Per review: no backend consumes params.speed today, so documenting it
would be misleading. The API-level plumbing and validation stay.
Signed-off-by: Anai-Guo <antai12232931@outlook.com>
---------
Signed-off-by: Anai-Guo <antai12232931@outlook.com>
* fix: CVE-2026-54290 security vulnerability
Automated dependency upgrade by OrbisAI Security
Signed-off-by: orbisai0security <mediratta@gmail.com>
Signed-off-by: Anupam Mediratta <mediratta@gmail.com>
* fix(deps): override hono transitive dep to eliminate CVE-2026-54290
Add package.json `overrides` field to force hono@4.12.25 across the
entire dependency graph, including the transitive copy pulled in by
@modelcontextprotocol/sdk. Previously bun.lock retained a scoped
`@modelcontextprotocol/sdk/hono` entry resolved to the vulnerable
hono@4.12.8; the override removes that entry so only the patched
version ships.
Assisted-by: Claude Code:claude-sonnet-4-6
Signed-off-by: Anupam Mediratta <mediratta@gmail.com>
---------
Signed-off-by: orbisai0security <mediratta@gmail.com>
Signed-off-by: Anupam Mediratta <mediratta@gmail.com>
* fix(ci): build the CUDA 13 image on Ubuntu 24.04
The amd64 `-gpu-nvidia-cuda-13` image is the only runtime image still
built FROM ubuntu:22.04. The Ubuntu 24.04 migration (#7769) bumped its
`ubuntu-version` to 2404 but left `base-image` on jammy, so the image
ships glibc 2.35 while adding the noble CUDA apt repository, and every
backend it unpacks is built on noble.
Backends therefore cannot dlopen the libraries they bundle. The vLLM
backend dies at import time with:
OSError: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.38' not
found (required by /backends/cuda13-vllm/lib/libnuma.so.1)
and torchcodec finds no usable libavutil because jammy ships ffmpeg 4.x
(libavutil.so.56) while torchcodec looks for .so.57 through .so.60.
Add a spec over the build matrices that fails when a base image and the
`ubuntu-version`/`ubuntu-codename` it is paired with disagree, or when
the runtime images are split across Ubuntu releases. Entries whose base
image does not name a release (JetPack) are left alone.
The `base-grpc-cuda-13-amd64` builder base stays on jammy: it only
compiles backends, and a lower glibc floor in a builder is safe.
Fixes#11059
Assisted-by: Claude:claude-opus-5 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ci): drop the build matrix invariant spec
Per review, the CI matrix guard does not belong in the tree. Only the
base image bump remains.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): stop the probe reaper from orphaning busy backends
The reconciler's liveness probe is a 1s gRPC HealthCheck, and a single
failed probe deleted the model's node_models row. A backend that is
merely busy cannot answer it: single-threaded Python backends (video and
avatar generation) block for minutes inside one request, so the reaper
was deleting registry rows for backends that were alive and mid-request.
The model then vanished from the nodes page while it was still
generating, and because the row was gone the in-flight decrement had
nothing to decrement ("DecrementInFlight: no matching row or already
zero"). Every subsequent request re-routed and re-staged the full model
from scratch.
Two guards:
- Replicas with in-flight requests are excluded in SQL. A row that is
actively serving is proof of life, and the running request is
exactly what stops the backend from answering the probe.
- Idle replicas must miss three CONSECUTIVE probes before removal, so
a transient blip cannot orphan a live replica. A successful probe
resets the streak.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(distributed): drop the local model stub when its last replica goes
In distributed mode every routed model leaves an in-process stub in the
frontend's ModelLoader, and DistributedModelStore.Range reports local
stubs UNION the registry rows. Every registry removal path deletes only
the DB row, so the stub outlived the replica and the model was reported
as loaded forever.
That is the "loaded on the home page, absent from every node" ghost:
/system reads the union and still sees the stub, while /api/nodes/models
reads the registry and correctly sees nothing. It never self-healed,
and both frontend replicas showed it independently.
The replica-removed chokepoint could not fix this as it stood, because
it held a SINGLE hook that the prefix cache already owned, and it was
registered only when the prefix cache was enabled. Registering a second
listener would have silently displaced the first.
- Turn replicaRemovedHook into a list (AddReplicaRemovedHook), so
independent subsystems can each register without displacing others.
- Add NewLocalStubInvalidator, which drops the local stub once no
healthy replica of the model remains anywhere in the cluster, and
wire it unconditionally in startup.
The stub is kept while another node still serves the model: the
frontend is right to consider it loaded, and each request re-routes
through SmartRouter to pick a live replica anyway.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(distributed): stop staging checksum sidecars back to workers
The file transfer server writes a "<file>.sha256" sidecar next to every
file it accepts. The sender walked the model directory with no filter,
so it staged those sidecars too, and the receiver duly wrote a sidecar
for each sidecar. Every staging pass multiplied the tree:
config.json -> config.json.sha256 -> config.json.sha256.sha256 -> ...
One LongCat snapshot had grown to 498 files, 466 of them chained, up to
29 levels deep, and the staged file count climbed on every pass. This
inflates each transfer and grows disk without bound on both ends.
Skip hash sidecars in stageDirectory, and mirror the skip in
countStageableFiles so the progress bar still reaches 100%. The check is
"a sidecar sitting next to a real file" rather than a blanket suffix
ban, so a model that genuinely ships a .sha256 payload with no
corresponding base file is still transferred.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(distributed): classify the liveness probe instead of gating on in_flight
The previous commit excluded replicas with in-flight requests from the probe
reaper. That was the wrong guard, and could invert the bug it fixed.
in_flight has no decrement guarantee: track() balances its increment with a
defer, but a frontend killed mid-request never runs it, and the load-time
reservation is released only when the first inference completes. Nothing
resets a leaked counter. Gating the reaper on it therefore meant a leaked
counter would shield a genuinely dead replica from ever being reaped.
Nor was patience alone a fix: three misses at the default interval is ~90s of
silence, while the generation that triggered this blocks for 15+ minutes.
The real conflation was in the probe itself. A gRPC HealthCheck against the
backend's serving port measures "is it idle enough to answer", not "does the
process exist", and probeLoadedModels discarded the error that tells them
apart. Because the gRPC client is lazy, the status code is decisive:
- DeadlineExceeded: transport fine, nothing serviced the RPC. Busy.
- Unavailable: nothing is listening. Gone.
ModelProber now returns a ProbeOutcome, and only ProbeUnreachable counts
toward the reap threshold. ProbeBusy clears the streak: it is evidence of
life. A blackholed network reads as busy too, deliberately, since whole-node
failure is the health monitor's job.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* feat(distributed): reconcile replicas against worker-reported processes
Probing a backend's own serving port cannot distinguish "busy" from "gone"
without inferring it from an error code. The worker can answer directly: it
spawned the process, holds the handle, and its reply is not blocked by
whatever that backend is doing.
Adds a models.running request-reply subject. The worker answers out of its
in-memory process table, reporting each live process as (modelID,
replicaIndex, address) — the supervisor's process keys are `modelID#replica`,
which is isomorphic to a NodeModel row, so the reconciler can diff the two
directly.
reconcileNodeProcesses runs before the port probe and reaps rows for models
the worker is not running. Models the worker vouches for get updated_at
bumped, which takes them out of the port prober's stale set entirely: that is
what keeps a backend deep in a long generation away from the probe in the
first place, rather than relying on classifying its silence after the fact.
A worker that does not answer is skipped, not assumed empty. A messaging
failure says nothing about the processes, and assuming the worst would delete
a node's rows on a transient NATS blip; the port probe stays as the fallback
for those nodes. Rows younger than probeStaleAfter are ignored so a freshly
created row is never judged against a process table that has not caught up.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
* fix(distributed): stop in_flight leaking and pin replicas against eviction
A leaked in_flight counter is not cosmetic. FindLRUModel,
FindGlobalLRUModelWithZeroInFlight and the router's eviction query all require
in_flight = 0, so a replica whose counter never came back is pinned and its
VRAM is unreclaimable for the lifetime of the process.
Two halves.
The source: routing reserves in_flight = 1 at load time so a freshly loaded
replica is not evicted out from under the request that caused the load. That
reservation was released ONLY by the first inference completing, so a route
torn down before any inference ran (client disconnect, handler error, failure
between load and the backend call) stranded it. newRouteResult now wires the
reservation to a sync.Once fired by whichever comes first, the first inference
or route teardown, and replaces three copies of the old wiring.
The backstop: a sweeper for counters leaked by paths that cannot run a defer
at all, such as a frontend killed mid-request.
Identifying a leak by elapsed time alone is unsafe. IncrementInFlight stamps
last_used at request START and nothing moves it while the request runs, so a
long generation is indistinguishable from a leak by age, and resetting there
would expose a serving model to eviction. The probe supplies the missing bit:
a backend that answers a health check promptly is not inside a request,
because that is precisely what a busy one cannot do. Requiring the row to also
be idle for 30 minutes covers backends that serve in parallel and can answer
while working, since those keep last_used fresh through each new increment.
Two existing tests asserted the old behaviour ("No decrement on Release").
That assertion was the leak, so both now pin the release instead.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Bump LLAMA_VERSION to 0d47ea7427463093e69128bf2c2f9cd06b3ee5b3 (73 commits
touching common/, src/ and tools/server/). Two upstream changes break the
backend:
* ggml-org/llama.cpp#20834 folded common_params::use_mmap / use_mlock /
use_direct_io into a single `load_mode` enum. LocalAI still exposes the three
as independent settings (`mmap`, `mmlock`, and the `direct_io` option), so
params_parse folds them once all three have been read, keeping the precedence
the separate booleans had: direct I/O bypasses the page cache, mlock implies
mmap, everything off is a plain buffered read. turboquant and bonsai compile
this same grpc-server.cpp against forks that predate the refactor, so
prepare.sh probes the checkout for LLAMA_LOAD_MODE_MMAP and generates
llama_compat.h with LOCALAI_LEGACY_LOAD_MODE set accordingly. Probing beats a
per-fork build flag here because the fork flavor targets disagree on whether
they forward CMAKE_ARGS or EXTRA_CMAKE_ARGS, and it heals itself once a fork
rebases past the refactor.
* The MiniMax M3 patch no longer applies. Upstream merged the model half of
llama.cpp#24523 (LLM_ARCH_MINIMAX_M3, src/models/minimax-m3.cpp, the gguf-py
constants and conversion/minimax.py) but not the chat half, so the patch is
re-cut to carry only the common/chat.cpp template detection and PEG parser,
rebased onto the new pin and onto the thinking_end_tag -> thinking_end_tags
rename. Dropping it wholesale (as #11008 did, reverted in #11136) would have
silently regressed MiniMax M3 tool calling and thinking.
Verified with a CPU docker build of the backend plus LoadModel and Predict
against a real GGUF over gRPC in all four load modes.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(realtime): accept legacy 'modalities' alias for output_modalities
OpenAI's Realtime *beta* used the field name `modalities`; the GA field is
`output_modalities`. LocalAI only binds `output_modalities`, so a client
sending the still-common beta field `modalities: ["text"]` has it silently
dropped by encoding/json and the session falls back to audio: TTS runs and the
client receives large response.output_audio.* frames even though it asked for
text-only.
Accept `modalities` as an alias on both session.update (RealtimeSession) and
response.create (ResponseCreateParams). The GA `output_modalities` wins when
both are present, so GA clients are unaffected. Applied at the two existing
resolution points via a small modalitiesWithAlias helper.
Fixes#11103
Signed-off-by: Anai-Guo <antai12232931@anaiguo.com>
* test(realtime): add JSON-boundary regression for modalities alias
Decode representative session.update and response.create payloads that
carry only the legacy beta `modalities` key and assert the effective
output modality resolves to text (not audio), reproducing the exact
expressions used in updateSession and triggerResponseAtTurn. This guards
against a wrong JSON tag or a missed call site letting encoding/json drop
the alias silently.
Also document output_modalities (and the accepted legacy modalities
alias) for text-only sessions in the realtime feature docs.
Signed-off-by: Tai An <antai12232931@outlook.com>
---------
Signed-off-by: Anai-Guo <antai12232931@anaiguo.com>
Signed-off-by: Tai An <antai12232931@outlook.com>
Co-authored-by: Anai-Guo <antai12232931@anaiguo.com>
* feat(backend): add vllm-cpp text-generation backend (vllm.cpp)
Wrap https://github.com/mudler/vllm.cpp - the LocalAI-team from-scratch C++20
port of vLLM (paged KV cache, continuous batching, prefix caching, safetensors
+ GGUF loading, no Python at inference) - as a Go gRPC backend over its stable
C ABI (ABI v2) via purego.
Backend (backend/go/vllm-cpp):
- Load -> vllm_engine_load: accepts a .gguf file or a config.json model dir
(anything else is refused, satisfying the greedy-probe rule); context_size
maps to max_model_len, options block_size/num_blocks/max_num_seqs size the
KV cache and scheduler admission.
- Predict -> vllm_complete (blocking); PredictStream -> vllm_complete_stream
with the per-delta C callback bridged into the gRPC stream. The backend
embeds base.Base (not SingleThread): concurrent requests batch continuously
in the engine's shared AsyncLLM scheduler.
- PredictOptions.Grammar -> the ABI's structured_grammar (GBNF), giving
grammar-constrained tool calling at parity with llama-cpp; the ABI also
exposes JSON-schema/regex/choice constraints.
- Hand-mirrored POD structs with layout locked by unit tests
(unsafe.Offsetof vs the C offsets) and a runtime vllm_abi_version gate.
- One portable library per platform (vllm.cpp uses per-file SIMD tiers with
runtime dispatch), so no avx/avx2/avx512 variant builds.
Wiring:
- backend-matrix: CPU amd64+arm64 (per-arch + manifest merge), CUDA 12/13
amd64 (120a;121a Blackwell fat binary), L4T arm64 (121a, GB10/DGX Spark -
the runtime-proven GPU target), Vulkan amd64, and Darwin arm64 Metal.
- backend/index.yaml meta + 12 image entries (latest/development x cpu,
cuda12, cuda13, l4t, vulkan, metal); bump_deps registration for the
VLLM_CPP_VERSION pin; root Makefile registration; test-extra runs the unit
specs (pure Go, no engine build).
- Importers: preference-only swaps - llama-cpp (GGUF) and vllm (safetensors)
advertise vllm-cpp via AdditionalBackends and emit backend: vllm-cpp
without tokenizer templating (the C ABI takes the FINAL prompt; templating
and tool parsing stay LocalAI-side). No auto-detect importer.
- Docs: backends list, top-level README maintained-engines table,
compatibility table.
Verified: 20/20 Ginkgo specs against the real pinned engine and
Qwen3.5-2B-UD-Q8_K_XL.gguf on CPU - blocking + streaming parity, greedy
determinism, stop words, GBNF-constrained generation, and 4 concurrent
streams; plus a dlopen/ABI-gate smoke of the built gRPC server binary.
Upstream ABI v2 + production structured-output wiring landed as
mudler/vllm.cpp@86013f3.
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vllm-cpp): ride the autoparser code path - engine-side chat templating and tool engagement (ABI v3)
The backend now implements AIModelRich (PredictRich / PredictStreamRich) over
vllm.cpp's ABI v3 chat entry points, so chat and tool calling ride the SAME
code path as the llama.cpp autoparser: the ENGINE renders the model's chat
template, decides when a tool call engages, and parses it - LocalAI receives
pre-parsed ChatDelta / ToolCallDelta protos exactly as it does from llama-cpp.
- With use_tokenizer_template + structured Messages, PredictOptions lowers to
ONE OpenAI chat request JSON (messages, tools, tool_choice, sampling,
stream_options.include_usage) for vllm_chat / vllm_chat_stream. tool_choice
auto lowers engine-side to a LAZY structural-tag decode constraint - free
text until the model emits the tool trigger, then the call is
grammar-constrained; required/named force a call. Tool output is parsed by
the engine's streaming Hermes-style parser; each chat.completion.chunk maps
onto ChatDeltas (content / reasoning_content / tool_calls) which the host
already prefers over Go-side tag extraction. Without structured messages the
plain path (LocalAI templating + optional GBNF grammar) applies unchanged.
- The engine resolves the chat template from the GGUF tokenizer.chat_template
metadata (or tokenizer_config.json); templates beyond its minja subset -
e.g. the full Qwen3.5 namespace()/macro template - degrade engine-side to a
Hermes-aware fallback prompt (tools schemas + <tool_call> instruction) with
a stderr witness, so structural-tag engagement keeps working.
- Importers now emit the same config shape as llama-cpp for vllm-cpp
(use_tokenizer_template: true, no-grammar autoparser flow); only the
llama-cpp-specific use_jinja option and the vllm-python parser options are
dropped.
- Pin bumped to mudler/vllm.cpp@aaed7ec (ABI v3 + chat-prompt resolution).
Verified against the real engine and Qwen3.5-2B-UD-Q8_K_XL.gguf on CPU: full
suite green - blocking chat, streaming deltas concatenating byte-equal to the
blocking answer, a REQUIRED tool call returning schema-valid arguments JSON,
and an AUTO run where the engine itself engages get_weather and streams parsed
tool deltas; plus unit specs for the request lowering, chunk->ChatDelta
mapping, and the C struct mirrors (ABI gate now v3).
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vllm-cpp): ABI v5 - engine-side parser selection for 30 tool dialects + reasoning
Bump the vllm.cpp pin to the autoparser-parity engine: 30 tool-call dialects
(every pure-text parser in the pinned vLLM registry, each ported 1:1 with its
upstream tests), 7 reasoning parsers, google/minja as the template renderer
(the full Qwen3.5 template now renders engine-side), per-family structural
tags (tool_choice required/named compiles the model's NATIVE syntax where
expressible), and template auto-detection for both parser axes.
Backend changes:
- cModelParams mirrors ABI v5 (tool_parser + reasoning_parser fields,
layout-locked by the offset tests; ABI gate now v5).
- New model options tool_parser:<name> / reasoning_parser:<name> pass through
to the engine; unset means template auto-detection (18-row tool marker
table; [THINK]->mistral, <think>->think_auto for reasoning); "none"
disables the reasoning split; unknown names fail the first chat call.
- Chat chunks parse the `reasoning` field (the pin renamed
reasoning_content), flowing into ChatDelta.ReasoningContent which the host
already prefers.
Live e2e against Qwen3.5-2B-UD-Q8_K_XL.gguf on CPU, full suite green: the
real chat template renders (no more fallback), reasoning auto-detection picks
think_auto so markerless answers stay pure content (the live run caught the
deepseek_r1 content-swallow upstream and drove the think_auto fix), required
tool_choice returns schema-valid arguments, auto tool_choice engages
engine-side and streams parsed deltas, and blocking/streaming stay
byte-identical. Turn latency also dropped (proper template EOS behavior).
Upstream program landed as mudler/vllm.cpp 86013f3..5fffe7e (ABI v2-v5,
minja, parser waves B1/B2/B4, reasoning seam, structural-tag registry,
think_auto).
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(vllm-cpp): bump the engine pin to the ENG-wave close-out
mudler/vllm.cpp@df8909b: the six engine-backed vLLM tool-parser families
(qwen3-coder/xml/mimo, kimi_k2, glm45/47, minimax_m2, gemma4, seed_oss)
text-reimplemented from their wire formats and held to the upstream test
suites - 39 registered dialects; the pinned vLLM registry is now covered
except the three Rust/Harmony-backed families, descoped by decision. kimi_k2
also gains a full native structural-tag builder; four new template
auto-detection rows land with test-pinned ordering.
Full backend e2e re-run green against Qwen3.5-2B-UD-Q8_K_XL.gguf on CPU.
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vllm-cpp): add the vllm-cpp-development gallery meta
The gallery grew the twelve latest/development image entries but was missing
the separate vllm-cpp-development meta (own capabilities map targeting the
-development image names), which every backend ships so the development
gallery resolves per-platform. Validated: all capability targets in both
metas resolve to existing entries, and every image URI's tag suffix matches
a backend-matrix build.
Also full-stack verified in this change's context (single-node local-ai from
this branch, locally-built backend under --backends-path, Qwen3.5-2B GGUF):
/v1/chat/completions non-stream (clean content + usage), streaming (SSE
deltas), tool_choice auto engaging get_weather engine-side with schema-valid
arguments and finish_reason=tool_calls, and streamed tool-call deltas in the
standard name-first cadence.
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vllm-cpp): repair the CI backend builds - gcc-14 -Werror + fat-arch Triton
Two distinct failures took down all five vllm-cpp backend builds on the PR:
1. gcc-14 (ubuntu:24.04 CI images; the local toolchain is gcc-13) fails the
engine build with -Werror=maybe-uninitialized in InputBatch::condense - a
false positive through a staging std::optional's raw storage. Fixed
upstream (mudler/vllm.cpp@61f3e85) by moving slot-to-slot directly;
verified BOTH ways under dockerized g++-14.2 (unfixed reproduces CI's two
diagnostics exactly, fixed compiles clean) with the engine's behavior
suites green. Pin bumped to that sha.
2. The amd64 CUDA builds died at CMake configure: the vendored Triton-AOT
cubin trees are per-arch and the engine refuses -DVLLM_CPP_TRITON=ON on a
multi-arch (120a;121a) fat build unless pinned to one tree, which would be
unsound for the other arch. Triton is now enabled only on the single-arch
arm64/GB10 build (where the cubins matter); the fat amd64 binary uses the
engine's non-AOT GDN path.
Backend e2e re-run green at the new pin (Qwen3.5-2B on CPU, full suite).
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vllm-cpp): cuda-12 images cannot compile compute_121a - target 120a only
The second CI round surfaced a CUDA-version constraint: the cuda-12 (12.8)
image's nvcc rejects 'compute_121a' (GB10 arch support landed with CUDA 13),
killing the amd64 cuda-12 build at nvcc. Gate the architecture list on
CUDA_MAJOR_VERSION (exported by Dockerfile.golang): cuda-12 builds consumer
Blackwell 120a only, cuda-13 keeps the 120a;121a fat binary, arm64/l4t
(cuda-13) keeps single-arch 121a with the Triton cubins. GB10 is arm64, so
the amd64 cuda-12 image never served it - no capability change.
Verified by Makefile dry-run variable dumps for all three combinations
(cuda12 -> 120a; cuda13 -> 120a;121a; cpu -> CUDA off).
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vllm-cpp): drop the cuda-12 variant - the engine needs the CUDA 13 toolchain
Third CI round, third layer: with the arch list already narrowed to 120a,
the cuda-12 (12.8) build still dies in ptxas compiling the sm_120a NVFP4 MMA
kernels ("Vector type too large, exceeds 128 bit limit") - the Blackwell fp4
path genuinely requires the CUDA 13 toolchain, and vllm.cpp supports
Blackwell-family GPUs only. Shipping a cuda-12 image without the fp4 kernels
would be a crippled build of an engine whose whole GPU story is fp4, so the
variant is dropped instead:
- backend-matrix: cuda-12 vllm-cpp entry removed (cuda-13 amd64, l4t arm64,
cpu, vulkan, metal remain).
- gallery: cuda12 image entries removed; the nvidia capability now resolves
to the cuda13 image in both metas; the nvidia-cuda-12 key is dropped so
older-driver hosts fall back to the CPU image instead of an unrunnable one.
- backend Makefile: BUILD_TYPE=cublas under CUDA_MAJOR_VERSION=12 now fails
fast with a clear message; cuda-13 keeps the 120a;121a fat binary and
arm64/l4t keeps 121a with the Triton cubins.
Verified: Makefile branch dumps for all four combinations (cuda12 loud
error, cuda13 fat, arm64 121a+Triton, cpu off), YAML parses, matrix filter
tests green, gallery capability targets all resolve.
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vllm-cpp): forward multi-turn tool identity and reasoning to the engine
chatRequestJSON dropped Message.ToolCallId and Message.Name on role="tool"
replies and Message.ReasoningContent on assistant history, so a second
turn after tool execution reached the engine's chat template without the
fields that bind a tool result to the call it answers. Forward all three
(present-only, matching the OpenAI wire shape) and pin vllm.cpp to
6a0bd3e7, where ChatMessage parses/round-trips tool_calls, tool_call_id,
name and reasoning and the minja adapter exposes them to the template
context.
Adds the round-trip request-lowering spec (user -> assistant tool_call ->
tool reply -> lowered request) and re-ran the gated e2e suite against the
new engine pin with a real Qwen3.5 GGUF: chat, reasoning split, streaming
parity, required-tool and auto-tool cases all green.
Assisted-by: Claude Code:claude-fable-5 [Bash] [Edit] [Read]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vllm-cpp): bump vllm.cpp for the darwin arm64 i8mm build fix
The darwin-metal CI job was the first build to compile the engine's arm
CPU-quant files on macOS and hit their Linux-only <asm/hwcap.h> /
<sys/auxv.h> includes. vllm.cpp 9e1c9025 detects i8mm per-OS (auxv on
Linux, sysctl on Apple Silicon) with kernels untouched. Gated e2e suite
re-run green against the new pin with a real Qwen3.5 GGUF.
Assisted-by: Claude Code:claude-fable-5 [Bash] [Read]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vllm-cpp): darwin build - bound cmake parallelism when nproc is absent
The macOS runners have no nproc, so JOBS evaluated empty and
`cmake --build -j$(JOBS)` became bare `-j`: unlimited clang jobs on a
3-core/7GB Mac, which swap-thrashed until the 6h GHA timeout (the log
shows "nproc: Command not found" and 7+ concurrent clang processes being
reaped at the cutoff). Use the same portable fallback chain as the other
darwin backends: nproc, then sysctl hw.ncpu, then 4.
Assisted-by: Claude Code:claude-fable-5 [Bash] [Edit] [Read]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
feat(distributed): cache staged-artifact hashes and publish load lifecycle
Every load request re-hashed every staged artifact on the controller
(probeExisting and the upload path both re-read the full file), which for
a large multi-file model on NAS-backed storage is minutes of pure
re-reading per request even when nothing changed - observed as ~9 minutes
of "Upload skipped (file already exists with matching hash)" before every
avatar generation. Cache the local hash in the same .sha256 sidecar the
worker-side transfer server already maintains, invalidated whenever the
sidecar is older than the file.
The whole staging+loading phase was also invisible: the NodeModel row was
only written after LoadModel succeeded, so /api/nodes and the UI showed
nothing while a cold load spent 10+ minutes staging - indistinguishable
from nothing happening. Publish the lifecycle instead: "staging" as soon
as the node is chosen, "loading" when the checkpoint load starts, and the
existing "loaded" on success, with the row removed on any failure so a
dead load does not leave a phantom replica. The early row also reserves
the replica slot against concurrent schedulers. The nodes view already
renders non-loaded states on model chips; style "staging" like "loading".
Audited every state-filtered registry/router query: eviction, routing,
reconciler and idle-model queries all filter state='loaded' explicitly,
so the new transitional rows are visible to observability surfaces but
inert to scheduling decisions (except slot occupancy, intentionally).
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
* fix(gallery): coalesce artifact download progress
Buffer high-frequency downloading events and forward only the latest event on a periodic tick. Flush progress synchronously at phase boundaries and shutdown to preserve ordering and final state.
Assisted-by: Codex:gpt-5
* fix(gallery): wire progress coalescing into model installs
Route artifact progress through the 250 ms coalescer and flush it on every model operation exit. Keep the legacy download callback unchanged.
Assisted-by: Codex:gpt-5
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(backend): add magpie-tts-cpp text-to-speech backend
Add a Go + purego backend wrapping the magpie-tts.cpp ggml port of NVIDIA's
Magpie TTS Multilingual 357M (encoder + autoregressive decoder over NanoCodec
tokens), producing 22.05 kHz mono audio in 5 baked voices (Aria, Jason, John,
Leo, Sofia; case-insensitive names or indices 0-4) across 9+ languages from a
single self-contained GGUF. Mirrors qwen3-tts-cpp / moss-tts-cpp: dlopen the
static-ggml shared library, bind the flat magpie_tts_capi_* C-API via purego
(no local C shim needed, the upstream .so exports it directly), and serve the
gRPC TTS + TTSStream methods behind base.SingleThread (the C context is not
reentrant across synthesize calls).
The backend CMakeLists translates the Makefile's -DGGML_{CUDA,METAL,VULKAN,HIP}
flags into upstream's MAGPIE_GGML_* toggles (upstream FORCE-overwrites the ggml
cache entries from those), pinned to magpie-tts.cpp v0.1.1
(e3f3dd1ebe22b64e7405f93b519f2d1930712568), which statically links ggml into
libmagpie-tts.so (ldd shows only system libs).
Wires the full registration: backend-matrix.yml (CPU amd64/arm64, CUDA 12/13,
Intel SYCL f16/f32, Vulkan amd64/arm64, ROCm, NVIDIA L4T + L4T CUDA 13, and
Darwin metal), backend/index.yaml metas and image entries, the root Makefile
build targets, the changed-backends backend-filter path mapping, the bump_deps
auto-bump matrix, a test-extra per-backend smoke job, the /backends/known
pref-only importer entry, the backend capabilities map (TTS + TTSStream, no
voice cloning), and the README / compatibility-table docs rows.
Verified locally: unit + e2e Ginkgo suites pass against the real q8_0 GGUF
(22.05 kHz mono WAV, RMS > 0.01), a live gRPC LoadModel + TTS round-trip
returns valid non-silent audio, and the pre-commit gates (make lint,
make test-coverage-check) pass, run manually with LOCALAI_TEST_HTTP_PORT
overriding the locally-occupied 9090.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* gallery: add magpie-tts-cpp model entries (q8_0 + f16)
Add the Magpie TTS Multilingual 357M GGUFs from mudler/magpie-tts.cpp-gguf to
the model gallery: q8_0 (~624 MB, near-lossless, fastest decode, recommended)
with an f16 (~784 MB) variant, both served by the magpie-tts-cpp backend.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* magpie-tts-cpp: bump pin to rewritten upstream v0.1.1 SHA
Upstream history was rewritten to purge accidentally committed build
artifacts; v0.1.1 now resolves to 6f7696cf.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Remove the versioned pre-commit hook and its installer while retaining CI coverage and conformance checks.
Assisted-by: Codex:gpt-5
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The stall watchdog arms as soon as the response body exists, but the
downloader then re-hashed the entire existing .partial before reading a
single byte from the network. On slow models storage (a CIFS share
reading at ~117MB/s) hashing a multi-GB partial outlasts the 60s stall
window, so the watchdog aborted every healthy resume with 'download
stalled: no data received for 1m0s'. The partial never grew, so every
retry re-paid the same hash and failed identically, wedging the install
permanently (any partial over ~7GB on such storage).
Open the partial and hash it before the HTTP request instead: the
watchdog now only measures actual network idle time, and the origin no
longer sits on an idle connection while the hash runs.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(trl): disable inline GRPO reward code by default (RCE)
POST /api/fine-tuning/jobs accepts reward_functions[].code, an inline Python
body, and compile_inline_reward() execs it against a restricted-builtins
allowlist (_SAFE_BUILTINS). That allowlist is not a security boundary:
().__class__.__bases__[0].__subclasses__() reaches os._wrap_close and thus
os.system, giving arbitrary code execution. The fine-tuning endpoint is
unauthenticated by default, so any caller could run code on the host.
Hardening the allowlist is a losing game against CPython introspection, so
inline reward code is now refused unless the operator explicitly opts in with
LOCALAI_TRL_ALLOW_INLINE_REWARD=true on the backend. Builtin reward functions
are unaffected. The gate lives in build_reward_functions(), the single point
all inline specs flow through. Docs updated to stop describing the allowlist as
a sandbox and to document the opt-in.
Fixes#11015
Signed-off-by: Isabel Wu <231155141+wuisabel-gif@users.noreply.github.com>
Co-authored-by: Isabel Wu <231155141+wuisabel-gif@users.noreply.github.com>
fix(model-artifacts): persist companion artifacts, not just the primary
A managed model can declare companion artifacts (LongCat-Video-Avatar-1.5
pulls its tokenizer, text encoder and VAE from the separate LongCat-Video
base repo via a target: companion artifact). preloadOne resolves the whole
set in memory, but the binding written back to disk carried only the
primary: persistArtifactBinding marshalled []Spec{result.Spec} and replaced
the entire artifacts: list with it, silently dropping every companion.
In a single process the loss is invisible because the in-memory config keeps
the companion. It bites on the next controller restart: the config reloads
from the mangled file with the primary alone, so withCompanionArtifactOptions
finds no resolved companion and synthesizes no base_model option. The remote
longcat-video backend then never receives base_model, falls back to
BASE_MODEL_ID and downloads the repo itself ("Downloading required files for
meituan-longcat/LongCat-Video"), failing the load with "base_model must point
to a LongCat-Video checkpoint".
This is why an explicit base_model:<path> added to the config options works
where the managed companion does not: an explicit option lives in options:,
which is never rewritten, while the managed companion lives in artifacts:,
which the binding overwrote.
Persist the full resolved set (primary + every companion), and widen
bindingNeedsPersistence to compare the whole artifact list so a companion
resolving for the first time still triggers a write. The single-node path is
unaffected: there the in-memory config already carried the companion, and the
staging/ModelPath resolution for a remote worker (nested per-model staged
root, #10949) is unchanged and already correct once the option is generated.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The Python gRPC bindings expose message fields as plain attributes
(request.language, request.caption), not Go/Java-style Get*() accessors.
Because request.language is an empty string when unset, the
request.language or request.GetLanguage() or "en"
expression falls through to request.GetLanguage(), which does not exist
on the generated Python message and raises AttributeError, surfaced to
clients as:
rpc error: code = Unknown desc = Exception calling application: GetLanguage
Every /v1/sound-generation request without an explicit language field
failed. Drop the bogus accessor calls (TTS already uses the plain-field
form a few lines below).
Signed-off-by: Tai An <antai12232931@outlook.com>
* fix(backends): choose the protoc generator from the protobuf runtime, and regenerate stubs after late installs
The vLLM backends still crash on startup with
VersionError: Detected incompatible Protobuf Gencode/Runtime versions when
loading backend.proto: gencode 7.35.0 runtime 6.33.6
despite #10735 and #10944. Three separate defects kept it alive.
1. runProtogen picked the generator from the installed *grpcio* version.
grpcio-tools' version tracks grpcio, but the gencode its bundled protoc
emits tracks *protobuf*, and the two move independently: grpcio-tools
1.82.1 (the version #10735 pins to, matching grpcio 1.82.1) requires
protobuf>=7.35.1 and stamps gencode 7.35.0. Pinning to grpcio could
therefore never constrain the gencode. Constrain the install to the
protobuf already in the venv instead and let the resolver pick the newest
compatible grpcio-tools. That both selects a generator the runtime accepts
and stops protogen from moving the runtime under the backend's other deps.
This is self-correcting, so the hardcoded GRPCIO_TOOLS_VERSION=1.78.0
escape hatch from #10944 is no longer needed and is removed.
2. The stubs were generated too early. Most branches of vllm/install.sh (and
vllm-omni) install vllm *after* installRequirements, and vllm re-resolves
the protobuf runtime as it lands. Stubs generated against the pre-vllm
runtime can end up newer than the runtime that finally ships, which is the
ROCm failure exactly. Regenerate once the dependency set is final.
3. rm -f of the .py sources left __pycache__ behind. CPython validates a .pyc
against source mtime and size, both of which can be unchanged across a
regeneration (the gencode triple is the same width whether it reads 7.35.0
or 6.33.5), so a stale backend_pb2.pyc could shadow the stub just written.
Also fail the build when the generated stub cannot be imported, so a
gencode/runtime mismatch surfaces at image build time instead of reaching
users as an opaque "grpc service not ready".
Verified by driving the real runProtogen through the ROCm install sequence in
a venv harness: before, gencode 7.35.0 against runtime 6.33.6 (reproducing the
reported error verbatim); after, gencode 6.33.5 against runtime 6.33.6 and the
stub imports cleanly.
Closes#10940Closes#10718
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8[1m] [Bash] [Edit]
* fix(backends): regenerate protobuf stubs in the other backends that install after installRequirements
Same defect as the vllm change: installRequirements generates the stubs at the
end of its own run, so any backend that installs further packages afterwards can
have the protobuf runtime moved out from under stubs that were already written.
The gencode stamped into backend_pb2.py then exceeds the runtime that ships and
the backend dies at model load with "grpc service not ready".
fish-speech already had this bug and worked around the symptom: it forces
protobuf>=5.29.0 after installRequirements precisely because "transitive deps
(wandb, tensorboard) may downgrade protobuf to 3.x but our generated
backend_pb2.py requires protobuf 5+". Regenerating after the pin addresses the
cause rather than propping up the runtime to match stale stubs.
Applied to the backends whose post-installRequirements step resolves a
dependency graph and can therefore move protobuf:
fish-speech -e . plus an explicit protobuf install
vibevoice pip install . (with deps)
llama-cpp-quantization gguf / GGUF_PIP_SPEC
trl gguf / GGUF_PIP_SPEC
Deliberately not applied to ace-step and chatterbox (both --no-deps, so the
dependency graph cannot change) or voxcpm (pins setuptools only). gguf does not
depend on protobuf today, but it resolves dependencies, and "this package does
not touch protobuf right now" is exactly the assumption that made the earlier
fix ineffective.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8[1m] [Bash] [Edit]
* fix(backends): resolve the protoc generator in a throwaway env so it cannot edit the backend's pinned deps
Installing grpcio-tools into the backend's own venv to generate the stubs also
drags its dependencies in: grpcio-tools 1.82.1 requires grpcio>=1.82.1, so a
backend that pinned grpcio==1.78.1 silently shipped 1.82.1 instead. Caught by
building the llama-cpp-quantization image and reading the versions back out of
the artifact:
before grpcio 1.82.1 (requirements.txt pins grpcio==1.78.1)
after grpcio 1.78.1 grpcio-tools absent from the venv entirely
Resolve the generator in a throwaway environment instead, still constrained to
the protobuf the backend ships so the gencode stays compatible. The backend's
dependency set is then exactly what its requirements files declared. protoc's
output is plain Python and carries no dependency on the interpreter that
produced it, so generating from a different env is safe; the import check still
runs under the backend's python, since that is the interpreter that has to load
the stubs at model load.
Verified on the rebuilt image: gencode 7.35.0, runtime protobuf 7.35.1, grpcio
back at its pinned 1.78.1, and the shipped stub imports cleanly against 7.35.1.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8[1m] [Bash] [Edit]
* fix(backends): bound the protoc generator by BOTH the installed grpcio and protobuf
The generated stubs impose two independent constraints, and every fix so far,
including the previous commit on this branch, satisfied one while violating the
other:
backend_pb2.py needs protobuf runtime >= gencode
backend_pb2_grpc.py needs installed grpcio >= grpcio-tools
Resolving the generator against protobuf alone picked grpcio-tools 1.82.1 for a
backend holding grpcio at 1.78.1, so the gencode was fine but the gRPC stub was
not:
RuntimeError: The grpc package installed is at version 1.78.1, but the
generated code in backend_pb2_grpc.py depends on grpcio>=1.82.1.
That is also why installing grpcio-tools into the backend venv appeared to work
earlier: it dragged grpcio up to match, which was load-bearing rather than the
regression it looked like. Isolating the generator removed the accidental fix
and exposed the missing constraint.
Bound grpcio-tools from both sides instead and let the resolver find the newest
version satisfying both. The protobuf ceiling makes it back off to an older
generator when the runtime trails, bounding the gencode; the grpcio ceiling
keeps the _grpc stub loadable. Resolved against the four real runtime pairs
observed in built images:
grpcio 1.78.1 / protobuf 7.35.1 -> grpcio-tools 1.78.0, gencode 6.31.1 OK
grpcio 1.78.0 / protobuf 6.33.6 -> grpcio-tools 1.78.0, gencode 6.31.1 OK
grpcio 1.82.1 / protobuf 6.33.6 -> grpcio-tools 1.81.1, gencode 6.33.5 OK
grpcio 1.82.1 / protobuf 7.35.1 -> grpcio-tools 1.82.1, gencode 7.35.0 OK
Also restore the import check to cover backend_pb2_grpc as well as backend_pb2.
Narrowing it to backend_pb2 is why the image build passed while CI failed: the
guard could not see the constraint that was actually broken.
Verified by running the CI sequence locally for llama-cpp-quantization, the
backend whose test failed:
make -C backend/python/llama-cpp-quantization -> exit 0
make -C backend/python/llama-cpp-quantization test -> exit 0, OK
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8[1m] [Bash] [Edit]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ⬆️ Update TheTom/llama-cpp-turboquant
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(turboquant): refresh HIP compatibility patch
The updated fork now carries its own HIP-safe peer-copy path, so the old hunk no longer applies. Keep only the event-creation compatibility change that the fork still needs.
