WhisperX silently returned a plain transcript when diarization lacked
the Hugging Face token required to load pyannote. Reject that request
clearly so callers do not mistake missing speaker labels for a
successful diarization.
Convert WhisperX seconds to the nanosecond duration unit used by the
transcription API.
Assisted-by: Codex:gpt-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
- the PR template's 'Signed commits' anchor pointed at a CONTRIBUTING
section that does not exist; repointed at the Commit messages
section
- the longcat-video backend README linked a docs page that was never
committed; replaced the dead link with plain text
- formal-verification/README.md used ../../../ for five in-repo
packages (escaping the repo root); fixed to ../
Two independent breakages on master make every open pull request red,
for reasons unrelated to the changes under review.
The e2e backend suite stopped compiling. Reply.message is `bytes` in
backend.proto, so res.GetMessage() returns []byte, and strings.ToUpper
wants a string. Every other call site in the file already converts.
tests/e2e-backends sits behind a build tag, so `go build ./...` never
compiled it and the breakage reached master unnoticed.
The darwin vllm build stopped resolving. Upstream vllm-metal deleted
its old dev tags and re-versioned to track the vLLM release it targets,
so the pinned wheel 404s. The coupled vLLM release also moved out of
upstream's install.sh into .github/vllm-release-tag.commit, and the
wheel's platform tag moved from macosx_11_0 to macosx_15_0.
Read the wheel name from the release's own asset listing rather than
composing it from a hardcoded platform segment, so a platform-tag
change cannot silently 404 again, and resolve the vLLM version from
the new metadata file with a fallback to the legacy installer. The
bump script and the extractor learn the same two-source lookup, so the
next nightly run converges on the pin checked in here instead of
reintroducing the break.
Assisted-by: Claude:claude-opus-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Add complete vLLM and SGLang entries with their exact tool parsers. Preserve an explicit zero temperature in both backend adapters.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Those backends only forwarded the flag when it was "true", so "false"
never reached apply_chat_template and Qwen3 kept thinking on.
Signed-off-by: lei_lei <96427312+leilei3167@users.noreply.github.com>
* test: make coverage failures observable
Keep per-root logs, reject concurrent coverage runs, and avoid relying on /bin/sleep in the worker timeout test.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: parallelize coverage without remote fixtures
Assisted-by: Codex:gpt-5 [apply_patch] [exec_command]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: add offline resource infrastructure
Introduce versioned resource manifests, a checksum-verified CAS preparer, offline test wrappers, and a guarded network transport. Replace live Hugging Face, GitHub, and OCI cases with deterministic fixtures and inject fixture metadata into importer discovery.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: enforce offline resource replay
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: harden offline resource refresh
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: expose slow coverage waits
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: eliminate avoidable wall-clock waits
Inject a clock into Hugging Face retry handling, reuse a process-scoped PostgreSQL container with per-spec schemas in the nodes suite, and poll local import jobs promptly.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: remove repeated fixture startup waits
Share PostgreSQL fixtures across parallel endpoint and agent suite workers, and make the worker Free deadline injectable so the wedged-backend test does not spend five seconds on wall-clock time.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: fix offline resource CI portability
Normalize Docker archive metadata before content addressing, derive archive checksums during explicit refreshes, make network lint portable to macOS, and prepare distributed images before running their offline suite.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: cache Go modules before offline tests
Warm the complete module graph before the Linux and macOS test jobs enter offline replay mode, so tool dependencies such as Ginkgo are not fetched through the guarded proxy.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: drop the static network lint in favour of real isolation
The offline test suite already prevents tests from reaching the network
twice over: run-test-linux-offline.sh puts the test process in a cgroup
and REJECTs egress outside the private ranges, and HardenedTransport
installs testnetwork.LocalGuard to refuse dials that resolve to a public
address. Both fail the test with a precise error at the moment of the
dial.
test-network-lint.sh added neither. Its diff stage defaulted to a HEAD
base, so on a clean checkout it compared the tree against itself and
inspected nothing; the branch's own commits were never examined. It only
produced output when an earlier job step dirtied the tree, and then it
matched a bare https?:// against whatever changed. make react-ui runs
npm install rather than npm ci, so CI rewrote
core/http/react-ui/package-lock.json and the lint reported an npm
registry URL as forbidden test network access:
+ "resolved": "https://registry.npmjs.org/hono/-/hono-4.12.25.tgz",
Its fingerprint stage was self-defeating in a quieter way: hashing the
whole tree's network-mechanism inventory meant every rebase onto a master
that touched any _test.go needed a manual baseline bump, so the check
mostly caught its own staleness.
Remove the script, its make target and the two prerequisite edges, along
with the test-network: fixture markers that existed only to suppress it.
The isolation itself is untouched.
Assisted-by: Claude:claude-opus-5 [go vet]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: keep hidden files in the offline test bundle artifact
Cherry-picked from 15a37b0ac on the remote branch. The offline bundle lives
under .cache/, which actions/upload-artifact skips by default, so the Linux
job packed an artifact missing the very file the next step restores.
The other half of 15a37b0ac moved test-network-lint out of the `test` and
`test-coverage` prerequisite lists into a recipe line, so parallel make could
not fingerprint the tree while generated fixtures were still changing. That
is dropped: the preceding commit removes the lint entirely, and the race it
worked around is one more reason a whole-tree fingerprint was the wrong
mechanism.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* refactor: share bounded exponential backoff
Use overflow-safe saturating arithmetic for retry delays across model import polling, downloads, registration, node operations, and model loading. Keep model import status checks responsive initially while capping their interval at 500ms.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: mirror Jetson Python wheels
Keep the CUDA aarch64 wheel subset in GHCR and serve it as a local PEP 503 index during L4T backend builds, preserving last-known-good packages through upstream outages.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* docs(agents): index the Jetson wheels mirror
Mention the GHCR-hosted L4T wheel mirror in the CI caching guide summary so maintainers can find its outage and cache documentation.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: add defensive build network proxy
Record build destinations and byte counts, retry observable idempotent HTTP downloads, and isolate explorer database tests that race under coverage.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(kokoros): implement updated backend trait
Return unimplemented for image upscaling, matching the backend's other unsupported modalities after the protobuf API update.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(ci): clear recovered proxy errors
Do not mark a request failed when a later safe retry succeeds.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: require HTTPS build interception
Inject a short-lived proxy CA into BuildKit and Dockerfile RUN steps, reject plain HTTP and opaque tunnels, and retain method/status/byte telemetry for verified HTTPS traffic.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(ci): preserve system trust in unproxied builds
Mount the generated interception CA at a dedicated secret path and add it to the trust bundle only in proxy-aware dependency stages. This prevents optional secret mounts from masking the system CA bundle in ordinary backend test builds.
Install the requested Go toolchain before starting the proxy and satisfy cleanup error checks found by CI lint.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(ci): persist build proxy trust
Install the generated proxy CA through the system-managed local certificate directory so ca-certificates upgrades retain it. Avoid turning canceled matrix jobs into proxy cleanup failures.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(ci): trust proxy in nested build scripts
Install the build proxy CA before nested source fetches, route the DS4 package setup through the HTTPS mirror helper, and avoid repeated OCI setup in gallery behavior tests.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(ci): use HTTPS apt sources for Bonsai
Rewrite ARM64 package sources before installing GCC and check gallery fixture cleanup errors so the optimized tests satisfy errcheck.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(privacy-filter): trust build proxy CA
Install the mounted build proxy certificate before privacy-filter's make target fetches its HTTPS sources, for both source and prebuilt builder paths.\n\nAssisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* test: fail on hidden offline egress
Count cgroup-scoped firewall rejects and fail the offline test harness with bounded aggregate diagnostics. Inject the gen-audio GGUF probe so fixture-backed importer tests do not attempt real network access.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(ci): preserve system CA trust
Build a combined runner certificate bundle instead of replacing public roots with the generated proxy CA. Centralize additive container installation in the shared proxy CA helper.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* feat(router): make KNN a first-class classifier with a persisted, curated corpus
Add `classifier: knn` — similarity-weighted voting over labelled
example prompts. Unlike score/colbert it needs no classifier model:
label knowledge lives in a corpus seeded and curated through the
admin API, so routing decisions are deterministic, auditable, and
grounded in graded experience rather than a model's opinion.