Assisted-by: Codex:gpt-5 [Codex]
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
materializeLocked built a download task for every file in the resolved
snapshot unconditionally. A completed file is promoted from
.downloads/<hash> into snapshot/<path> and its blob deleted, so on any
re-entry (a controller pod roll, a resubmit, a crash) the new pass built a
task whose .downloads blob no longer existed, re-downloaded the whole file
from Hugging Face, and its AfterDownload even removed the already-complete
snapshot copy first. The only resume that worked was the downloader's
per-file .partial resume for a file caught mid-transfer; completed files
were never skipped.
Production consequence: installing longcat-video-avatar-1.5 (~35 GB after
allow_patterns) on a cluster whose controller rolls hourly (Flux image
automation) never converged across ~14 hours. Each roll restarted from the
first shard; the completed bytes on disk were repeatedly deleted and
re-fetched, and the artifact never promoted. curl of the same files from
inside the pod ran fine, proving the loss was the materializer re-fetching,
not the network.
Before building a task, check whether the file is already materialized and
verified in this staging tree's snapshot/ and, if so, keep it and count it
complete instead of downloading. "Materialized" means a regular file of the
expected size that passes the same verifyDownloadedFile check the download
path uses, so the kept manifest entry is byte-for-byte identical to a fresh
one and integrity is re-checked. The manifest requires a SHA-256 for every
file and non-LFS files carry none to borrow, so a hash is unavoidable for
the manifest anyway; a full re-hash of local disk is still orders of
magnitude cheaper than re-downloading, and the downloader re-verifies any
file it does fetch. Manifest entries are now written at their snapshot index
rather than appended in completion order, so a mix of skipped and downloaded
files keeps the resolved order that committedResult and staging read. The
unconditional root.Remove(destination) now runs only on the fresh-download
path; a kept file survives. Skips are logged at INFO with count and bytes so
an operator can see resume working.
This is the resume-side counterpart to the sibling defects on this path:
read/write error conflation and transient retry (#10985), hash-verify
progress accounting and silent success on an expired deadline (#11026), and
the response-header hang (#11053). The download machinery resumed a single
in-flight file; the materializer above it still threw away every completed
file on restart. It also makes orphan-partial adoption worth its cost:
an adopted tree's completed files were re-downloaded anyway until now.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(nodes): never schedule a model onto a node that cannot store it
A worker whose models filesystem was 100% full kept advertising
`status: healthy`, stayed a scheduling candidate, was picked to host a
70 GB video model, accepted the staging request, transferred ~17 GB and
only then failed:
staging .../whisper-large-v3/model.fp32-00001-of-00002.safetensors:
upload to node b7bacbf4-... failed with status 500:
writing file: /models/longcat-video-avatar-1.5/...: no space left on device
The node was at 937G/937G/0-avail. Total elapsed before the truth
surfaced: 16 minutes, for a decision that could never have succeeded.
The worker health signal only ever proved liveness. `/readyz`
(WorkerReadiness/NATSReadiness) checks the NATS link; `status: healthy`
in the registry is driven by heartbeat recency. Node capacity carried
VRAM and RAM but no disk figure at all, and the router compared model
size against VRAM only — nothing anywhere looked at free space on the
filesystem that staging actually writes to.
Report it, then use it:
- Workers now measure the filesystem backing their MODELS directory
(not `/` -- staged weights land in the models path, and that mount is
very often separate) and report `total_disk`/`available_disk` on
registration and on every heartbeat. Free disk moves faster than VRAM
under staging traffic, so the per-heartbeat refresh matters.
- The SmartRouter drops nodes that cannot store the model before it
picks one. The requirement comes from `modelPayloadBytes` -- the same
local paths `stageModelFiles` uploads, already computed for the
size-derived load budget -- plus a 5% / 1 GiB margin, rather than a
fixed percentage of the node's disk. A percentage threshold would take
a small-but-usable node out of rotation for models it could hold, and
on a homogeneous cluster would strand every node at once.
- When no node fits, scheduling fails immediately with an error naming
the requirement and each node's free space, instead of picking one and
discovering it mid-transfer.
Two deliberate non-changes. Low disk does not mark a node `unhealthy`:
the check is per model, so a node too small for one model stays a valid
target for smaller ones. And `total_disk == 0` means "does not report
disk" (pre-upgrade worker, or a failed stat), not "full" -- such nodes
pass through untouched so a rolling upgrade never empties the candidate
pool. A genuinely full node is distinguishable: non-zero total, zero
available. Registry read failures are logged and scheduling continues
unfiltered; a database hiccup must not wedge a cluster.
Free space is surfaced on the node detail page next to VRAM, since the
incident's signature was a node that looked entirely healthy.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
* feat(nodes): make the disk-headroom check operator-controllable
The admission check added in the previous commit had no off switch. A
scheduler-side veto with no escape hatch is a liability: our size
estimate can be wrong (deduplicating or compressing filesystems, a
backend that fetches its own weights rather than loading the staged
copy), and an operator who hits that has no way out but a downgrade.
Add one knob with two surfaces that share a single source of truth:
- `--distributed-disk-headroom-check` / `LOCALAI_DISTRIBUTED_DISK_HEADROOM_CHECK`
(default true), following the `--distributed-prefix-cache` pattern for
a default-on distributed feature.
- `distributed_disk_headroom_check` in the runtime-settings registry, so
it can be flipped without a restart from `POST /api/settings` and from
Settings -> Distributed in the WebUI.
Both write `DistributedConfig.DiskHeadroomDisabled`, and the SmartRouter
reads that member LIVE on every scheduling decision through a closure
over the application config rather than a value snapshotted at
construction. Env/CLI sets the boot value, the runtime setting overrides
it live, last write wins, and there is exactly one member to read.
Snapshotting would have made the runtime toggle a no-op until restart.
Disabled means WARN, not SKIP. Selection goes back to ignoring free disk
-- byte for byte the pre-check behaviour -- but the check still runs, and
when it would have rejected every node it says so, naming the knob that
suppressed it. Going quiet when switched off would reproduce the exact
condition that made the original incident expensive: a cluster doing
something that could not work and saying nothing. Disabling is also
logged once at startup. Warning only on the total-rejection case keeps
it actionable rather than chatty on a heterogeneous cluster.
Also fixes a false positive in the check itself: shared-models mode
(LOCALAI_DISTRIBUTED_SHARED_MODELS) stages nothing at all -- every node
already mounts this models directory at this path -- so demanding the
full checkpoint size of free space per node would have rejected a
cluster that needs no new bytes. The check is skipped there entirely.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Two lifecycle defects observed on a 2-replica distributed cluster.
The install endpoints mint a job UUID, hand the operation to an unbuffered
channel, and answer HTTP 200 immediately. The gallery worker is a single
goroutine that processes operations serially, and the first status write
happens inside modelHandler/backendHandler — i.e. only once the worker
actually starts the work. An operation queued behind a running install
therefore had no status at all: GET /models/jobs/<uuid> answered
"could not find any status for ID" and GET /models/jobs did not list it,
so the endpoint reported success for work nothing could observe. On the
paths that sent directly rather than from a goroutine, the same unbuffered
channel blocked the HTTP handler for the whole duration of the in-flight
install, which is how a replica came to accept no /models/apply at all
while /readyz stayed green.
Admission now goes through EnqueueModelOp/EnqueueBackendOp, which publish a
"queued" status before handing the operation over, so a job ID is queryable
from the instant it is handed out. Delivery selects on the operation's
context, so cancelling a still-queued operation releases the delivery
goroutine instead of stranding it on a send that will never be received,
and an operation the worker never accepts becomes a terminal failure rather
than a silent leak.
The worker also had no panic containment. A panic in any handler propagated
out of the single consumer goroutine and killed the process, taking every
queued operation with it; it is now contained to the operation that caused
it. The two ignored galleryStore.Create errors are logged, and the model and
backend delete endpoints now run under the same ID they hand back — they
previously ran under an empty ID and returned a status URL for a job that
could never have a status.
Second, an operation orphaned by a controller replaced mid-download kept
reporting phase=downloading, processed=false, error=none while nothing was
downloading. The PostgreSQL side does recover on its own (FindDuplicate
ignores rows untouched for 30 minutes and CleanStale marks them failed), but
the reaper only ever corrected the database. The in-memory statuses map that
GET /models/jobs/<id> and /api/operations actually read was never corrected,
so every replica kept serving the frozen tick indefinitely. ReapStaleOperations
now reconciles the in-memory copy with the reap.
Note that operation ownership is still not tracked: gallery_operations has a
FrontendID column that nothing writes, so a live operation and one whose owner
died are distinguished only by a 30-minute staleness timeout. Narrowing that
window needs a lease/heartbeat mechanism and is out of scope here.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Three measured HTTP-layer regressions on a live deployment, fixed together
because they all shape the bytes on the wire.
1. No compression. The server sent no Content-Encoding regardless of what
the client asked for, confirmed with curl straight at 127.0.0.1:8080 so
it was not an ingress artefact. Adds gzip middleware, on by default and
configurable via LOCALAI_DISABLE_HTTP_COMPRESSION and
LOCALAI_HTTP_COMPRESSION_MIN_LENGTH (default 1024 bytes so tiny bodies
are not wastefully wrapped). Streaming routes are skipped explicitly:
an SSE Accept header, a WebSocket upgrade, and the completion / SSE /
log-tail path prefixes, because whether a completion request streams is
decided by the request body, which the middleware runs too early to see.
Already-compressed formats (woff2, png, mp4, ...) are skipped too; gzip
made those marginally larger. Measured over the embedded React build:
JS+CSS 2815 KB raw to 808 KB gzipped (3.48x).
2. No cache headers on content-hashed assets. Vite hashes the filenames,
so a given /assets/ URL can never change content, yet they shipped with
no Cache-Control, ETag or Last-Modified, and the browser re-fetched the
whole bundle on every navigation with no conditional request available.
/assets/* now carries public, max-age=31536000, immutable. index.html
stays no-cache so a deploy is picked up, and the unhashed locale JSONs
get a short TTL rather than the immutable one.
3. Unbounded trace endpoints. /api/traces returned 21,033,606 bytes in
4.65s and /api/backend-traces 3,471,682 bytes in 1.50s, and the admin
UI polls both every few seconds. The ring buffer holds up to 1024
entries, each embedding full input_text payloads. Both list endpoints
now take limit / offset / full, default to 50 entries, and strip the
heavy fields (request and response bodies plus headers for API traces,
body and data for backend traces) unless full=true. Every trace gets a
process-lifetime ID and GET /api/traces/{id} and
/api/backend-traces/{id} serve the full record, which is what the UI
fetches when a row is expanded. The list body stays a JSON array;
paging metadata rides in X-Total-Count, X-Trace-Offset and
X-Trace-Limit. Reproducing the live shape in a test, the polled payload
goes from 21,131,097 bytes to 7,201 bytes.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
build-test.yaml, yaml-check.yml and secscan.yaml had no concurrency block at
all, so every push to a PR stacked another full batch instead of superseding
the previous one. build-test carries a macos-latest job, the scarcest runner
class we use, and secscan fires on every push to every branch because its
`push:` trigger is unfiltered.
build-test and yaml-check use the same group idiom as lint.yml and the other
eleven workflows that already have one: key on the PR number so pushes to a PR
share a group, and cancel only on pull_request. On a master push the key falls
back to github.sha and cancel-in-progress is false, so master runs never cancel
each other -- that is deliberate, since backend.yml builds only the backends a
given commit touched and superseding would drop those builds.
secscan needs a different key: it has no pull_request trigger, so the shared
idiom would fall back to the unique-per-commit sha and dedup nothing. It groups
on github.ref instead, and excludes master from cancellation for the same
per-commit reason. Cancelling a superseded feature-branch scan is safe because
the only output is a SARIF upload and code scanning keeps the latest result
per ref.
No behaviour change on master for any of the three.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
A gallery model install hung for 94 minutes with zero bytes transferred, no
error, no retry and no abort, leaving a partial tree frozen at 18G. The last
log line was the download starting, then silence:
14:06:19 INFO Downloading url=".../LongCat-Video-Avatar-1.5/resolve/<rev>/base_model/diffusion_pytorch_model-000..."
The retry machinery from #10985 was working (two retries fired at 14:05:01 and
14:06:14); the third attempt simply never returned. The install never
completed, the model config was never written, and nothing surfaced the
failure.
The stall watchdog added earlier wraps the response *body*, so it only starts
guarding once downloadClient.Do() has returned. The transport had no
ResponseHeaderTimeout, so a peer that completes the dial and TLS handshake,
reads the request, and then never sends a status line parks Do() for the
process lifetime. IdleConnTimeout governs pooled idle connections, not an
in-flight request. Both the body request and the HEAD that probes for Range
support were unguarded.
Bound the header wait at the transport, not the client: a client-level Timeout
would also bound the body and truncate multi-tens-of-GB downloads. The knob is
opt-in (WithResponseHeaderTimeout) rather than a default in HardenedTransport,
because a streaming endpoint may legitimately withhold headers until it has
something to say, and capping that would break the streaming clients that share
this constructor.
Also fix a classification trap this exposed: net/http reports a
ResponseHeaderTimeout as an error satisfying errors.Is(err,
context.DeadlineExceeded), which IsRetryable read as "the caller gave up" and
refused to retry. An explicit transient marking now outranks the cancellation
sentinels; a caller who genuinely gave up is still caught by the ctx.Err()
check. The resume probe's error is likewise marked transient, so a momentarily
wedged origin no longer turns a resumable download into a hard install failure.
Third defect found in this download path, after #10985 (read vs write errors
conflated) and #11026 (hash verification emitted no progress and an expired
deadline returned success).
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
A backend reinstall could poison every subsequent model load on a worker
node until the worker process was restarted.
gallery.InstallBackend (and gallery.UpgradeBackend) replace a backend by
renaming the live directory to `<name>.install-backup`, moving the staged
directory into place, then deleting the backup. A working directory
follows the inode across a rename, so a backend process that outlives
that swap ends up with a deleted inode as its CWD, and every getcwd(2)
in it fails with ENOENT.
Observed on a Jetson Thor worker in distributed mode after two
successive reinstalls of cuda13-nvidia-l4t-arm64-longcat-video-development.
A later model load failed with:
rpc error: code = Internal desc = failed to load LongCat model: [Errno 2] No such file or directory
The backend's own traceback shows it dying while importing torch, before
touching any model file:
backend.py line 142 in LoadModel
backend.py line 300 in _import_torch
torch/_library/custom_ops.py lib._register_fake(...)
torch/library.py:183 caller_module = inspect.getmodule(frame)
inspect.py:1013 f = getabsfile(module)
inspect.py:983 return os.path.normcase(os.path.abspath(_filename))
<frozen posixpath>, line 415, in abspath
FileNotFoundError: [Errno 2] No such file or directory
os.path.abspath calls os.getcwd() for a relative path. Scanning /proc
inside the worker container found the deleted CWD directly:
pid 23467 CWD DELETED: /backends/cuda13-nvidia-l4t-arm64-longcat-video-development.install-backup (deleted)
Restarting the worker container cleared it (dead CWD count 1 -> 0).
Python backends import torch lazily inside LoadModel, so such a survivor
still answers HealthCheck and keeps its gRPC port. It looks healthy and
only detonates when a model is actually loaded through it.
The install paths already stop running processes before replacing the
directory (installBackend's force branch, upgradeBackend, backend.delete),
but they resolve them by name. That bookkeeping reaps nothing whenever
the recorded name no longer resolves into the install's identity set: a
legacy entry with an empty backendName, backendIdentity degraded to
name-only matching after a ListSystemBackends failure, or an earlier
reinstall having already rewritten the metadata.json that carries the
alias. Any of those leaves a live process whose directory is about to be
unlinked, and nothing downstream notices, because the reuse gate checks
liveness and name -- and the name is precisely what does not change
across a reinstall.
Record the directory each supervised process runs out of, plus that
directory's identity at spawn time, and compare with os.SameFile before
reusing the process. This needs none of the name bookkeeping to have
been correct. Both reuse gates are covered: processMatchesBackend (the
install fast path) and startBackend's own already-running branch, which
now force-stops such a survivor so the fresh spawn chdirs into the newly
installed directory. Processes with no recorded directory are accepted,
so a rollout does not restart every running backend once.
This matters more with #11024 pending: making GPU backends visible to
the upgrade checker will have AutoUpgradeBackends fan upgrades out to
worker nodes at scale, and every one of those is a reinstall. Left as
is, a rare manual-upgrade footgun becomes a fleet-wide one.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The num_ctx clamping specs added in #11032 construct their fixture with
`config.ModelConfig{ContextSize: &existing}`, but ContextSize is not a
direct field of ModelConfig: it belongs to LLMConfig, which ModelConfig
embeds inline. Go allows reading a promoted field but not setting one in
a composite literal, so the test file has never compiled:
helpers_internal_test.go:33:31: unknown field ContextSize in struct
literal of type "github.com/mudler/LocalAI/core/config".ModelConfig
This broke `make lint` on master from bf19758e0 onward, and because the
typecheck failure takes down the whole package it also reds tests-linux
and tests-apple on every PR branched after that commit.
Use the same literal form the rest of the tree already uses for this
field (see core/backend/options_internal_test.go).
Worth noting the specs were not merely uncompiled but inert: #11032 is a
DoS fix (an unauthenticated client raising the context ceiling drives
KV-cache allocation), and its regression guard was never actually
running. Verified the restored specs are functional by stubbing out the
ceiling clamp, which fails the "does not let an oversized num_ctx raise
an existing context ceiling" spec as intended.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(backend/python): don't await sync servicer behaviors in AsyncModelIdentityInterceptor
The model-identity interceptor (added for #10952) is installed on every Python
backend's gRPC server. Its grpc.aio variant invokes the wrapped servicer
behavior itself and awaits the result unconditionally:
result = await original(request, context) # LoadModel
return await original_unary(request, context) # guarded RPCs
async for response in original_stream(request, context): # streaming
But a backend's servicer methods may be plain sync functions. The transformers
backend, for one, defines `def LoadModel` and `def Embedding` (not `async def`).
grpc.aio's own dispatch adapts both shapes, but this interceptor calls the
behavior directly and bypasses that. For a sync method `original(...)` returns a
message object, not a coroutine, so the `await` raises:
TypeError: object Result can't be used in 'await' expression
The model loads, then the LoadModel RPC dies on return; the guarded sync
Embedding fails the same way. It happens on every platform, not just one backend
build. CI never caught it because AsyncModelIdentityInterceptor had no
behavioral test -- only an "is it installed" assertion.
Fix: await only when the behavior actually returned an awaitable
(inspect.isawaitable), mirroring grpc.aio's own sync/async adaptation. The
streaming guard iterates a sync generator with `for` and an async one with
`async for`.
Adds async-path coverage to model_identity_test.py exercising both sync and
async LoadModel / guarded-unary / streaming behaviors. The sync cases fail on
the current code with the TypeError above and pass with this fix.
Signed-off-by: stefanwalcz <stefan.walcz@walcz.de>
* fix(backend/python): dispatch sync servicer behaviors off the event loop
Addresses review feedback: awaiting only awaitable results removed the
TypeError, but still ran a sync LoadModel/Embedding -- and stepped a sync stream
via next() -- on the asyncio event-loop thread, so a slow load/inference/stream
could freeze all aio RPC handling.
Route sync behavior through run_in_executor (a worker thread) while awaiting
native async behavior directly. A callable wrapper that returns an awaitable is
run in the thread and its awaitable awaited back on the loop. Sync streaming
pulls each item via the executor with a done sentinel, so StopIteration cannot
escape through a Future.
Adds regression tests that record the handler thread id and assert it differs
from the event-loop thread, for LoadModel, a guarded unary RPC and a sync stream.
Signed-off-by: stefanwalcz <stefan.walcz@walcz.de>
---------
Signed-off-by: stefanwalcz <stefan.walcz@walcz.de>
Establishing an MCP session held the session-cache mutex across
client.Connect with no per-connect timeout. An unreachable remote server
(bounded only by the 360s httpClient timeout) or a stdio server whose
initialize handshake never completes therefore blocked the caller and,
because the mutex was held, every other MCP request for that model too.
In the UI this shows up as the MCP "Servers" widget spinning forever.
It is most visible for cloud-proxy models: their chat path bails out
before the MCP tool block, so it never warms the session cache in the
background. The widget's /v1/mcp/servers/<model> call is then the first
and only code that connects synchronously, in the request foreground.
The session, once established, stays bound to the shared context (it is
cancelled later via the cached cancel func on eviction/shutdown), so we
can't pass a WithTimeout context to Connect: firing the timeout would tear
a healthy session down, and cancelling the shared context would also kill
sibling servers that already connected. Instead connectMCP runs Connect on
the shared context in a goroutine and stops waiting after the discovery
timeout, returning an error for that one server without disturbing the
others. A stalled goroutine is reaped when the model's sessions are
cancelled. Applied to both SessionsFromMCPConfig and
NamedSessionsFromMCPConfig.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The gRPC deadline for the remote LoadModel call was a fixed 5m. It starts
only after the backend install and file staging have completed, so it
covers the worker's checkpoint read and pipeline init alone - work whose
duration is proportional to the bytes on disk. A fixed value is therefore
a model-size cliff, not a timeout.
Measured in production: a 70 GB video checkpoint (longcat-video-avatar-1.5)
on an NVIDIA Jetson Thor worker failed reproducibly with
"rpc error: code = DeadlineExceeded" after 953.5s of wall clock. Backend
install plus staging consumed ~11m, then LoadModel got its 5m and expired.
The load never had a chance, and the operator saw only a generic
DeadlineExceeded with no hint that a config value was the cause.
Raising the constant does not fix this. It moves the cliff to the next
larger model - the cluster has to support 600 GB checkpoints - and it makes
a genuinely wedged SMALL model hang for the whole inflated duration before
anyone notices, which is a real regression in failure latency.
So derive the budget from the checkpoint size instead:
budget = 5m + 20s/GiB, capped at 6h
2 GiB -> 5m40s, 70 GiB -> 28m20s, 600 GiB -> 3h25m. The per-GiB rate is
deliberately pessimistic (~54 MB/s of weight read) because the errors are
not symmetric: too long costs only failure latency on a load that was going
to fail anyway, too short is a guaranteed false failure on a healthy load.
The size is measured from the frontend's local model files, over the same
path set stageModelFiles uploads. When those files are not present locally -
a backend handed a bare HuggingFace repo id fetches its own weights on the
worker - there is nothing to measure and the budget stays at today's 5m.
An explicit LOCALAI_NATS_MODEL_LOAD_TIMEOUT still wins outright, in both
directions: a shorter override is honoured, so an operator who wants fast
failure is not silently extended by the heuristic.
The cold-load hold needed widening to match. It extends on staging progress,
but LoadModel reports none, so once the last byte lands the hold expires a
stall window later and would cancel a load still well inside its own budget.
scheduleAndLoad now extends the hold by the load budget plus the staging
margin as it enters the load phase; ModelLoadCeilingFor stays the hold's
starting budget rather than its maximum.
Finally, a deadline that does expire now names the budget, the checkpoint
size it was derived from, and the knob that overrides it, instead of
surfacing a bare "context deadline exceeded".
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(completions): reject empty PromptStrings in streaming to avoid index-out-of-range panic
The streaming branch of CompletionEndpoint only guarded len(config.PromptStrings) > 1
before unconditionally reading config.PromptStrings[0]. A completion request whose
prompt field is an empty array, an array of non-strings, or omitted leaves
PromptStrings with length 0, so PromptStrings[0] panics with index out of range and
crashes the handler goroutine.
Guard for exactly one prompt string instead, returning a clean error for the 0-length
case as well as the pre-existing multi-prompt case.
Signed-off-by: Tai An <antai12232931@outlook.com>
* fix(completions): return 400 for malformed streaming prompt
Reject streaming completion requests whose prompt does not resolve to
exactly one string (omitted prompt, empty array, or a multi-element
array) with an HTTP 400 before writing any SSE headers, instead of
returning a plain error that Echo surfaces as a 500. Extract the guard
into validateStreamingPromptStrings and cover the three reported
payloads with a regression test.
Fixes#11021
Signed-off-by: Tai An <antai12232931@outlook.com>
---------
Signed-off-by: Tai An <antai12232931@outlook.com>
* fix(ollama): cap num_ctx so it cannot wrap negative when cast to int32
applyOllamaOptions copied a client-supplied options.num_ctx straight into
cfg.ContextSize with only a > 0 check. That value is later cast to int32
before it reaches the backend (core/backend/options.go), so a num_ctx
above math.MaxInt32 silently wrapped into a negative context size that
was then sent to the LoadModel gRPC call. Both /api/chat and /api/generate
share applyOllamaOptions, so both endpoints were affected.
Cap num_ctx at math.MaxInt32 so the later cast stays positive, and add
internal regression coverage for the overflow, in-range, and unset cases.
num_ctx remains an intentional user override, so this does not re-impose
the hardware-aware auto context clamp; that policy choice is left to
maintainers.
Fixes#11022
Signed-off-by: Tai An <antai12232931@outlook.com>
* fix(ollama): clamp num_ctx to model context ceiling, not just int32
Per review on #11032: capping only at math.MaxInt32 still let an
unauthenticated request replace the hardware/model-derived context
limit with ~2.1B tokens, so a real backend could attempt a catastrophic
KV-cache allocation. Treat any existing positive cfg.ContextSize as the
server ceiling and clamp num_ctx down to it (smaller values still
honored), while retaining the int32-safe bound when no smaller ceiling
exists. Shared by /api/chat and /api/generate via applyOllamaOptions.
Add regression coverage proving num_ctx=2,000,000,000 cannot replace an
existing 4096/8192 ceiling.
Signed-off-by: Tai An <antai12232931@outlook.com>
---------
Signed-off-by: Tai An <antai12232931@outlook.com>
The "Bump Backend dependencies" workflow has failed every night for the
last two weeks. #11012 fixed one cause (repos renamed under localai-org);
what is left is rate limiting.
bump_deps.sh fans out to ~25 parallel matrix jobs that each query
api.github.com anonymously. Anonymous calls are capped at 60/hour per
source IP and GitHub-hosted runners egress through shared NAT addresses,
so a random handful of jobs draw HTTP 403 and die at curl exit 22 with an
empty response. Last night that hit ggml-org/whisper.cpp and
mudler/depth-anything.cpp -- both public and resolvable, nothing wrong
with either pin.
Route every bump script through a shared gh_curl helper that sends
GITHUB_TOKEN when present (1000/hour instead of 60) and retries transient
failures, including the 403s that plain --retry ignores. The helper
suppresses xtrace around the call so the Authorization header cannot land
in a public job log.
bump_docs.sh had a sharper version of the same bug: it piped an
unchecked response into `jq -r .tag_name`, so a throttled request
resolved to the string "null" and would have been published as the docs
version. It now refuses to write anything it cannot resolve to a tag.
Verified locally by running all four scripts end to end against their
real upstreams: correct SHAs/tags written, exit 0; a nonexistent repo now
fails with a named diagnostic instead of a bare exit 22 and leaves the
pinned file untouched; the token is absent from the xtrace output; and
the scripts still work unauthenticated.
Assisted-by: Claude:opus-4.8 [Claude Code]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(gallery): repoint qwen3-4b/qwen3.5-9b dflash drafters at post-rename GGUFs
The drafters both entries referenced were converted from the pre-merge DFlash
PR branch and carry dflash.target_layer_ids. llama.cpp reads dflash.target_layers
and refuses the load. The stored values are offset by +1 relative to the HF-side
field, so the files cannot be repaired by renaming the key and must be replaced.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ci): add apexentries HuggingFace client
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci(apexentries): build the HF client via pkg/httpclient
The apexentries HuggingFace client was constructed as a raw
&http.Client{Timeout: 60s}. The repo convention (documented in
.golangci.yml, which cannot express this as a forbidigo pattern) is that
all outbound HTTP goes through pkg/httpclient, which refuses redirects by
default and sets a TLS 1.2 floor. The std client follows redirects and
forwards custom credential headers to the redirect target on a cross-host
hop (GHSA-3mj3-57v2-4636). Only a User-Agent is sent today, but this
calls an external API and an HF_TOKEN header added later would leak.
Switch to httpclient.NewWithTimeout, preserving the 60 second timeout.
No behaviour change for the current header set.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ci): discover APEX tiers by filename suffix
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ci): resolve unsloth counterparts and sharded quants
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ci): render APEX child entries with the dflash/mtp tag rule
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci(apexentries): set backend, known_usecases and cross-repo drafters
RenderChild left three gaps against the hand-written gallery entries.
The generated entries reference gallery/virtual.yaml, which supplies no
backend, so every generated entry named no engine at all. All comparable
hand-written entries set backend: llama-cpp in overrides; do the same.
Set known_usecases to [chat] alongside it: LocalAI falls back to the
backend defaults when it is absent, so this is convention rather than
breakage, but generated entries should not read differently from their
neighbours.
The drafter was also assumed to live in the repo publishing the weights.
Speculative pairings routinely cross repos, and a drafter URI built from
the weights repo 404s at install time. Add ChildInput.DraftRepo, used for
both the drafter URI and its local path, falling back to Repo when empty
so pairings that do ship the drafter alongside the weights are unchanged.
The dflash/mtp tagging rule is untouched: the tag still follows SpecType
and nothing else.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ci): dedupe generated entries against the existing gallery
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* apexentries: canonicalize HF URIs and dedup the generated batch
Merge exists to stop a second gallery entry being added for weights the
gallery already ships, but two gaps let duplicates through on a bulk run.
The URI key was compared as an exact string while render.go only ever emits
https://huggingface.co/{repo}/resolve/main/{file} and the gallery records
1038 of its URIs in huggingface://{repo}/{file} shorthand. A generated
unsloth rung whose weights are already shipped in shorthand was therefore
not recognised. canonicalURI reduces both spellings to one key and is
applied on both sides, taking care that the repo is exactly the first two
path segments so sharded quants in a subdirectory still match. A URI in
neither form is returned untouched so other hosts dedup on their literal
string.
Merge also never accounted for entries it had just accepted, so two
generated entries sharing a name or a primary URI both landed in add.
Several APEX repos share one base model and resolve to the same unsloth
counterpart, so the identical rungs are generated twice under the same
name. Batch state is tracked locally rather than written back into the
caller's ExistingIndex, which a caller may reasonably reuse.
Name is still checked before URI: a name collision must block the add
regardless of the weights.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ci): verify variant and tagging invariants in the gallery index
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ci): scope the apex-entries verifier to what it can actually judge
The verifier reported 60 problems against the real gallery, 57 of which were
llama.cpp assumptions meeting entries from other backends. A gate that is wrong
57 times out of 60 cannot gate anything.
- The weight-count check catches a quant label collision in llama-cpp quant
discovery, so it now runs only for overrides.backend: llama-cpp. Entries with
no declared backend are skipped because their weights are declared in the
referenced url: template, which the verifier never reads.
- The dflash/mtp tag check now implements the per-backend table in
.agents/adding-gallery-models.md instead of assuming llama.cpp's spec_type:
vocabulary. ds4 declares mtp_path:/mtp_draft:; sglang declares
speculative_algorithm: in a file this verifier cannot follow, so sglang
entries are not judged in either direction. The check stays bidirectional
within the backends it does judge.
- sha256 is now required on .gguf files only, since every non-GGUF asset in the
index belongs to a hand-curated entry outside this generator's scope.
Against the current gallery this leaves exactly the three genuine problems:
two entries setting spec_type:draft-mtp without the mtp tag, and one entry
whose overrides.mmproj names a file it does not download.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci(apexentries): anchor quant matching and invert the sha256 rule
UnaccountedQuants matched files to wanted quants with strings.Contains, which
reproduces the substring collision it was written to warn about: Q8_0 is a
substring of UD-Q8_0, so a repo publishing only UD-Q8_0 was reported as
publishing an unbuilt Q8_0. Subdirectory-sharded UD quants are the normal
unsloth layout for large repos, so this fired on realistic input.
Match on the quant label as an anchored token instead, the way
DiscoverUnslothQuants does, so the diagnostic and the discovery it audits
cannot disagree about what a file is. Root-level shards, the layout the
diagnostic mainly exists to catch, stay detected.
The sha256 requirement was scoped to .gguf, which exempted seven real model
weights: wan_2.1_vae.safetensors and clip_vision_h.safetensors across the
wan-2.1-*-ggml entries, both load-bearing weights named by gallery/wan-ggml.yaml.
Invert the rule so a checksum is required on everything except metadata
extensions, which keeps a future weight format covered by default rather than
silently exempt.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ci): wire the apexentries command
Adds the generation path to the apexentries command: list the mudler APEX
repos, discover each one's quality ladder and its unsloth counterpart's quant
rungs from the filenames actually published, render a child entry per build
plus a family parent carrying the variants list, dedup against the gallery,
and write the additions to -out or append them with -apply.
Discovery shortfalls are reported at discovery time rather than left to the
verifier. A quant or a tier that discovery drops leaves no trace in a finished
gallery file, and because an empty imatrix ladder falls back to the plain one,
a repo whose imatrix filenames all fail to match downgrades the whole family
silently instead of erroring.
Merge's single reused map is split into two reported categories. A URI match
means the gallery already ships exactly these weights and referencing the
existing entry is correct; a name collision means an unrelated entry owns the
name and referencing it would substitute a different build.
Multimodal children now declare known_usecases [chat, vision]. An explicit
known_usecases suppresses the backend-default fallback, so a chat-only entry
carrying an mmproj never matches the vision or multimodal gallery filters.
.github/ci is invisible to go list ./..., so a workflow names both generator
packages explicitly and their specs finally run on pull requests.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ci): gather APEX builds under the base model entry
The hub for a family is the BASE model entry, never a generated *-apex
parent. Somebody looking for qwen3.6-35b-a3b has to find every build of
those weights under that one name, so a competing qwen3.6-35b-a3b-apex
hub would split the family and leave half of it invisible.
When the gallery already ships the base entry, a variants block is
spliced into it textually, leaving its description, icon, tags,
overrides and files untouched. Only a family whose base model the
gallery does not ship gets a new hub, still named for the base model and
carrying one of the discovered builds as its own payload so it declares
a backend the verifier can judge.
The line editing is factored into .github/ci/galleryedit, shared with
the variantproposals job, so the two cannot drift apart on where a
variants block belongs.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(apexentries): treat an unreadable optional counterpart repo as absent
HuggingFace answers 401 Unauthorized, not 404, for a repository that does
not exist when the request carries no credentials. FetchRepoFiles treated
only 404 as absence, so probing for the OPTIONAL unsloth counterpart hard
failed for every family that legitimately has none: 27 of the 45 APEX
families are community merges that will never have an unsloth build, and a
full run failed all of them.
Split the fetch so the two call sites can apply different policies to the
same response. The APEX repo itself stays strict: a 401 or 403 on a repo
the run requires is a real failure and still errors. Only the optional
probe tolerates it, because without a token 401 cannot be told apart from
absence.
That collapse is lossy in one direction, since a private or gated repo also
answers 401, so the skipped candidates are named in the run summary
alongside the other silent-shortfall counters instead of being dropped in
silence.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci(apexentries): report full-precision sources as a known exclusion
The 45 APEX repos publish their unquantized F16 sources next to the
imatrix ladder, flat or sharded. Discovery correctly emits nothing for
them, but they were landing in the unclassified total, leaving a
permanent baseline of 24 benign lines on every run.
That baseline is what the unclassified check exists to prevent: a
standing count of known-benign files is exactly what hides the one file
that ever genuinely matters. Count full-precision sources separately and
give them their own summary line, so unclassified returns to 0 and stays
loud when something really is an unknown shape.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(apexentries): namespace local paths by owner and enable MTP builds
localPath namespaced downloads by the repo basename alone, so two repos
publishing the same filename under different owners collapsed to one local
path. LiquidAI/LFM2.5-8B-A1B-GGUF and unsloth/LFM2.5-8B-A1B-GGUF collided that
way, and both were offered from the same hub, so installing the second either
overwrote the first model's weights or was skipped as already present while
recording a sha256 that did not match the bytes on disk. The owner is now its
own path segment: owner/repo is globally unique on HuggingFace and neither half
can contain a separator, so uniqueness holds by construction.
Verify gains a check for the whole class, that no local filename may map to two
different upstream URIs. It surfaces seven pre-existing collisions in the
gallery, which are left alone here.
Entries built from the *-APEX-MTP-GGUF repos now configure MTP rather than
shipping the heads inert, matching the pattern the hand-written MTP entries
already use: spec_type:draft-mtp with spec_n_max and spec_p_min, tagged mtp, and
no draft_model because the heads live in the weights. RenderChild no longer
requires a separate drafter file before it will configure a spec type, while the
cross-repo drafter path is unchanged.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): add the APEX GGUF families as variant ladders
Adds the imatrix quality ladder from each mudler/*-APEX-GGUF repo, a fixed
subset of unsloth quant rungs where a counterpart repo exists, and the MTP
builds, then attaches them to the base model entry so one entry offers every
build of the same weights and LocalAI picks the one that fits the hardware.
Ten existing base model entries gain a variants list; twenty-seven families that
the gallery had no base entry for get one. Builds are discovered from the
filenames each repo actually publishes rather than derived from its name, since
six repos ship a stem that differs from their repo name. Every file carries a
sha256 taken from the HuggingFace API.
Assisted-by: Claude Opus 4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Testing the progress-based cold-load deadline on the live cluster surfaced a
false positive. The stall window observed UPLOAD bytes only, but the staging
path has a phase that does real work while moving zero upload bytes: the
resumable-upload verify phase.
When a shard is already present on the worker from an earlier attempt, the
frontend HEADs it, hashes the local copy to confirm it matches, and skips the
transfer. Staging a 70 GB model with 56 GB already staged:
17:27:34 INFO Upload skipped (file already exists with matching hash) ...
17:28:20 INFO Upload skipped (file already exists with matching hash) ...
17:29:07 INFO Upload skipped (file already exists with matching hash) ...
... six-plus consecutive minutes, no bytes uploaded at all
~45s per skipped ~4 GB shard. That is correct and desirable - it is what makes
resume work - but it was indistinguishable from a stall. At 45s per shard it
sits inside the 5m window, so the run in flight was fine; the problem is the
600 GB scale this machinery exists to enable, where one shard can plausibly hash
for longer than the window. The guard would then fire during verification of a
transfer that is working perfectly.
Verified mechanism: probeExisting() HEADs the worker and then calls
downloader.CalculateSHA(). The staging progress callback is only consulted
inside doUpload(), which the skip path never reaches, so observeLoadProgress was
called zero times for the whole verify phase.
Verification exposed a second, worse bug in the same path: CalculateSHA consults
no context at all. An expired cold load kept hashing to completion, compared the
hashes, and returned success - reporting a file as staged on a dead load. The
failure only surfaced on the NEXT file, whose HEAD died immediately. That is
exactly the shape of the red test here, which fails on shard 3.
Fix: hash in 1 MiB chunks via hashFileWithActivity(), ticking the cold-load
deadline per chunk and checking ctx per chunk. A successful HEAD also counts,
since a 200 with a content hash proves the worker is serving right now.
Counting hash progress does not make a dead transfer look alive: hashing is
bounded, terminating work proportional to file size, in probeExisting it runs
only after a HEAD proved the worker was up, and the 24h absolute cap still
bounds the whole hold. The alternative of simply widening the window was
rejected - it would reintroduce the size cliff this work removes.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
CheckUpgradesAgainst resolved gallery entries through AvailableBackends,
which drops every entry the *local* host cannot run. In distributed mode
the host running the check is a CPU-only controller while the GPU
backends live on worker nodes, so FindGalleryElement returned nil for
every cuda/rocm/l4t entry and those backends were silently skipped.
Measured on a live cluster: GET /backends reported 48 installed
backends, POST /backends/upgrades/check evaluated 5 — all of them plain
or cpu-prefixed. The 43 skipped were all hardware-specific builds. As a
result cuda13-nvidia-l4t-arm64-longcat-video-development stayed at
sha256:0b8dc851 while the registry tag held sha256:38dae6ff, and a cuDNN
packaging fix sat unnoticed on a GPU worker for two days.
Every name looked up here is already installed somewhere in the cluster,
so hardware compatibility was decided at install time; re-deciding it
against the controller is wrong. Switch both CheckUpgradesAgainst and
UpgradeBackend to AvailableBackendsUnfiltered.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ⬆️ Update antirez/ds4
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(ds4): link new tensor parallel objects
The updated ds4 revision split tensor-parallel transport and layer placement into separate translation units. Build and link those objects on CPU, CUDA, and Metal builds.
Assisted-by: Codex:gpt-5
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
A 70 GB video checkpoint (longcat-video-avatar-1.5) could not be loaded on a
distributed cluster. The request failed with HTTP 500 after 1499.98s - exactly
the 25m00s cold-load ceiling - while staging was demonstrably healthy: 26 of 57
files and 39 GB transferred at a sustained ~26 MB/s, zero errors, no stalls. It
was not wedged, it was killed by a timer.
ModelLoadCeilingFor covers node selection, backend install, file staging and the
remote LoadModel. Install and load carry their own budgets; staging was covered
only by a FIXED 5-minute margin. But staging time is bytes over bandwidth, not a
constant: 70 GB at 26 MB/s needs ~45m against a 25m ceiling, so the failure is
deterministic for any sufficiently large model rather than a flake. Simply
raising the constant moves the cliff to the next model size - the deployment
target here is checkpoints of 600 GB and beyond.
The ceiling's real purpose is that "a wedged worker can never pin the lock
indefinitely". Progress, not elapsed time, is what distinguishes a wedged worker
from a large one. The hold is now a deadline that extends whenever the transfer
reports bytes and expires a 5-minute stall window after they stop:
- A large model transferring fine continues, for hours if needed.
- A worker that died mid-transfer still fails within the stall window.
Progress is observed at byte level on the transfer itself, via the existing
staging progress callback. Per-file completion would be too coarse - a single
600 GB shard would be indistinguishable from a stall for hours. The observation
point is back-pressured by the socket, so it reflects the network rather than
local disk reads. Observation is coarsened to one timer touch per stall/20 so
the per-read callback stays cheap.
The base budget (unchanged, and still derived from the install and load
timeouts) continues to cover the steps that report no progress, so
LOCALAI_NATS_MODEL_LOAD_TIMEOUT keeps working exactly as before. An absolute
cap of 24h bounds the hold even while progress keeps arriving, so a peer
trickling bytes forever cannot pin the advisory lock; 600 GB at the measured
26 MB/s is ~6.5h, so the cap sits far above any legitimate transfer.
Also fixes the incoherent layering the same error exposed: the resumable upload
carried a 1h retry budget nested inside the 25m ceiling, so the inner budget was
unreachable and the message still blamed it ("failed after 1 attempts within
1h0m0s budget") while the 25m parent was the actual killer. The upload now
adopts the caller's deadline when there is one, and applies its fixed budget
only when nothing above bounded it - which also stops a fixed 1h from
reintroducing the size cliff under the now-extendable parent.
This is the successor to #10968, where a hardcoded 5-minute LoadModel gRPC
timeout was replaced by this derived ceiling. Fixing the inner timeout exposed
the outer ceiling as the new binding constraint.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The Realtime guide incorrectly sent the Opus backend through the model gallery endpoint. Point users to the backend gallery API and document the UI and CLI alternatives.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
backendLoader logged "BackendLoader starting" at INFO as its very first
statement, unconditionally. That reads as "a model is being loaded", but
backendLoader is not only a load path: in distributed mode Load()
deliberately bypasses the local cache and calls backendLoader on every
inference request so SmartRouter can re-pick a replica per request. The
model is already resident, no process is spawned, and nothing is loaded,
yet the banner fires at request rate.
On a live cluster this produced ~5 "BackendLoader starting" lines per
second for a single embedding model, sustained, starting 22 seconds
after the load had already completed. The model was state=loaded with
in_flight=0 and exactly one backend process on the worker. It looked
exactly like a retry storm and cost real debugging time during an
unrelated production investigation. The adjacent "effective runtime
tuning" banner, documented as "logged once per load", had the same
problem for the same reason.
Emit both banners at INFO only when the model is not already resident,
and keep the per-call trace at DEBUG for anyone following the routing
path. isResident is a plain store lookup with no health probe and no
eviction, so it is safe on the per-request hot path (unlike
checkIsLoaded, which probes and can evict).
Same class of defect as #10985: a log line that sends the reader after
the wrong thing.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The "Bump Backend dependencies" workflow has failed every night for over
ten days. Four upstreams — ced.cpp, moss-transcribe.cpp, voice-detect.cpp
and rf-detr.cpp — moved from the mudler org to localai-org, so the GitHub
API answers 301 for the old slugs. ced.cpp additionally renamed its
default branch to main.
bump_deps.sh fetched without -L or -f and never checked the response, so
the redirect's JSON body was passed straight to sed, which died with
"unterminated `s' command". The loud failure was luck: an error body
without slashes would have been substituted into the Makefile as the new
pin, silently corrupting the version and shipping it in a bump PR.
Point the matrix at the new slugs and branch, and harden the script so a
bad response can never reach sed: follow redirects, fail on HTTP errors,
and require a bare 40-hex SHA before rewriting anything. Also refresh the
now-stale repository URLs in the backend Makefiles, test scripts,
backend/index.yaml and the docs.
Verified all 25 matrix entries resolve to a commit SHA and that the four
previously-failing jobs run end to end against the real API.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Picks up mudler/go-processmanager#7, which closes the check-then-act
window in Run's "already started" guard. Concurrent Run calls on one
handle could each observe a nil p.proc, each start a process and each
launch a monitor goroutine; every monitor does `defer close(p.done)`
against a channel created once in New, so the second monitor to see its
process exit panicked on close of a closed channel. The same window
raced on p.proc itself.
LocalAI does not hit this today: the only New/Run pair
(pkg/model/process.go:178-191) runs a freshly created handle, and
core/services/worker/supervisor.go only ever calls Stop on handles it
holds. The bump is defensive, and keeps the dependency from drifting
further behind a fix in the process lifecycle we rely on.
No exported signature changes upstream; ErrProcessAlreadyRun is
additive and keeps the historical "command already started" prefix, so
any caller matching on that text is unaffected. Nothing in this repo
matches it.
Verified: go build ./core/... ./pkg/... clean; go vet clean;
go test -race ./pkg/model/ ./core/services/worker/ both ok.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Bash] [Edit]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
ci(gallery): propose variant groupings for review on a schedule
A gallery entry may declare `variants:`, references to other entries that
are alternative builds of the same weights, and auto-selection then installs
the best build for the host. Those families exist only because humans curated
them in two manual sweeps.
The gallery agent dedupes on the HuggingFace repo URL and picks one
quantization per model, so it never adds a second build of a repo it already
has, and consequently never creates a family and never joins one. A model
published across two repos lands as two unrelated standalone entries. The
grouping decays as the gallery grows and nothing notices.
Add a scheduled job, in the same shape as the checksum checker: compute
offline, edit the index textually, open a pull request against ci-forks. It
proposes and never decides. Grouping is a judgement call that has gone wrong
in both directions, so the value is catching drift and surfacing candidates
with their evidence.
Three grouping signals, taken from the manual sweeps: same name once
quantization markers are stripped, the `:` config-suffix convention, and the
same primary weight filename once quantization markers are stripped. The
third requires the same upstream repository. Excluding auxiliary files is not
enough on its own: bert-embeddings, an ultravox audio model and a roleplay
finetune all declare a primary file called llama-3.2-1b-instruct-q4_k_m.gguf,
and grouping on that is the same error that linked four wan-2.1 entries and
Z-Image-Turbo to qwen3-4b.
Add gallery/variant-exclusions.yaml, a checked-in rejection ledger. A job
that re-proposes declined candidates every night becomes noise and gets
ignored. Declining a proposal is one flow-mapping line a reviewer adds inside
the proposal pull request itself. Seeded with the six -abliterated pairs whose
base is also in the gallery, the mistral-small multimodal pair, the whisper-1
alias, the kokoros language set, and the recurring finetune tokens. qat and
apex are deliberately not on it: they are quantization techniques.
Proposals refuse to nest, to let two parents claim one target, to target an
entry that installs nothing, and to touch a merge anchor, since a variants key
added to an anchor is inherited by every merging child. The anchor refusal
names every entry that would inherit, which is the worklist a human needs.
Run against the pre-sweep gallery, the job rediscovers 12 of the 19 groupings
the second manual sweep made, with no false positives. The rest it reports as
refusals or ledger declines rather than missing silently.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Every writer used to stage into the same `.artifacts/.partial/<cacheKey>`.
That was safe only because the artifact lock held: two writers that both
believed they had it opened the same blob with O_APPEND and interleaved
their bytes into one file, while the resume probe read the other writer's
in-flight size. SHA verification caught the damage only after both had
burned the entire download.
#10986 restored the lock's precondition on CIFS but left the dependency in
place. Suffix the staging tree with a writer identity drawn once per
process run, so concurrent writers cannot corrupt each other whatever the
lock does. The lock stops being a correctness dependency and becomes a
pure efficiency optimisation: a lock failure now costs a duplicated
download, not a corrupted one.
Commit stays an atomic rename. The loser of a commit race reconciles onto
the winner's tree instead of surfacing a bare ENOTEMPTY for work that
actually succeeded, since the artifact is content-addressed and both trees
hold the same verified bytes.
Writer-unique staging means a crashed writer's tree is no longer
overwritten by its successor, so two things are added to keep it from
becoming a disk leak and a resume regression:
- A sweep reclaims trees whose contents have been untouched for 24h,
matching the window the startup reaper already uses for stray *.partial
files. It reads the newest mtime anywhere inside the tree, because
writing a blob never touches an ancestor, and refuses any name this
package did not write. A live download writes continuously, and the
downloader's stall watchdog aborts a silent one long before it could
look abandoned.
- Adoption lets a restarted process claim a dead predecessor's tree for
the same artifact and resume from its bytes, which a tens-of-gigabytes
repo depends on. The claim is an atomic rename, so racing adopters
cannot both win. It runs only under the artifact lock - which is
released exactly when the owning process dies - and only on a tree idle
for 5 minutes as a second line of defence for when the lock does not
exclude.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(worker): give the worker a real health endpoint (#10987)
The image bakes in a single HEALTHCHECK that curls
http://localhost:8080/readyz, but the same image also runs `local-ai
worker`, which serves HTTP on the gRPC base port minus one and never
binds 8080. Every worker container was therefore permanently
`unhealthy` (43 consecutive failures observed on a production node),
which is worse than having no healthcheck: a genuinely broken worker and
a perfectly good one both report `unhealthy`, so the signal carries no
information and orchestration that keys on it misbehaves.
The worker already served /readyz on that port via the file-transfer
server, but as a constant 200 — it only proved the listener was bound,
which is precisely the failure mode at issue. Readiness now tracks the
live NATS connection: all of a worker's actual work (backend lifecycle
events, inference dispatch, file staging) arrives over NATS, so a worker
whose link is dead is up and useless. Registration is already implied,
since the server only starts after registration succeeds.
This reports something the controller cannot already see. The node
registry's status/last_heartbeat is fed by an HTTP heartbeat to the
frontend, a different network path from NATS — a worker can keep
heartbeating while its NATS connection is dead and still look healthy in
the registry. /healthz stays a constant 200: liveness must not follow
readiness, or a NATS blip becomes a cluster-wide restart storm.
The HEALTHCHECK is now a script that derives its endpoint from the mode
the container is actually running plus the env vars that configure the
bind address, so a frontend moved off 8080 with LOCALAI_ADDRESS (broken
the same way) and a worker on a non-default base port are both probed
correctly. Modes with no HTTP surface (agent-worker, one-shot commands)
report healthy rather than false-unhealthy. HEALTHCHECK_ENDPOINT remains
as an explicit override, so the workaround shipped in
docker-compose.distributed.yaml keeps working; both overrides in that
file are now unnecessary and have been removed.
Also fixes the latent --start-period gap. Since #10949 a frontend's
startup preload materializes HuggingFace artifacts before the HTTP
server binds (31 GB observed on a live cluster), so a healthy replica
can legitimately fail probes for a long time. --start-period is Docker's
knob for exactly this: failures inside it leave the container `starting`
instead of burning retries, and it ends early on the first success, so a
generous 60m costs a fast-starting container nothing. --timeout drops
from 10m to 10s — it is a per-probe deadline, and a localhost curl that
has not answered in 10s is itself the fault being detected.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
In distributed mode the Open Responses store is process-local: a
sync.OnceValue over a map behind an RWMutex. With several frontend
replicas behind a round-robin load balancer, every request that lands on
a replica other than the creator misses.
Measured on a live 2-replica cluster (#10993): the same response id
returns 200 on the creating replica and 404 on its peer, and a cancel on
the peer returns 404 without ever invoking CancelFunc, so generation runs
to completion on the other replica while the caller is told the response
does not exist. previous_response_id chaining fails through the same
lookup.
Split the state by what can actually cross a process boundary:
- Replicated: response metadata (request, response resource, owner,
expiry, stream/background flags) via syncstate.SyncedMap, the same
component finetune, quantization and agent tasks already use. A local
miss in Get/FindItem now falls back to it and returns a read-only
remote view, so polling and chaining resolve on any replica.
- Delegated: cancellation. context.CancelFunc is a function pointer and
exists only in the creating process, so a cancel that lands elsewhere
is broadcast on responses.<id>.cancel and applied by whichever replica
holds the function. The broadcast is fire-and-forget rather than
request/reply: if the owner crashed or was scaled down nobody answers,
and the handler must not block on a reply that will never come. The
replicated status moves to cancelled either way, which is truthful,
since a dead owner's generation died with its process.
- Refused: streaming resume. The resume buffer is a byte log plus a live
notification channel and cannot be replicated without shipping every
token over the bus. A resume that reaches the wrong replica now returns
HTTP 409 naming the owning replica via the new ErrResponseNotLocal,
instead of an empty event list that looks like a finished stream. It is
deliberately distinct from ErrOffsetLost, which means the owner's
buffer evicted the requested events.
Standalone deployments never call EnableDistributed and keep exactly the
previous process-local behaviour.
Fixes#10993
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
gallery: remove duplicated entries and lint against them coming back
gallery/index.yaml declared eight names twice: deepseek-r1-distill-llama-8b,
llama3.2-3b-enigma, qwen3-asr-0.6b, qwen3-asr-1.7b, qwopus-glm-18b-merged,
voice-en-us-kathleen-low, whisper-large-q5_0 and whisper-small-q5_1.
FindGalleryElement resolves a reference by returning the first match, so in
every pair the second copy was unreachable: it could not be installed, could
not be selected as a variant target, and could not be corrected, because any
edit to it went to a copy nobody reads. A reference to such a name is also
ambiguous to anything reasoning over the catalog, which is why the variant
proposal job refuses to propose against them.
Each pair was compared both as parsed entries and as raw text, and all eight
were byte-identical apart from position. None of the sixteen blocks defines a
YAML anchor or pulls one in with a merge key, so nothing was reachable only
through a deleted block, and no entry named a removed copy as a variant target.
Removing the second copy of each therefore changes no behaviour: the parsed set
loses exactly eight entries and every surviving entry is field-for-field
unchanged.
The removal is textual, by line range, so the diff is pure deletions rather than
a reflow of forty thousand lines.
checkNoDuplicateEntryNames is the rule that keeps them out, added beside the
existing gallery invariants and reporting in the same style.
checkSingleVariantClaim closes the adjacent gap in the same place. VariantParents
resolves a build claimed by two parents by taking the first in gallery order and
calls that deterministic "for a gallery the linter would reject", but nothing
rejected it: the invariant was held by curation alone. Now it is a rule, and the
comment describes something real. No target is doubly claimed today, so the rule
is green on arrival.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
flock(2) on CIFS/SMB returns EACCES when another client holds the lock:
the kernel maps STATUS_LOCK_NOT_GRANTED and STATUS_FILE_LOCK_CONFLICT to
-EACCES and never produces EWOULDBLOCK on that path. gofrs/flock only
recognises EWOULDBLOCK as contention, so TryLockContext returned a bare
"permission denied" and Ensure aborted. Both replicas then fell back to
legacy loading, which makes the worker download the whole repo in-band
inside LoadModel and blow the remote-load deadline.
Replace TryLockContext with an explicit wait loop over a new Locker
interface, classifying EWOULDBLOCK/EAGAIN/EACCES/EBUSY as contention.
EACCES is ambiguous at the syscall boundary but not here: the lock file
is already open O_CREATE|O_RDWR, so a real permission problem would have
failed the open with an *fs.PathError, and flock(2) documents no EACCES
on Linux at all. The wait is bounded (DefaultLockWait, overridable via
WithLockWait), so even a misclassification degrades to a delay. On
timeout the committed result is re-checked before reporting the new
ErrLockContended, so a peer that finished the work still wins.
Locker also exists so the contention path is testable without a network
filesystem: nothing in CI can make flock(2) return EACCES on demand.
Raise the fallback to error for a managedArtifactBackends backend, via a
shared config.LogArtifactFallback used by both call sites. For those
backends the legacy path is not graceful degradation, and the operator
otherwise sees only a timeout with no causal link. The fallback stays
non-fatal.
Drop the os.Chmod(layout.Lock, 0o600) after acquisition: flock.New
already creates the file 0600, and the chmod was gratuitous risk on a
nounix mount that ignores modes.
Fixes#10981
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
#10970 gave the four PredictOptions RPCs a model-identity check so a
backend reached through a stale distributed route rejects the request
instead of answering from whatever model it holds (#10952). Every other
modality shares that exposure: the route is cached by host:port, a worker
can recycle a stopped backend's port for another model's backend, and a
liveness-only probe cannot tell a stale row from a valid one.
Extends the same mechanism to the 21 remaining request messages that reach
a backend through the router, using the pattern #10970 established rather
than a parallel one:
- proto: ModelIdentity on each modality request message.
- controller: populated from ModelConfig.Model at the call site that also
builds ModelOptions, so load-time and request-time values are equal by
construction.
- backends: one generic guard in pkg/grpc/server.go (27 Go backends), the
method set in backend/python/common (36 Python backends), llama-cpp
(AudioTranscription/Stream, Rerank, Score) and privacy-filter
(TokenClassify).
- reconcile already drops the stale row on IsModelMismatch; no change.
TTSRequest and SoundGenerationRequest get a SEPARATE ModelIdentity field
rather than reusing their existing `model`: FileStagingClient rewrites
`model` to a worker-local path, so comparing it would reject valid
requests in exactly the configuration this guards.
AudioEncode/AudioDecode are deliberately left unguarded: the opus codec
backend is loaded from a literal rather than a ModelConfig, so no value
carries the equality guarantee the comparison depends on. The four
bidirectional stream RPCs are out of scope; they bypass reconcile.
Empty means skip on both sides, so an old controller, an old backend, and
the bare request structs in tests/e2e-backends all keep working.
Assisted-by: Claude Code:claude-opus-4-8 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
PR #10975 taught the backend matrix filter about shared build inputs, but
left two paths that still rebuild nothing.
Go backends link code from the main tree. `go list -deps ./backend/go/...`
resolves to exactly six pkg subtrees (audio, grpc incl. base/grpcerrors/proto,
httpclient, sound, store, utils), identical for GOOS/GOARCH in
{linux,darwin} x {amd64,arm64}. Editing any of them changes the shipped
binary, but they sit outside every backend directory so the prefix match
never saw them. Enumerating those six rather than taking all of pkg/ is the
point: all of pkg/ changes in ~8.6% of commits, these six in 2.0% — the same
order as the already accepted scripts/build/ rule (1.9%). Blast radius
199/417 Linux, 26/56 Darwin; the ~21 core-server-only pkg subtrees still
rebuild nothing, and neither do _test.go files.
.github/backend-matrix.yml was excluded wholesale because matching its path
would rebuild all 417 entries on every new-backend PR. That hid a real hole:
editing an existing entry's base-image, build-type or cuda version changes
the image it produces while touching no file the filter can see. Since the
change is within a structured file, compare it against the base revision and
rebuild only the entries whose fields actually differ — 1 entry for a
base-image edit, 0 for a comment or whitespace edit, and all 417 only when
the previous revision cannot be resolved. This also closes a third hole: a
new matrix entry for an existing backend (a new CUDA variant, say) touches
nothing under that backend's directory and previously rebuilt nothing.
changed-backends.js fetches the base revision via the contents API, and only
when the changed-file list actually names the matrix file, so the common path
costs no extra request.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(http): make /readyz reflect startup readiness instead of always 200
/readyz was registered as a static handler returning 200 unconditionally,
so it carried no information: it was green whenever it could be reached at
all. Readiness could not distinguish "serving" from "still starting", and
any future change that started the HTTP listener earlier would silently
turn the probe into a lie.
Track startup completion on the Application (atomic flag, flipped at the
very end of New() on the success path only) and have the readiness handler
consult it per request, returning 503 with a small JSON body while startup
is in progress. A nil readiness source fails open so embedders keep the
historical behaviour.
/healthz is deliberately left readiness-independent. Liveness and readiness
answer different questions, and failing liveness during a long preload makes
an orchestrator restart the pod mid-download so the preload never finishes.
This matters because since #10949 the startup preload materializes
HuggingFace artifacts for managed backends: tens of GB for a large model
(31 GB observed on a live cluster). Both probes stay in quietPaths and stay
exempt from auth.
Note the listener is still started only after New() returns, so today the
not-ready state is not observable over HTTP. Moving the listener earlier is
a separate, deliberate decision and is not made here.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* chore(gitignore): anchor the mock-backend pattern so its source dir is traversable
The bare `mock-backend` pattern matched the *directory*
tests/e2e/mock-backend/, not just the binary built into it. Git will not
descend into an ignored directory even for tracked files, so
`git add tests/e2e/mock-backend/main.go` required -f. This was hit while
working on #10970.
Anchor it to the artifact's full path. The built binary stays ignored (it is
also covered by tests/e2e/mock-backend/.gitignore) while the source directory
becomes traversable again.
Verified with `git check-ignore -v`: a new source file under
tests/e2e/mock-backend/ is no longer ignored, and the binary produced by
`make build-mock-backend` still is.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* chore(coverage): raise the coverage ratchet from 48.5% to 54.2%
The committed baseline had drifted well below reality: it still read 48.5%
while a full instrumented run measures 54.2%. A stale-low baseline makes the
gate meaningless — coverage could regress by more than 5 percentage points
and still pass.
Raising a ratchet is a deliberate act, not something to fold into an
unrelated fix, so it gets its own commit. The headroom was earned by tests
landed in #10946, #10947, #10948, #10949, #10956, #10967, #10968, #10970 and
#10975.
Measured with `make test-coverage` on this branch (the same instrumented run
`make test-coverage-baseline` uses: ginkgo over ./pkg and ./core plus the
in-process tests/e2e suite, --covermode=atomic, --coverpkg over core/... and
pkg/..., generated protobuf excluded). The run completed with exit 0 and zero
spec failures; the total was then written with the exact command the
test-coverage-baseline target uses:
go tool cover -func=coverage/coverage.out \
| awk '/^total:/{gsub(/%/,"",$NF); print $NF}' > coverage-baseline.txt
Verified afterwards with scripts/coverage-check.sh, which reports OK.
Note the measured figure includes the readiness specs added earlier on this
branch, so it is a demonstrated floor rather than an estimate.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Two independent defects in the download path, both surfaced by the same
incident (#10982).
A failed `io.Copy` was always reported as "failed to write file", because
`io.Copy` folds read and write errors into a single return value. A
peer-cancelled HTTP/2 stream therefore presented as a filesystem failure and
sent an investigation after mount permissions while the disk was healthy. The
source is now wrapped in a recorder so the error names the side that actually
broke, and a write failure names the `.partial` it was writing rather than the
final blob path.
The plan runner returned on the first task error with no retry, so one
transient stream cancel discarded every file already downloaded in a
multi-file materialization. The `.partial` resume machinery already existed
but was unreachable because nothing made a second attempt. Transient failures
(dropped transport, mid-stream read failure, stall, 5xx, 429) are now retried
with bounded exponential backoff and resume from the partial; permanent ones
(4xx, checksum mismatch, local write failure, caller cancellation) fail
immediately.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
feat(gallery): group 21 more model families under variants
Second variant-grouping sweep. QAT and APEX builds are now treated as
quantization techniques rather than distinct weights, per maintainer
ruling, so they group with their base entry instead of standing alone.
Adds 15 new families: quantization and serving-config pairs for
llama-3.2-1b/3b-instruct, dolphin-2.9-llama3-8b, phi-2-chat, ideogram-4,
meta-llama-3.1-8b-instruct, omnivoice-cpp and qwen3-tts-cpp; the gemma-3
4b/12b/27b QAT families; and three cross-backend pairs (silero-vad plus
its sherpa-onnx build, and the vibevoice TTS and ASR builds shared
between the vibevoice-cpp and crispasr backends). The cross-backend
pairs are the first entries that meaningfully exercise engine-preference
ranking during auto-selection.
Restructures four gemma-4 families (31b-it, 26b-a4b-it, e2b-it, e4b-it).
Those bare entries were skipped by the first sweep, which left a QAT
build as parent by default. The bare entry is what installs when nothing
else fits, so it reclaims the parent slot and the former parent becomes
a plain target. Every pre-existing relationship is preserved; nothing is
dropped and nothing nests. gemma-4-12b-it has no bare entry, so it is
left as is.
qwen3-tts-cpp is a YAML anchor with nine merging children, so the five
children that did not already override variants get an explicit empty
list to stop them inheriting the parent's.
Abliterated builds stay excluded: abliteration edits the weights to
remove refusal behaviour, which makes them a different model rather than
another build of the same one.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(system): expose raw detected capability for model meta resolution
Model meta gallery entries express hardware fallback through candidate
ordering rather than a capability map, so they need the undecorated
detected capability string without Capability's default/cpu fallback
chain.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactor(system): drop duplicate capability accessor, cover DetectedCapability
ReportedCapability was added with a body identical to the existing
DetectedCapability. Keep one accessor and move the specs onto it, since
DetectedCapability had no direct coverage of its no-fallback behavior.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): parse IEC binary size suffixes (KiB..PiB)
ParseSizeString accepted only SI suffixes, so a "20GiB" floor was rejected
outright. Model and VRAM sizes are conventionally quoted in IEC units, and
silently reading GiB as GB would understate a floor by about 7%.
Purely additive: these inputs previously returned an unknown-suffix error.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): add Candidate type for meta model entries
Candidate is one option in a meta entry's ordered variant list. It names a
concrete gallery entry and declares when that entry suits the host.
EffectiveMinVRAM resolves the VRAM floor, letting an authored min_vram win
over a nightly-inferred one. An unparseable floor errors instead of being
treated as absent: swallowing a typo would turn a constrained candidate into
an unconstrained one and select a too-large variant rather than fail loudly.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): add hardware-aware model variant resolver
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): allow gallery model entries to declare variant candidates
A gallery entry with a non-empty candidates list is a meta entry: it names
an ordered list of concrete entries and resolves to the first one the host
can satisfy, instead of describing model files directly.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): resolve meta model entries to hardware-appropriate variants at install
Meta gallery entries carry an ordered candidate list; at install time the
first candidate the host satisfies is resolved and its payload installed
under the meta's name, so the model keeps a stable name regardless of which
variant backs it. The resolution is recorded in the installed gallery
config so a reinstall honors a prior pin and operators can see the backing
variant.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): key meta pin recall on the installed name and detach resolved entries
Six review findings on the meta-entry install path.
Pin recall was keyed on the gallery entry name while applyModel writes the
record under the install name (req.Name when supplied), so a meta installed
under a custom name with a pin lost that pin on reinstall and was silently
re-resolved onto a different variant, possibly swapping its backend. Compute
the install name with applyModel's own precedence before the recall.
ResolveMetaModel returned a shallow struct copy, so the resolved entry's
Overrides aliased the gallery entry's map and the install path's in-place
mergo merge wrote the caller's request into the shared catalog. Detach
Overrides, ConfigFile, AdditionalFiles, URLs and Tags. Not exploitable today
only because this path re-unmarshals the gallery per call, which is a
property nobody should have to rely on.
Also: overlay the meta's name onto the persisted config for meta installs so
the gallery file no longer records the variant's name; move the pinned-VRAM
warning below the variant validation so a pin naming a nonexistent entry does
not warn about VRAM before failing for an unrelated reason; and stop seeding
config.URLs in the config_file branch, which duplicated every declared URL.
Add seven network-free specs driving InstallModelFromGallery with a meta
entry: variant payload wins over the meta's legacy url fallback, the
resolution record round-trips to disk, a pin is recorded and honored on
reinstall including under a custom install name, and the resolved entry does
not alias the gallery's maps.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): deep-copy meta overrides and make two specs functional
ResolveMetaModel detached the resolved entry's Overrides and ConfigFile with
maps.Clone, which only copies the top level. Gallery overrides are nested in
practice (parameters.model is near-universal) and the install path merges the
caller's request with mergo.WithOverride, which recurses into nested maps and
overwrites them in place, so the gallery entry's own inner maps were still
reachable and still got rewritten by the last caller to install.
Copy both maps all the way down instead, recursing through the container shapes
a YAML decoder produces. ConfigFile is not mutated on the install path today,
but it carries the same kind of nested payload and leaving it shallowly cloned
would invite the bug back.
Also fix two specs that passed whether or not their target fix was present:
- "does not write the caller's overrides back into the gallery entry" re-read
the catalog from disk, which re-unmarshals fresh structs and so cannot
observe in-memory aliasing. It now asserts against the in-memory gallery
entry and drives the real mergo merge.
- "round-trips the resolution record to disk under the meta's name" asserted a
name that is already correct in the config_file branch. It now drives the url
branch via a file:// fixture, where the meta-name overlay actually applies.
Both were verified red by reverting their fix.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(gallery): lint meta model entry invariants in index.yaml
Adds Ginkgo specs that parse the shipped gallery/index.yaml and enforce
the invariants that keep meta entries safe: a legacy url fallback equal
to the final candidate's url, references only to existing non-meta
entries, a min_vram floor on every candidate but the last-resort one,
a capability drawn only from the vocabulary the system can report, and
descending VRAM floors within a capability group.
The capability check is the only compensating control for a typo there.
Candidate matching is a case-sensitive exact comparison against
SystemState.DetectedCapability(), so an unknown value never matches and
falls through silently instead of erroring. The vocabulary therefore
mirrors the raw return set of getSystemCapabilities(), which notably
excludes "cpu": that is a fallback key inside Capability(capMap) on the
meta backend path, never a reported capability. A CPU-only host reports
"default".
These pass vacuously until the pilot meta entry lands; the guard is
intentionally in place before the thing it guards.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(gallery): close coverage gaps in the meta entry lint
The ordering invariant grouped candidates by capability and asserted floors
descend within a group. A candidate with an EMPTY capability matches every
host, so it does not belong in its own group: it dominates every later
candidate whose floor is at or above its own, across capability groups.
Track a running minimum floor over the unconditional candidates instead,
which subsumes the old same-group check for the empty capability.
Every spec skipped non-meta entries, so with zero meta entries in the index
all five bodies were no-ops. Aligning GalleryModel.IsMeta() with
GalleryBackend.IsMeta(), whose semantics are deliberately opposite, would
have made all of them pass while checking nothing. Extract each invariant
into a helper over a slice of entries returning the violations it finds, and
cover those helpers with synthetic fixtures so the logic stays tested at zero
meta entries. The index-driven specs are now a thin application of already
proven logic.
Also assert the index parses non-empty, report every violation in one run
rather than aborting on the first, and parse the index once for the suite.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci(gallery): add nightly denormalization of meta model candidates
Fills the read-only backend, quantization and inferred_min_vram fields on
meta gallery candidates and opens a PR, modeled on the existing
checksum_checker job. Computing these needs network access, so it happens
nightly rather than at install time.
An authored min_vram is never modified: a human who measured a real load
knows more than a pre-download estimate does.
The index is rewritten via yaml.Node rather than a document round-trip. A
full round-trip reflows all ~26k lines of gallery/index.yaml, which would
bury the computed values and make the nightly PR unreviewable. The rewrite
touches only the three derived keys, so authored styling survives and a run
that computes nothing leaves the file untouched.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ci): keep the gallery denormalize diff reviewable and self-healing
The nightly denormalization job edits YAML nodes instead of round-tripping
structs so its PR stays small enough for a human to review, but the write
path undid that: yaml.Marshal re-encoded the node tree at yaml.v3's default
4-space indent and dropped the leading document marker, reflowing roughly
6000 lines around the handful of real changes. Encode through
yaml.NewEncoder at the index's authored 2-space indent and restore the
header. A write that changes three fields now changes three lines.
Stale inferred_min_vram values were also never cleared. Both skip paths
(an authored min_vram is present, or the candidate is the last resort)
returned before touching the field, so a candidate that gained a floor or
became the last resort after a reorder kept an inferred value that
EffectiveMinVRAM reported as a real constraint, failing the meta lint with
no way for the job to self-heal. Clear the field before both skips.
The workflow discarded a whole night's work on any single failure: the
program exits 1 when a candidate cannot be estimated, which aborted the job
before the PR step, so one unreachable candidate blocked every other
refresh indefinitely. Capture the status, open the PR with what was
computed, mark the PR body as partial, and fail the run afterwards so the
problem still surfaces.
Also preserve the index's existing file mode instead of forcing 0644, and
drop the redundant //go:build ignore tag, since Go already skips dot
directories and the sibling modelslist.go carries no tag.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): add nanbeige4.1-3b meta entry with hardware-resolved variants
Adds the first real meta entry to the gallery index. It resolves to the
Q8_0 build on hosts with at least 6GiB of VRAM and to the Q4_K_M build
everywhere else, installing either payload under the stable name
nanbeige4.1-3b.
The entry carries a url equal to its final candidate's url. LocalAI
releases that predate candidates support parse the index non-strictly
and drop the key silently, so without that url they would list the entry
and install nothing. A regression spec parses the index the way those
releases do and asserts every meta entry stays installable for them.
Also teaches core/schema/gallery-model.schema.json about candidates. The
schema sets additionalProperties: false at the top level, so an author
following CONTRIBUTING.md and adding the yaml-language-server comment
would otherwise get a validation error on this entry.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): make candidate entries complete, installable entries
Reworks hardware-resolved gallery variants after a design pivot. There is no
longer a separate "meta" entry kind. A gallery entry is a normal, complete
entry that may additionally carry candidates:, a list of hardware-gated
upgrades over itself, and the entry is itself the last-resort candidate.
The previous design relied on a bare url: as the fallback for LocalAI releases
that predate candidates support. That fallback is empty in practice: none of
the 80 gallery/*.yaml files carry a top-level files:, and 1216 of 1281 index
entries carry their payload in the index entry itself, so a url alone yields a
config template with nothing to download. Since every released LocalAI reads
gallery/index.yaml live from master, merging a payload-less entry would have
shown every existing user a model that installs to a broken state. Making the
entry its own base candidate removes the problem at the root: old clients drop
the candidates key and install the entry exactly as they do today.
Resolution order is now explicit pin, then capability plus VRAM over the
declared upgrades, then the entry itself. The entry ALWAYS installs: when its
own min_vram or capability is unmet the installer warns and installs it
anyway, because there is nothing below it and refusing would make the gallery
behave worse the newer the client is. A pin naming the entry's own name is
valid and is how an operator declines an upgrade.
IsMeta() becomes HasCandidates(), ResolveMetaModel becomes ResolveVariant, and
the persisted meta_name record key becomes entry_name. GalleryBackend.IsMeta()
is a separate concept and is untouched.
The lint drops the three rules the pivot makes wrong (url equality with the
final candidate, no inline payload, unconstrained final candidate) and gains
one: the entry's own floor must sit strictly below every candidate's, since a
base that outranks a candidate makes that candidate unreachable.
The pilot entry is now the existing nanbeige4.1-3b-q4, which gains a 2GiB
floor of its own and a single 6GiB upgrade to nanbeige4.1-3b-q8, replacing the
separate nanbeige4.1-3b entry added in d0d441bb4.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): select model variants by hardware fit, not authored order
Gallery entries could already carry a list of alternatives, but selection was
an authored, ordered, first-match policy: every candidate declared a
`capability` string and the VRAM floors had to descend in a hand-tuned order.
That pushed hardware knowledge onto whoever edits the gallery and made ordering
load-bearing, so a reordered list silently changed what users installed.
None of it was necessary. SystemState.IsBackendCompatible already derives
hardware support from a backend name alone: it knows MLX and metal are
Darwin-only, CUDA is NVIDIA-only, ROCm AMD-only, SYCL Intel-only. Selection can
read that instead of asking authors to restate it.
Authoring is now just a list of names:
- name: qwen3.6-27b
min_memory: 4GiB
variants:
- model: qwen3.6-27b-mlx-8bit
- model: qwen3.6-27b-gguf-q8
min_memory: 28GiB
and all the intelligence moved into the selector. Given a host it drops the
variants whose backend cannot run here, drops those whose known memory
requirement exceeds what the host has, and takes the LARGEST of what is left,
because a bigger footprint is a higher quality quantization of the same model.
A variant of unknown size is kept, since nothing proves it does not fit, but it
ranks last so a proven fit always beats a guess. An explicit pin still wins
outright, and if nothing survives the entry installs its own payload: the base
always installs, this never refuses.
Available memory is VRAM when a GPU was detected and system RAM otherwise, read
through xsysinfo so a cgroup limit is honored and a container gets its own
limit rather than the node's RAM.
Capability disappears entirely, from the types, the schema and the lint. VRAM
and RAM collapse into one `min_memory`, because a model's footprint is roughly
the same wherever it lives and one figure is compared against whichever applies.
The lint rules about ordering, the capability vocabulary and floor
relationships are deleted with the hazards they described; what remains is that
every variant names an entry that exists and does not itself declare variants,
plus that any memory figure actually parses.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* gallery: size model variants with a live probe, drop the nightly denormalizer
Selection needs each variant's size to decide whether it fits and to rank
largest-first. That figure was written into the index by a nightly job, which
made the gallery carry a derived value that could drift from the entry it was
derived from. Derive it at install time instead.
pkg/vram already sizes a model without downloading it, and the gallery UI
already uses it: a remote GGUF header range-fetch, then an HTTP HEAD for the
content length, then any declared size:. It caches its results, so reuse it
rather than writing a second probing path.
A probe failure must never fail an install, so an unprobeable variant is
treated as unknown: it survives the memory filter, because nothing proves it
does not fit, and it ranks last, so a known-good fit always beats a guess. If
every probe fails, selection still terminates on the base entry.
The probe is injected through ResolveEnv rather than called directly, for the
same reason the backend compatibility check is: specs pin an exact size, or an
exact failure, without reaching the network.
With that in place three things are dead weight and go:
- The nightly job and the fields it populated. Variant.Backend was redundant
because the backend is resolved live from the referenced entry during
selection, and Quantization was display-only that nothing read.
- min_memory on the base entry. The base always installs and its floor could
only warn, so it could not change any outcome.
- The lint rules and schema entries for both.
min_memory on individual variants stays, as the override for when the probed
size is wrong. An authored figure now suppresses the probe entirely rather
than merely outranking it, so it costs no round trip.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): expose model variants for selection over API, CLI and MCP
A gallery entry may carry `variants:`, alternative builds of the same model.
Selection already worked at install time, but nothing could see what an entry
offered or ask for a specific build, so the feature was undrivable.
Listing: `GET /api/models` now reports `variants` and `auto_variant` for the
entries that declare variants. Each variant carries its resolved backend, its
measured size and whether it fits this host. `auto_variant` is what installing
without a choice would pick right now.
The new gallery.DescribeVariants runs the same variantOptions + SelectVariant
pass the installer runs, so the reported default cannot drift from what
installing actually does, and HostResolveEnv is extracted so both derive the
host and share pkg/vram's probe cache from one place.
Performance: an entry that declares no variants returns early without touching
the probe, so the ~1280 ordinary entries cost exactly what they cost before.
Selection: `variant` is accepted on POST /models/apply, as a query param on
POST /api/models/install/:id, on the gallery apply file/string request, as
`local-ai models install --variant`, and as a parameter on the install_model
MCP tool (both the httpapi and inproc clients). Empty means auto-select.
An unknown variant name now fails the install naming what was requested. This
closes a real hole: an entry declaring no variants short-circuits before
selection runs, so a requested variant was previously dropped silently and the
install reported success.
startup.InstallModels ends in a variadic model list, so install options could
not be appended to it; InstallModelsWithOptions is added alongside and
InstallModels delegates to it. No caller signature changed.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): drop the redundant variant min_memory field
Variant.MinMemory was an authored override for when the live probe misreads
a variant's footprint. It duplicated an existing field: probeEntryMemory
already passes the entry's declared size: into EstimateModelMultiContext,
whose cascade prefers that declared size over its own guesswork. Correcting
size: on the referenced entry fixes the figure for every consumer rather
than only for variant selection, so min_memory shadowed the right answer.
A variant is now nothing but a name. Its effective size is exactly the probe
result, and an unknown stays unknown: it survives the filter and ranks last.
EffectiveMemory loses its error return along with the field. The authored
string was the only thing that could fail to parse, so the error had no
remaining source and was propagating dead nil-checks through SelectVariant,
DescribeVariants and the pin warning.
Selection behaviour is unchanged. The specs covering probe-derived sizing,
ranking, filtering, the unknown-size path, pin recall, entry/variant
metadata split and deep-copy isolation all survive; the three install specs
that needed a definite size now declare it through the referenced entry's
own size:, which exercises the documented escape hatch directly.
gallery/index.yaml is untouched: no entry ever carried the key.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): rank the entry's own build against its variants
Variant selection pulled the declaring entry's own payload, the base, out
of the candidate set and consulted it only once every declared variant had
been rejected. Two real failures followed.