Epistemic gate: corpus entries below knn.similarity_threshold cannot
vote; when none clears it the classifier activates no labels and the
router uses the fallback — a prompt unlike all labelled experience is
treated as undecidable, not guessed. Decisions record
nearest_similarity (also on fallback rows) so admins can see how far
the nearest labelled experience was; the Routing tab explains
out-of-corpus fallbacks and shows per-label corpus counts.
Persistence: one JSONL file per router under
<data path>/router-corpus (text, labels, vector, embedder
fingerprint). The file is the source of truth; the local-store index
is rebuilt from it at classifier build time and stays a pure
in-memory index. Entries recorded under a different embedding model
re-embed on load. Also corrects the docs' false claim that
local-store collections persist — the embedding cache never survived
restarts (and still doesn't); the corpus does.
Corpus input is API-only by design (entries may contain example user
content): POST /api/router/{name}/corpus seeds (labels validated
against declared policies, embedded server-side, indexed
immediately), GET .../corpus/stats inspects — label counts only,
entry texts are never returned by any surface — DELETE .../corpus
wipes. Admin-gated like the sibling router endpoints, and exposed as
MCP tools (seed_router_corpus / get_router_corpus_stats /
clear_router_corpus) in both the httpapi and inproc clients with
coverage-test route mappings.
Plumbing: VectorStore gains SearchK (top-K was hardcoded to 1);
local-store gets InsertBatch/Delete as optional fast paths;
RouterConfig gains a knn block (embedding_model, k,
similarity_threshold, vote_threshold, store_name) with meta-registry
fields; the classifier dropdown now offers knn and the
previously-missing colbert; embedding_cache is ignored (with a
warning) for knn — it IS an embedding-KNN lookup; the stale
/api/instructions intelligent-routing entry is rewritten (it
described a classifier that no longer exists); swagger regenerated.
Tests: KNN vote/gate specs with hand-computed vote shares, corpus
manager suite (restart reload without re-embedding, fingerprint
re-embed, dedupe, hostile store names), middleware specs (corpus
routing, gate fallback, config validation, cache-wrap refusal),
corpus endpoint specs pinning the texts-never-returned contract, MCP
catalog + route-mapping gates, and a Playwright spec for corpus
stats and the out-of-corpus decision detail.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(router): name consulted corpus neighbours in knn decisions
Every knn decision (decision log rows and the /api/router/decide
response) now carries neighbors: the K retrieved corpus entries by
descending similarity - including ones below the epistemic gate, which
is what makes fallback decisions diagnosable - each as {id, similarity,
labels}. The id is the entry's content hash (first 8 bytes of the
SHA-256 of its text, hex): stable across reseeds and re-embeds, and
text-free, so an external platform that seeded the corpus can recompute
text->id on its own copy and bucket decisions by corpus region (per-
region reliability accounting) without corpus text ever leaving the
server. A corrupt index payload surfaces as an id-less neighbour at a
real similarity instead of disappearing.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* refactor(router): deduplicate knn plumbing and cut corpus hot-path waste
Post-review cleanup of the knn-first-class-router branch; no behaviour
changes on the API surface.
Reuse/altitude:
- RouterKNNConfig.ResolvedStoreName is now the single source of the
router-corpus-<name> default (was hand-derived in four files).
- corpus.ResolveKNNRouter + corpus.Seed carry the shared model
resolution and seed validation; the REST endpoints and the assistant
MCP client are thin transport adapters over them, with sentinel
errors mapped to HTTP statuses at the echo boundary.
- middleware.NewClassifierDeps assembles the classifier dependency set
once for all five entry points (OpenAI, Anthropic, realtime, decide,
corpus) instead of five hand-copied literals.
- router.AllClassifiers feeds both the status endpoint and the
unknown-classifier error, ending the classifier-list drift.
- Per-classifier requirements moved out of validateRouterPolicies into
their buildClassifier arms; the knn arm owns its embedding_cache
opt-out instead of a name-check in the shared wrap tail.