A variant whose size the probe cannot determine deliberately survives the
memory filter, because nothing proves it does not fit. As the only survivor
it then won outright on any host, however small: a 2GiB machine installed an
unmeasured variant in preference to the 4GiB build the entry itself ships,
with no warning. 241 of the 1280 current index entries carry no files and no
size, which is exactly that shape.
"Largest wins" also broke whenever the base was the largest. An author
writing a Q8 entry that offers a Q4 downgrade for small hosts, a natural
shape that nothing in the lint, schema or docs discourages, had the Q4
installed on every large host instead.
Make the base an ordinary participant. It is still exempt from both filters,
so selection always terminates on something installable, but it is now
ranked against the variants: a proven fit first and largest, then the base,
then any variant whose size nothing could measure. Both failures disappear
together. The base is probed for its size accordingly, which it was not
before, because an unsized base would lose every contest to an unmeasurable
variant.
FellBackToBase is kept but narrowed to "no declared variant survived",
rather than "the base was chosen", since the base now also wins on merit and
that is not worth warning about.
A recalled variant pin also became a permanent install failure. A pin the
caller supplies on this request must stay fatal, but one recalled from
._gallery_<name>.yaml can be invalidated by any later gallery edit, and
failing on it turned one rename into a model that could never be reinstalled
or upgraded again short of deleting a dotfile the user has never heard of.
A stale recalled pin is now dropped with a warning naming it, and selection
runs as if it had never been recorded.
Also drop the last textual reference to two abandoned designs from the
DetectedCapability comment, correct the documented variants JSON example,
which showed a memory_bytes of 0 that omitempty makes impossible, and remove
an em dash from the install skill.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): budget variant memory from RAM when a GPU reports no VRAM
Variant selection read its memory budget from VRAM whenever a GPU
capability was detected, and from system RAM only when none was. Apple
Silicon satisfies the first branch and fails the premise: arm64 macs report
the metal capability unconditionally, without probing anything, while
TotalAvailableVRAM has no discrete VRAM pool to find and returns zero. The
budget therefore came out as zero on every Mac.
Zero drops every variant carrying a known size, so the base build was
installed on all of them however much memory the machine had. The feature
was inert on the platform, and silently: falling back to the base is a
legitimate outcome, so nothing looked wrong.
Take VRAM only when it is actually a number, and fall back to RAM
otherwise. On a unified-memory host RAM is not an approximation of the
budget, it is the budget, since the GPU shares it. A discrete GPU whose
VRAM could not be read also lands on RAM, which overstates what the card
holds but understates nothing the host has; the previous zero understated
both.
An unreadable RAM figure still yields zero and still installs the base, so
a genuinely unknown host is not talked into a larger download.
This is what turned tests-apple red: "installs a fitting variant's payload
under the entry's own name" asserts on selection, and the runner resolved
to the base because its budget was zero. The added specs pin the branch
directly rather than relying on a macOS runner to notice again.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): add a model variant picker to the models gallery
PR #10943 shipped the server side: a gallery entry may declare `variants:`,
`GET /api/models` attaches `variants` and `auto_variant` to declaring
entries, and `POST /api/models/install/:id` accepts a `variant` query
parameter. Nothing in the UI consumed any of it, so the feature was not
reachable from the browser. This wires it up.
modelsApi.install takes an optional second argument and appends an encoded
`?variant=` only when one is given, so every existing call site keeps
sending exactly the request it sent before.
On the models table, an entry that declares variants gets a split button.
The primary Install still installs the auto-selected build, because auto is
the default and the point of the feature; the chevron opens a menu for a
deliberate override. It follows the Backends.jsx precedent: one shared
Popover re-anchored per row, rendering .action-menu items, which brings
Escape, outside-click and focus return along with it. An entry that
declares no variants renders exactly as it did before.
A variant that does not fit is dimmed but stays selectable, since the server
honors an explicit choice with a warning rather than refusing it.
memory_bytes is omitempty on the wire, so an absent key means the size is
unknown and never zero. A single helper guards both the menu and the detail
row, because formatBytes would otherwise render a falsy value as "0 B",
which reads as "needs nothing".
The expanded detail row gains a Variants section listing each build's
backend, size, whether it fits, which is the entry's own build, and which
one auto-selection would pick, built from the existing DetailRow helper and
.badge classes.
Eight Playwright specs cover the picker, including that plain Install sends
no variant parameter and that choosing one sends it. One pre-existing
assertion was scoped with .first(): the Variants section legitimately adds
more llama-cpp badges to the detail row, which tripped strict mode.
UI line coverage 49.42% -> 49.36% against a 40.0 baseline and 0.8pp
tolerance; branch coverage rose 72.04% -> 72.66%.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): describe model variants from a companion endpoint
Variant description probes each referenced entry's weight files over the
network: an HTTP HEAD plus a ranged GET, serial, five seconds per probe
with no aggregate deadline. Running it inline in GET /api/models made one
listing cost (entries x variants) round trips. The Manage page fetches
with items=9999, so at 200 declaring entries that is ~1000 serial probes,
minutes of a blocked handler and gigabytes of range traffic for a single
page load. Only one entry declares variants today, but the feature exists
so that many will.
Follow the precedent already set for VRAM estimates. The listing now
reports only has_variants, a length check on loaded metadata that touches
nothing, and GET /api/models/variants/:id returns the description for one
entry, mirroring estimate/:id in route shape, auth and error handling.
DescribeVariants itself is unchanged; only its caller moved.
The picker fetches lazily at the two points where a user asks to see
variants, opening the split-button menu and expanding the detail row, and
caches per entry for the page session. An entry declaring no variants
issues no request at all.
A spec counts real HTTP hits on the weight files, so it goes red if
description becomes reachable from the listing path again through any
caller.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): filter the model gallery to entries that declare variants
The gallery is heading towards showing parent entries and hiding the
individual builds they reference, so a user sees one row per model
rather than six quantizations of it.
Adoption is a single entry today, so defaulting to that would leave a
one-row gallery. This ships the migration-phase inverse instead: the
default is untouched, and a toggle narrows the list to only the entries
that declare variants. It previews the end state and changes nothing
until someone asks for it.
The filter is server-side, next to term/tag/backend/capability and above
the pagination arithmetic. The listing paginates at 9 items, so
narrowing on the client would leave totalPages and availableModels
describing the unfiltered set and hand the user empty pages. It selects
on HasVariants(), which reads already-loaded metadata, so it issues no
variant probes.
The parameter is named has_variants after the listing field it selects
on, and is compared against "true" like the other boolean query params
(all_users, save_checkpoint), so has_variants=false reads as absent.
With it omitted the response is byte-for-byte what it was before.
The control is the shared Toggle component, matching the fitsFilter
toggle already on this page: same wrapper class, same icon and label
shape, same localStorage persistence. Unlike fitsFilter it resets to
page 1 on change, which a server-side filter has to do.
Stacking the toggle with a tag or backend filter easily yields nothing
while one entry declares variants, so the empty state now names the
variants filter as the cause rather than leaving a user to conclude the
gallery is broken.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): render gallery model descriptions as Markdown
Gallery descriptions are Markdown, but the React UI dumped them raw, so a
model whose description opens with an ATX heading showed a literal
"# Qwen3.6-27B [](https://chat.qwen.ai)" in the list.
Full-description areas now render through renderMarkdown (marked +
DOMPurify), matching how Backends.jsx and the Manage detail panels already
handle the same content:
- Models.jsx expanded detail row
- VoiceLibrary.jsx voice detail header
The truncated one-line previews must not render block Markdown: a leading
"#" would become an <h1> and wreck the row height and rhythm. They get a new
stripMarkdown() helper instead, which reduces Markdown to a single line of
readable plain text. It is used for the cell text and for the title tooltip,
since a tooltip full of "[](url)" is no better than a cell full of it:
- Models.jsx gallery table description cell
- Manage.jsx model and backend resource-row descriptions
stripMarkdown walks marked's lexer output rather than running regexes over
the source, so what it strips is by construction what renderMarkdown would
have rendered, and it needs no new dependency. Output lands in JSX text
nodes, so React escapes it; no new dangerouslySetInnerHTML beyond the two
full-description sites, both of which run DOMPurify.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): strip Markdown from the backends table description cell
Commit b35d630cf fixed this for gallery models but left the Backends admin
page with the same asymmetry: its detail panel renders the description
through renderMarkdown, while the collapsed table row dumped the raw gallery
string into both the cell body and the title tooltip.
That is user-visible. 40 of the 949 entries in backend/index.yaml carry
Markdown - insightface uses inline code backticks, others use lists and
links - and backend descriptions also contain embedded newlines, so the
one-line cell showed literal syntax.
The cell now runs stripMarkdown over the description once and uses the
result for the text and the title, matching Models.jsx and the
ResourceRowDesc component in Manage.jsx. The '-' placeholder is preserved,
and now also fires when a description reduces to nothing after stripping.
The detail panel is untouched and no new dangerouslySetInnerHTML is
introduced: stripMarkdown output lands in a JSX text node, so React escapes
it.
Three Playwright specs cover it: a description with a heading, inline code
and a link renders as clean text with no literal syntax and no block
element in the cell, the title tooltip carries the same stripped text, and
a backend without a description still shows the placeholder.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ui(models): polish the variant detail view and scope rendered Markdown
The gallery detail pane rendered every field through the same two-column
label/value row, including the description. Multi-paragraph prose in a value
cell ran eight rows tall at the top of the pane on a ~1200px measure, breaking
the grid's rhythm exactly where the eye enters. Move it into its own full-width
block above the table, capped at a 68ch measure, keeping the label.
Rendered Markdown had no scoped typography anywhere in the app, so a
description opening with `#` inherited the browser default 2em inside a 13px
surface while a `##` further down was indistinguishable from body text. Add a
reusable .markdown-body block mapping h1-h6, paragraphs, lists, links, code,
blockquotes, images and tables onto the existing type scale, and apply it to
every renderMarkdown() consumer: the models detail, the backends detail, both
Manage details and the voice library detail.
Rebalance the variants list so the name leads. Backend and size drop from
badge/secondary weight to muted metadata; the FITS badge goes entirely, since
it was true of nearly every row and so said nothing, while the variant that
does not fit keeps a warning badge and a dimmed name. AUTO-SELECTED stays
marked because it answers what a plain Install produces. Rows share the
parent's grid tracks via subgrid so name, backend, size and status line up
down the list instead of raggedly following name length.
Finally, make each variant row actionable. It looked like a list of choices
but was inert text, with per-variant install hidden behind the split-button
chevron elsewhere; each row is now a button onto the existing
handleInstall(modelId, variant) path, with hover, keyboard focus and a
disabled state while an install is in flight.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): collapse the listing to one row per model
The listing supported has_variants=true, which narrowed to entries that
DECLARE variants. With adoption at three entries that showed three rows,
which is useless; it was always a placeholder.
Replace it with the view that is actually useful: the deduplicated
gallery. Show every entry installable in its own right and nothing twice,
which means the parents plus every entry nobody references, and hide only
the builds another entry already offers as a variant, since those are
reachable through their parent.
The parameter is renamed to collapse_variants accordingly: the filter is
no longer a predicate on a row's own metadata but a view over the whole
gallery. Default stays off, so the response with the parameter absent is
unchanged.
VariantReferencedIDs never reports an entry that declares variants of its
own, so parents are always visible. That guarantees every hidden entry
has a visible entry offering it, and no chain can strand a row. Variant
resolution already refuses to install such a reference, but the listing
has to stay coherent in the presence of a gallery that has one rather
than silently swallowing entries. Self-references and dangling references
hide nothing.
The referenced set is computed over the whole gallery rather than over
what the other filters left, so an entry is hidden because a parent
offers it and never because of what the user searched for. The pass is
over metadata already in memory: it resolves nothing over the network and
triggers no variant description or size probe, so the listing's zero-probe
contract still holds.
The UI toggle keeps its behaviour (persistence, page reset, clear
filters) and becomes "One row per model", which says what the user gets.
Its localStorage key moves too, since the stored value meant a different
filter.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): show the collapsed model listing by default
The gallery listing is what a user reaches for to answer "what can I
install". Answering that with several rows for the same model, one per
build, makes the reader do the deduplication the collapsed view already
does, so the collapsed view is the one to land on.
The UI now asks for collapse_variants=true unless the toggle says
otherwise. The server default is deliberately untouched: a request with
the parameter absent still returns the full listing, because other API
clients depend on that response and collapsing it under them would be a
breaking change. Opting out omits the parameter rather than sending
false, so it asks for exactly the listing everyone else gets.
The stored preference changes vocabulary from '1'/'0' to 'on'/'off'. The
previous build wrote it from an effect that runs on mount, so a stored
'0' recorded that the page had been opened rather than that anyone chose
the expanded view, and honouring it would pin every earlier visitor to a
default they never picked. Only the new vocabulary counts as a choice;
a legacy '1' meant the collapsed view and is what the new default gives
anyway, so no earlier deliberate choice is lost.
Collapsing being the default also changes what the empty state may say
about it. An opted-into filter can be named as the cause of an empty
result; a default cannot, so the filters keep the top line and the
collapsed view drops to a hint below it, shown only once filters are
narrowing the set. For the same reason "Clear filters" now restores the
collapsed default instead of switching it off, and the toggle alone no
longer counts as a filter worth offering to clear.
The label stays "One row per model": it describes the view the user is
looking at rather than an action, so it reads the same whether it is
opted into or out of.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* gallery: group alternative builds of the same weights under variants
Sweep the gallery for entries that are alternative builds of the same
weights (different quantization, precision, or runtime format) and declare
them as variants of a single parent row, so the listing offers one row per
model instead of one row per quantization and the installer picks the
largest build that this host can actually run.
41 families over 95 entries, turning 54 entries into variants.
The parent is the bare-named entry wherever one exists, so nothing changes
about what any existing entry installs. Ranking already selects the largest
fitting build regardless of which entry is nominally the parent, so the
parent only decides the pathological case where nothing fits. For the ten
families that have no bare-named entry, the smallest build is the parent,
since that is the one that has to install when nothing fits.
Grouping was verified against the actual model filenames rather than the
entry names alone. Different parameter sizes, languages, finetunes, and
products that merely share a name prefix are left as separate rows: the
qwen3.6 APEX and pi-tune finetunes, the DFlash and MTP speculative-decoding
pairings, English-only versus multilingual Whisper, the QAT versus non-QAT
Gemma 4 weights, and the abliterated FLUX build are all distinct models.
Six parents define YAML anchors that other entries pull in with a merge key,
which would have handed their variants to every merging child. For the two
depth-anything anchors that would have made fourteen unrelated entries
advertise the base model's builds as their own. All 26 merging children
therefore carry an explicit empty variants list, which overrides the merged
key and is equivalent to the key being absent.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): rank model variants by host backend preference
Variant auto-selection filtered candidates by whether their backend can
run on the host, then ranked the survivors by size alone. The backend
never influenced the choice beyond that gate, so a Mac offered both an
MLX build and a llama.cpp build kept neither filtered and installed
whichever was larger, leaving the native accelerated runtime unused. The
same held for CUDA against CPU on NVIDIA and ROCm against Vulkan on AMD.
Rank by the host's backend preference between the fit tier and size: fit
stays a filter, preference decides among the builds the host can equally
hold, and size still separates builds on equally preferred runtimes.
The preference data stays in one declarative table in pkg/system, now
read by a prefix lookup instead of a switch, so adding a capability or
reordering one host's runtimes is a one-line edit and the gallery's
ranking code carries no per-backend branching. MLX joins the metal rule
ahead of metal itself, which is inert for the existing alias-resolution
consumer because no alias group holds a candidate named for mlx.
An unrecognised backend, an unrecognised capability and an absent
preference list all collapse to the previous size-only ordering rather
than erroring or dropping candidates.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): rank variants by engine name, not backend build tag
Variant auto-selection ranked candidates with
SystemState.BackendPreferenceTokens, but that function and the variant
ranker speak different vocabularies.
BackendPreferenceTokens returns BUILD TAGS ("cuda", "rocm", "sycl",
"vulkan", "metal", "cpu"). It exists to match installed backend build
directory names like "llama-cpp-cuda-12" during alias resolution in
ListSystemBackends. Variant ranking instead matches a gallery entry's
`backend:` value, which is an ENGINE NAME: "llama-cpp", "vllm",
"vllm-omni", "sglang", "mlx" and the rest. No engine name in
gallery/index.yaml contains "cuda", "rocm", "sycl" or "vulkan".
preferenceRank matches by substring, so on an NVIDIA host the tokens
[cuda, vulkan, cpu] matched neither "llama-cpp" nor "vllm", every
candidate scored identically and size alone decided. The NVIDIA, AMD,
Intel, darwin-x86 and vulkan rules were all inert. Only metal appeared
to work, and only because the token "mlx" happens to equal an engine
name. The mismatch does not error, it silently deletes the feature.
Separate the two vocabularies. backendBuildTagPreferenceRules keeps the
build tags and its original output for every capability, including
metal, whose "mlx" token is removed again; its alias-resolution consumer
is byte-identical to before. engineNamePreferenceRules is new, holds
engine names, and is read by the new EnginePreferenceTokens, which
HostResolveEnv wires into the renamed ResolveEnv.EnginePreference. Both
tables sit adjacent under one block comment naming each vocabulary and
each consumer, and share one lookup helper so their semantics cannot
drift.
On NVIDIA the order is vLLM, then SGLang, then llama-cpp: vLLM is the
throughput engine and a model published with a vLLM build is published
that way because that build is the one worth running. AMD and Intel get
the same order, since rocm and intel builds of both serving engines
ship. Metal prefers mlx over llama-cpp. Vulkan prefers llama-cpp, the
only LLM engine with a Vulkan build. darwin-x86 and unknown
capabilities are deliberately absent rather than guessed at, degrading
to the size-only ordering that predates preference.
preferenceRank stays generic and names no engine and no capability, so
adding a runtime remains a one-line table edit.
Specs pin the NVIDIA and metal rules through the live table and the real
HostResolveEnv wiring, so emptying the engine table or wiring the build
tag source back in both go red. A regression table asserts
BackendPreferenceTokens' original output per capability, and mirrored
locks assert neither table carries the other's vocabulary.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: record that variant selection ranks by engine before size
A gallery entry can now declare variants, and selection ranks the builds a
host can run by engine preference before size. Nothing told a contributor
adding a backend that engineNamePreferenceRules exists, so a new engine would
silently rank below every known one and lose to whatever build happened to be
larger on hosts where it should have won.
Document the step where a backend is added, warn against the sibling
backendBuildTagPreferenceRules table (build tags, not engine names: the wrong
table matches nothing, scores every candidate equally and disables the
preference without erroring), and index it from AGENTS.md.
Fix the authoring and user docs, which still claimed the largest surviving
build wins. An author grouping builds under one entry has to be able to
predict what a user gets, and size alone no longer decides it.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(cli,mcp): describe variant auto-selection as preference before size
The CLI flag help and the install_model tool schema both still said
auto-selection takes the largest build that runs. Ranking now puts engine
preference ahead of size, so on NVIDIA a vLLM build wins over a larger
llama.cpp one. An assistant reading the old schema would tell users the
wrong thing.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): prefer llama.cpp over GPU serving engines on hosts with no GPU
engineNamePreferenceRules had no row for the "default" capability, which
getSystemCapabilities() returns both when no GPU is detected and when a GPU
is present but under the 4 GiB VRAM floor. A missing row yields an empty
preference list, which preferenceRank reads as "score everything equally",
collapsing variant selection to size alone.
That would be harmless if the hardware filter dropped GPU serving engines on
such a host, but it does not. IsBackendCompatible derives support from the
engine NAME, and "vllm" and "sglang" contain none of the darwin, cuda, rocm
or sycl tokens it keys on, so they fall through to its closing "return true".
A vLLM variant therefore survives on a CPU-only box and wins whenever its
build is the larger of the two on offer: the machine installs vLLM in
preference to llama.cpp.
darwin-x86 had the identical hole. It was documented as a deliberate omission
because nothing accelerates on an Intel Mac, which is true about acceleration
and wrong about consequence: with every engine tied, download size decides.
Add rows for both putting llama-cpp first. The GPU engines are enumerated
behind it rather than left unmatched: an unmatched engine already ranks below
every listed one, so llama.cpp would win either way, but unmatched engines
also tie with each other and let size decide among them. Naming them fixes
that order. MLX is left off the darwin-x86 row on purpose so it ranks last,
since IsBackendCompatible admits darwin-tokened engines on that capability
even though MLX needs Apple silicon.
Preference orders survivors and never filters, so a model published only as a
vLLM build is still installed on a host with no GPU; there is a spec for it.
Surveyed every other value getSystemCapabilities() can return. nvidia, amd,
intel and vulkan have rows; the l4t and cuda-refined values reach the nvidia
row by prefix; "apple" and "" cannot reach the vendor fallthrough because the
darwin and no-GPU branches return earlier. default and darwin-x86 were the
only live holes.
BackendPreferenceTokens and its build-tag table are untouched, and
preferenceRank stays generic, naming no engine and no capability.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* gallery: prefer speculative-decoding builds when they fit
Rank serving features between engine preference and size, so a host that can
hold a DFlash or MTP build of a model's weights installs it instead of the
plain build. Both answer faster for the same output, so whenever one survives
the filters there is no reason to take the plain build.
Precedence is now fit, then engine, then serving feature, then size. Engine
outranks the feature deliberately: a serving feature makes the right engine
faster, it does not make a wrong engine right, so a plain vLLM build still
beats a DFlash llama.cpp build on NVIDIA. Fit outranks both, and a drafter
pairing is strictly larger than the plain build, so the existing size filter
drops it on a host too small for it before this axis is consulted.
The order lives in a third preference table in pkg/system, alongside the build
tag and engine name tables. It is the odd one of the three: not keyed by
capability, because no hardware prefers a plain build over an equivalent
faster one, and matched against whole segments of a gallery ENTRY NAME rather
than as a substring of a backend value. Nothing on a gallery entry declares a
serving feature, and tags are not a usable substitute: gemma-4-e2b-it:sglang-mtp
carries an mtp tag while ornith-1.0-9b-mtp and qwen3.6-27b-nvfp4-mtp carry
none. Entry names are author-supplied free text, unlike the closed engine
vocabulary, so a short marker can turn up inside an unrelated word and whole
segment matching is what keeps smtp-assistant from ranking as an MTP build.
The block comment over the tables now documents all three together and states
what each is matched against; the ranking code names no feature, so adding one
stays a one-line edit to the table.
29c49203b rejected these entries as serving configurations rather than
alternative builds of the same weights. The definition is now "alternative ways
to serve the same model", which includes them, so regroup 14 entries under 12
parents. Judged by the files each entry points at: the qwen3.6, qwen3.5, qwen3
and deepseek pairings are the base GGUF plus a drafter, the gemma-4 QAT MTP
entries are the same QAT weights at a different quantization plus an MTP
drafter, and the two sglang MTP entries describe themselves as the same model
served with speculative decoding. Left separate: qwen3.6-27b-mtp-pi-tune, a
finetune with its own weights, and every entry whose base model LocalAI does
not ship as its own row, which is the whole Qwopus line plus gemmable-4-12b-mtp,
mimo-7b-mtp:sglang and qwen3.5-4b-dflash.
None of the twelve parents defines a YAML anchor, so no variants key can leak
through a merge key and no empty override was needed this time. The index was
edited by line insertion only.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test: check env restore errors in capability and variant specs
errcheck flagged ten unchecked os.Setenv and os.Unsetenv returns in the
specs added while the pre-commit hook was being skipped. Restoring an env
var is exactly the place a silent failure leaks state into the next spec,
so assert on it rather than suppressing the linter.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): make the mtp tag authoritative for serving-feature ranking
Variant auto-selection ranks survivors by fit, then engine, then serving
feature, then size. The serving-feature lookup read only whole alphanumeric
segments of a variant's entry name, because tags were inconsistent: every
dflash entry carried a dflash tag, but only 7 of 20 MTP entries carried an
mtp tag.
Tag the 13 untagged MTP entries, then teach the lookup to read tags as well
as names. A tag is now the authoritative signal and is compared whole and
case-insensitively, which is safe precisely because a tag is a deliberate
declaration rather than free text: there is no word-inside-a-word failure
mode, so the segment splitting the name half needs is unnecessary there.
The name check stays as a fallback rather than being replaced. Switching to
tags only would have regressed the six already-grouped entries on the day it
shipped, and would depend on tagging discipline that does not exist yet.
The lookup still names no feature, so adding one remains a one-line edit to
servingFeaturePreferenceTokens.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): make a declared tag the sole serving-feature signal
Variant auto-selection ranks survivors by fit, then engine, then serving
feature, then size. The serving-feature lookup recognised a speculative build
by either a declared tag or a whole segment of its entry name. Drop the name
half: a tag is now the only signal.
A name is author-supplied free text and a naming convention is not a contract,
so reading a marker out of one infers a capability nobody declared. The gallery
already had the failure in it: the four NVFP4 entries name MTP-bearing weights
while setting no option that enables speculative decoding, and being live
variants they were winning the feature axis without answering any faster.
overrides.options was considered as the replacement and rejected. It carries
spec_type:draft-mtp / spec_type:draft-dflash, which is what actually turns the
feature on, but that spelling is llama.cpp's config vocabulary: ds4 spells the
same feature mtp_path and sglang spells it speculative_algorithm in a
referenced config. Keying a cross-backend ranking decision on one backend's
option syntax would rank the other backends' builds as plain. Options are the
curation-time check instead, and never reach the selection logic.
With no fallback left, tag correctness is load bearing, so audit every entry
against the rule "tagged when the entry configures that feature, in whatever
vocabulary its backend uses". Three entries configure MTP untagged and gain the
tag (hy3, glm-5.2, qwythos-9b-claude-mythos-5-1m, all spec_type:draft-mtp with
no marker in their names). Four carry the tag while configuring nothing and
lose it: qwen3.6-27b-nvfp4-mtp, qwen3.6-35b-a3b-nvfp4-mtp,
qwopus3.6-27b-coder-mtp-nvfp4 and qwopus3.6-27b-v2-mtp-nvfp4, whose only option
is use_jinja:true. The dflash side was checked independently rather than assumed
consistent: all five dflash entries declare spec_type:draft-dflash and all five
are tagged, so it needed no edits.
Four entries keep a tag that a literal spec_type-only reading would strip,
because they configure MTP through a different backend: deepseek-v4-flash-q2-mtp
via ds4's mtp_path/mtp_draft, and the three sglang entries via
speculative_algorithm in their referenced configs. Stripping those would
contradict the reason spec_type was rejected as the signal and would demote four
genuinely faster builds to plain.
The index was edited by line insertion and deletion only, never round-tripped
through a serializer. A resolved-tag diff across all 1272 named entries, taken
after merge keys are applied, shows exactly these 7 changing and no entry
gaining or losing a tag through an anchor.
The two specs that pinned the name fallback are inverted rather than deleted,
since a name silently promoting a build is the regression worth guarding. The
whole-token guard survives on the tag path, where smtp must still not match mtp.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): make deepseek-v4-flash variant targets installable
Clicking install on deepseek-v4-flash failed with "invalid gallery model".
The parent entry is fine, but all four entries it was grouped with declared
neither url: nor config_file:, and applyModel needs one of the two to have
anything to build a config from. They carry urls: (plural), the informational
HuggingFace link list, which is a different field. None of the four was ever
independently installable, so grouping them routed a previously-working
install into a broken entry.
Give each the url: the parent already resolves through. virtual.yaml is a
no-op base, and applyModel passes overrides to InstallModel separately from
the fetched config, so backend: ds4, the parameters and the ssd/mtp options
all still land exactly as authored. This is the same pattern the parent and
many other GGUF entries in the index already use.
Add the lint rule that should have caught this. checkVariantReferences only
proved a target exists and is not itself a parent, which is structural
validity: an entry can exist, declare no variants, and still be
uninstallable. checkVariantTargetsInstallable mirrors applyModel's
precondition instead, and names the parent, the target and the missing
fields, because whoever hits it is reading a gallery entry and has no reason
to know applyModel exists.
The two index-driven resolution specs live in their own Ordered container:
an Ordered container stops at its first failure, so sharing one with the lint
rules let a lint breach skip them silently.
Nine further entries gallery-wide have the same defect and are unrelated to
variants, so they are broken installs that predate this branch. They are left
alone here rather than buried in a regression fix, and widening the rule to
cover every entry is deferred with them so the gate can ratchet up in one
step instead of needing a skip list.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): install entries with no url or config_file on an empty base
applyModel had three branches: fetch a base config from url:, build one from
an inline config_file:, or fail with "invalid gallery model". An entry
declaring neither is now installed on an empty base config, with overrides:
and files: supplying everything.
This is what the ~345 entries pointing at gallery/virtual.yaml were already
getting. That stub is five lines carrying name, description and license.
description and license are overwritten from the gallery entry immediately
after the fetch, and the name never reaches disk because InstallModel prefers
the install name. Crucially applyModel passes model.Overrides to InstallModel
as a separate argument rather than merging it into the fetched config, so
nothing an author writes depends on that base existing. The fetch bought a
round trip to GitHub and nothing else.
That makes f4ef80173 the wrong fix, so it is unwound. The four url: lines it
added to the deepseek-v4-flash variants are reverted: they are a pointless
network fetch now, and the family installs without them.
Relaxing the branch would hide a real authoring mistake, so a payload rule
replaces the base-config rule. An entry with no url, no config_file, no
overrides and no files installs nothing and would leave an empty model
directory while reporting success, so it is refused by name. The caller's
request counts toward the payload, because its overrides and files are merged
into the install exactly as the entry's own are. urls: (plural) is the
informational link list and does not count, which is what the four entries
that shipped broken had and why they were still uninstallable.
checkVariantTargetsInstallable asserted every variant target declares a url:
or a config_file:, which is no longer true and would now reject correct
authoring. checkEntriesInstallSomething pins what survives instead, and covers
every entry rather than only variant targets: the hazard is a half-written
stanza and a parent can be one as easily as a target. The old rule was scoped
to targets precisely because nine unrelated entries would have failed a
gallery-wide version; those nine are valid now, so the deferred ratchet
happens here in one step. 1280 entries, zero violations.
Those nine (aurore-reveil_koto-small-7b-it, lfm2-1.2b, the six liquidai_lfm2
entries and deepseek-v4-pro-q2-ssd) become installable for free. Each carries
overrides: and files:, and one of them is driven through the real install path
in a spec.
The no-fetch spec is paired rather than bare: an assertion that nothing was
fetched proves nothing unless something could have been, so a control runs the
same fixture with a url: pointing at a base config that is not there and
asserts the install fails. Only then does the identical fixture without the
url passing mean the read was skipped.
Follow-up, deliberately not here: the ~345 entries still naming virtual.yaml
can drop their url:. That is 345 index edits with their own risk, and mixing
them in would bury this change.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ui(models): let search bypass the variant collapse, drop the toggle
The models page collapsed the gallery to one row per model by default and
offered a toggle to see every individual build. Because the collapse composed
with the search term, a build another entry offers as a variant could not be
found by typing its name, so the toggle was the only way to reach those builds
in the UI. A user who typed a name they knew existed got "no models found",
which reads as "that model does not exist".
Collapse is for browsing; search is for finding. An explicit search term now
bypasses the collapse in the listing handler, so a name lookup returns matching
entries whether or not a parent offers them. The term is trimmed once at the
top of the handler, so whitespace is neither a search nor a bypass; previously
an untrimmed blank term also narrowed the listing to whatever contained a
space. Tag and backend deliberately do not bypass: they refine a listing the
user is still reading rather than name an entry already known to exist.
That makes the toggle redundant, so it goes, along with its i18n strings in all
six locales, its localStorage persistence, its participation in "Clear filters"
and the empty-state hint telling users to turn it off. The hint was doubly
stale: it pointed at a control that no longer exists, and it was untrue exactly
when a user has a search term, since searching now sees every build. The page
always requests the collapsed listing.
The stored preference key is left inert rather than cleaned up: nothing reads
it, so a user who had the toggle off simply gets the collapsed view.
collapse_variants stays on the API, off by default, because other clients want
either view and the UI dropping its control is no reason to remove a working
parameter.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): give the models gallery filter form a deliberate structure
The filter area had accreted controls into one undifferentiated flow. The
"Fits in GPU" toggle and the backend select were direct children of
.filter-bar, the same wrapping container as the 18 taxonomy chips, so their
position was decided by how many chips happened to wrap at the current width
rather than by any layout intent. At narrow widths they were pushed past the
right edge of that container's horizontal scroll and became unreachable
entirely.
Restructure into three bands inside the house .filter-bar-group wrapper that
components/FilterBar.jsx already uses on Backends and the System tabs:
1. query scope: search plus the backend select
2. taxonomy: the chip row, alone, free to wrap
3. refinements: fits-in-GPU and context size, under a hairline rule
The backend select leads the chips rather than trailing them because picking a
backend disables the use cases that backend cannot serve, so it gates the row
below it. Fits-in-GPU and context size share a band because they are one
control group: the context size is the length the VRAM estimate is computed at,
and that estimate is what the fits filter tests against.
Chips had no visible keyboard focus indicator. The global focus ring is wrapped
in :where(), so it carries the specificity of a bare :focus-visible, ties with
.filter-btn and loses on source order, leaving focused chips showing their
resting drop shadow. Restate the ring where it outranks both resting and hover.
Also: aria-pressed on the chips, a real label association and aria-valuetext on
the context slider (it steps over an index, so it announced "2"), disabled chip
styling moved off inline styles, a prefers-reduced-motion block for the chip
transition, and the hard-coded English "Context:" moved into all seven locales.
No behaviour change: same filters, same state, same requests. Page reset on
change, localStorage persistence and "Clear filters" verified unchanged.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): let the models recommendations panel fade into the background
The "Recommended for your hardware" strip rendered at full height on every
visit regardless of how many models were already installed, costing 186px at
1600px wide (287px at 1100px, where its cards wrapped to two rows) and pushing
the first gallery row to y=554 / y=703.
Make its prominence track how much the user still needs it. The panel now
defaults to a one-line summary once anything is installed, and both the
collapse choice and the existing dismissal persist:
collapsed = explicit user choice, if one exists
: installedCount > 0
The preference is three-valued on purpose. A boolean cannot tell "the user
expanded it" apart from "the user has never chosen", and those need opposite
handling when the installed count later crosses zero: someone who deliberately
opened the panel on an empty instance should not have it collapse out from
under them when their first model finishes installing.
Collapsed keeps the card, icon, title and a suggestion count, so the panel is
recovered by clicking what you are already looking at rather than by hunting.
Expanded is unchanged, because for a user with nothing installed it was never
the problem. Collapsed reclaims 145px at 1600 and 420, and 246px at 1100.
Models.jsx gains a statsLoaded flag: stats initializes to installed:0, so
reading it before the fetch resolves would render expanded and collapse a frame
later, which is exactly the layout shove this removes.
The dismissal key moves to the page's localai-models-* convention; the old
localai_rec_models_dismissed is still read, never written, so an existing
dismissal is honoured rather than resurrected by the rename.
Accessibility: the disclosure is a real button whose accessible name is the
visible title alone, with state on aria-expanded and aria-controls resolving in
both states, because the grid is hidden via the hidden attribute rather than
unmounted. That also keeps the four install buttons out of the tab order while
collapsed. The app's global focus ring applies; no per-component outline is
added, per the warning in App.css. Reveal animates opacity and transform only,
never height, and both it and the chevron rotation are disabled under
prefers-reduced-motion.
Only en had a recommended block, so the other six locales were falling back to
English for the whole panel. Translated the complete block rather than adding
one orphaned key to files that would still render the title in English.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(downloader): recover from a leftover .partial on non-HTTP URIs
An interrupted download leaves a `<file>.partial` behind. The partial
handling in DownloadFileWithContext gated resume on `err == nil &&
uri.LooksLikeHTTPURL()`, so for any URI that is not literally http(s)
the branch fell through to `else if !errors.Is(err, os.ErrNotExist)`,
which with a nil err is true. The download then failed with an error
wrapping nil:
failed to check file ".../Ternary-Bonsai-27B-Q2_g64.gguf" existence: <nil>
Every gallery file URI uses `huggingface://`, so a single interrupted
download made that model permanently uninstallable until someone
deleted the partial by hand. The `<nil>` in the message compounded it
by pointing debugging at a filesystem failure that never happened.
Restructure the handling as an explicit switch over the four real
states: partial exists and is resumable, partial exists and is not
resumable (discard and restart, as already done for an HTTP server
without range support), no partial, and a genuine stat failure. The
error branch is now only reachable with a non-nil error, names the
path that was actually stat'd, and wraps with %w.
Discarding is required for correctness and not merely convenience: the
writer opens the partial with O_APPEND, so an un-resumed download would
concatenate a fresh body onto stale bytes.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): tell the models gallery's variant rows apart, and let browsing see every build
Both variant surfaces rendered name, backend and size. For two builds of one
model that is close to no information: a variant exists precisely because the
same weights are offered another way, so the backend usually matches and the
sizes usually land within a few hundred megabytes. Comparing
ternary-bonsai-27b-pq2 against ternary-bonsai-27b-q2-g64 meant reading two names
that differ by a suffix nobody has defined anywhere in the UI.
Report the quantization and the serving features on VariantView, and derive both
server-side from the referenced entry rather than parsing names in the browser,
so every client reads the same format out of the same file the installer will
hand the backend.
Quantization comes from overrides.parameters.model first, falling back to the
file list. That order is load bearing: entries routinely ship a vision tower
alongside the language model at a different quantization, so reading the file
list first reports the mmproj's format. Matching walks `-` and `.` delimited
segments right to left; `_` deliberately does not split, because it separates the
parts INSIDE a quant token and splitting on it reports Q4 for a Q4_K_M build. A
second, looser pass takes a segment's `_`-delimited tail, which catches the
gemma-4-E2B_q4_0-it.gguf style; it runs second so a precise match can never lose
to a fuzzy one further right in the name. An entry naming no format reports
nothing, which is the honest answer for a backend served from a directory of
weights.
Features are the same tag-against-vocabulary match servingFeatureRank already
ranks on, over the same host preference list. A build can therefore never be
shown as faster than one selection did not actually reward, nor rewarded without
being shown; a spec pins that agreement rather than trusting it.
The compact dropdown gets the quantization on its meta line and the bare feature
token. The detail row, which has the room, gets the quantization as its own
monospaced column so precision lines up down the list, and the feature spelled
out, because DFLASH names nothing to a user who has not met it. The referenced
entry's description stays out of both: the detail row already renders the
parent's prose above the table, and a second block per variant would push a
three-variant list past a screen to restate what the columns now say precisely.
The collapse toggle comes back. 462583f38 dropped it once search bypassed the
collapse, on the reasoning that nothing was unreachable any more. That holds for
finding a build whose name you know and does not hold for browsing: no sequence
of actions enumerated the 68 builds the default view hides. Collapse is for
browsing and search is for finding, and the toggle was the browsing half.
It goes in the refinements band 0d4823362 established, not back among the
taxonomy chips where its position depended on how many chips happened to wrap. It
leads that band because it decides how many rows the other two refine over, and
because unlike fits-in-GPU it is unconditional: a host with no GPU still browses.
The search bypass is untouched and re-checked by a spec in the toggle's default
state, since restoring the control must not restore the dead end it replaced. The
empty-state hint returns but only without a search term, because a term bypasses
the collapse and the hint would otherwise point at a control that cannot change
the result. The stored preference reads 'on'/'off' only: an older build wrote
'1'/'0' from an effect that ran on mount, so those record that the page was
opened, not that anyone chose a view.
Also fixes a latent flake it exposed. The collapse_variants spec compared whole
response bodies byte for byte, and the listing envelope carries live host
telemetry that drifts between two calls milliseconds apart, so it was asserting
on the machine's memory pressure. It now compares everything the parameter
governs -- the entries, their serialization and the paging -- and is green 25/25
where it was failing about one run in three.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): let the models gallery show a variant's full details
The variant list in an entry's expanded detail row says how the builds
differ: name, backend, quantization, size, and the auto-selected, base
and serving-feature markers. It cannot say what any one of them is. A
variant's own description, tags, license, source links and file list are
unreachable anywhere in the UI, because while the collapse is on a
variant has no gallery row of its own.
Give each variant row an info control that reveals its entry, rendered by
the same ModelDetail a top-level row gets, so a field added to the detail
view appears here too. variantData is withheld from the nested render: a
variant may declare variants of its own, and recursing would nest a
picker inside a picker two levels deep already.
An inline disclosure rather than a modal. The control sits inside a table
row that is already expanded, inside a variant list within that; a dialog
opened from there stacks a dismissal on a dismissal for a handful of
extra fields about the entry the user is already reading, and breaks the
page's own expand idiom. The third level is carried by an inset and a
left rule instead of another card.
The entry is fetched by exact name from the listing, once, on first use.
The listing already returns every field the detail view renders, and a
search term bypasses the variant collapse server-side, so no new endpoint
is needed and neither the listing nor DescribeVariants gains any work.
Expanding a row costs nothing; a variant nobody opens costs nothing. A
name the listing no longer returns is stated, not blanked: an empty panel
reads as a rendering fault rather than as a lookup that came back empty.
The control is a sibling of the install button, not a descendant, so
asking about a build can never install it.
The variant list keeps its content-sized columns via a trailing filler
track instead of max-content sizing, so the rows are unchanged while the
panel spanning them gets the pane width its file table needs.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): let search respect the collapse instead of switching it off
The models listing collapsed to one row per model, and an explicit search term
turned that off wholesale. Searching while collapsed therefore answered with the
individual builds a parent already offers, which are exactly the rows the view
the user asked for has no place for: typing "mtp" returned
qwen3.6-27b-nvfp4-mtp, a row that is invisible the moment the box is cleared.
The bypass was the right shape of fix for the wrong half of the problem. What a
search must not do is answer "no models found" for a build the gallery does
hold; that does not require abandoning the grouping the user asked for.
So the term is now matched against every entry either way, hidden builds
included, and the collapse decides how a match is reported rather than which
matches exist. Collapsing stops being a filter that drops rows and becomes a
substitution: a match on a build another entry offers is reported as that entry,
the one installable in its own right. Nothing becomes unfindable and nothing
comes back that the requested view cannot show.
Substitution happens after search, tag and backend, so every filter is judged
against the build that really carries the name, tag or backend rather than
against a parent that merely offers it; the other order would let backend=vllm
match a parent whose own backend is something else. The price is that the
surfaced row shows the parent's own metadata while the match was on a variant,
which is what grouping means, and the alternative is claiming the gallery holds
no such build. It happens before the count and the page math, so both describe
the rows actually handed out rather than the matches that produced them.
A parent already in the result keeps its own position and absorbs its matching
variants there, which is what leaves the browsing listing ordered exactly as it
was; a parent surfaced only by a variant takes the position of the first variant
that surfaced it. Either way it appears once, however many of its builds matched
and whether or not it matched itself. Search preserves gallery order rather than
scoring, so a surfaced parent has a real position rather than an invented one.
VariantParents never reports an entry that declares variants of its own, so a
parent is never itself hidden and one hop always lands on a visible row. The
handler follows exactly one anyway: refusing the second is what makes a gallery
the linter would have rejected terminate rather than loop.
The empty-state hint pointing at the toggle goes with it for every server-side
filter. Substitution means a match is always reported as some row, so the
collapse can no longer be why a term, a chip or a backend came back empty, and
naming it there sends the user to a control that cannot change the result. It
survives for the fits filter alone, which runs in the browser after the
substitution and judges the surfaced entry's own size: there the build that fits
really can be filtered out along with a parent that does not.
Searching a build's exact name while collapsed now answers with its parent, so
the result no longer contains the string the user typed. That is intended, and
the row is the one they can act on, but it is a real rough edge: nothing on the
row explains the connection. Closing it properly means reporting which variant
matched so the UI can say so, which the listing does not do today.
ResetGalleryModelCache is added for tests. The model cache is a package global
keyed by nothing, so a background refresh one spec triggers can land in the
middle of the next and answer it with the previous spec's gallery; the extra
specs here made that fail about one run in five. It waits for the in-flight
refresh to publish before clearing, since clearing alone only narrows the
window.
Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The backend matrix path filter only matched files under a backend's own
directory, so a change to shared build infrastructure rebuilt nothing at
all: an empty matrix, every job green, and the change reaching no image.
PR #10946 fixed scripts/build/package-gpu-libs.sh shipping a partial
4-of-8 cuDNN library set, which mixed versions with the venv's pip cuDNN
and produced CUDNN_STATUS_SUBLIBRARY_VERSION_MISMATCH at inference time.
It merged 1h48m after the weekly full-matrix cron had already run, so no
backend image ever received the fix and nothing signalled that it had
been un-shipped.
Add a SHARED_BUILD_INPUTS table mapping each shared path to the narrowest
set of matrix entries it can honestly invalidate, plus a generic rule for
backend/Dockerfile.<x> (which each entry already names). A full matrix is
417 Linux + 56 Darwin builds, so package-gpu-libs.sh now rebuilds the 176
Python entries rather than everything. Unclassified files under
scripts/build/ fall back to a full rebuild deliberately: over-building is
recoverable, silently shipping nothing is not.
Extract the filtering logic to scripts/lib/backend-filter.mjs so it can be
unit-tested without bun, js-yaml or a GitHub API round-trip, and run those
tests from the existing lint workflow via `make test-ci-scripts`.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(distributed): reject wrong-model requests at the backend (#10952)
In distributed mode the controller caches a NodeModel row naming a backend's
host:port. A worker can recycle a stopped backend's gRPC port for a different
model's backend, and probeHealth verifies liveness rather than identity, so the
probe succeeds against whatever now occupies the port and the request is
dispatched to the wrong backend. The caller gets a silent wrong-model answer.
Nothing in the request could catch this: PredictOptions had no model field, so
model identity crossed the wire only in ModelOptions.Model at LoadModel time,
and the cached-hit path issues no LoadModel. Every backend's "model not loaded"
guard checks a nil handle, which a process holding a different model passes, so
the stale row was never dropped either.
Add PredictOptions.ModelIdentity and enforce it at the point of use:
- The controller populates it in gRPCPredictOpts from ModelConfig.Model, the
same expression ModelOptions feeds to model.WithModel and therefore the
same value the backend received as ModelOptions.Model. Both are read from
one config value in one function, so they are equal by construction and the
comparison cannot false-reject.
- Backends compare it against what they loaded and return NOT_FOUND with a
fixed sentinel. Enforced in pkg/grpc/server.go (27 Go backends), an
interceptor in backend/python/common (all 36 Python backends, no
per-backend change), and the llama-cpp / ik-llama-cpp / ds4 C++ servers.
That is every backend with real exposure: kokoros answers all four RPCs
with unimplemented and privacy-filter implements none of them.
- The router's reconcile drops the stale replica row on a mismatch, so the
next request reloads somewhere correct.
Empty means "skip the check" on both sides: a controller that predates the
field sends nothing, a backend loaded by such a controller has nothing to
compare, and the C++ server synthesizes PredictOptions internally for ASR. That
keeps upgrades working in both directions.
Scoped to the four PredictOptions RPCs. TTSRequest.model and
SoundGenerationRequest.model are deliberately NOT validated: FileStagingClient
already rewrites them to worker-local absolute paths, so in distributed mode
they already differ from the load-time value and comparing them would reject
valid requests.
IsModelMismatch requires both the NOT_FOUND code and the sentinel, unlike the
neighbouring helpers which accept either. insightface's Embedding returns
NOT_FOUND "no face detected" on a PredictOptions RPC, and a code-only check
would drop a healthy replica row on every faceless image.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* chore(deps): bump the pip group across 6 directories with 1 update
Bumps the pip group with 1 update in the /backend/python/ace-step directory: torch.
Bumps the pip group with 1 update in the /backend/python/llama-cpp-quantization directory: torch.
Bumps the pip group with 1 update in the /backend/python/longcat-video directory: torch.
Bumps the pip group with 1 update in the /backend/python/sglang directory: torch.
Bumps the pip group with 1 update in the /backend/python/trl directory: torch.
Bumps the pip group with 1 update in the /backend/python/vllm-omni directory: torch.
Updates `torch` from 2.10.0+rocm7.0 to 2.12.1+cpu
Updates `torch` from 2.10.0 to 2.12.1+cpu
Updates `torch` from 2.12.1 to 2.12.1+cu130
Updates `torch` from 2.9.0 to 2.12.1+cpu
Updates `torch` from 2.10.0 to 2.12.1+cpu
Updates `torch` from 2.7.0 to 2.12.1+cu130
---
updated-dependencies:
- dependency-name: torch
dependency-version: 2.12.1+cpu
dependency-type: direct:production
dependency-group: pip
- dependency-name: torch
dependency-version: 2.12.1+cpu
dependency-type: direct:production
dependency-group: pip
- dependency-name: torch
dependency-version: 2.12.1+cu130
dependency-type: direct:production
dependency-group: pip
- dependency-name: torch
dependency-version: 2.12.1+cpu
dependency-type: direct:production
dependency-group: pip
- dependency-name: torch
dependency-version: 2.12.1+cpu
dependency-type: direct:production
dependency-group: pip
- dependency-name: torch
dependency-version: 2.12.1+cu130
dependency-type: direct:production
dependency-group: pip
...
Signed-off-by: dependabot[bot] <support@github.com>
* fix(deps): preserve platform-specific torch requirements
Keep the 2.12.1 CPU bump only where uv resolves it cleanly, and restore ROCm, CUDA, MPS, and unrelated transformers constraints that Dependabot rewrote to incompatible wheel variants.
Assisted-by: Codex:gpt-5 [uv]
---------
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Every vibevoice requirements file pulled diffusers straight from
git+https://github.com/huggingface/diffusers. That branch now reports
itself as 0.40.0.dev0 and requires huggingface-hub>=1.23.0,<2.0, while
transformers>=4.51.3,<5.0.0 (which upstream VibeVoice mandates) still
caps huggingface-hub at <1.0. Because a git URL offers the resolver
exactly one candidate version, uv has nothing to backtrack to and the
install fails outright:
Because only diffusers==0.40.0.dev0 is available and diffusers==0.40.0.dev0
depends on huggingface-hub>=1.23.0,<2.0 [...] we can conclude that your
requirements are unsatisfiable.
This broke the vibevoice build on every variant - cpu (amd64/arm64),
cuda 12/13, l4t 12/13, intel and rocm, plus the darwin metal job - and
has been failing the weekly full-matrix rebuild for three weeks. It is
not caught by master pushes because backend builds are path-filtered
there, so it only surfaces on the Sunday cron and on release tags.
Use the PyPI package instead. That is what upstream VibeVoice declares
in its own pyproject.toml, and what every other LocalAI backend already
does - vibevoice was the only one tracking the git branch. With a real
release series available the resolver settles on diffusers 0.39.0 with
huggingface-hub 0.36.2 and transformers 4.57.6, and it can keep
backtracking on its own if upstream shifts again.
Verified with uv pip compile against cpu, cublas12, cublas13, hipblas,
intel, mps and l4t13: all resolve to that same coherent set. l4t12 only
resolves on aarch64, since its Jetson index ships no x86_64 torch wheel.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Bash] [uv]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Adds inference parameter defaults for the minimax-m3 model family and
includes a vendored patch of upstream llama.cpp PR #24523 to recognize
the minimax-m3 architecture. Once the upstream PR merges, the patch can
be removed and LLAMA_VERSION bumped normally.
Changes:
- backend/cpp/llama-cpp/patches/0001-add-minimax-m3-support.patch:
vendored patch from ggml-org/llama.cpp#24523 (Preliminary MiniMax-M3
support). Applied by prepare.sh during the build; keeps the pinned
LLAMA_VERSION pointing at the latest upstream tag.
- core/config/inference_defaults.json: add minimax-m3 family entry
(temperature=1.0, top_p=0.95, top_k=40, min_p=0.01,
repeat_penalty=1.0, matching the existing minimax defaults) and
register it in the patterns list before the shorter minimax-m2.7
entry for correct longest-match-first ordering.
Upstream: depends on ggml-org/llama.cpp#24523
Closes: https://github.com/mudler/LocalAI/issues/10820
Signed-off-by: Nandana Dileep <110280757+nandanadileep@users.noreply.github.com>
The worker's gRPC port allocator grew monotonically with no upper bound:
nextPort started at the base port and incremented whenever freePorts was
empty, and nothing checked 65535. Past that it handed out integers that
cannot be bound, surfacing as an opaque "backend won't start".
#10961 estimated this needed ~15,000 concurrent-peak allocations, i.e.
effectively unreachable. It is not, because of a second defect: the
"process died unexpectedly" branch in startBackend deleted the process
map entry without releasing its port at all. That port was leaked, never
quarantined and never reused. A crash-looping backend leaks one port per
restart, so a backend dying every 30s walks 50051 to 65535 in about five
days. The leak, not concurrent peak, is the realistic route to exhaustion.
Fixing the leak alone would have been wrong. Releasing that port makes it
re-bindable, and the death path is the one teardown path with no
request/reply to carry StoppedProcessKeys back to the controller (#10952's
eager row removal), so a stale NodeModel row could then resolve to a live
listener belonging to a different backend. probeHealth verifies liveness,
not identity, so the request is silently misrouted. The 15s port
quarantine does not cover this: the only reaper is the per-model health
check at ~45s, and it can be disabled outright. The residual was masked
only because the port was never rebound.
So both are fixed together:
- The allocator takes an explicit [basePort, LOCALAI_GRPC_MAX_PORT] range
and returns ErrNoFreePort naming the range, the live backend count, the
quarantined count, and the knob to raise. Exhaustion is now diagnosable
instead of surfacing as an unbindable port.
- Released ports carry per-key affinity: a port is offered back to the
process key that last held it before any other key. Process keys
(modelID#replica) and NodeModel rows (nodeID, modelName, replicaIndex)
are isomorphic, so a port that can only be re-bound by its previous
owner can only ever be named by that owner's row, which that key's
re-registration overwrites. Misrouting to a different model becomes
impossible by construction rather than by racing the quarantine timer.
Affinity is a preference, not a reservation: under range pressure an owned
port is stolen with a warning, because a guaranteed outage is worse than a
rare misroute window on a port long out of quarantine. Claiming a port
evicts its previous owner's entry, keeping ownership injective over ports
so the affinity map can never exceed the range width regardless of how
many distinct model keys the worker sees.
Ownership also expires. It is only load-bearing while a controller row
could still name the port, which the per-model reaper bounds at roughly
45s, so it lapses after five minutes and the port becomes ordinary free
space again. Holding it indefinitely would have made every distinct model
the worker ever served consume a port permanently: every release path is
keyed, so nothing would ever be unowned, the allocator would climb to the
end of its range on distinct-key count rather than concurrency, stealing
would become routine, and the steal warning would tell operators to widen
a range that was not the constraint. With expiry, reaching the steal
branch means the worker is genuinely out of concurrent capacity, so that
advice is correct when it appears.
Closes#10961Closes#10952
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(distributed): backend discovery hid worker-installed backends
Backend discovery endpoints filter on installed-state, which on a
distributed controller derives from the controller's own filesystem. A
backend lives on the worker node that runs it, so every backend an admin
installed on a GPU worker read as "not installed" and vanished from the
listing. #10947 fixed the sibling capability filter on the same endpoints,
so a fine-tuning-capable GPU worker now made the backend listable while
the installed-state filter still dropped it: the dropdown stayed empty.
The controller cannot derive this locally, but it already aggregates the
per-node view that GET /backends renders, so discovery reuses the active
BackendManager rather than growing a second path. Three surfaces shared the
root cause and route through the same helper now:
- GET /backends/available (Installed is now cluster-wide)
- GET /api/fine-tuning/backends
- GET /api/quantization/backends
The response stays a boolean rather than an installed-on-N-of-M count:
per-node install state is already served by GET /backends nodes[], and
per-node control by POST /api/nodes/:id/backends/install, so a summary is
all these dropdowns need.
A nil provider (single-node) leaves the local filesystem as the only source
and reproduces today's listing exactly, and a registry error degrades to
that same listing instead of blanking the catalog.
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(worker): reap deleted backends and stop models that live on a worker
Three related backend-lifecycle defects, all reachable from the same
production incident on a Jetson/Thor worker: a deleted backend's gRPC
process survived ~40 minutes with its directory removed from disk, a later
model load was routed to that orphan and failed with a certifi path pointing
into the deleted directory, and the admin could not stop the model because
the frontend reported it as not loaded.
1. backend.delete orphaned the process it claimed to delete
------------------------------------------------------------
s.processes is keyed by `modelID#replicaIndex` (buildProcessKey), so the
backend name never appeared in a key and was recorded nowhere on the
process. backend.delete resolved its target via isRunning/stopBackend, whose
prefix path only matches a bare *modelID* - a delete keyed on a backend name
resolved to zero keys, the stop silently no-op'd, and the files were removed
out from under a live process.
The install fast path then handed that orphan back out: it returns any live
process for the (model, replica) slot without checking which backend started
it, so a reinstalled variant inherited the deleted backend's port.
- Record backendName on backendProcess, threaded installBackend ->
startBackend.
- Add resolveProcessKeysForBackend, matching the recorded name and resolving
alias <-> concrete via ListSystemBackends *before* DeleteBackendFromSystem
erases the metadata that carries the alias. Alias resolution failure
degrades to name-only matching so a delete never fails on it.
- backend.stop goes through resolveStopTargets, which accepts a backend
name, a model name, or an exact modelID#replica key. Its payload field is
named "backend" but is published with all three meanings: the admin UI
sends a backend name, UnloadRemoteModel sends a model name, and the
router's abandoned-load reap (#10948) sends an exact replica key.
Narrowing it to backend names alone would strand the latter two.
backend.delete stays strict - its identifier is unambiguously a backend.
- Gate the install fast path on processMatchesBackend so a slot held by a
different backend is restarted rather than reused. Processes with no
recorded name (pre-upgrade) are accepted, so rollout does not restart
every running backend.
- stopBackendExact reports a real stop failure - the process still being
alive afterwards, which is precisely what finishBackendStop already
detects to keep the entry and its port reserved - and backend.delete no
longer replies success when it knew about a process and could not kill it.
"No process was running" stays a success but is logged, so the orphan case
is visible rather than silent.
2. /backend/shutdown reported a running model as missing
---------------------------------------------------------
ModelLoader.deleteProcess short-circuits on a miss in this replica's
in-memory store. In distributed mode the authoritative record of "is this
model loaded" is the shared node registry: a frontend replica that never
served the model itself (load balancer picked a peer, or the replica
restarted) has no local entry. The remote unload path that pkg/model
documents ("when ShutdownModel is called for a model with no local process,
UnloadRemoteModel is called") sat behind that short-circuit, unreachable in
exactly the case it exists for. #10865 reworked this function but kept the
short-circuit at the top, so the gap survived that refactor.
- deleteProcess consults the remote unloader on a local-store miss, via a
shared unloadRemote helper so this branch and the existing
no-local-process branch both prefer #10865's RemoteModelContextUnloader,
preserving force propagation across the distributed boundary.
- UnloadRemoteModelContext reports ErrRemoteModelNotLoaded when no node has
the model; it previously returned nil, making a no-op stop
indistinguishable from a real one. The converse case (nodes have it, none
could be stopped) already errors since #10865 joined the per-node
failures, so that half of the original fix was dropped as redundant.
- Only when the model is absent locally AND cluster-wide does the endpoint
report not-found, now 404 naming both scopes rather than a bare 500.
- modelNotFoundErr becomes the exported ErrModelNotFound so the HTTP layer
can map it without string matching; watchdog's identity comparison becomes
errors.Is.
3. Coverage for the bounded Free() that #10865 shipped untested
----------------------------------------------------------------
The original branch also bounded the pre-stop Free(), but #10865 landed that
fix first (workerBackendFreeTimeout, applied in both stopBackendExact and
handleModelUnload). That production change is therefore DROPPED here as
superseded - master's version is strictly better, since it also releases the
supervisor mutex across the call and keeps the port reserved until
termination completes.
What #10865 did not ship is a test, and the bound is load-bearing: the
router-side reap in #10948 sends backend.stop for an abandoned load, and
against a wedged backend an unbounded Free would swallow that stop before it
reached the process. Nothing failed if the bound regressed.
The spec stands up a real gRPC backend server whose Free handler never
returns - what a Python backend looks like when its single worker thread
(PYTHON_GRPC_MAX_WORKERS=1 on 37 backends) is occupied by a stuck LoadModel.
A stub socket is not sufficient and was tried first: without a completed
HTTP/2 handshake, gRPC's own ~20s connect timeout ends the call, so that
version passed against the very bug it targets. With the connection READY,
only the caller's deadline can end it, so the spec hangs to its 60s limit if
the timeout is removed and passes with it.
Its fixture process is deliberately never started. go-processmanager v0.1.1
writes Process.pid from readPID() without synchronization, so a live process
races its own monitor goroutine under -race - reproducible with a bare
Run()+Stop() and unrelated to this spec. Since
scripts/model-lifecycle-conformance.sh runs this package with -race and is
fail-closed, starting one would turn that gate red on an upstream defect. An
unstarted process still proves the point: the stop is reached and the slot
released, which is exactly what an unbounded Free prevents.
Verified: make lint (new-from-merge-base origin/master) reports 0 issues;
scripts/model-lifecycle-conformance.sh passes all three stages including the
FizzBee liveness check (1458 states, IsLive: true).
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): keep remote unload idempotent, ask presence separately
2035a4d25 made UnloadRemoteModel return ErrRemoteModelNotLoaded when no node
holds the model, so ShutdownModel could answer 404 instead of a misleading
500. That narrowed a shared adapter contract to serve one caller and broke
the documented idempotent-unload guarantee, which CI caught on PR #10956:
[FAIL] Node Backend Lifecycle (NATS-driven) > NATS backend.stop events
should be no-op for models not on any node [Distributed]
Expected success, but got: model not loaded on any node
The spec name states the contract outright. The matching unit assertion was
updated in that commit; this e2e one was missed because it lives under
tests/e2e/ with no build tags and does not run in package-scoped test runs.
Caller audit - who breaks when an idempotent unload becomes an error:
- pkg/model/watchdog.go:902 (LRU memory reclaimer) is the serious one. It
untracks a model ONLY when shutdown returns nil or ErrModelNotFound. A new
error type means the model is never untracked, so the reclaimer keeps
re-selecting the same entry and never reclaims - a live wedge whenever a
local store entry outlives the remote model.
- core/services/galleryop/managers_local.go:43 (DeleteModel) would warn on
every deletion of an already-unloaded model.
- core/services/modeladmin/{state,config,remote_sync}.go stop instances
best-effort against models that are frequently not loaded.
- deleteProcess itself: the no-local-process branch returns the unload result
directly, so a stale local entry for a model no longer on any node turned a
previously-successful cleanup into a failure.
Only ShutdownModel wants the distinction, and only on the local-store-miss
path. So the distinction moves to the caller instead of the contract:
- UnloadRemoteModel/UnloadRemoteModelContext return nil again when no node
has the model, and ErrRemoteModelNotLoaded is removed.
- New optional RemoteModelPresenceChecker (HasRemoteModel) answers the
question directly. deleteProcess consults it BEFORE unloading, because an
idempotent unload cannot report afterwards whether anything was stopped.
Absent locally AND cluster-wide is the only case that reports 404.
- A failed registry lookup is surfaced rather than reported as absence: an
unreachable registry is not evidence a model is gone, and answering a
confident 404 off a failed lookup is how an operator gets told a running
model does not exist.
- Unloaders that predate the extension keep working - deleteProcess attempts
the unload rather than refusing it - and compile-time assertions in the
nodes package now pin all three optional interfaces, since both are
consumed by runtime type assertion where drift degrades behavior silently
instead of failing the build.
The contract is now pinned at both levels that disagreed, each spec pointing
at the other: "with no nodes returns nil" in unloader_test.go and "should be
no-op for models not on any node" in node_lifecycle_test.go.
Verified: full distributed e2e suite 233 passed / 0 failed (the suite that
failed 232/1 in CI); pkg/model and core/services/nodes green; make lint
new-from-merge-base reports 0 issues.
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): drop replica rows when a worker stops a backend
A worker returns a stopped backend's gRPC port to its allocator as soon as
the process is confirmed dead, and hands it to the next backend that starts.
The controller's NodeModel row for the old address survives, and both
SmartRouter.probeHealth and the HealthMonitor per-model probe verify
liveness, not identity, so once an unrelated backend binds the recycled port
the stale row passes every check and the request is served by the wrong
backend instead of failing.
backend.delete is newly able to trigger this: before #10956 a delete never
actually stopped a process, so it never recycled a port. backend.upgrade has
the identical gap and always did — upgradeBackend force-stops every process
using the binary and starts none back up, while
DistributedBackendManager.UpgradeBackend never removes rows. model.unload is
the one path that gets this right today: it calls RemoveAllNodeModelReplicas
straight after StopBackend.
Report the process keys the worker terminated on the delete and upgrade
replies, and drop the matching rows in RemoteUnloaderAdapter, which already
holds a ModelLocator with RemoveNodeModel. All three call sites funnel
through that adapter, so no new interface, DB migration, or proto change is
needed. A key is reported only once its process is confirmed gone, so the
list stays trustworthy on the partial-failure replies too.
Old workers never populate the new fields. ReportsStoppedProcesses tells
"stopped nothing" apart from "does not report", so an old worker's silence
falls back to the pre-existing probe-based staleness recovery instead of
being mistaken for a completed cleanup.
Quarantine released ports for a short window as an interlock covering the
NATS round-trip between the worker freeing the port and the controller
dropping the row. It is deliberately not derived from HealthCheckInterval:
that cadence is operator-tunable and the per-model reaper can be disabled
outright, so coupling a worker-local constant to it would be silently wrong
on some clusters. Eager row removal is the fix; the delay only closes the
handoff gap.
Identity verification in probeHealth was considered and rejected: Health and
Status carry no backend identity, so it needs a proto change plus an
implementation in 36 Python and 4 C++ Health servicers, it is fail-open for
any backend not yet rebuilt, and the probeCache short-circuit means it would
not even execute during the 30s window where the misroute happens.
Fixes#10952
Refs #10954, #10956
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(deps): bump go-processmanager, assert real backend termination
go-processmanager wrote Process.PID from readPID() with no synchronization
while its own monitor goroutine cleared the same field on exit, so a bare
Run()+Stop() tripped the race detector without any concurrent access from
the caller. LocalAI hit this on every backend stop.
Upstream fixed it in a94e2b7 by guarding PID with a mutex and adding
CurrentPID() as a race-safe accessor. The exported field was kept to avoid
a breaking change but is now deprecated: a direct read still races the
monitor. No tag carries the fix yet, so pin the pseudo-version.
GetGRPCPID reads through CurrentPID() instead of the field. The accessor
returns the same string under an RLock, so the empty-PID and strconv error
paths are unchanged; it is the only direct field read in the tree.
With the race gone, the Free-timeout spec no longer has to leave its
fixture process unstarted. It now runs a real child and asserts the child
genuinely exits, which is exactly what the earlier workaround gave up: the
spec could show the stop was reached and the slot released, but not that
SIGTERM ever landed. Termination is observed through Done(), which closes
only once the library has waited on the child. The pidfile-based liveness
helpers cannot serve here, because Stop() deletes the pidfile while
releasing the handle and so reports "not alive" even if no signal was sent.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ⬆️ Update CrispStrobe/CrispASR
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(crispasr): initialize only declared submodules
The latest upstream commit contains an undeclared CrispASR gitlink that makes a blanket recursive submodule update fail. Limit initialization to the two submodules used by the backend build.
Assisted-by: Codex:gpt-5 [Codex]
* fix(crispasr): resolve vendored WebRTC from project root
CrispASR now builds a vendored WebRTC VAD, but its include paths assume CrispASR is the top-level CMake project. Extend the existing embedded-project rewrite to the shared third_party root.
Assisted-by: Codex:gpt-5 [Codex]
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(gpu): detect GPUs via sysfs when no pci.ids database is present
ghw.GPU() calls pci.New() before it reads /sys/class/drm and fails
outright when it cannot find a pci.ids database file. jaypipes/pcidb
embeds no database and has network fetch disabled by default, so on an
image that ships no pci.ids, GPU enumeration returns an error and every
detection path downstream goes dark.
The Dockerfile installs pciutils only in the vulkan and cublas branches,
so the Intel image had no pci.ids. A correctly passed-through Arc A310
was reported as "No GPU detected" with zero VRAM even though clinfo and
sycl-ls both enumerated it inside the same container. NVIDIA and AMD
images were shielded by their nvidia-smi / rocm-smi binary fallbacks;
Intel has no equivalent, leaving it fully exposed.
Read PCI vendor IDs directly from /sys/class/drm/card*/device/vendor,
which needs no database, and consult that from DetectGPUVendor. The
same scan replaces the ghw-only guard in getIntelGPUMemory, which is
what had been blocking the working clinfo path and keeping VRAM at
zero. Install hwdata in the base image stage as well, so ghw stops
failing for every image variant rather than only Intel.
Also apply the documented NVIDIA > AMD > Intel priority to the ghw
path, which previously returned whichever card DRM enumerated first
and so reported "intel" on a machine with an Intel iGPU at card0 and
an NVIDIA dGPU at card1.
HasGPU() carried the same blindness plus one of its own: it matched
the requested vendor against ghw's card description with a
case-sensitive Contains, so "nvidia" never matched the pci.ids
spelling "NVIDIA Corporation". It only worked because that same
description embeds the lowercase kernel driver name ("nvidia",
"amdgpu"), and it returned false outright whenever ghw errored. Route
it through the shared vendor lookup so it matches case-insensitively
and falls back to sysfs. It feeds the GPU option and NGPULayers
defaults in core/config/gguf.go.
Fixes#10941
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactor(gpu): key vendor detection off the numeric PCI ID in both paths
The ghw and sysfs legs were identifying vendors by different means: ghw
by substring-matching the pci.ids vendor name, sysfs by the numeric PCI
vendor ID. ghw already exposes that same numeric ID via
DeviceInfo.Vendor.ID, read from the kernel's modalias rather than from
the database, so the name matching was both a duplicate mechanism and
the weaker of the two.
It is weaker because a card absent from an outdated pci.ids gets
Name: "unknown" while its ID is still correct. Detection then failed
even though ghw had enumerated the card successfully. Verified in a
container with a vendor-less pci.ids and an Arc's modalias: before,
DetectGPUVendor returned ""; after, "intel".
Both legs now resolve through the same pciVendorIDs table and share the
hex parsing, with the vendor name kept only as a fallback for devices
exposing no parseable ID.
ghwHasVendor is deliberately not a priority pick, unlike vendorFromGHW:
HasGPU("intel") must stay true on a hybrid-graphics host whose discrete
NVIDIA card outranks the integrated Intel one.
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gpu): silence the gosec G304 on the sysfs attribute read
gosec flags os.ReadFile with a non-literal path. The path here is the
DRM root (a package constant in production, a temp dir under test)
joined with a ReadDir entry name and a fixed attribute filename, so no
external input reaches it.
gosec's suggested autofix, os.Root, cannot be used: /sys/class/drm/cardN
is a symlink into the PCI device tree, and os.Root refuses to traverse
it ("path escapes from parent"), which would disable the whole scan.
Assisted-by: Claude:claude-opus-4-8 gosec golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
request.language usually carries an ISO 639-1 code (e.g. "de"), which
OpenAI-compatible clients such as Home Assistant / wyoming_openai send,
but qwen_asr.validate_language() only accepts full English names
("German") and raises ValueError otherwise. Normalize the requested
language: accept full names case-insensitively, translate ISO codes
(with optional region suffix like "de-DE") to the expected name, and
pass anything unrecognised through so qwen_asr still reports it clearly.
Fixes#10958
Signed-off-by: Tai An <antai12232931@outlook.com>
llama.cpp picks a random per-process media marker (ggml-org/llama.cpp#21962),
so LocalAI renders the prompt with a "<__media__>" sentinel and swaps in the
backend's real marker after probing ModelMetadata.
That probe was gated on an exact match against "llama-cpp", the gallery's meta
backend name. A model config pinning a concrete build ("vulkan-llama-cpp",
"cuda12-llama-cpp", "rocm-llama-cpp", ... and their -development counterparts)
runs the same llama.cpp gRPC server but skipped the probe, so MediaMarker
stayed empty, no substitution happened, and the prompt reached mtmd still
carrying the sentinel. mtmd_tokenize then counted zero markers against one
bitmap and every image request failed with "Failed to tokenize prompt".
The same early return also skipped thinking-mode detection and tool-format
marker extraction, so a pinned variant silently lost reasoning and native
tool-call parsing too.
Add IsLlamaCppBackend, which recognises the whole variant family (plus the
empty auto-detect name, which resolves to llama.cpp) while excluding
ik-llama.cpp, a separate engine that merely shares the suffix.
Fixes#10945
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): make the remote LoadModel deadline configurable
The router hardcoded a 5 minute gRPC deadline for the remote LoadModel
call. Staging finishes before the timer starts, so those five minutes
cover only the worker backend's own checkpoint load and pipeline init.
A cold load of meituan-longcat/LongCat-Video-Avatar-1.5 (~83 GB) on an
ARM64 Thor worker fails at exactly 302s with DeadlineExceeded while the
backend process is still making progress (CPU time accumulating, RSS
moving as weights are mapped), so the load was cut short rather than
wedged.
Add LOCALAI_NATS_MODEL_LOAD_TIMEOUT / --model-load-timeout mirroring the
existing backend-install timeout knob, defaulting to 5m so unset
clusters keep today's behaviour.
The cold-load hold ceiling (which bounds how long one load may hold the
per-model advisory lock) was derived from the install timeout alone, so
raising the load deadline past it would have been silently clipped.
Derive it from both budgets via ModelLoadCeilingFor:
max(install + load + 5m staging margin, 25m)
With the defaults that is 15m + 5m + 5m = 25m, identical to the previous
constant, and the 25m floor means shrinking either budget can never
tighten the ceiling below what clusters relied on before.
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): reap the abandoned replica when a remote load times out
The gRPC deadline on the remote LoadModel call only cancels the client
side. A backend blocked in a synchronous weight load never observes its
cancelled handler context, so when scheduleAndLoad gave up it left the
worker loading with nobody waiting for the result.
Observed on an ARM64 Thor worker loading LongCat-Video-Avatar-1.5: the
client returned DeadlineExceeded at 302s, and the backend process was
still alive 30 minutes later having pulled ~57GB from HuggingFace. Every
retry stacked another multi-GB loader on the worker; they had to be
reaped by hand via POST /api/nodes/:id/models/unload.
Send backend.stop for the exact `modelID#replicaIndex` process key we
just abandoned. The exact key matters: a bare model ID stops every
replica on that node, including healthy ones serving traffic.
Only a deadline or cancellation triggers the reap. Any other LoadModel
failure is the backend answering, which means its handler returned and
the process is idle - stopping it there would discard a warm process and
its downloaded weights. The reap is best-effort and never replaces the
load error the caller is waiting on.
The `modelID#replicaIndex` format was already hand-rolled in two places
(the worker's buildProcessKey and pkg/model's log store). Rather than add
a third, export model.BackendProcessKey from pkg/model, the lowest common
dependency of both sides.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 golangci-lint
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(model-artifacts): materialize longcat-video checkpoints on the controller
longcat-video loads a checkpoint directory: its backend.py takes
request.ModelFile when os.path.isdir(request.ModelFile) and otherwise
falls back to snapshot_download. That places it in the same class as
transformers/vllm/diffusers/sglang, but the allow-list added in #10910
did not enumerate it, so PrimaryArtifactSpec returned no managed
artifact for a bare HuggingFace repo id.
The consequence in distributed mode: nothing was acquired on the
controller, ModelFileName fell through to the raw repo id, and staging
skipped the resulting phantom /models/<owner>/<repo> path. The worker
received a blank ModelFile, fell back to request.Model, and downloaded
~83GB from HuggingFace inside the remote LoadModel deadline - so the
load could only ever fail with DeadlineExceeded while an abandoned
backend process kept downloading.
Note this materializes the full repository. The backend restricts its
own snapshot_download with allow_patterns, and the avatar repo ships
both base_model/ and base_model_int8/ where only one is ever loaded;
inferred specs have no way to carry patterns today. Tracked separately.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): warn when staging skips a non-existent model path
stageModelFiles logs "Staging model files for remote node" up front, then
silently drops any path field that does not exist on the controller. The
skip itself is legitimate and must stay: a backend outside
managedArtifactBackends that takes a bare HuggingFace repo id gets an
optimistically constructed path (ModelFileName falls through to the raw
model reference) that was never materialized, and sources its own weights
on the worker. Erroring would break those configs.
But at debug level the operator is left with a reassuring staging line and
no trace of the skip, so a genuine controller-side acquisition gap is
indistinguishable from a healthy pass-through - it surfaces much later as
a remote LoadModel timeout, on a worker that is quietly downloading tens
of gigabytes. Raise the skip to warn and name the field, path, node and
tracking key. Behavior is unchanged.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(model-artifacts): allow a config to declare companion artifacts
A composed pipeline needs more than one HuggingFace snapshot.
LongCat-Video-Avatar-1.5 loads its own transformer but takes the
tokenizer, text encoder and VAE from the separate LongCat-Video base
repo, so a single-artifact config cannot express it and the backend is
left to fetch the second repo itself at load time.
Widen the artifact model to target: model plus any number of named
target: companion entries. Normalize accepts the new target and
constrains a companion name to [a-z0-9][a-z0-9_-]{0,63} because that
name is the option key the backend later receives; a companion may not
claim primary_file, which only means anything for a load target.
ModelConfig.Validate requires exactly one primary and requires it first,
since Artifacts[0] is what ModelFileName, size estimation and staging all
resolve from.
Both acquisition paths now loop instead of touching index 0 alone:
preloadOne for an already-installed config, bindPrimaryArtifact for a
gallery install. Failure policy differs by provenance. An inferred
primary keeps its warn-and-fall-back, because the legacy download path
still exists for it. Companions are explicit by construction, so they are
all-or-nothing: a config naming one is asserting the backend needs it,
and failing at the acquisition boundary is far more legible than a
missing-weights error surfacing later inside the backend.
The cache key is deliberately unchanged. It hashes source identity only,
never name or target, so every already-installed managed model still hits
its existing snapshot instead of silently re-downloading. Two specs pin
that: one proving a companion and a primary with identical sources agree
on the key, and one pinning the digest of a known primary outright.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(model-artifacts): hand resolved companion snapshots to the backend
A materialized companion is useless until the backend can find it, and
its location is a content-addressed cache key that does not exist until
the artifact resolves. A static gallery override cannot carry that, and
persisting it into the config YAML would rot the moment a re-resolve
produced a new key.
Synthesize it instead at load time: each resolved companion becomes
"<artifact name>:<snapshot path>" in ModelOptions.Options, reusing the
key:value convention backends already parse for options like
attention_backend. The value stays relative to the models directory so a
remote worker can resolve it under its own ModelPath once staging has
rewritten the model root. An option the author set explicitly always
wins, so pinning a companion to a local checkout still beats the managed
snapshot.
longcat-video resolves base_model through ModelPath, the same convention
qwen-tts, voxcpm, outetts and ace-step already use for companion assets.
Its sibling-directory heuristic is deleted: it looked for a LongCat-Video
directory next to the model, which cannot exist under the content
addressed .artifacts/huggingface/<key>/snapshot layout, so it was dead
code the moment the model became managed.
The gallery entry declares both repositories and restricts each with
allow_patterns. The avatar repo ships base_model/ and base_model_int8/
and only ever loads one, so fetching the whole repo would roughly double
the download. The patterns match the entry's own options (use_distill
true, use_int8 default false); enabling use_int8 here also requires
adding base_model_int8/**, which is called out in the entry.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): stage managed artifact trees from the models root
Staging anchored the worker's models directory on the primary snapshot
whenever a model was managed, so a companion snapshot could not reach the
worker at all.
frontendModelsDir was derived by stripping the Model relative path off
the end of ModelFile. For a managed artifact nothing matches: ModelFile
is .artifacts/huggingface/<key>/snapshot while Model stays a bare
HuggingFace repo id, so the strip was a no-op and the "models directory"
came out as the snapshot itself. Two consequences, both silent. Staging
keys lost the .artifacts/huggingface/<key>/snapshot prefix, so two
snapshots of one model were indistinguishable on the worker. And a
companion, which lives in a sibling snapshot directory outside the
primary, fell outside that directory entirely: StagingKeyMapper.Key
collapsed its files to bare basenames and resolveOptionPath could not
resolve the relative option at all, so it was skipped without a word.
Derive the models root from the artifact tree instead when the path runs
through it, and compute the worker's ModelPath from the file's path
relative to that root rather than from the Model field. The legacy layout
is unaffected: where Model really is the relative path, the new
derivation reduces to the old one, which a regression spec pins.
This deliberately changes an invariant that router_dirstage_test.go
pinned: for a managed primary, ModelFile and ModelPath were both the
snapshot directory, and staging keys were relative to it. Now ModelFile
is the snapshot, ModelPath is the models root above it, and keys keep the
full relative path. That spec is updated rather than accommodated, with
the reasoning recorded inline, because the old invariant is exactly what
made a sibling companion unreachable.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(ci): build Bonsai backend images
Register the Bonsai C++ source path with the backend matrix filter so changes select its image jobs. Also make shared llama.cpp changes rebuild the Bonsai and Turboquant fork images in the actual matrix, not only their test flags.\n\nAssisted-by: Codex:gpt-5 [Codex]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(backends): list backends runnable on worker nodes in distributed mode
GET /backends/available filtered the gallery against the system state of
the host serving the request. In a distributed deployment that host is the
controller, which typically has no GPU, while the GPUs live on worker
nodes. Any meta backend whose capabilities map lacks a "default" (or "cpu")
key was therefore dropped from the listing entirely — longcat-video,
vllm-omni, ltx-video, parakeet, edgetam and qwentts were invisible in the
UI even though installing them by name on a GPU worker worked fine.
Workers now report their own meta-backend capability at registration and
the controller persists it on the node row. The controller cannot derive
it: OS-dependent capabilities (metal, darwin-x86, nvidia-l4t) and the CUDA
runtime refinements are only observable on the worker. Nodes registered
before this field existed fall back to a coarse capability derived from
their GPU vendor and VRAM.
Backend discovery then evaluates compatibility as the union over healthy
backend nodes, so a backend runnable on any node is offered while one no
node can run stays hidden. Each remote capability is evaluated through a
capability-pinned system state, otherwise a forced capability on the
controller image (LOCALAI_FORCE_META_BACKEND_CAPABILITY or
/run/localai/capability) would silently override every worker's verdict.
With no registered nodes the listing is byte-for-byte what it was, so
single-node deployments are unaffected.
Also fixes the same-root-cause misclassification in /api/operations, which
used the capability-filtered listing to decide whether an operation was a
backend or a model install. A GPU-only backend installing on a worker is
still a backend operation on the controller, so that lookup is now
unfiltered.
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(backends): union worker capabilities in backend discovery
Implementation for the specs added in the previous commit, plus the two
remaining discovery endpoints.
Capability-filtered backend discovery evaluated compatibility against the
system state of the host serving the request. In a distributed deployment
that host is the controller, which typically has no GPU, while the GPUs
live on worker nodes. Any meta backend whose capabilities map lacks a
"default" (or "cpu") key was dropped entirely — longcat-video, vllm-omni,
ltx-video, parakeet, edgetam and qwentts were invisible in the UI even
though installing them by name on a GPU worker worked fine.
Workers now report their own meta-backend capability at registration and
the controller persists it on the node row. The controller cannot derive
it: OS-dependent capabilities (metal, darwin-x86, nvidia-l4t) and the CUDA
runtime refinements are only observable on the worker. Nodes registered
before this field existed fall back to a coarse capability derived from
their GPU vendor and VRAM.
Discovery then evaluates compatibility as the union over healthy backend
nodes, so a backend runnable on any node is offered while one no node can
run stays hidden. Each remote capability is evaluated through a
capability-pinned system state, otherwise a forced capability on the
controller image (LOCALAI_FORCE_META_BACKEND_CAPABILITY or
/run/localai/capability) would silently override every worker's verdict.
With no registered nodes the listing is byte-for-byte what it was, so
single-node deployments are unaffected.
Four surfaces shared this root cause and are all routed through the same
helper now:
- GET /backends/available
- GET /api/fine-tuning/backends
- GET /api/quantization/backends
- /api/operations backend-vs-model classification, which additionally
had no reason to filter by capability at all: a GPU-only backend
installing on a worker is still a backend operation on the
controller, so that lookup is now unfiltered.
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
cuDNN 9 is a dispatcher (libcudnn.so.9) plus seven sublibraries the dispatcher
dlopen()s by bare soname. Only the dispatcher is ever a DT_NEEDED, so ldd finds
it and never the seven. The allowlist force-copied three of them
(libcudnn.so*, libcudnn_ops.so*, libcudnn_cnn.so*) into every CUDA backend,
which is wrong in both directions at once: too few libraries for a backend that
uses cuDNN, and too many for one that does not.
On an L4T fleet, ten of the eleven backends carrying cuDNN were in a broken end
state; the one that was correct was correct by accident, being BUILD_TYPE=cpu
so package_cuda_libs never ran for it.
longcat-video bundled 4 of 8 at 9.24.0 over a complete pip set at 9.20.0.48
in its venv. libbackend.sh puts lib/ on LD_LIBRARY_PATH, searched before
DT_RUNPATH, so the bundle won and the rest still came from the venv:
CUDNN_STATUS_SUBLIBRARY_VERSION_MISMATCH.
Nine others bundled 3 of 8 and had no venv cuDNN. None bundled
libcudnn_graph, which libcudnn_cnn has a hard DT_NEEDED on, so it resolved
out of the runtime image and the process ran bundled 9.22.0 against system
9.23.2.
Five of those nine - llama-cpp, whisper, rfdetr-cpp, sam3-cpp,
stablediffusion-ggml - do not reference cuDNN at all. ggml goes through cuBLAS.
They were carrying ~57 MB of cuDNN with no consumer, and completing the family
for them would have taken that to ~576 MB for nothing.
Sizes overall: backends with no cuDNN consumer shed ~57 MB each (seven
instances on the fleet measured, plus longcat's ~60 MB), while the ones that
genuinely use cuDNN grow from ~57 MB to ~576 MB, because the five missing
sublibraries are ~517 MB, dominated by libcudnn_engines_precompiled. Net on
that fleet is an increase of roughly 570 MB. That growth is the bug being paid
off, not a regression: those backends only work today by silently borrowing the
missing five from the runtime image. Whether the engines set can be trimmed is
an open question, not addressed here.
So bundle per backend, by what that backend actually needs:
- venv has a complete pip cuDNN -> bundle nothing; $ORIGIN resolves the pip
set, which is the one its torch was built against (longcat-video)
- venv has no pip cuDNN -> bundle the complete family. Stays
conservative rather than detecting consumers: for a Python backend they sit
inside the venv (torch, ctranslate2, onnxruntime) where the sweep does not
look (vllm)
- no venv, nothing references cuDNN -> bundle nothing (llama-cpp, whisper,
rfdetr-cpp, sam3-cpp, stablediffusion-ggml)
- no venv, something references it -> bundle the complete family
(face-detect, voice-detect)
The no-venv case needs no new machinery. Go backends stage their own shared
object into package/lib, which IS the target dir, so sweep_transitive_deps
already pulls the dispatcher when it is a genuine dependency - that is exactly
how libcudnn_graph reached longcat. cuDNN simply comes off the force-copy list,
and complete_cudnn_family fills in the seven dlopen'd sublibraries around
whatever the sweep found. Detection is a string scan rather than ldd, so a
consumer that only dlopen()s cuDNN is seen too; over-matching costs an unused
library, under-matching costs a backend that cannot load.
Keeping bundled and pip versions in agreement instead is not viable: nothing
here pins nvidia-cudnn (zero occurrences), torch is unpinned for l4t13 except
longcat-video, and the fleet already runs five concurrent cuDNN versions -
9.19.0.56, 9.20.0.48, 9.22.0, 9.23.2, 9.24.0.
verify_cudnn_bundle asserts the end state: exactly one complete cuDNN visible to
whoever needs one - never both, never partial, and never zero for a backend that
references it. Zero is correct and common otherwise. It deliberately does not
accept the build image's system cuDNN as completing a partial bundle, which is
the shape that had been shipping silently; the build image is not the runtime
image. A version check alone would have missed longcat too, whose four bundled
libs were all 9.24.0 and mutually consistent.
Match per family for the other components for the same dlopen reason: TensorRT
(libnvinfer_plugin, libnvinfer_builder_resource), cuBLAS, cuFFT, cuSPARSE,
cuSOLVER, nvRTC. Exclusions bind inside copy_lib so they cover the sweep.
The packaging scripts' shell tests ran nowhere in CI. Add make
test-build-scripts and a lint workflow job so they gate every PR.
Fixes#10905
Assisted-by: Claude:claude-opus-4-8 golangci-lint shellcheck
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Pin vLLM protogen to grpcio-tools 1.78.0 so its generated code remains importable by protobuf 6.33.x, and remove stale generated artifacts before regeneration.
Closes#10940
Assisted-by: Codex:gpt-5 [Codex]
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Avoid holding the global loader lock across backend lifecycle waits and propagate forced shutdown through distributed workers. Track parallel requests with in-flight counters and reserve worker ports until process termination.
Add focused race tests and an authoritative FizzBee lifecycle model with a fail-closed conformance target.
Assisted-by: Codex:GPT-5 [FizzBee] [Ginkgo]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
The Vite build emitted path-absolute asset URLs (base: '/'). index.html
entry scripts and the favicon were rewritten to include the reverse-proxy
prefix in serveIndex, but two reference kinds are not in index.html and so
bypassed that rewrite:
- CSS `url()` font references (e.g. Font Awesome .woff2), which the browser
resolves relative to the stylesheet and which `<base href>` never affects
- lazily-imported route chunks, whose preload base came from the absolute
Vite base
Under a subpath mount (X-Forwarded-Prefix: /llm/) both were fetched from the
origin root, 404ing — missing-glyph "tofu" icons and broken lazy-loaded pages.
Switch Vite to a relative base ('./') so every generated URL resolves against
the file that references it: CSS fonts and route chunks now load from
`/llm/assets/...`, and index.html's now-relative entry refs resolve via the
`<base href>` serveIndex already injects on every response. Root deployments
are unaffected. The existing path-absolute rewrite in app.go still covers the
public `/favicon.svg`.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The weekly "Dependabot Updates" pip job for /backend/python/diffusers has been
failing with `private_source_authentication_failure` against the Jetson pip
index (https://pypi.jetson-ai-lab.io/jp6/cu129/), referenced by that backend's
requirements-l4t12.txt. diffusers is the only dependabot-configured pip
directory that pulls from that private index, so it is the only update job that
fails; the other backends update cleanly.
torch and transformers are deliberately pinned in this backend for
reproducibility (see backend/python/diffusers/requirements-*.txt and #9979), so
we do not want dependabot bumping them anyway. Ignoring both dependencies for
this directory stops dependabot from resolving them against the unreachable
Jetson index and keeps the weekly update job green, without removing update
coverage for the rest of the backend's dependencies.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The managed-artifact materializer stages a HuggingFace snapshot into a
directory (.artifacts/huggingface/<key>/snapshot/). That is the right load
target for directory-consuming backends (transformers, vLLM, diffusers, ...),
but PrimaryArtifactSpec inferred a managed artifact from ANY HuggingFace-shaped
model reference regardless of backend. A single-file backend such as llama.cpp
or whisper was therefore handed the snapshot directory instead of the weight
file and failed to load it.
The /import-model importer already guards this with a backend allow-list
(managedArtifactBackends), but the loader-side inference did not. Move the
allow-list into core/config as IsManagedArtifactBackend and apply it in
PrimaryArtifactSpec: only directory-consuming backends may have an artifact
inferred from a bare reference; every other backend stays on the legacy
download-to-file path. An explicit artifacts: block still bypasses the gate,
where single-file snapshot resolution handles the load path.
The importer now shares the same predicate, so both paths agree on which
backends auto-materialize.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(model-artifacts): load single-file HF snapshots from the file, not the dir
The managed Hugging Face artifact materializer (#10825) always pointed
backends at the snapshot *directory*
(.artifacts/huggingface/<key>/snapshot). For a single-file model
reference such as huggingface://nomic-ai/nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf,
the GGUF lives *inside* that directory, so llama.cpp was handed a
directory and failed with "gguf_init_from_reader: failed to read magic".
This has kept the tests-aio job red on master since the feature merged
(the embeddings e2e tests could not load text-embedding-ada-002).
Record the single file of a one-file snapshot as Resolved.PrimaryFile and
have ModelFileName() resolve to snapshot/<PrimaryFile> when it is set.
Multi-file snapshots (e.g. transformers repos consumed as a directory)
keep pointing at the snapshot directory. PrimaryFile is derived from the
resolved contents and is deliberately excluded from the artifact cache
key. estimateModelSizeBytes now derives the snapshot directory from the
cache key instead of ModelFileName(), so its manifest lookup is unaffected
by the file-vs-directory resolution.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The artifact progress bridge mapped every PhaseVerifying event to a flat
95%. The materializer emits PhaseVerifying once per file (from each file's
AfterDownload hook) and downloads run sequentially, so the first small file
to finish pinned the bar at 95% - and, because progress is monotonic, it
stayed at 95% for the entire remaining download (e.g. a 70GB checkpoint
reporting 95% at 410MB / 69.7GB).
Track per-file verify proportionally to the running aggregate bytes, the
same way downloading does. CurrentBytes already reflects "completed files +
this file", so the percentage advances honestly. The flat 95%/99% is now
reserved for the genuinely once-per-install Committing/Persisting phases.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The Operate → Traces "API Traces" panel already recorded who made each
request (user_id/user_name) but never showed it, and did not capture the
caller's network identity at all. Operators asked to see the requesting
user (#10886) and the client IP + user agent (#10887) so a trace can be
attributed to who/what issued it.
Backend: add ClientIP and UserAgent to APIExchange and populate them from
echo's c.RealIP() (honours X-Forwarded-For / X-Real-IP behind a trusted
proxy) and the request's User-Agent header. Both are omitempty and the
/api/traces swagger response is map[string]any, so this is additive.
UI: add a sortable "User" column to the API traces table and a metadata
block (User / Client IP / User Agent) at the top of the expanded row
detail. Fields render only when present, so older buffered traces and
unauthenticated/local requests degrade cleanly.
Adds an e2e spec covering the new column value and the expanded metadata.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The Operate -> Traces table rendered the request time with the time of day
only, so entries that span more than one day were ambiguous. Add a
formatDateTime helper (localized date + existing time-with-millis) and use it
for the Traces "Time" column, keeping the cell on a single line. The shared
formatTimestamp used by the log views is unchanged.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
One agent turn runs several internal LLM generations (tool selection,
reasoning, final answer) that all emit stream_event deltas over the same
per-agent SSE channel. The chat page accumulated every 'content' delta
into a single live bubble and ignored the 'done' boundary events, so the
internal generations' text (e.g. the English tool-selection rationale)
merged with — and visually corrupted — the streamed final answer.
Reset the accumulated content/reasoning on 'done': each generation gets
a clean live bubble, and the authoritative full answer still arrives via
the final json_message event as before.
Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de>
chore(moss-transcribe-cpp): bump pin to CUDA K-quant embed fix
Bumps the moss-transcribe.cpp pin to 190a569c, which merges the
host-side embed-lookup fallback for K-quant token_embd tensors
(localai-org/moss-transcribe.cpp#2).
Before this, running a q5_K/q4_K/q6_K moss-transcribe GGUF on CUDA
(or any non-CPU backend) aborted in getrows.cu with
"unsupported src0 type: q5_K" because ggml's GET_ROWS op has no
K-quant implementation on GPU, killing the backend process on the
first request. The engine now dequantizes the needed rows on the
host when the backend cannot run GET_ROWS for the tensor type,
producing bit-identical results.
Fixes#10862
Assisted-by: Claude:claude-opus-4-8 [Bash] [Edit]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Add the q8_0 (default) and f16 gallery entries for the moss-tts-cpp backend, each
pulling the MOSS-TTS-Local v1.5 GGUF plus the MOSS-Audio-Tokenizer-v2 codec and
the text tokenizer from mudler/MOSS-TTS-Local-Transformer-v1.5-GGUF. The backend
auto-discovers the codec and tokenizer siblings; output is 48 kHz stereo with
reference-audio voice cloning.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(backend): add moss-tts-cpp text-to-speech backend
Add a Go + purego backend wrapping the moss-tts.cpp ggml port of the OpenMOSS
MOSS-TTS-Local v1.5 text-to-speech model (GPT-J local transformer decoded through
MOSS-Audio-Tokenizer-v2), producing 48 kHz stereo audio with optional
reference-audio voice cloning. Mirrors the qwen3-tts-cpp backend: dlopen the
static-ggml shared library, bind the moss-tts.cpp C-API via purego, and serve
the gRPC TTS method. A thin C shim holds the pipeline handle and copies engine
PCM into a Go-freeable buffer.
Wires the CI registration: backend-matrix.yml (CPU, CUDA 12/13, Intel SYCL
f16/f32, Vulkan, ROCm, NVIDIA L4T, plus Darwin metal), backend/index.yaml metas
and image entries pointing at mudler/MOSS-TTS-Local-Transformer-v1.5-GGUF, the
root Makefile build targets, and the changed-backends.js path mapping.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: list the moss-tts-cpp backend among the LocalAI-maintained engines
Add moss-tts.cpp to the README "Backends built by us" table, the
Text-to-Speech compatibility table, and the reference-audio voice-cloning
backend list, so the new backend is documented alongside its peers.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(moss-tts-cpp): pin moss-tts.cpp to the squashed single-commit release
moss-tts.cpp history was collapsed to a single commit; repoint MOSSTTS_CPP_VERSION
to ee722b8e9205ee9b1b1c398a4e87e4e393e9be41.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* backend(moss-tts-cpp): add the moss-tts-cpp-development gallery meta
The gallery had the -development image entries but no matching -development
meta anchor (as locate-anything-cpp and depth-anything-cpp have), so the master
build was not installable as a gallery backend. Add moss-tts-cpp-development
mirroring the production meta with the -development capability image names.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Google shipped the Gemma 4 MTP drafter heads and llama.cpp merged native
support in ggml-org/llama.cpp#23398. LocalAI's pinned llama.cpp already
carries it, and the config plumbing (draft_model + core/config/mtp.go)
was built for exactly this path, but no official Gemma 4 gallery entry
wired it up.
Add llama.cpp draft-mtp speculative-decoding variants for the dense
sizes, sourced from the unsloth QAT GGUF repos (target UD-Q4_K_XL +
mtp-*.gguf drafter + BF16 mmproj):
- gemma-4-e2b-it-qat-mtp
- gemma-4-e4b-it-qat-mtp
- gemma-4-12b-it-qat-mtp
- gemma-4-31b-it-qat-mtp
These replace the previously commented-out attempts, which were disabled
because the Janvitos/boxwrench drafter GGUFs declared the architecture as
`gemma4_assistant` (underscore) and failed to load on stock llama.cpp.
The unsloth drafters use the upstream `gemma4-assistant` (hyphen) spelling
that mtp.go's isDraftOnlyAssistantArch expects, so they load without any
backend patch. The 26B-A4B MoE is intentionally omitted (the upstream PR
reports no meaningful MTP speedup for it).
Also fix gemmable-4-12b-mtp: it loaded the draft-only `-mtp` GGUF as the
main model with no draft_model set, which cannot run standalone. It now
loads the target as the model, wires the drafter via draft_model, enables
spec_type:draft-mtp, and downloads both files.
All sha256 pins were taken from the HuggingFace API lfs.oid (reliable
content hash even for Xet-backed repos).
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
StopP2P() read and wrote a.p2pCtx/a.p2pCancel without holding
a.p2pMutex, and StartP2P() reassigned both fields with no lock at
all -- including when RestartP2P() calls it from a background
goroutine after releasing the mutex. Both paths are reachable from
POST /api/settings (empty p2p_token -> StopP2P, non-empty ->
RestartP2P), so concurrent requests race on the same fields.
Take a.p2pMutex in StopP2P and around the field publication in
StartP2P, factor the shared teardown into stopP2PLocked() so
RestartP2P reuses it, and route the goroutine error path through
StopP2P instead of touching a.p2pCancel unlocked.
Signed-off-by: Anai-Guo <antai12232931@anaiguo.com>
Co-authored-by: Anai-Guo <antai12232931@anaiguo.com>
* ⬆️ Update CrispStrobe/CrispASR
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(crispasr): rewrite c2pa-audio submodule path for subproject builds
CrispASR a38cb89 adds a crispasr_c2pa_native static library whose sources
live in the new third_party/c2pa-audio git submodule, located via
CMAKE_SOURCE_DIR in src/CMakeLists.txt. That variable assumes CrispASR is
the top-level CMake project; LocalAI embeds it via add_subdirectory, so
the path resolved to backend/go/crispasr/third_party/c2pa-audio and every
build variant failed at CMake generate with 'Cannot find source file:
c2pa_native.cpp'.
Extend the existing talk-llama sed workaround to also rewrite the
c2pa-audio reference to PROJECT_SOURCE_DIR, which is correct both
standalone and as a subproject. The submodule itself is already checked
out by the recursive submodule init. Verified locally: the exact CI error
reproduces with CMAKE_SOURCE_DIR, and with the rewrite CMake configure,
crispasr_c2pa_native, and crispasr-lib all build cleanly on a CPU-only
fallback configuration.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-8
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The turboquant and bonsai backends copy backend/cpp/llama-cpp/ wholesale
into their build directories and reuse its Makefile/prepare.sh against
their own llama.cpp forks. When PR #10837 added
backend/cpp/llama-cpp/patches/0001-add-minimax-m3-support.patch, the
copied patches/ directory was mis-applied to the fork checkouts: the
fork trees diverge from upstream, hunks rejected, and because the
patch-apply loop in prepare.sh ran before set -e took effect the build
kept going and died much later with a confusing compile error
("'LLM_ARCH_MINIMAX_M3' was not declared in this scope"). This broke
tests-turboquant-grpc on that PR.
Two hardening changes:
- turboquant/bonsai Makefiles: delete the copied patches/ directory
right after the cp -rf of backend/cpp/llama-cpp/. Patches vendored
for upstream llama.cpp must never be applied to the forks; each fork
carries its own patch series under backend/cpp/<backend>/patches/,
applied by its apply-patches.sh.
- llama-cpp prepare.sh: run the patch-apply loop under set -e so a
rejecting patch fails fast and loudly at apply time instead of
surfacing as a downstream compile error. A missing or empty patches/
directory remains a no-op success, so all existing callers (the
llama-cpp Makefile targets and the turboquant/bonsai copies) are
unaffected when no patches ship.
Exposed by PR #10837.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(settings): add declarative runtime-settings field registry
One fieldSpec row per RuntimeSettings field, with a reflection
completeness spec so a field added without a registry row is a red
test instead of a silently-dropped setting (the #10845 bug class).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-fable-5
* refactor(settings): drive ToRuntimeSettings/ApplyRuntimeSettings from the field registry
Behavior-preserving: ~350 hand-written per-field lines become two loops
over runtimeSettingsFields, gated by a To->Apply->To round-trip spec.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-fable-5
* feat(settings): baseline-driven startup merge for persisted runtime settings
ApplyRuntimeSettingsAtStartup compares the live config against
DefaultRuntimeBaseline (option-less-run defaults incl. kong-injected
flag defaults) instead of per-field == 0 guards. Fixes persisted
lru_eviction_max_retries, tracing_max_items, agent_job_retention_days,
memory_reclaimer_threshold, galleries and autoload flags being
silently ignored at boot.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-fable-5
* fix(settings): registry-driven startup merge, applied before consumers
loadRuntimeSettingsFromFile becomes a thin wrapper over
ApplyRuntimeSettingsAtStartup and runs at the top of New(), before
model configs capture app-level defaults. WithThreads stops eagerly
resolving 0 so a persisted thread count survives restart while
LOCALAI_THREADS still wins (#10845); the physical-core fallback moves
after the merge.
Also: run.go now injects the memory-reclaimer threshold unconditionally
so the option-less boot matches DefaultRuntimeBaseline and a UI-saved
threshold survives restart.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-fable-5
* refactor(settings): file watcher delegates to the registry merge; shared API-key merge
Manual edits to runtime_settings.json now behave like a boot-time load
(env still wins) instead of the inverted diverged-from-startup guard
that ignored most manual edits. MergeAPIKeys dedups env keys in one
place for the endpoint and the watcher.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-fable-5
* docs(settings): document unified runtime-settings precedence
Document the single env/CLI > runtime_settings.json > defaults rule,
applied identically at boot, on POST /api/settings, and on manual file
edits, plus the two known limitations (default-valued env vars are
indistinguishable from unset; API-changed fields hot-apply on the next
restart only). Also add a completion debug log when the watcher applies
runtime_settings.json.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-fable-5
* test(settings): reset the global VRAM cap leaked by the round-trip spec
The round-trip spec applies vram_budget=12GiB, whose post-loop hook
installs a process-global default cap; without a reset every spec
ordered after it runs under that phantom budget. Also drop a stale
enumeration in the ApplyRuntimeSettings doc comment.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-fable-5
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The gRPC configuration table only listed the two fields with a one-line
description each, without defaults, without explaining what the total
load window looks like, and without hinting when a user should adjust
them. In practice the default 20 attempts x 2 s = 40 s window is way
too tight for large NVFP4 / FP8 models on slow storage or first-run
CUDA-graph capture, and the resulting kill (exitCode=120, 'context
canceled') looks like a backend crash even though the backend is still
making legitimate forward progress.
Extend the section with:
- Defaults column (20 and 2) added to the table
- Prose explaining that these govern the readiness handshake between
LocalAI and a freshly spawned backend (Health polling loop)
- Total-load-window formula
- Concrete failure signature so users can recognize a timeout-kill
vs. a real backend crash
- Example configuration for a ~10 min cold-load window (grpc.attempts
140, attempts_sleep_time 5), with a note that inference-timeouts and
the watchdog are unaffected.
The sglang Python backend inherits the default Status RPC from
backend_pb2_grpc.BackendServicer, which raises NotImplementedError.
LocalAI's backend-monitor polls /backend.Backend/Status periodically on
every registered backend; when the call fails, /backend/monitor returns
HTTP 500 and downstream inference requests to the sglang backend are
blocked even though the model is loaded and answering directly via the
gRPC endpoint.
Add a minimal Status shim that mirrors the existing Health method and
returns StatusResponse{state=READY} unconditionally. This unblocks the
monitor path; a state-aware follow-up (UNINITIALIZED during load, BUSY
under active inference) is left for a subsequent change.
Reproduced on DGX Spark (GB10, arm64-l4t-cuda-13 image) with the sglang
v0.5.15 backend and Qwen3-Coder-Next-NVFP4-GB10; verified locally that
patching the shim in place immediately restores /backend/monitor and
inference across the sglang slot.
* fix(audio-transform): serialize WebSocket writes to avoid concurrent-write panic
AudioTransformStreamEndpoint writes to the same Gorilla WebSocket connection
from two goroutines: the backend-forwarding goroutine emits binary PCM frames
(and can call sendWSError on a backend recv error), while the read loop calls
sendWSError for malformed mid-stream JSON or a backend send failure. Gorilla
WebSocket permits only one concurrent writer, so these writers race and can
panic with "concurrent write to websocket connection", resetting the client
session; a -race build reports the data race directly.
Wrap the connection in a lockedConn that serializes WriteMessage behind a
mutex, mirroring the existing lockedConn used by the openresponses WebSocket
endpoint. Reads stay on the single read loop, so only writes need the lock.
Fixes#10844
Signed-off-by: Tai An <antai12232931@outlook.com>
* chore: empty commit to re-trigger checks
Signed-off-by: Anai-Guo <antai12232931@anaiguo.com>
---------
Signed-off-by: Tai An <antai12232931@outlook.com>
Signed-off-by: Anai-Guo <antai12232931@anaiguo.com>
Co-authored-by: Anai-Guo <antai12232931@anaiguo.com>
When the watchdog's busy-killer decides a backend has been busy past the
busy timeout, it shuts it down via ModelLoader.ShutdownModel -> deleteProcess,
which grabs ml.mu and then waits for IsBusy() to clear BEFORE stopping the
process. But a backend that exceeds the busy timeout is, by definition,
stuck on an in-flight gRPC call, so the graceful wait never returns, ml.mu
is held forever, and every other ml.Load blocks — including the shared
opus backend load at the start of every realtime (WebRTC) session. New
realtime connections then hang at "Connected, waiting for session..."
whenever the watchdog is enabled, while logs repeatedly print the
watchdog's busy / "active connection" line.
Fix: add a force shutdown path (ShutdownModelForce / deleteProcess(s,
force=true)) that stops the process FIRST — dropping the stuck call's
gRPC connection and unblocking it — instead of waiting on it. Route the
watchdog's busy-killer and busy LRU / group / memory evictions through
the force path; keep the graceful wait for idle and user-initulated
unloads. Graceful/unforced kills are unchanged.
Regression test: the watchdog busy-killer uses ShutdownModelForce.
Fixes#10391
Assisted-by: opencode:glm-5.2 [opencode]
Signed-off-by: Nandana Dileep <110280757+nandanadileep@users.noreply.github.com>
feat(bonsai): add PrismML llama.cpp fork backend + Bonsai gallery models
Adds a new `bonsai` backend that runs the PrismML fork of llama.cpp
(github.com/PrismML-Eng/llama.cpp, `prism` branch), which ships the Q1_0
(1-bit) and Q2_0 (ternary / 1.58-bit) weight-quantization kernels used by the
Bonsai and Ternary-Bonsai models. Stock llama.cpp cannot decode these quants.
Modeled on the turboquant backend: reuses backend/cpp/llama-cpp/grpc-server.cpp
against the fork's libllama via a thin wrapper Makefile, so the sub-2-bit models
are served with the same OpenAI-compatible API. No grpc-server allow-list patch
is needed (bonsai adds weight quants, transparent to the server, not KV-cache
types), and the reused server compiles cleanly against the fork with no skew
patches (validated locally via a CPU docker build; patches/ is present but empty
for any future re-pin skew).
Backend wiring: backend/cpp/bonsai/, .docker/bonsai-compile.sh,
backend/Dockerfile.bonsai, top-level Makefile targets, backend-matrix.yml build
rows (CPU, CUDA 12/13, L4T, SYCL f32/f16, Vulkan, ROCm/hipblas), backend/index.yaml
meta-backend + per-platform images, and a nightly bump_deps entry tracking the
`prism` branch.
Gallery: 8 entries across 4 families - bonsai-8b-1bit, ternary-bonsai-8b (+g64,
+pq2), bonsai-27b-1bit (vision), ternary-bonsai-27b (+pq2, +g64, vision). The 27B
models wire the mmproj vision tower; the DSpark speculative drafter GGUFs are not
wired (custom semi-autoregressive drafter, not a standard llama.cpp draft model).
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(watchdog): guard StopWatchdog with watchdogMutex to prevent double close
StopWatchdog checked, closed and cleared a.watchdogStop without holding
a.watchdogMutex, while startWatchdog and RestartWatchdog reassign and close the
same channel under that lock.
POST /api/settings dispatches to StopWatchdog or RestartWatchdog depending on
ApplicationConfig.WatchdogShouldRun(), so both are reachable concurrently. Two
callers can observe a non-nil watchdogStop and both close it, which panics with
'close of closed channel' and takes the server down.
Take the mutex, matching the other two writers. StopWatchdog is only called from
the settings handler, which holds no lock, so this cannot deadlock.
Fixes#10841
Co-authored-by: Anai Guo <antai12232931@anaiguo.com>
Finetune() compiled every model cutstrings/extract_regex entry via regexp.Compile
and called xlog.Fatal on failure, which terminates the entire local-ai process.
A single model config with an invalid regex (e.g. cutstrings: ["("]) turns one
/v1/chat/completions request into a process-level denial of service.
Log the compile error and skip the offending pattern instead. The mutex is
released before continuing, and skipping avoids dereferencing the nil regexp
that removing the fatal would otherwise leave behind.
Fixes#10843
Signed-off-by: Tai An <antai12232931@outlook.com>
ApplyRuntimeSettings persists the performance settings (threads,
context_size, f16) on the live /api/settings path, but the startup
loader loadRuntimeSettingsFromFile never read them back, so a value
saved via the Middleware UI was silently ignored on the next restart:
the model booted with the CLI/physical-core default and GET /api/settings
echoed that default instead of the saved value (#10845).
Threads needs special handling: unlike context_size/f16, WithThreads
eagerly resolves an unset (0) value to xsysinfo.CPUPhysicalCores() at
option-apply time, so options.Threads is never 0 in the loader and the
usual "== default" heuristic cannot tell an env/CLI value from the
physical-core fallback. Detect LOCALAI_THREADS/THREADS explicitly so the
env still wins over the persisted file value.
Signed-off-by: Anai-Guo <Anai-Guo@users.noreply.github.com>
Co-authored-by: Anai-Guo <Anai-Guo@users.noreply.github.com>
Add stable and development gallery variants for Linux and Darwin, and wire the backend build matrix so the referenced images are published.
Assisted-by: Codex:gpt-5 [yq]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
Pairs unsloth/Qwen3.5-4B-GGUF (Q4_K_M target) with the
AtomicChat/Qwen3.5-4B-DFlash-GGUF Q8_0 drafter (quantized from
z-lab/Qwen3.5-4B-DFlash, upstream GGUF arch `dflash`), same shape as
the existing DFlash entries.
Assisted-by: Claude Code:claude-fable-5 [Bash] [Read] [Edit]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): add vrambudget primitive for per-node VRAM caps
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): apply default VRAM budget in xsysinfo aggregate getters
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): wire LOCALAI_VRAM_BUDGET flag to xsysinfo default budget
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): persist VRAM budget via runtime settings with live apply
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(vram): reset process-global VRAM budget after runtime-settings spec
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): add VRAM budget field to Settings page
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): store and enforce per-node VRAM budget in the node registry
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): apply per-node VRAM budget in router hardware defaults
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): report worker VRAM budget in node registration
The distributed worker now reports its operator-set VRAM budget string
(LOCALAI_VRAM_BUDGET) to the server on registration. The worker keeps
reporting RAW total/available VRAM and never sets the xsysinfo
process-global budget (that stays standalone-only); the server resolves
and enforces the budget uniformly (Task 6).
Also closes a Task 6 gap: on re-registration, a struct Updates zero-skips
an empty budget, so a worker that dropped LOCALAI_VRAM_BUDGET left the
stale cap in place. For non-admin-override nodes the budget columns are
now force-written (map Updates) even when empty, so removing the env var
clears the cap; admin overrides are preserved unchanged.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* style(vram): drop em dash from worker-clear comment
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): add node VRAM budget admin endpoints
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): add node VRAM budget control to the node UI
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vram): expose set_node_vram_budget MCP admin tool
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(vram): document LOCALAI_VRAM_BUDGET and node VRAM budget UI
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vram): avoid double-applying VRAM budget in GetResourceAggregateInfo
The GPU-branch aggregate returned by GetResourceInfo is sourced from
GetGPUAggregateInfo, which already caps total/free/used against the
process-wide VRAM budget. GetResourceAggregateInfo then applied the
budget a second time. For an absolute budget this is idempotent, but for
a percentage budget b.Apply resolves the ceiling as a fraction of its
input total, so a second pass yields P*(P*T) instead of P*T and distorts
UsagePercent (read by the memory reclaimer in pkg/model/watchdog.go).
Remove the redundant second application so the budget is applied exactly
once, against the raw physical totals, upstream in GetGPUAggregateInfo.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vram): implement SetNodeVRAMBudget on mcp assistant test stub
The LocalAIClient interface gained SetNodeVRAMBudget; the stubClient in
core/http/endpoints/mcp used by the assistant tests is a separate
implementer and needs the method too (broke golangci-lint typecheck and
both test jobs).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* test(core/http): make the suite's HTTP port overridable
app_test.go and openresponses_test.go hardcoded 127.0.0.1:9090. When
another service already listens on 9090 the suite does not fail fast:
the server goroutine logs the bind error and the specs then poll
whatever is squatting the port until Eventually times out. On machines
where 9090 is permanently taken this makes the pre-commit coverage gate
impossible to pass.
Introduce testHTTPAddr, defaulting to 127.0.0.1:9090 (what CI has
always used) and overridable via LOCALAI_TEST_HTTP_PORT for local runs.
Assisted-by: Claude:claude-fable-5 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): make per-node backend upgrade actually upgrade
The node detail page's Upgrade button reused the node-scoped install
path (POST /api/nodes/:id/backends/install). That fires NATS
backend.install with force=false, and the worker's install handler is
deliberately "ensure installed": when the backend binary already exists
on disk it short-circuits without touching the gallery. Since only an
installed backend can be upgraded, the whole chain was a guaranteed
successful no-op - the UI then toasted "backend upgraded" without even
waiting for the async job.
Route upgrades through the real force-reinstall path instead:
- BackendManager.UpgradeBackend now receives the ManagementOp (like
InstallBackend already did) so implementations can honor
op.TargetNodeID.
- DistributedBackendManager.UpgradeBackend scopes the backend.upgrade
fan-out to op.TargetNodeID when set, and errors when the target node
does not report the backend as installed.
- New POST /api/nodes/:id/backends/upgrade endpoint enqueues an
Upgrade=true node-scoped op (async 202 + jobID, mirroring install).
- NodeDetail UI calls the new endpoint and reports the dispatch
("Upgrading ... on this node...") instead of claiming success; the
Operations panel tracks the actual job.
Verified against a live local cluster (NATS + Postgres + two workers):
the target worker stops the running process, force-reinstalls from the
gallery and re-downloads the OCI image; the second worker receives no
backend.upgrade event; upgrading a backend missing from the target node
fails the job with a clear error.
Assisted-by: Claude:claude-fable-5 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
PyTorch 2.13 XPU pulls oneAPI 2026 libraries that conflict with the oneAPI 2025.3 backend image. Pin torch and torchaudio to the matching 2.11 XPU pair so the build resolves a coherent 2025.3 runtime.
Assisted-by: Codex:GPT-5 [uv]
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
SetDefaults injected the llama.cpp server options cache_reuse
(ApplyServingDefaults) and parallel (ApplyHardwareDefaults, re-applied
per selected node by the distributed router) onto every model config
regardless of backend. Every other backend ignores options it does not
understand, so this was harmless until longcat-video, which strictly
validates its options and fails LoadModel with
"unknown model option(s): cache_reuse, parallel".
Gate both injections behind a new UsesLlamaCppServingOptions allow-list
(llama-cpp plus the empty/auto-detect case that resolves to llama.cpp
from a GGUF file, mirroring how llamaCppDefaults is registered). This
follows the existing UsesLlamaSamplerDefaults precedent for llama-only
defaults. The typed NBatch field is deliberately left alone: it is a
proto field every backend simply ignores, which is why batch never
triggered the error.
Also harden the longcat-video backend to warn-and-ignore unknown model
options and request params through a testable select_known_options
helper, matching the other LocalAI Python backends, so a future
server-injected option cannot break loading again.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
handleRegenerate rebuilt the outbound message from the display-only
message.files metadata ({name, type: 'file'|'image'|..., content}),
which doesn't carry the base64/textContent payload sendMessage's
file-building loop expects. As a result, regenerating any answer whose
own question had an attachment silently dropped that attachment from
the resent message. This wasn't fork-specific, but forking a chat and
then regenerating an earlier (now non-last) answer is the natural way
to hit it.
Fix by reusing the original message's already-assembled `content`
verbatim (it already has the file text / image_url / audio_url /
video_url parts embedded from the first send) instead of trying to
reconstruct it from lossy display metadata.
Fixes#10806
Assisted-by: Claude:claude-sonnet-5
Signed-off-by: ajuijas <189517297+ajuijas@users.noreply.github.com>
Co-authored-by: ajuijas <189517297+ajuijas@users.noreply.github.com>
- Replace hardcoded text with useTranslation hook in UI components
- Add localization support for both English (en) and Indonesian (id) locales
Signed-off-by: Dedy F. Setyawan <dedyfajars@gmail.com>
* feat(ui): add voice library workflow
Give administrators a production-ready flow to record or upload consented reference audio, manage reusable profiles, inspect API usage, discover compatible models, and hand a saved voice directly to text-to-speech.
Assisted-by: Codex:gpt-5
* feat(voice): add managed voice cloning profiles
Make reusable reference voices manageable through the admin API instead of requiring model-directory and YAML edits. Discover compatible installed and gallery models from server-side backend capabilities, retain explicit model configuration controls, and stage saved references for supported backends.
Expose profile management through REST and MCP, document backend-specific behavior, and cover the workflow from profile creation through real Qwen3-TTS synthesis. Harden the agent-job HTTP test against completion racing cancellation.
Assisted-by: Codex:gpt-5
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(backends): add LongCat video and avatar generation
Assisted-by: Codex:GPT-5 [apply_patch] [exec_command] [web]
* refactor(config): declare model I/O modalities
Make model configs declare input and output modalities so capability discovery no longer branches on backend or checkpoint names. Complete the LongCat gallery and user documentation, make the SDPA patch apply to the pinned upstream revision, and stabilize the Agent Jobs race exposed by the required hook.
Assisted-by: Codex:GPT-5 [web]
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Add four ready-to-run DFlash speculative-decoding entries for the
llama.cpp backend, now that upstream DFlash support (draft-dflash) is in
the pinned llama.cpp. Each entry bundles a full target model with its
small z-lab block-diffusion drafter and sets spec_type:draft-dflash,
spec_n_max:15, and flash attention (required by DFlash):
- qwen3-4b-dflash (Qwen3-4B + Qwen3-4B-DFlash drafter)
- qwen3.5-9b-dflash (Qwen3.5-9B + Qwen3.5-9B-DFlash drafter)
- qwen3.6-27b-dflash (Qwen3.6-27B dense + drafter)
- qwen3.6-35b-a3b-dflash (Qwen3.6-35B-A3B MoE + drafter)
The 4B pair uses the base Qwen3-4B target (not Qwen3.5-4B): its drafter
reports general.name "Qwen3 4B DFlash" and is the canonical pairing
documented upstream. All drafters were downloaded and verified to carry
GGUF architecture "dflash" (not the fork-only "dflash-draft" /
"DFlashDraftModel") so they load in the upstream backend, and every
drafter SHA256 was confirmed against the downloaded bytes.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* docs: refresh LocalAI homepage
Reframe the homepage around LocalAI's modular multimodal runtime, native inference engines, deployment range, and built-in platform capabilities. Remove the outdated video in favor of current product visuals and clearer paths into the documentation.
Assisted-by: Codex:gpt-5
* docs: give homepage a full-width canvas
Let the product homepage opt out of Relearn's persistent sidebar and duplicate title while preserving the documentation shell on interior pages. Tighten the responsive bounds for narrow screens.
Assisted-by: Codex:gpt-5
* docs: fit homepage to the Relearn content flow
Remove the full-width shell exception and use a single-column homepage inside the standard documentation layout. This avoids competing scroll containers and the compressed split hero.
Assisted-by: Codex:gpt-5
* docs: hide homepage scroll rail
Preserve Relearn's content scrolling while removing the visible scrollbar beside the landing-page hero.
Assisted-by: Codex:gpt-5
* docs: contain homepage sections within docs column
Prevent landing-page headings, figures, and section grids from widening Relearn's content pane or exposing overflow rails.
Assisted-by: Codex:gpt-5
* docs: remove nested homepage scrollbars
Wrap the quick-start command within its column and suppress component-level scrollbar tracks across the landing page.
Assisted-by: Codex:gpt-5
* docs: remove outdated gallery screenshot
Drop the stale Model Gallery image from the homepage until a current product visual is available.
Assisted-by: Codex:gpt-5
* docs: fix homepage architecture link
Point the homepage CTA at the generated reference/architecture route.
Assisted-by: Codex:gpt-5
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
When a model config has no explicit backend, the model loader greedily
probes every installed backend and binds to the first Load that
succeeds. opus and local-store were the only in-tree backends with no
model artefact to validate, so they accepted anything — an LLM
installed after them could silently bind to the audio codec or the
vector store and then fail at inference with "unimplemented"
(see #9287).
opus now accepts only its own name (what the realtime WebRTC path
sends) or none. local-store namespaces are arbitrary (router caches,
biometrics, user-named stores), so core's StoreBackend now marks
genuine store loads with a store:// prefix on the gRPC model name and
the backend refuses names without it; core and backend ship from the
same release, so the convention upgrades in lockstep.
Also repair the bit-rotted 'make test-stores' bootstrap (the suite
never registered external backends, so BACKENDS_PATH was dead weight)
and add the Load-validation rule to the adding-backends checklist.
Related: #9287
Assisted-by: Claude:claude-fable-5 golangci-lint
Signed-off-by: Richard Palethorpe <io@richiejp.com>
The vibevoice transcription e2e hangs until the go test timeout when
the HF CDN is slow: the ASR Q4_K model is >10 GB, downloadFile capped
every curl attempt at --max-time 600 (needs a sustained ~17 MB/s to
fit), and curl's --retry restarts from byte zero, so no attempt ever
makes forward progress. This killed the job twice on PR #10764 and
previously forced skipping it on release tags (#10567).
Replace the wall-clock cap with stall detection (--speed-limit 1 MiB/s
over --speed-time 120s) and resume from the bytes already on disk with
-C -, retrying from Go because curl does not re-evaluate the resume
offset on its internal retries. Resume against the HF Xet CDN was
verified by killing a transfer mid-flight and confirming the next
invocation appended (114 MB -> 235 MB, GGUF magic intact).
Also parameterize the suite timeout (BACKEND_TEST_TIMEOUT, default
30m) and raise it to 120m for the vibevoice transcription wrapper: a
10 GB download plus 25 specs does not fit in 30m even on a good day,
and the job-level GHA timeout there is already 150m.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(vibevoice-cpp): true streaming TTSStream via vv_capi_tts_stream
Replaces the synth-to-tempfile TTSStream hack with a real streaming path:
binds the new vv_capi_tts_stream callback ABI via a single reusable purego
callback (CGO_ENABLED=0-safe, no runtime/cgo), copies each int16 PCM window
into the gRPC results channel after the streaming WAV header.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* test(vibevoice-cpp): real-model streaming integration test with TTFA measurement
Gated behind VIBEVOICE_IT=1, this Ginkgo spec dlopens the engine .so and
drives the exact Go->purego->C TTSStream/TTS path against the real
vibevoice-realtime-0.5B model. It measures time-to-first-audio for the
streaming path versus the batch path and asserts the streaming win:
44-byte WAV header first, >=2 PCM windows, non-silent audio, and
TTFA < total_stream. Without the env var the spec skips so CI and
normal go test are unaffected.
Measured: TTFA 2.38s vs batch deliver-time 39.96s (first audio in 5.9%
of the batch time, ~17x faster), 18 stream chunks, non-silent 24kHz PCM.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* chore(vibevoice-cpp): pin streaming-decoder engine build
Bumps VIBEVOICE_CPP_VERSION to the streaming-decoder engine commit that
adds vv_capi_tts_stream (localai-org/vibevoice.cpp#8). Re-pin to the
merged master commit once that PR lands.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* chore(vibevoice-cpp): re-pin to merged streaming-decoder commit
localai-org/vibevoice.cpp#8 merged to master as 000e372; move the pin
off the PR branch commit onto the merged master commit.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* test(vibevoice-cpp): check writer errors in TTFA report (errcheck)
golangci-lint errcheck flagged the unchecked fmt.Fprintf calls that
print the streaming TTFA headline. Build the report once with
fmt.Sprintf and write it per destination with an explicitly discarded
error, matching the GinkgoWriter reporting idiom used by the other
backend tests.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-fable-5 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
C++/ggml transcription + speaker diarization + timestamps backend. Purego
dlopens libmoss-transcribe.so (ggml statically linked) from moss-transcribe.cpp
and serves offline AudioTranscription, parsing the [start][Sxx]text[end] output
into segments with nanosecond timestamps. Adds the importer (surfaces in
GET /backends/known), backend-matrix (Linux + Darwin/metal), backend/index.yaml,
and a gallery entry (default q5_k GGUF from mudler/moss-transcribe.cpp-gguf).
Local L0 smoke (go build + go test ./... = 16 pass, golangci-lint 0 issues)
passed against the real libmoss-transcribe.so. The pre-commit coverage gate
(full pkg/core + tests/e2e) could not run in the authoring sandbox (no live
models, port 9090 held); CI must enforce it before merge.
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Link the f5-tts library into the crispasr backend so CrispASR's native
F5-TTS runtime (SWivid F5-TTS, 22-layer DiT flow-matching + built-in Vocos
vocoder) is compiled in. The single self-contained GGUF auto-detects as
f5-tts through the session router, so no explicit backend selector is
needed. Add the f5-tts-crispasr gallery entry (cstr/f5-tts-GGUF) and an
env-gated e2e synthesis spec.
F5-TTS is voice-cloning only and has no baked speaker: it clones from a
reference WAV plus its transcript, supplied via the voice/voice_text
options. The gallery description documents this bring-your-own-reference
requirement.
Verified e2e on the pinned engine (278fb79): the GGUF auto-detects as
f5-tts, the reference voice loads, and synthesis produces a valid 24 kHz
mono WAV.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(schema): accept reasoning_content as inbound alias for reasoning
Interleaved-thinking clients (cogito, vLLM/DeepSeek-style) emit reasoning_content
on assistant turns. Accept it as an inbound alias so reasoning survives the
tool-result loop; canonical reasoning wins when both are present. Emission is
unchanged (still reasoning).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(schema): pin interleaved reasoning+tool_calls round-trip
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(openai): pin reachedTokenBudget truncation detection
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(anthropic): add thinking and signature fields to content blocks
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(anthropic): parse inbound thinking blocks into reasoning
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(anthropic): emit thinking blocks with synthetic signature on tool turns
Extract buildAnthropicContentBlocks so non-streaming content assembly is
unit-testable, and prepend a thinking block (with an opaque synthetic
signature) before text/tool_use blocks when the request opts into thinking.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(anthropic): stream thinking_delta and signature_delta before tool_use
Extract anthropicStreamSequence so the streaming block order is unit-testable,
and emit content_block_start(thinking) -> thinking_delta -> signature_delta ->
content_block_stop before the tool_use block sequence when thinking is enabled.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: add interleaved thinking with tool calls guide
Add a features guide describing interleaved thinking: an assistant turn
carrying reasoning and tool_calls together, the reasoning-round-trip
contract (including the reasoning_content inbound alias and Anthropic
thinking blocks with a synthetic signature), per-backend enablement
(reasoning_format for llama.cpp, reasoning_parser/tool_call_parser for
vLLM/SGLang plus the vLLM auto-config hook), a worked request/response
example, and known limitations. Cross-link from model-configuration,
text-generation, and openai-functions.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(backends): pin grpcio-tools to the installed grpcio in runProtogen
runProtogen installed grpcio-tools unpinned, so the protoc it bundles
stamped backend_pb2.py with the newest Protobuf gencode (7.35.0). When a
backend caps the protobuf runtime lower -- vLLM pins protobuf to 6.33.6 --
the import-time guarantee runtime >= gencode fails:
google.protobuf.runtime_version.VersionError: Detected incompatible
Protobuf Gencode/Runtime versions ... gencode 7.35.0 runtime 6.33.6
The backend crashes on `import backend_pb2` before it can serve, which
surfaces to the user as "grpc service not ready". It was mis-reported as a
ROCm/gfx1201 failure in #10718 but is not GPU-specific and affects every
vLLM variant (and any backend that caps protobuf below the latest gencode).
Pin grpcio-tools to the grpcio version the backend already installed --
they release in lockstep -- so the generated gencode stays in step with
the protobuf runtime. Falls back to unpinned when grpcio isn't present.
Closes#10718
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The OIDC verifier was built with a bare oidc.Config{ClientID: ...}, so
go-oidc applied its default of accepting RS256-signed ID tokens only. An
identity provider configured with an EC signing key (e.g. Authentik) issues
ES256-signed tokens, and the callback failed verification with:
failed to verify ID token: oidc: malformed jwt: unexpected signature
algorithm "HS256"; expected ["RS256"]
surfacing to the user as HTTP 500 "failed to fetch user info" (#10677; the
underlying cause became visible after the logging fix in #10679).
Set SupportedSigningAlgs to the standard asymmetric algorithms
(RS256/384/512, ES256/384/512, PS256/384/512, EdDSA). All are verified
against the provider's published JWKS. HS256 is intentionally excluded: it
is symmetric and would validate against the client secret, a different and
security-sensitive trust model.
Tested with a functional spec that signs an ES256 ID token and confirms it
verifies with the configured algorithms and is rejected under go-oidc's
RS256-only default (using oidc.StaticKeySet, no network).
Closes#10677
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Backend log capture into the per-model BackendLogStore (which feeds the
UI "Backend Logs" page and /api/backend-logs) was opt-in and off by
default in single mode, while worker/distributed mode force-enables it
via SetBackendLoggingEnabled(true). There was no CLI flag either, so the
only way to populate the store was the Settings UI toggle - and the page
was silently empty out of the box. Distributed "just worked"; single
mode looked broken.
Default EnableBackendLogging to true in NewApplicationConfig so single
mode matches worker mode. The store is a small in-memory ring buffer, so
the cost is negligible.
Now that the default is on, loadRuntimeSettingsFromFile's usual
"only flip false->true" merge would ignore a persisted false and revert
the UI toggle-off on every restart. There is no env var/CLI flag for
this setting, so an explicit persisted value is now authoritative in
both directions, letting the toggle-off survive a restart.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The image backends call PIL Image.save(request.dst) without a format, so
Pillow infers the encoder from the file extension. The core passes an
absolute staging path ending in .tmp (e.g. /staging/localai-output-*.tmp),
which Pillow can't map to a format, raising "unknown file extension: .tmp"
and crashing the worker right after a successful GPU inference.
Pass format="PNG" explicitly. LocalAI serves generated images as PNG
regardless of the temporary path, so this is always correct and no longer
depends on the extension of the destination the core happens to allocate.
diffusers is the reported backend (#10727); vllm-omni and tinygrad carry
the identical latent crash for any .tmp staging destination.
Closes#10727
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
fix(transcription): honor model-config language/translate, add language form field
The /v1/audio/transcriptions endpoint read only input.Language /
input.Translate from the parsed request, and the request middleware never
populates those from a multipart upload -- nor did it read a `language`
form field. As a result the model config's parameters.language /
parameters.translate (a valid PredictionOptions field under `parameters:`)
were silently ignored, and multilingual models like canary defaulted to
translating into English even when the YAML set language: ru,
translate: false (#10655).
Resolve both with clear precedence: the request form field wins, then any
language on the parsed request, then the model config default. This also
makes the endpoint honor OpenAI's `language` form parameter, which was
not read before.
Applies to both the streaming and non-streaming paths (the resolved
values are built into the shared TranscriptionRequest). Note this ensures
the language/translate flags reach the backend; whether a given engine
acts on them is up to the backend.
Closes#10655
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
A client that keeps polling a model whose load fails (e.g. a backend that
crashes deterministically on init) triggered a fresh backend start on
every request: request -> load -> crash in ~10s -> 500, repeat on the
next poll. Each attempt could leak GPU/CUDA state, and under
LOCALAI_SINGLE_ACTIVE_BACKEND it kept stealing the active slot from
healthy models. The existing loading-coalesce map only dedups
*concurrent* loads, so sequential polls were never covered.
Track load failures per modelID in ModelLoader. After a load fails,
refuse fresh load triggers for that model until a cooldown elapses,
returning a typed ModelLoadCooldownError that the HTTP layer maps to 503
with a Retry-After header. The cooldown grows exponentially per
consecutive failure (base, doubling, capped at 5m) and resets on a
successful load. The coalesced follower-retry of an in-flight burst
bypasses the gate, so a genuinely concurrent burst still gets its one
retry -- only new, independent triggers are refused, matching the
report's "refuse new load-triggers" wording.
Configurable via --model-load-failure-cooldown /
LOCALAI_MODEL_LOAD_FAILURE_COOLDOWN (default 10s, 0 disables), plumbed
through ApplicationConfig and applied unconditionally at startup.
Closes#10719
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
InstallBackend extracted the artifact directly into the target directory
with no pre-clean, so a reinstall overlaid the new files onto the old
ones. Files present in a previous version but absent in the new artifact
(a stale .so, an orphaned package dir) survived and could shadow the new
build at import time -- e.g. an old vllm shared object lingering next to
a freshly pulled one. Only a failed download cleaned the directory.
Stage the download/extraction into a `<name>.install-tmp` dir, validate
run.sh is present, write metadata, then atomically swap it into place
(rename current -> .install-backup, staging -> current, drop backup),
rolling back on failure. This mirrors the atomic swap UpgradeBackend
already performs, so install and upgrade now leave identical on-disk
state with no orphaned files.
Reported as part of #10720.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The nvidia-l4t-cuda-13-arm64 vLLM backend left `vllm` unpinned, so the
prebuilt image drifted onto whatever aarch64 wheel was latest at build
time (0.23.x). On GB10 / DGX Spark (Grace Blackwell, unified memory),
0.23 crashes deterministically during cold model loads with an empty
"Engine core initialization failed" set and pins GPU memory until a host
reboot.
vLLM 0.24.0 carries vllm-project/vllm#45179 ("release cached device
memory under pressure on UMA GPUs during weight loading"), which the
reporter verified fixes the crash on GB10. Pin the L4T requirements to
0.24.0 to match the already-pinned cublas13 build
(requirements-cublas13-after.txt) and keep the image deterministic.
Editing this file also re-triggers the single-arch L4T image build via
the path filter, republishing the gallery image with 0.24.0 (the
single-arch matrix builds again after #10703).
Closes#10722
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Allow llama.cpp model configs to select the backend devices used for offload, matching upstream --device behavior so users can exclude a display or debug GPU.
Signed-off-by: rvmzes <rvmzes@rvmzess-MacBook-Pro.local>
Co-authored-by: rvmzes <rvmzes@rvmzess-MacBook-Pro.local>
* ⬆️ Update leejet/stable-diffusion.cpp
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(stablediffusion-ggml): pass chroma knobs via model_args after upstream API change
Upstream stable-diffusion.cpp bb849711 removed the dedicated
chroma_use_dit_mask / chroma_use_t5_mask / chroma_t5_mask_pad fields from
sd_ctx_params_t and now reads them from the generic model_args key=value
spec (parse_key_value_args). Assigning the old struct members broke the
gosd.cpp build. Emit the three options into model_args instead so the
existing chroma controls keep working. Verified by building
libgosd-fallback.so against the pinned upstream commit.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
GitHub Actions refuses to instantiate a matrix that would generate more
than 256 jobs. It does so silently: the job hangs forever at "Waiting for
pending jobs" and the whole run is marked `failure` while every other job
stays green. This is exactly what happened on the v4.6.1 tag build
(run 28786533892): the single-arch build matrix had grown to 268 entries,
so `backend-jobs-singlearch` (and its downstream merge) never produced a
single job, and the release build "failed" with no failing job to point at.
The single-arch list is the one that grows unbounded as backends are added,
so shard it across a fixed number of matrix jobs (SINGLEARCH_SHARDS=4,
~67 entries each today, headroom to ~1020 backends). Each merge shard
`needs:` only its matching build shard, preserving the "merge waits only on
its own build" property that keeps slow CUDA/ROCm builds from gating
multi-arch manifest assembly.
changed-backends.js now emits per-shard matrix/has-* outputs and throws
loudly if a shard ever reaches the 256 limit (telling the maintainer to
bump SINGLEARCH_SHARDS and add matching job blocks) instead of letting
GitHub drop the overflow silently. backend.yml and backend_pr.yml define
the four build + four merge shard jobs; multi-arch and darwin groups are
untouched.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
@@ -34,7 +34,7 @@ The build matrix is data-only YAML at `.github/backend-matrix.yml` (not inside `
**Without an entry here no image is ever built or pushed, and the gallery entry in `backend/index.yaml` will point at a tag that does not exist.** The `dockerfile:` field must point at `./backend/Dockerfile.<lang>` matching the language bucket from step 1 (e.g. `Dockerfile.python`, `Dockerfile.golang`, `Dockerfile.rust`). The `tag-suffix` must match the `uri:` in the corresponding `backend/index.yaml` image entry exactly.
**`scripts/changed-backends.js` registration — REQUIRED for any new dockerfile suffix.** This is the single most common omission, because it has no effect on the PR that adds the backend (when no prior path filter could catch it anyway) — it only breaks the *next* PR that touches your backend's directory, which then gets zero CI jobs and looks broken for unrelated reasons. Edit `scripts/changed-backends.js:inferBackendPath` and add a branch BEFORE the more-generic suffixes:
**Path-filter registration — REQUIRED for any new dockerfile suffix.** This is the single most common omission, because it has no effect on the PR that adds the backend (when no prior path filter could catch it anyway) — it only breaks the *next* PR that touches your backend's directory, which then gets zero CI jobs and looks broken for unrelated reasons. Edit `scripts/lib/backend-filter.mjs:inferBackendPath` and add a branch BEFORE the more-generic suffixes:
@@ -54,7 +54,9 @@ for (const e of m.include.filter(e => e.backend === '<your-backend>')) {
}"
```
A quick way to find the right insertion point: `grep -n 'item.dockerfile.endsWith' scripts/changed-backends.js`.
A quick way to find the right insertion point: `grep -n 'item.dockerfile.endsWith' scripts/lib/backend-filter.mjs`.
If your backend consumes a *shared* build input that lives outside its own directory (a new script under `scripts/build/`, a new file copied into every image), add a rule to `SHARED_BUILD_INPUTS` in the same file — the per-backend prefix match cannot see those, and a miss ships your change to no image at all. See `scripts/lib/backend-filter_test.mjs` for the pattern; `make test-ci-scripts` runs it.
**`bump_deps.yaml` registration — REQUIRED for any backend pinning an upstream commit.** If your backend's Makefile has a `*_VERSION?=<sha>` pin to a third-party repo, the daily auto-bump bot at `.github/workflows/bump_deps.yaml` won't notice it unless you register the backend in its matrix. The bot runs `.github/bump_deps.sh` which `grep`s for `^$VAR?=` in the Makefile you list — so the pin MUST live in the Makefile (not in a separate shell script). The bump for ds4 (#9761) had to walk this back because the original landed the pin in `prepare.sh`, which the bot can't see. Pattern (for `antirez/ds4`):
@@ -115,7 +117,7 @@ Wiring a backend into `includeDarwin:` is more than the matrix entry:
1.**`includeDarwin:` entry** — `tag-suffix: "-metal-darwin-arm64-<backend>"`, `build-type: "metal"`, `lang: "go"` for go+ggml backends; omit `build-type` for the bespoke C++ ones (llama-cpp / ds4 / privacy-filter). Match an existing entry of the same shape.
2.**`backend/index.yaml`** — add `metal:` to the backend's `capabilities` map (main and `-development`) and concrete `metal-<backend>` / `metal-<backend>-development` image entries pointing at the `-metal-darwin-arm64-<backend>` images.
3.**C/C++ backends only** — add an `inferBackendPathDarwin` case in `scripts/changed-backends.js` returning `backend/cpp/<backend>/` (the generic fallthrough assumes `backend/<lang>/`, which is wrong for a C++ source tree driven with `lang: go`), and give `run.sh` a Darwin branch that exports `DYLD_LIBRARY_PATH` instead of `LD_LIBRARY_PATH`. If the build is bespoke (single `grpc-server` + dylib bundling), model it on `scripts/build/ds4-darwin.sh` and add a `backends/<backend>-darwin` make target plus a gated step in `.github/workflows/backend_build_darwin.yml`.
3.**C/C++ backends only** — add an `inferBackendPathDarwin` case in `scripts/lib/backend-filter.mjs` returning `backend/cpp/<backend>/` (the generic fallthrough assumes `backend/<lang>/`, which is wrong for a C++ source tree driven with `lang: go`), and give `run.sh` a Darwin branch that exports `DYLD_LIBRARY_PATH` instead of `LD_LIBRARY_PATH`. If the build is bespoke (single `grpc-server` + dylib bundling), model it on `scripts/build/ds4-darwin.sh` and add a `backends/<backend>-darwin` make target plus a gated step in `.github/workflows/backend_build_darwin.yml`.
4.**C++ proto gotcha** — if the backend compiles the generated gRPC/protobuf in a separate CMake target (e.g. `hw_grpc_proto`), that target must link `protobuf::libprotobuf` + `gRPC::grpc++` so the Homebrew include dirs propagate; otherwise macOS fails with `google/protobuf/runtime_version.h not found` (Linux hides this because apt headers sit in `/usr/include`).
The CI path filter only builds a backend on a PR when a file under its directory changes, so a darwin-only YAML edit builds nothing — touch a file under `backend/<lang>/<backend>/` (a one-line comment is enough) in the same PR.
| `backendBuildTagPreferenceRules` | build tags (`cuda`, `rocm`, `metal`) | installed build directory names, as a substring | alias resolution in `ListSystemBackends` |
| `engineNamePreferenceRules` | engine names (`vllm`, `llama-cpp`, `mlx`) | a gallery entry's `backend:`, as a substring | gallery variant ranking |
| `servingFeaturePreferenceTokens` | serving features (`dflash`, `mtp`) | a gallery entry's `tags:`, compared whole and case-insensitively, and nothing else | gallery variant ranking, one rank below the engine |
**Putting a token in the wrong table matches nothing and does not error**: every
candidate scores equal and the next sort key decides, so the preference silently
stops existing. The block comment above all three tables spells the contract out.
The serving feature table is the odd one: it is not keyed by capability, because
no hardware prefers a plain build over an equivalent faster build of the same
weights. It reads a declared tag and nothing else. The entry name was the
original signal and is gone: a naming convention is not a contract, and names
are author-supplied free text where a short marker like `mtp` turns up inside
unrelated words or on weights whose entry enables nothing.
`overrides.options` was rejected for the mirror-image reason: `spec_type:` is
llama.cpp's config vocabulary, whereas a cross-backend ranking decision must
work the same for `ds4`'s `mtp_path:` and `sglang`'s `speculative_algorithm:`.
**If your backend can serve the same weights faster** (speculative decoding,
multi-token prediction), say so in the docs for its gallery entries so curators
tag them: the tagging rule and the per-backend evidence table live in
[adding-gallery-models.md](adding-gallery-models.md). A backend never needs to
appear in the token table itself; it ranks builds, not engines.
Leaving your backend out is a valid choice when no ordering can be justified for
it. It then ranks below every known engine and selection falls back to size,
which is the behaviour that predates preference.
**Leaving a whole capability out is not.** A missing row gives that host an
empty preference list, so size alone decides among everything that survives the
filters, and the filter will not save you: `IsBackendCompatible` derives hardware
support from the engine NAME, so `vllm` and `sglang` carry no darwin, cuda, rocm
or sycl token and are never dropped on a host with no GPU. That is why `default`
(no usable accelerator, including a GPU under the 4 GiB VRAM floor) and
`darwin-x86` both have rows putting `llama-cpp` first. Every capability
`getSystemCapabilities()` can return needs a row unless every engine really is
equally at home there. When you add one, enumerate the engines you are demoting
rather than relying on them falling through unmatched: unmatched engines all tie
with each other, so size decides among them.
## Documenting the backend (README + docs)
A backend is not "added" until it is discoverable. Update the user-facing docs:
@@ -243,7 +308,7 @@ After adding a new backend, verify:
- [ ] Backend directory structure is complete with all necessary files
- [ ] Build configurations added to `.github/backend-matrix.yml` for all desired platforms (per-arch entries with `platform-tag` for multi-arch; `builder-base-image` for llama-cpp / ik-llama-cpp / turboquant)
- [ ]**OS coverage considered**: added to `includeDarwin:` (macOS/Apple Silicon) if the backend can build there — with the `backend/index.yaml``metal:` capability + `metal-<backend>` image entries, a `run.sh` Darwin/DYLD branch and `inferBackendPathDarwin` case for C++ backends — or the PR explains why an OS is unsupported. Do not ship Linux-only by default.
- [ ]**OS coverage considered**: added to `includeDarwin:` (macOS/Apple Silicon) if the backend can build there — with the `backend/index.yaml``metal:` capability + `metal-<backend>` image entries, a `run.sh` Darwin/DYLD branch and `inferBackendPathDarwin` case (in `scripts/lib/backend-filter.mjs`) for C++ backends — or the PR explains why an OS is unsupported. Do not ship Linux-only by default.
- [ ] Meta definition added to `backend/index.yaml` in the `## metas` section
- [ ] Image entries added to `backend/index.yaml` for all build variants (latest + development)
- [ ] Tag suffixes match between workflow file and index.yaml
@@ -251,6 +316,8 @@ After adding a new backend, verify:
- [ ] No YAML syntax errors (check with linter)
- [ ] No Makefile syntax errors (check with linter)
- [ ] Follows the same pattern as similar backends (e.g., if it's a transcription backend, follow `faster-whisper` pattern)
- [ ]**`Load` validates its input and refuses models it can't serve.** When a model config has no explicit `backend:`, the model loader greedily probes *every* installed backend with the model's name and binds to the first `Load` that succeeds — an accept-anything `Load` will capture arbitrary LLMs (issue #9287). Backends that load a real artefact get this for free (the load fails); backends with no artefact must gate on the name: `opus` accepts only its own name (or none), `local-store` requires the `store.NamespacePrefix` namespace marker sent by `core/backend/stores.go`.
- [ ]**Gallery variant ranking considered**: if this backend should be preferred over another on some hardware, it is listed in `engineNamePreferenceRules` (NOT `backendBuildTagPreferenceRules`, NOT `servingFeaturePreferenceTokens`) in `pkg/system/capabilities.go`. A missing entry silently ranks it last and lets the next sort key decide.
- [ ] Documented: added to the category list in `docs/content/features/backends.md` (and any new endpoint/realtime capability documented under `docs/content/`)
- [ ] If it is an in-house native C/C++/GGML engine, added to the maintained-engines table in the top-level `README.md`
@@ -28,7 +28,6 @@ The core Go suites (`./pkg`, `./core`, plus the in-process integration suite `./
- **Build tags (`COVERAGE_TAGS`, passed via `GINKGO_TAGS`):** defaults to `debug auth`. The `auth` tag is required to compile the real (sqlite-backed) auth implementation and its ~150 `//go:build auth` tests — without it those files aren't built, the tests don't run, and the gate scores auth against a stub (~3.7% instead of ~38%). If you add new tag-gated tests, extend `COVERAGE_TAGS` or they won't count (and likely won't run in CI at all).
-`make test-coverage-check` — runs `test-coverage`, then `scripts/coverage-check.sh` fails the build if total coverage is **below** the committed baseline in `coverage-baseline.txt`. The Linux job in `.github/workflows/test.yml` runs this instead of `make test`.
-`make test-coverage-baseline` — regenerates and overwrites `coverage-baseline.txt` from the current run.
-`make install-hooks` — sets `core.hooksPath` to the versioned `.githooks/`, whose `pre-commit` runs checks scoped to what's staged: Go changes → `make lint` + `make test-coverage-check`; `core/http/react-ui/` changes → `make test-ui-coverage-check` (Playwright e2e + UI coverage gate). A commit touching neither is skipped; bypass with `git commit --no-verify`. The hook resolves golangci-lint's new-from base to `upstream/master` → `origin/master` → `master`, so it works from a fork clone where `origin/master` is stale (passed to `make lint` via `LINT_NEW_FROM`).
### React UI coverage
@@ -38,12 +37,11 @@ The React UI (`core/http/react-ui/`) has **no component/unit tests** — its onl
- **Browser:** the flake dev shell ships `chromium` and exports `PLAYWRIGHT_CHROMIUM_PATH`; `playwright.config.js` uses it via `launchOptions.executablePath`, and the Makefile skips `playwright install` when it's set. This avoids Playwright's downloaded browser, which can't resolve system libs (`libglib-2.0`, …) on NixOS. In CI (no `PLAYWRIGHT_CHROMIUM_PATH`) the Makefile falls back to `playwright install --with-deps chromium`.
- The app is a React SPA, so coverage accumulates across in-app navigation within a test; a full `page.goto`/reload resets it.
-`.nycrc.json` uses `all: true`, so **every `src/**` file is in the report**, including 0%-coverage ones — that's how you spot features with no test at all (sort the HTML report or `coverage-summary.json` by line% ascending).
- **UI coverage gate:** `make test-ui-coverage-check` runs the suite then `scripts/ui-coverage-check.sh`, failing if total line coverage drops more than `UI_COVERAGE_TOLERANCE` below `core/http/react-ui/coverage-baseline.txt`. `make test-ui-coverage-baseline` regenerates the baseline. Runs in CI (`tests-ui-e2e.yml`) and pre-commit on `core/http/react-ui/` changes.
- **UI coverage gate:** `make test-ui-coverage-check` runs the suite then `scripts/ui-coverage-check.sh`, failing if total line coverage drops more than `UI_COVERAGE_TOLERANCE` below `core/http/react-ui/coverage-baseline.txt`. `make test-ui-coverage-baseline` regenerates the baseline. Runs in CI (`tests-ui-e2e.yml`).
- **Why it has a tolerance (unlike the strict Go gate):** UI e2e coverage is *non-deterministic*. Specs that assert on state and end while async/lazy render work is still in flight collect those lines only when the render beats the coverage teardown — so the total drifts with machine speed/load (a fast local box reads higher than a slow CI runner), diffusely across many specs. The tolerance absorbs that drift, so set the baseline *below* the slow-CI floor, never to a fast-local `make test-ui-coverage-baseline` number, or CI flaps.
- **Raising coverage is cheap:** a *render-smoke* spec (navigate to a route, assert its header renders) mounts a lazy page and runs its full render + initial effects, capturing most of its lines in a few lines of test — see `e2e/page-render-smoke.spec.js`. Auth is disabled in the test server (`isAdmin=true`), so `RequireAdmin`/`RequireFeature` routes render without a mock. The most *deterministic* win is removing a race: make a spec `await` a rendered element before ending (see `e2e/agents.spec.js` → AgentCreate) so its lines count every run.
Rules (both gates):
- **Install the hooks:** `make install-hooks` once per clone so lint + coverage run pre-commit. Don't lean on CI for what the hook catches.
- **Don't work around the gate:** never `git commit --no-verify`, and never hand-lower a baseline or widen a tolerance to turn a red gate green. The ratchet only moves up.
- **Don't weaken the gate:** never hand-lower a baseline or widen a tolerance to turn a red gate green. The ratchet only moves up.
- If a change drops coverage, **add tests** (sort `coverage-summary.json` by line% ascending to find untested code) rather than editing the baseline. When coverage legitimately rises, commit the regenerated baseline (`make test-coverage-baseline` / `test-ui-coverage-baseline`).
- The Go gate is **strict — no tolerance**; `covermode=atomic` keeps it deterministic. The UI gate keeps a small tolerance only because its e2e coverage isn't.
@@ -114,8 +114,97 @@ Both `backend.yml` (push) and `backend_pr.yml` (PR) generate their matrix dynami
- **Tag pushes**: `FORCE_ALL=true` is set from the workflow side (`startsWith(github.ref, 'refs/tags/')`) — releases rebuild every backend regardless of diff.
- **Schedule / `workflow_dispatch`**: no `event.before`, falls through to "run everything" automatically.
### Shared build inputs
The per-backend prefix match only sees files under a backend's own directory, so a change to shared build infrastructure would rebuild *nothing* — an empty matrix, every job green, and the change reaching no image. That silently un-shipped PR #10946 (a partial-cuDNN packaging fix in `scripts/build/package-gpu-libs.sh`), which merged 1h48m after the weekly cron and so sat unbuilt for a week.
`SHARED_BUILD_INPUTS` in `scripts/lib/backend-filter.mjs` closes that hole. Each rule maps a shared path to the narrowest set of matrix entries it can honestly invalidate, since a full matrix is 417 Linux + 56 Darwin builds:
| Changed path | Rebuilds |
|---|---|
| `backend/backend.proto` | nothing if the edit is additive-only, otherwise everything (see below) |
| `backend/Dockerfile.<x>` | the Linux entries whose `dockerfile:` names it |
| `backend/python/common/` | Python, Linux + Darwin |
| `scripts/build/package-gpu-libs.sh` | every Linux entry (Python, Go and C++ all run it) |
| `scripts/build/<lang>-darwin.sh` | the Darwin entries that build target routes to |
| `.github/workflows/backend_build[_darwin].yml` | everything on that OS |
| anything else under `scripts/build/` (except `*_test.sh`) | everything — conservative default for unclassified packaging inputs |
Deliberately excluded: `backend/index.yaml` (gallery metadata, never enters an image), `.github/backend-matrix.yml` (adding a backend would rebuild all of them), `backend/Dockerfile.base-grpc-builder` (owned by `base-images.yml`), and the root `Makefile` (touched in ~11% of commits, and its backend-relevant edits arrive alongside the backend directory anyway). `make test-ci-scripts` pins all of this.
#### `backend/backend.proto` is content-filtered, not path-filtered
Every language consumes the proto, so a path rule for it can only ever say "rebuild all 473 images". It changes in ~1.3% of commits, and that was enough to make it the single largest CI cost driver in the repo: on 2026-07-29 four runs totalling 935 queued jobs traced to nothing but a proto edit, one of which (#11158) was a six-line diff adding `bool cache_prompt = 8;`.
An additive proto edit cannot change how a backend that never references the new symbol behaves, so `filterMatrix()` suppresses the rule for one. `changed-backends.js` fetches `backend/backend.proto` at the base revision (same contents-API pattern as `.github/backend-matrix.yml`) and hands both texts to `protoChangeIsAdditive()`, which compares them structurally rather than textually:
- **Additive, rebuilds nothing**: a new field with an unused number, a new message, a new enum value, a new RPC. Comment, whitespace and ordering changes also land here.
- **Breaking, rebuilds everything**: a removed, renumbered, retyped or renamed field, a dropped RPC, a changed `option` or `package`. So does an unresolvable base revision, matching the run-all posture used for a truncated diff.
Checked against every proto commit in the preceding six months, all nine resolvable ones classify as additive. Note the tradeoff this accepts: generated stubs do change for an additive edit, so image bytes would differ on a rebuild even though behavior does not. That is the same standard already applied when the filter declines to rebuild on unrelated `pkg/` changes, and the weekly cron remains the backstop.
The Sunday 06:00 UTC cron on `backend.yml` exists specifically because path filtering can leave Python backends frozen on stale wheels. `DEPS_REFRESH` (below) only fires when the build actually runs, so an untouched Python backend would never re-resolve its unpinned deps. The weekly cron is the safety net.
## Content-blind PRs skip the workflows that cannot see them
`backend_pr.yml` and `test-extra.yml` filter themselves (matrix generation and a `detect-changes` job), so a gallery-only or docs-only PR costs them about one job each. The Go and image workflows had no filter of any kind, so a one-line `gallery/index.yaml` edit queued 20 jobs, and a docs-only PR queued the same.
This is worth more than it looks. Measured over the week to 2026-07-30, **97% of CI wall-clock is queueing, 3% is execution** (median queue ~5h against a 4-20min median job). Cutting job count is therefore the only lever that shortens feedback time; making individual jobs faster moves 3%.
The volume is real: 13 gallery-only PRs merged that week with 10 open at once, and 78 of the 137 PRs opened were bot-generated.
`paths-ignore` on the PR trigger of `image-pr.yml` (7 jobs), `build-test.yaml` (3), `lint.yml` (2) and `tests-e2e.yml` (1) drops 13 of those 20. The excluded set:
| Path | Why no image or Go build can see it |
|---|---|
| `gallery/**` | Model-gallery metadata, parsed at runtime, never copied into an image |
| `docs/**`, `examples/**`, `**/*.md` | Never enter an image or a binary. `lint.yml` already excluded these before gallery was added |
### `backend/{cpp,go,python}/**` on `image-pr.yml` and `build-test.yaml` only
Version-pin bumps dominate PR volume: 48 `update/*` PRs in the week to 2026-07-30, from 16 pins, each a two-line diff. Most edit nothing but one `backend/*/<name>/Makefile`.
Neither of those two workflows can observe such a change. `make build` is `go build ./cmd/local-ai`, GoReleaser builds the same plus `./cmd/launcher`, and the core image's final stage ships only `entrypoint.sh`, `healthcheck.sh` and that binary. The per-backend trees are copied into the builder but nothing in them reaches the output.
What still triggers a full run, because none of it lives under those prefixes:
-`backend/backend.proto` — feeds `protogen-go`, so it does change the binary.
-`go.mod` / `go.sum` — the `go mod tidy` before-hook.
-`backend/Dockerfile.*` and anything else directly under `backend/`.
Deliberately **not** applied to:
| Workflow | Why it must keep seeing `backend/**` |
|---|---|
| `test.yml` | `TEST_PATHS` explicitly includes `./backend/go/cloud-proxy/...`, `./backend/go/local-store/...` and `./backend/go/valkey-store/...` |
| `lint.yml` | `.golangci.yml` carries `backend/`-scoped rules, so golangci-lint covers that tree |
| `tests-e2e.yml` | The e2e suite drives real backends over gRPC |
| `backend_pr.yml` | This is the workflow whose entire job is to rebuild the changed backend |
What still runs, and why it has to:
| Workflow | Why it keeps running |
|---|---|
| `test.yml` (`tests`) | `core/gallery/variants_lint_test.go` reads the real `gallery/index.yaml` and asserts the index invariants (no duplicate entry names, no build claimed by two parents). This is the only schema-level check the gallery has. |
| `yaml-check.yml` (`Yamllint`) | Lints `gallery/` for syntax. |
| `backend_pr.yml`, `test-extra.yml` | Already self-filtering; they stop after the detect step. |
Two properties this relies on:
-`paths-ignore` skips a run only when **every** changed file matches, so a PR touching the gallery *and* Go code still runs everything. That is what makes the exclusion safe rather than a hole.
-`master` carries no branch protection and no rulesets, so a skipped workflow reports no status and nothing waits on it. If required status checks are ever introduced, these four entries must be excluded from the required set or PRs will hang on "Expected — Waiting for status to be reported".
### `image.yml` on master push is gated too, by a job rather than a path filter
The same reasoning applies to master pushes, and the volume is larger there: on 2026-07-30, **12 of the 23 queued `image.yml` runs** were commits like "add 1 new model to gallery" or a docs fix, each rebuilding all 18 container images.
`image.yml` now has a `changes` job that decides once whether the push can affect any image; the other 11 jobs carry `needs: changes` plus an `if:` on its output. Verified against the shipped `Dockerfile`: the final stage copies only `entrypoint.sh`, `healthcheck.sh` and the `local-ai` binary, there is no `go:embed` of `gallery/` or `docs/`, and the gallery is fetched at runtime from `github:mudler/LocalAI/gallery/index.yaml@master`. A gallery-only commit therefore produces byte-identical images, and the gallery change reaches users through GitHub immediately whether or not an image is rebuilt.
Two properties to preserve if you touch it:
- **It is a job gate, not `paths-ignore`.** `paths-ignore` on `push` also applies to tag pushes, and a tag created on an existing commit carries an empty commits list, which would silently skip the release image build. The gate short-circuits to "build" for `refs/tags/*`, and for any push whose base commit is missing, zero, or unresolvable.
- **The merge jobs must name the gate explicitly.** They use `if: ${{ !cancelled() && ... }}`, and `!cancelled()` is true when a dependency is *skipped*, so without the extra condition they would run and try to merge manifest lists for images that were never built.
## The `DEPS_REFRESH` cache-buster (Python backends)
Every Python backend goes through the shared `backend/Dockerfile.python`, which ends with:
@@ -151,15 +240,38 @@ RUN --mount=type=cache,target=/root/.ccache,id=<backend>-ccache-${TARGETARCH}-${
bash /usr/local/sbin/compile.sh
```
The compile script exports `CMAKE_C/CXX/CUDA_COMPILER_LAUNCHER=ccache` so CMake threads ccache through gcc/g++/nvcc. `cache-to: type=registry,mode=max` exports the cache mount data into the registry cache, so subsequent builds restore it.
The compile script exports `CMAKE_C/CXX/CUDA_COMPILER_LAUNCHER=ccache` so CMake threads ccache through gcc/g++/nvcc. Cache scope is per `(TARGETARCH, BUILD_TYPE)` so e.g. cublas-12 doesn't share with cublas-13 (their CUDA headers differ; cross-pollination would just be cache misses anyway).
On a `LLAMA_VERSION` bump, most translation units are byte-identical to the previous version's preprocessed source — ccache returns the previous `.o` and skips the real compile. Same for LocalAI source changes that don't actually touch llama.cpp's CMake inputs. Cache scope is per `(TARGETARCH, BUILD_TYPE)` so e.g. cublas-12 doesn't share with cublas-13 (their CUDA headers differ; cross-pollination would just be cache misses anyway).
### ⚠️ This ccache does nothing in CI today
This section previously claimed that `cache-to: type=registry,mode=max` "exports the cache mount data into the registry cache, so subsequent builds restore it". **That is not true.** BuildKit does not export the contents of a `--mount=type=cache` to a registry cache export. A cache mount lives in the builder's local state, and every CI job gets a fresh runner with a fresh builder, so `/root/.ccache` starts empty on every single build.
Measured on 2026-07-30 from the `ccache -s` output the compile script already prints (it runs `ccache -z` first, so the numbers are per-build):
| Job | Commit touched | Build time | ccache |
|---|---|---|---|
| 89766266951 (llama-cpp, cublas 13) | `backend/go/magpie-tts-cpp/Makefile` only | 6369s | **0 / 889 hits**, and 0 / 1778 |
The first two are the decisive control: commit `90355cd44` changed exactly one file, `backend/go/magpie-tts-cpp/Makefile`, nowhere near llama.cpp. The engine source was byte-identical to the previous build, which is precisely the case this section says ccache should serve, and the hit rate was still **0.00%**. A cache that was being restored but merely matching poorly would show partial hits; 0-of-N is the signature of an empty cache.
So the paragraph above about `LLAMA_VERSION` bumps reusing previous `.o` files describes an intended design that is not in effect. `Dockerfile.{llama-cpp,ik-llama-cpp,turboquant,bonsai,ds4,privacy-filter}` pay the ccache wrapper overhead and get nothing back. Multi-hour C++ rebuilds are recompiling identical translation units from scratch.
**Do not "fix" this by adding cache mounts to more Dockerfiles.** Wiring the same mount into `Dockerfile.golang` (215 of the 434 matrix entries) was measured locally at 18% faster on a rebuild after a source edit, with a 71.5% ccache hit rate — but only because the local test reused one builder across both builds. In CI it would be a no-op for exactly the reason above.
Making this actually work needs the cache to live outside the builder. The options, none of them free:
- **ccache `remote_storage`** (ccache ≥ 4.4, HTTP or Redis backend) or **sccache** with an S3/GCS/Redis backend. Genuinely works across runners; needs a cache service to point at. quay.io is a registry, not a blob store, so the existing infra does not cover it.
- **Round-trip the cache dir through `actions/cache` on the runner**: restore it, pass it in, and export it back out via a build stage output. No external infra, but clunky, and the repo already sits at GitHub's 10 GB cache ceiling while the llama-cpp ccache alone is capped at 5 GB.
Until one of those lands, treat C++ backend builds as always-cold and spend the effort on not running them instead (path filtering, see above).
## Composite actions
Two composite actions handle runner-side prep:
- **`.github/actions/free-disk-space/action.yml`** — wraps `jlumbroso/free-disk-space@main` plus an explicit apt purge of dotnet/android/ghc/mono/etc. Reclaims ~6–10 GB on `ubuntu-latest`. No-op on self-hosted runners. Used by `backend_build.yml`, `image_build.yml`, `test.yml`, `tests-aio.yml`, etc.
- **`.github/actions/free-disk-space/action.yml`** — wraps `jlumbroso/free-disk-space@main` plus an explicit apt purge of dotnet/android/ghc/mono/etc. Reclaims ~6–10 GB on `ubuntu-latest`. No-op on self-hosted runners. Used by `backend_build.yml`, `image_build.yml` and `base-images.yml` — the jobs that actually build images. Deliberately **not** used by `test.yml`, which runs no buildx step.
- **`.github/actions/setup-build-disk/action.yml`** — relocates Docker's data-root to `/mnt` on hosted X64 runners. GHA hosted `ubuntu-latest` ships ~75 GB of unused space at `/mnt`; combined with the free-disk-space cleanup this gives ~100 GB working space — enough for ROCm dev image + vLLM torch install + flash-attn intermediate layers. No-op on self-hosted and on non-X64 hosted runners. Used by `backend_build.yml`, `image_build.yml`, `base-images.yml`.
Both actions run before any docker buildx step.
@@ -200,10 +312,20 @@ Eviction is rarely needed in normal operation — `DEPS_REFRESH` handles weekly
## What the cache does **not** cover
- The `free-disk-space` and `setup-build-disk` composite actions run on every job — these reclaim runner-state, not Docker layers, so BuildKit caches don't apply.
- The `free-disk-space` and `setup-build-disk` composite actions run on every job — these reclaim runner-state, not Docker layers, so BuildKit caches don't apply.`test.yml` deliberately does **not** use `free-disk-space`: it runs no buildx step, and the multi-GB fixture downloads that once justified it left `make test` in the test-suite reorg.
- Intermediate artifacts of `Build (PR)` are not pushed anywhere — PRs only build for verification.
- Darwin builds (see below) — macOS runners have no Docker daemon, so the registry-backed BuildKit cache cannot apply.
### The Linux Go workflows set `cache: false` on purpose
`test.yml`, `lint.yml`, `tests-e2e.yml` and friends pass `cache: false` to `actions/setup-go@v5`, unlike the darwin jobs. This looks like an oversight and is not.
Measured over the week to 2026-07-30, the `Set up Go` step has a **median of 11 seconds** on these runners. There is essentially nothing to win: the module download is not where the time goes. The expensive steps are compilation and test execution (`Test (with coverage gate)` at ~18.6min, `Test Backend E2E` at ~14.5min), and Go's build cache would have to survive across runners to touch those.
Enabling it also has a real cost. GitHub caps Actions cache at **10 GB per repo and the repo already sits at that ceiling** (31 entries), so every `setup-go` entry written by a branch with a distinct `go.sum` (222-375 MB on Linux, up to 1.4 GB on macOS) evicts something else. See the darwin cache budget below.
Before re-enabling this, measure `Set up Go` again and confirm it has actually become slow. If room is needed in the 10 GB budget, the cheapest evictions are the `docker.io--tonistiigi--binfmt` entries (~30 MB each, trivially re-fetched).
## Darwin native caches
`backend_build_darwin.yml` runs natively on `macOS-14` GitHub-hosted runners — there is no Docker, no BuildKit, no cross-job registry cache. Instead, the reusable workflow uses `actions/cache@v4` for four native caches that mirror the spirit of the Linux cache (warm by default, weekly refresh for unpinned Python deps, PRs read-only).
@@ -237,6 +359,26 @@ GitHub Actions caches are limited to 10 GB per repo. Steady-state worst case: ~8
One residual self-hosted reference remains in `test-extra.yml` (`tests-vibevoice-cpp-grpc-transcription` uses `bigger-runner` for the 30s JFK-decode timeout headroom). That's a separate concern.
### Small always-on jobs routed to `arc-runner-set`
The hosted pool is shared across the whole *account*, not per repo, so a burst in one repo starves the others. On 2026-07-31 it went to **zero scheduled jobs for 35 consecutive minutes** with 39 jobs queued, while `arc-runner-set` completed 12 jobs without interruption over the same window. Actions was healthy globally at the time (other public repos were scheduling normally), so this is an account-level throttle, not an outage.
`gh-pages.yml` (`build` + `deploy`) is therefore routed to `arc-runner-set` when `github.repository == 'mudler/LocalAI'`. It needs no fork-safety clause because it only triggers on push-to-master and `workflow_dispatch`, so it never executes pull-request code. The repository guard keeps forks (which have no such runner label) from queueing forever. It fetches its own toolchains via `setup-go` / `actions-hugo` and uses no `sudo`/`apt`.
#### What the `arc-runner-set` image actually contains
Measured 2026-07-31 on run `30637392862` by a preflight step, not assumed:
That is why `lint.yml` is **not** on the self-hosted pool. Both of its jobs were routed there and both failed in one second: `golangci-lint` needs `make` (for `make protogen-go`, itself needing `curl`+`unzip` to fetch protoc, and for `make lint`), and `build-scripts` additionally needs a C toolchain because the packaging-script tests compile a throwaway binary and inspect it with `ldd`. Both jobs are back on `ubuntu-latest`.
The preflight steps were deliberately left in place. They cost about a second on the hosted pool and mean that whenever the runner image gains `make` + `gcc`, re-routing is one `runs-on:` line per job and any remaining gap reports itself by name rather than as an opaque mid-build failure.
Note for any future re-route: `lint.yml` also triggers on `pull_request`, and a fork PR runs untrusted contributor code. That must never reach a persistent self-hosted runner, so any re-route has to stay push-only, e.g. `${{ (github.event_name == 'push' && github.repository == 'mudler/LocalAI') && 'arc-runner-set' || 'ubuntu-latest' }}`.
## Touching the cache pipeline
When changing `image_build.yml`, `backend_build.yml`, any of the `backend/Dockerfile.*` files, `Dockerfile.base-grpc-builder`, `.docker/install-base-deps.sh`, `.docker/<backend>-compile.sh`, or `scripts/changed-backends.js`:
@@ -65,7 +65,42 @@ This is enforced by `forbidigo` (see `.golangci.yml`): `http.DefaultClient` and
The project documentation is located in `docs/content`. When adding new features or changing existing functionality, it is crucial to update the documentation to reflect these changes. This helps users understand how to use the new capabilities and ensures the documentation stays relevant.
- **Docs-with-code rule**: When you change user-facing behavior (API endpoints, CLI flags, config keys, or features), update the corresponding page under `docs/content/` in the SAME change, not as a follow-up. A user-facing change without a matching docs update is incomplete. The PR template carries a checklist item for this.
- **Feature Documentation**: If you add a new feature (like a new backend or API endpoint), create a new markdown file in `docs/content/features/` explaining what it is, how to configure it, and how to use it.
- **Configuration**: If you modify configuration options, update the relevant sections in `docs/content/`.
- **Examples**: providing concrete examples (like YAML configuration blocks) is highly encouraged to help users get started quickly.
- **Shortcodes**: Use `{{% notice note %}}`, `{{% notice tip %}}`, or `{{% notice warning %}}` for callout boxes. Do **not** use `{{% alert %}}` — that shortcode does not exist in this project's Hugo theme and will break the docs build.
## React UI styling
The React UI ships a design system in `core/http/react-ui/src/App.css`: design
tokens, form grids, data tables, stat cards, callouts, plus a small semantic
A release is not finished when the tag is pushed. The GitHub release, the blog post and the demo clips ship together, because the changelog says what moved and the post and the clips are what make anyone care.
## What a release must include
1.**Labels on the merged PRs.** GitHub generates the raw notes from PR labels, so label first, generate second. Wrong labels mean a miscategorised changelog that has to be edited by hand.
2.**`RELEASE_NOTES_vX.Y.Z.md`** at the repository root, in the house style: what changed, why it matters, PR numbers so people can read the diffs.
3.**A blog post under `website/content/blog/`.** One post per release, front matter with `title`, `date`, `author`, `category: "Release"`, `tags`, `summary` and `extracss: ["blog.css"]`. Cover the two or three changes that alter what a user does day to day, not the whole changelog, and link the PR numbers. See `website/content/blog/what-landed-in-localai-4-8.md` for the shape.
4.**Demo clips for the notable features.** Anything visible (a new backend, a UI change, a new endpoint, a measured speedup) gets a short screen recording. Put the file in `website/static/media/`, reference it from the blog post, and reuse it on the marketing pages where it fits.
A release without a post and without clips is incomplete, in the same way a user-facing code change without a docs update is incomplete.
## Clip conventions
- MP4, H.264, no audio track unless the feature is about audio. Keep them short (10 to 30 seconds) and loopable.
- Record the real thing. A clip from the engine's own benchmark suite or a real session, never a mockup.
- Where the change is a speedup, record both sides on the same machine on the same input, so the comparison is honest.
- Name the file after the feature, not the release (`vllm-race.mp4`, not `v4-8-demo.mp4`), so it stays reusable once the release is old.
- The marketing site plays clips with `muted loop playsinline preload="none"` and a `data-lazy` attribute, which the site's IntersectionObserver uses to play and pause them on scroll. Follow that pattern for anything you add.
## Order of work
Label the PRs, generate and edit the release notes, cut the draft release, record the clips while the branch is still fresh in your head, then write the post against the notes and the clips. Publishing the release and merging the post should happen on the same day.
The `creating-localai-releases` skill drives steps 1 to 3 and captures the React UI screenshots that go into the notes.
Beyond the parser names above, `Options[]` carries `--` prefixed engine flags (`--enable-prefix-caching`, `--kv-cache-dtype:fp8_e5m2`). `apply_options_to_engine_args` in `backend/python/common/vllm_utils.py` maps them onto `AsyncEngineArgs` fields, and it must run **before**`AsyncLLMEngine.from_engine_args()` - applying them afterwards is a silent no-op, which is exactly what issue #11130 was.
Things to keep straight when touching this:
- Precedence is typed proto fields → `options:` → `engine_args:`. `applyEngineArgDefaults` in `core/config/hooks_vllm.go` therefore skips seeding a production default whose key the user already set as an option, otherwise the later `engine_args:` pass would silently override them.
- Only `--` prefixed entries are engine flags; `tool_parser:`/`reasoning_parser:` and friends keep their meaning. Parser lookups accept both spellings via `normalize_option_key`.
- Unknown or uncoercible flags warn and are skipped, unlike `engine_args:` which is strict - `Options[]` is a shared bag and knows entries this mapping doesn't.
- Field types come from the annotation's *base* (`Literal["auto","float16"]` is not a float). The helper's tests are stdlib-only: `make test-python-helpers`.
Auto-defaults for known model families live in `core/config/parser_defaults.json` and are applied:
- at gallery import time by `core/gallery/importers/vllm.go`
- at model load time by the `vllm` / `vllm-omni` backend hook in `core/config/hooks_vllm.go`
if echo "$staged" | grep -qE '\.go$'; then go_changed=1; fi
if echo "$staged" | grep -qE '^core/http/react-ui/'; then ui_changed=1; fi
if echo "$staged" | grep -qE '^(core/http/endpoints/openai/(coordinator|respcoord|turncoord|conncoord|compactcoord|ttscoord)/|formal-verification/)'; then rt_changed=1; fi
if [ "$go_changed" -eq 0 ] && [ "$ui_changed" -eq 0 ] && [ "$rt_changed" -eq 0 ]; then
echo "pre-commit: no Go, React UI, or realtime-spec changes staged — skipping."
exit 0
fi
if [ "$go_changed" -eq 1 ]; then
# Resolve the ref golangci-lint's new-from-merge-base should compare
# against. .golangci.yml pins origin/master, which is correct in CI
# (origin == the canonical repo) but wrong from a fork clone, where
# origin/master lags behind and lint would report the whole upstream
# backlog. Prefer upstream/master, then origin/master, then master.
lint_base=""
for ref in upstream/master origin/master master; do
if git rev-parse --verify --quiet "${ref}^{commit}" >/dev/null 2>&1; then
`nemotron-3-nano-omni-30b-a3b-reasoning-apex`) are **ordinary builds**, not hubs.
They are referenced from their hub's variants list like any other rung, and are
never deleted or renamed.
## Flags
| Flag | Default | Meaning |
|------|---------|---------|
| `-index <path>` | `gallery/index.yaml` | Gallery index to dedup against. Read only, unless `-apply` is passed. |
| `-only <a,b,c>` | (all) | Comma-separated full repo names (`mudler/Foo-APEX-GGUF`) to restrict generation to. A name that matches nothing is reported as a warning, since it is a typo rather than an empty result. |
| `-out <path>` | (none) | Write the entries to add to this file. Nothing is written to the gallery. |
| `-apply` | `false` | Splice the variants into `-index` and append the new entries to it. |
| `-verify <path>` | (none) | Verify a gallery index and exit. Ignores every other flag. |
Either `-out` or `-apply` is required, otherwise the run has nothing to do.
`-apply` splices variant lines into existing entries and **appends** new ones. It
never re-serialises the index: it is roughly 40,000 lines, and a YAML round trip
would reflow the whole file, drop the anchors and merge keys the gallery relies
on, and produce a diff nobody can review. On the three-family sample the splice
is 24 added lines across 3 hunks with zero deletions.
## Discovery is by filename suffix, never by repo name
Builds come from the files a repo actually publishes. A filename is never
constructed from a repo name, because the two disagree:
`mudler/gemma-4-26B-A4B-it-APEX-GGUF` ships `gemma-4-26B-A4B-APEX-*.gguf`, and
five other repos likewise drop a suffix (`-it`, `-2603`) or a vendor prefix
(`NVIDIA-`) that the repo name carries. Composing a URL from the repo name would
produce a 404 for every one of them, and the 404 would only surface after the
entry shipped.
The quality ladder is matched on the trailing tier marker, `-(I-)?(Quality|
Balanced|Compact|Mini|Nano).gguf`. The `I-` prefix marks the imatrix ladder. The
imatrix ladder is emitted when it is non-empty and the plain ladder is used only
as a fallback, because two of the 45 repos publish no imatrix tiers at all and
must still contribute. Eleven repos carry a fifth `I-Nano` rung, so nothing
assumes a fixed number of rungs.
Every run prints, per repo, the counts that discovery accounted for. If the
number of classified files is short of the number of `.gguf` files the repo
publishes, the shortfall is printed as `UNCLASSIFIED`. That check is a set
difference on counts rather than a second pass over filenames: a second matcher
would duplicate the tier regex and the two copies would drift. The failure it
catches is quiet. A publishing-script typo that breaks every imatrix filename in
a repo does not produce a short ladder; it makes the imatrix ladder empty, and
the fallback then downgrades the whole family to the plain ladder with nothing
said. A downstream HTTP check cannot catch it either, because it validates the
URLs that were emitted, and an undiscovered tier emits none.
The same reasoning applies to `UNACCOUNTED QUANT`, printed when the unsloth
counterpart demonstrably publishes a wanted quant that produced no build. It is
reported at discovery time because a dropped quant leaves no trace at all in the
finished gallery file.
## sha256 always comes from the API
Every file stanza takes its `sha256` from the HuggingFace models API
(`lfs.sha256`). A GGUF the API describes without one is a fatal error for that
family: the repo is reported by name and the run ends non-zero. It is never
substituted from another field, because that is exactly how a Xet hash ends up
masquerading as a content hash.
## The dflash / mtp tagging rule
An entry is tagged `dflash` or `mtp`**if and only if** it configures the
matching `spec_type:draft-<feature>`. Variant ranking reads tags and nothing
else, so a tag that does not match the configuration either promotes a build
that is no faster or hides one that genuinely is.
A repo name is not configuration. `mudler/Qwen3.6-35B-A3B-APEX-MTP-GGUF` ships
weights that carry MTP heads; an entry that does not enable them is not an MTP
entry and is not tagged as one.
A generated hub inherits the tags of the build it carries as its payload, rather
than rebuilding them from the base set, so a hub whose payload configures a
`spec_type` stays tagged consistently with the overrides copied alongside it.
## Reuse reporting: two categories, not one
Generated entries are deduped against the gallery and against the batch itself.
The run prints the result under two separate headings, because the two cases are
not equivalent:
- **URI MATCHES** mean the gallery, or an earlier entry in this batch, already
ships exactly these weights. Pointing the hub at the existing entry is correct
and needs no thought.
- **NAME COLLISIONS** mean an entry already owns the name but holds different
weights. Referencing it would point the hub at a build other than the one
generated. Every one of these must be inspected by hand.
The run then prints `HUBS SPLICED`, listing every reference that will be added to
an entry the gallery already ships along with the line it will be added at, and
`HUBS CREATED` for the families that get a new hub. The splices are the part a
review has to read closely, because they modify entries somebody else wrote.
Hubs are deliberately kept out of the merge. A new hub carries the family's top
rung as its own payload, so URI dedup would fold the hub into that rung and the
family would lose the very entry point this command exists to create.
## Workflow: sample first, then the full set
Never run the full generation straight into the gallery. Generate a small,
deliberately awkward sample, have it reviewed, then run the rest.
```bash
# 1. Sample three families that between them cover the awkward shapes:
# a standard four-rung repo, one with the extra I-Nano rung AND a file stem
# that differs from its repo name, and one whose unsloth counterpart shards
fmt.Printf("\nREPOS SKIPPED AS UNAVAILABLE (%d) - HuggingFace answered 401/403, which is indistinguishable from absent without a token; check none of these is a real gated repo\n",len(skipped))
b.WriteString("This is a proposal, not a decision. The gallery agent adds one build per model and never joins an existing family, so entries that are alternative builds of the same weights drift apart as the gallery grows. This job re-applies the grouping heuristics from the manual sweeps and asks a human to confirm.\n\n")
b.WriteString("Each family below lists the parent, the variants, and the evidence that they are the same weights. **Reject anything whose evidence you do not believe.**\n\n")
b.WriteString(fmt.Sprintf("To decline a family permanently, add one line to `%s` in this pull request and close it:\n\n",ledgerPath))
b.WriteString(fmt.Sprintf("### Declined by the ledger (%d)\n\n",len(r.Suppressed)))
iflen(r.Suppressed)==0{
b.WriteString("Nothing the heuristics found was already on the ledger.\n\n")
}else{
b.WriteString("Candidates the heuristics found and the ledger has already settled. They are listed so the ledger's effect stays visible rather than silently shrinking the job's output.\n\n")
b.WriteString(fmt.Sprintf("### Aliases, not variants (%d)\n\n",len(r.AliasSkipped)))
b.WriteString("These entries install byte for byte the same payload. An alias exists so clients can send a particular name; folding it under another entry would hide that name.\n\n")
b.WriteString("---\n\nOpened by `.github/ci/variantproposals`. Heuristics and the rejection ledger live there and in the ledger file; a wrong proposal is a bug in one of the two.\n")
returnb.String()
}
funcjoinSignals(signals[]Signal)string{
iflen(signals)==0{
return"inferred through another member of the family"
}
out:=make([]string,0,len(signals))
for_,s:=rangesignals{
out=append(out,"`"+string(s)+"`")
}
returnstrings.Join(out,", ")
}
funcdescribeEvidence(eEvidence)string{
varparts[]string
ife.SharedStem!=""{
parts=append(parts,fmt.Sprintf("same name once quantization markers are stripped: `%s`",e.SharedStem))
}
ife.SharedFile!=""{
parts=append(parts,fmt.Sprintf("same primary weight filename once quantization markers are stripped: `%s`",e.SharedFile))
// A parent that is itself somebody's variant would create a chain, which
// the gallery's own resolution refuses to install.
ifowner,claimed:=claimedBy[parentName];claimed{
returnnil,&Refusal{Members:names,Reason:fmt.Sprintf("the natural parent %q is already a variant of %q; proposing it as a parent would nest variants",parentEntry.Name,owner)}
returnnil,&Refusal{Members:names,Reason:fmt.Sprintf("the natural parent %q is already proposed as a variant of %q; proposing it as a parent would nest variants",parentEntry.Name,owner)}
}
// Adding a variants key to an anchor is inherited by every entry that
// merges it, silently grouping models nobody proposed. Handling that means
// editing each merging child too, which is a larger change than this job
// should make unsupervised, so it refuses and hands the reviewer the list.
Reason:fmt.Sprintf("the parent %q defines YAML anchor &%s, and a variants key added there is inherited by the %d entries that merge it (%s). Grouping this family by hand also means adding an explicit `variants: []` to each of those entries",
returnnil,&Refusal{Members:names,Reason:fmt.Sprintf("%q already offers variants of its own, so it cannot itself be a variant target",target.Name)}
}
if!target.Installable(){
returnnil,&Refusal{Members:names,Reason:fmt.Sprintf("%q has no url, config_file, overrides or files, so it is not independently installable",target.Name)}
returnnil,&Refusal{Members:names,Reason:fmt.Sprintf("%q is already a variant of %q; a target claimed by two parents is not something the gallery resolves predictably",target.Name,owner)}
return0,fmt.Errorf("more than one entry is named exactly %q (%s), so which one is the base build is a judgement this job will not make",familyStem,strings.Join(names,", "))
}
// No shared stem to be named after. An entry whose name every other member
// extends is still recognisably the base one, and this is the only handle
// left for families whose weights carry no readable quantization token at
// all, such as the ONNX builds.
ifprefix,ok:=uniquePrefixMember(ix,members);ok{
returnprefix,nil
}
best:=-1
bestWidth:=1<<20
for_,m:=rangemembers{
e:=ix.Entries[m]
width:=unknownWidth
ifprimary,ok:=e.PrimaryWeightFile();ok{
width=BuildWidth(primary)
}
// Members are visited in gallery order, so a strict comparison leaves
// the earliest entry holding a tie and the choice is deterministic.
ifwidth<bestWidth{
best,bestWidth=m,width
}
}
ifbest<0{
return0,fmt.Errorf("no member could be identified as the smallest build")
}
ifbestWidth==unknownWidth{
names:=make([]string,0,len(members))
for_,m:=rangemembers{
names=append(names,ix.Entries[m].Name)
}
return0,fmt.Errorf("no member declares a weight file whose quantization can be read (%s), so the smallest build cannot be identified",strings.Join(names,", "))
}
returnbest,nil
}
// uniquePrefixMember reports the single member whose name every other member's
stale-issue-message:'This issue is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 5 days.'
stale-pr-message:'This PR is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 10 days.'
| [.agents/preparing-a-release.md](.agents/preparing-a-release.md) | Cutting a release: PR labels, `RELEASE_NOTES_vX.Y.Z.md`, the blog post under `website/content/blog/`, and the demo clips under `website/static/media/` |
## Quick Reference
- **Git hooks & coverage gates**: Run `make install-hooks` once per clone so the pre-commit lint + coverage gates run. **Never bypass them with `git commit --no-verify`, and never lower a coverage baseline or widen a gate's tolerance to turn a red gate green** — the coverage ratchet only moves up. If a change drops coverage, add tests to raise it (e.g. render-smoke specs). See [.agents/building-and-testing.md](.agents/building-and-testing.md).
- **Coverage gates**: Never lower a coverage baseline or widen a gate's tolerance to turn a red gate green — the coverage ratchet only moves up. If a change drops coverage, add tests to raise it (e.g. render-smoke specs). See [.agents/building-and-testing.md](.agents/building-and-testing.md).
- **Logging**: Use `github.com/mudler/xlog` (same API as slog)
- **Go style**: Prefer `any` over `interface{}`
- **Comments**: Explain *why*, not *what*
- **Docs**: Update `docs/content/` when adding features or changing config
- **Docs (docs-with-code rule)**: When you change user-facing behavior (API endpoints, CLI flags, config keys, or features), update the corresponding page under `docs/content/` in the SAME change, not as a follow-up. A user-facing change without a matching docs update is incomplete. See also the documentation conventions in [.agents/coding-style.md](.agents/coding-style.md).
- **New API endpoints**: LocalAI advertises its capability surface in several independent places — swagger `@Tags`, `/api/instructions` registry, auth `RouteFeatureRegistry`, React UI `capabilities.js`, docs. Read [.agents/api-endpoints-and-auth.md](.agents/api-endpoints-and-auth.md) and follow its checklist — missing any surface means clients, admins, and the UI won't know the endpoint exists.
- **Admin endpoints → MCP tool**: every admin endpoint that an admin would manage conversationally (install/list/edit/toggle/upgrade) MUST also be exposed as an MCP tool in `pkg/mcp/localaitools/`. The LocalAI Assistant chat modality and the standalone `local-ai mcp-server` consume that package; drift between REST and MCP is a real risk. Read [.agents/localai-assistant-mcp.md](.agents/localai-assistant-mcp.md) — the `TestToolHTTPRouteMappingComplete` test fails until you wire the new tool and update the route map.
- **Releases ship with a post and clips**: a release is not done at the tag. It needs labelled PRs, `RELEASE_NOTES_vX.Y.Z.md`, a blog post under `website/content/blog/`, and a short demo clip in `website/static/media/` for each notable feature. See [.agents/preparing-a-release.md](.agents/preparing-a-release.md).
- **Build**: Inspect `Makefile` and `.github/workflows/` — ask the user before running long builds
- **Backend OS coverage**: a new backend must target every OS it can build for, not just Linux. `.github/backend-matrix.yml` has two matrices — `include:` (Linux) and `includeDarwin:` (macOS / Apple Silicon). Most C/C++/GGML and many Python backends build on Darwin too — wire the `includeDarwin` entry + `backend/index.yaml``metal:` entries, or say in the PR why an OS is unsupported. See the darwin checklist in [.agents/adding-backends.md](.agents/adding-backends.md).
- **Gallery variant ranking**: a gallery entry can declare `variants` (alternative builds of the same weights), and LocalAI ranks the ones a host can run by engine preference first, size second. A new backend that should be preferred on some hardware must be listed in `engineNamePreferenceRules` in `pkg/system/capabilities.go`; the sibling `backendBuildTagPreferenceRules` speaks build tags rather than engine names, and using the wrong table matches nothing without erroring. See [.agents/adding-backends.md](.agents/adding-backends.md).
- **UI**: The active UI is the React app in `core/http/react-ui/`. The older Alpine.js/HTML UI in `core/http/static/` is pending deprecation — all new UI work goes in the React UI
@@ -198,7 +198,6 @@ For AI-assisted development, see [`AGENTS.md`](AGENTS.md) (or the equivalent [`C
- Prefer modern Go idioms — for example, use `any` instead of `interface{}`.
- Use [`golangci-lint`](https://golangci-lint.run) to catch common issues before submitting a PR.
- Run `make install-hooks` once per clone to enable the pre-commit hook: Go changes run `make lint` + the coverage gate (`make test-coverage-check`); `core/http/react-ui/` changes run the Playwright e2e suite (`make test-ui`). Bypass a single commit with `git commit --no-verify`.
- Use [`github.com/mudler/xlog`](https://github.com/mudler/xlog) for logging (same API as `slog`). Do not use `fmt.Println` or the standard `log` package for operational logging.
- Use tab indentation for Go files (as defined in `.editorconfig`).
@@ -268,7 +267,7 @@ make test-e2e
### React UI tests and coverage
The React UI (`core/http/react-ui/`) is covered by Playwright e2e specs, gated by a **monotonic line-coverage ratchet** (`make test-ui-coverage-check`, run in CI and pre-commit). The metric is non-deterministic — a fast local box reads higher than a slow CI runner for the same code — so a small tolerance is unavoidable.
The React UI (`core/http/react-ui/`) is covered by Playwright e2e specs, gated by a **monotonic line-coverage ratchet** (`make test-ui-coverage-check`, run in CI). The metric is non-deterministic — a fast local box reads higher than a slow CI runner for the same code — so a small tolerance is unavoidable.
**If your change lowers UI coverage, raise it back by adding specs — do not widen the tolerance or hand-lower the baseline.** A *render-smoke* spec (navigate to a page, assert its header is visible) cheaply covers an entire lazy page. See `core/http/react-ui/e2e/page-render-smoke.spec.js` and the full policy in [.agents/building-and-testing.md](.agents/building-and-testing.md#react-ui-coverage).
@@ -177,7 +177,7 @@ For more details, see the [Getting Started guide](https://localai.io/basics/gett
## Latest News
- **June 2026**: New native biometric backends from the LocalAI team: [voice-detect.cpp](https://github.com/mudler/voice-detect.cpp) for speaker recognition and voice analysis (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++, wav2vec2 age/gender/emotion) and [face-detect.cpp](https://github.com/mudler/face-detect.cpp) for face detection, recognition, demographics and anti-spoofing (SCRFD/ArcFace, YuNet/SFace). Both are from-scratch C++/ggml engines with no Python or onnxruntime at inference, self-contained GGUF weights, bit-exact parity with the reference, and GPU cuDNN parity, replacing the heavier Python `insightface` and `speaker-recognition` backends ([PR #10441](https://github.com/mudler/LocalAI/pull/10441)).
- **June 2026**: New native biometric backends from the LocalAI team: [voice-detect.cpp](https://github.com/localai-org/voice-detect.cpp) for speaker recognition and voice analysis (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++, wav2vec2 age/gender/emotion) and [face-detect.cpp](https://github.com/mudler/face-detect.cpp) for face detection, recognition, demographics and anti-spoofing (SCRFD/ArcFace, YuNet/SFace). Both are from-scratch C++/ggml engines with no Python or onnxruntime at inference, self-contained GGUF weights, bit-exact parity with the reference, and GPU cuDNN parity, replacing the heavier Python `insightface` and `speaker-recognition` backends ([PR #10441](https://github.com/mudler/LocalAI/pull/10441)).
- **June 2026**: New [realtime voice assistant demo](https://github.com/localai-org/localai-realtime-demo) (a tiny Go client for the Realtime API with a full talk-back voice loop and tool calling), plus [streaming of the realtime LLM / TTS / transcription pipeline stages](https://github.com/mudler/LocalAI/pull/10176) and [configurable WebRTC ICE candidates](https://github.com/mudler/LocalAI/pull/10231).
- **June 2026**: Big speech push: the [parakeet.cpp](https://github.com/mudler/parakeet.cpp) ASR engine gains [NeMo-faithful segment timestamps](https://github.com/mudler/LocalAI/pull/10207), a [multilingual streaming Nemotron-3.5 model](https://github.com/mudler/LocalAI/pull/10199), [dynamic batching for concurrent transcription](https://github.com/mudler/LocalAI/pull/10112) and [CUDA graphs](https://github.com/mudler/LocalAI/pull/10273); the new [CrispASR backend](https://github.com/mudler/LocalAI/pull/10099) adds multi-architecture ASR + TTS, and [60 Piper TTS voices across 42 languages](https://github.com/mudler/LocalAI/pull/10296) land in the gallery (plus [per-request TTS instructions and params](https://github.com/mudler/LocalAI/pull/10172)).
- **June 2026**: New backends and models: [locate-anything.cpp](https://github.com/mudler/LocalAI/pull/10264) for open-vocabulary object detection via ggml, [Ideogram4 image generation](https://github.com/mudler/LocalAI/pull/10201) in stablediffusion-ggml, [llama.cpp video input](https://github.com/mudler/LocalAI/pull/10216), and the [Gemma 4 QAT family with MTP speculative-decoding pairs](https://github.com/mudler/LocalAI/pull/10215). Plus an [interactive CLI chat mode](https://github.com/mudler/LocalAI/pull/10226) and [RAG source citations in agent responses](https://github.com/mudler/LocalAI/pull/10228).
@@ -231,13 +231,21 @@ Most backends wrap a best-in-class upstream engine. A handful of them are native
| Backend | What it does |
|---------|-------------|
| [vllm.cpp](https://github.com/mudler/vllm.cpp) | From-scratch C++20 port of vLLM for text generation: paged KV cache, continuous batching, prefix caching, safetensors + GGUF loading, engine-enforced structured output, on CPU, CUDA, Metal and Vulkan |
| [parakeet.cpp](https://github.com/mudler/parakeet.cpp) | C++/GGML port of NVIDIA NeMo Parakeet ASR (tdt/ctc/rnnt/hybrid), with cache-aware streaming transcription |
| [ced.cpp](https://github.com/mudler/ced.cpp) | C++/GGML port of the CED audio-tagging models: sound-event classification (527-class AudioSet) over REST and the realtime API for live recognition |
| [voxtral.c](https://github.com/mudler/voxtral.c) | Voxtral Realtime 4B speech-to-text in pure C |
| [moss-transcribe.cpp](https://github.com/localai-org/moss-transcribe.cpp) | C++/GGML port of OpenMOSS MOSS-Transcribe-Diarize: joint long-form transcription, speaker diarization and timestamping in a single pass |
| [moss-tts.cpp](https://github.com/mudler/moss-tts.cpp) | C++/GGML port of the OpenMOSS MOSS-TTS family: text-to-speech (MOSS-TTS-Local v1.5, 48 kHz stereo) with reference-audio voice cloning, through the MOSS-Audio-Tokenizer neural codec |
| [magpie-tts.cpp](https://github.com/mudler/magpie-tts.cpp) | C++/GGML port of NVIDIA's Magpie TTS Multilingual 357M: 22.05 kHz mono text-to-speech in 5 voices and 9+ languages, with the NanoCodec neural codec and tokenizer/G2P embedded in a single GGUF |
| [ced.cpp](https://github.com/localai-org/ced.cpp) | C++/GGML port of the CED audio-tagging models: sound-event classification (527-class AudioSet) over REST and the realtime API for live recognition |
| [voice-detect.cpp](https://github.com/localai-org/voice-detect.cpp) | Speaker recognition and voice analysis (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++, wav2vec2 age/gender/emotion), replacing the Python speaker-recognition backend |
| [voxtral-tts.c](https://github.com/mudler/voxtral-tts.c) | Mistral Voxtral-4B-TTS text-to-speech in pure C: 20 preset voices across 9 languages, 24 kHz WAV output, no dependencies beyond libc |
| [vibevoice.cpp](https://github.com/mudler/vibevoice.cpp) | Native port of Microsoft VibeVoice for TTS (voice cloning) and long-form ASR with speaker diarization |
| [face-detect.cpp](https://github.com/mudler/face-detect.cpp) | Face detection, recognition, demographics and anti-spoofing (SCRFD/ArcFace, YuNet/SFace), replacing the Python insightface backend |
| [free-splatter.cpp](https://github.com/localai-org/free-splatter.cpp) | Pose-free 3D reconstruction (FreeSplatter): turns a handful of plain photos into 3D Gaussians, no camera poses or GPU required |
| [trellis2.cpp](https://github.com/localai-org/trellis2cpp) | C++/GGML port of Microsoft TRELLIS.2: single-image to textured 3D mesh (GLB with PBR materials) |
# Gated on cublas because the variable means nothing to any other build, so a
# stray CUDA_MAJOR_VERSION in the environment must not break `make clean` or
# a CPU build. It does still error for `BUILD_TYPE=cublas make clean`, which
# is the right trade: that invocation is asking about a CUDA build tree.
$(error CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) has no architecture list here (12 and 13do). Leave it empty for a native build, or pass CUDA_ARCHITECTURES explicitly.)
$(warning audio-cpp: libomp not found at '$(LIBOMP_PREFIX)'; building without OpenMP (single-threaded host DSP). Install it with `brew install libomp`, or set LIBOMP_PREFIX.)
CMAKE_ARGS+= -DENGINE_ENABLE_OPENMP=OFF
endif
else
# Portable Linux CPU. Upstream wires this to GGML_BACKEND_DL +
# GGML_CPU_ALL_VARIANTS + $ORIGIN rpath, so one build serves every CPU
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