- adminOnly replaces four inline copies of the admin gate in the
middleware routes.
- localVectorStore.Search delegates to SearchK (identical traces).
Efficiency:
- Manager.Add embeds outside the manager mutex and appends to the
JSONL file (O(new) instead of O(corpus) rewrite); a torn tail from a
crash mid-append is tolerated on read and repaired on next write.
- Stats memoises per store keyed on the file's stat fingerprint and no
longer takes the manager mutex, so the 5s status poll stops parsing
vector-laden JSONL and stops blocking behind seeds.
- KNN Classify decodes each neighbour payload once (was twice) and
builds refs and votes in a single pass with one fallback return.
- Corpus file writes fsync before rename/close.
- The corpus manager is built eagerly in newApplication (sync.Once
dropped); test helper dead branch removed.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(router): bind knn corpus vectors to an embedder fingerprint and fail closed on mismatch
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(mcp): align corpus tool prompts and the mutating-tool safety list
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(proto,backend): report embedding shape from the llama-cpp backend
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(embeddings): Go-side pooling — mean/last/decayed_mean with half-life
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(embeddings): accept chat messages[] and per-request pooling on /v1/embeddings
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(middleware): name the failing fields when post-merge validation 400s
An intermittent post-merge validation failure surfaced as an opaque 400
during integration (pooling scheme mismatch that no client had sent).
Log the model, the request's pooling override, and the merged config's
pooling fields at the failure point so the next occurrence identifies
whether the request or the stored config carried the bad value.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(embeddings): scheme override must not inherit the config's half-life
A model config defaulting to decayed_mean pooling carries
pooling_half_life_tokens; a request overriding the scheme to mean/last
without its own half-life inherited that value, and post-merge
validation rejected the pair the server itself had assembled. Zero the
inherited half-life when the overridden scheme is not decayed_mean; a
request that explicitly pairs a half-life with a non-decayed scheme
still 400s.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix embedding pooling validation and router bounds
Declare backend embedding layouts and reject incompatible pooling modes. Reset local-store dimensions after a full clear, validate KNN thresholds, and add real backend and store integration coverage.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: run local-store integration tests
Build and install the local-store backend in the Linux test job, then run the existing store integration suite so new specs are discovered automatically.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
The upstream editable install pins generic PyTorch packages. It
replaces the HIP wheels with CUDA wheels in ROCm images.
Remove those pins only for hipBLAS builds before the editable install.
Keep the existing CPU and CUDA dependency behavior unchanged.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(ci): parse current vllm-metal version pins
vllm-metal renamed its installer pin from vllm_v to VLLM_VERSION, breaking both the nightly bumper and the Darwin backend installer after a bump. Share a strict parser that accepts both formats and cover the transition with shell regressions.
Assisted-by: Codex:gpt-5 [Codex]
* fix(ci): parse scoped vllm-metal pins
The pinned vllm-metal installer declares its version as a local shell variable. Accept that optional declaration while retaining strict validation of the assignment and semantic version.
Assisted-by: Codex:gpt-5.4
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(vllm): align Intel basekit runtime
The latest vLLM XPU requirements install oneAPI 2026 runtime packages. The 2025.3.0 base image ships an older libsycl/UR loader pair and fails while importing torch with an undefined urDeviceWaitExp symbol. Use the current repository-wide 2025.3.2 Intel basekit patch level, which carries the compatible loader.
Assisted-by: Codex:gpt-5 [systematic-debugging]
* fix(vllm): pin Intel source build to release
Build the Intel XPU backend from vLLM 0.26.0 instead of the moving main branch, and use the Triton XPU version required by that release's torch 2.12 dependency.
Assisted-by: Codex:gpt-5 [systematic-debugging]
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Every CUDA sglang image failed in the 2026-08-02 full-matrix rebuild:
-gpu-nvidia-cuda-12-sglang, -gpu-nvidia-cuda-13-sglang and
-nvidia-l4t-cuda-13-arm64-sglang, all with the same build error.
Building cuda-tile==1.6.0rc3
x Failed to build `cuda-tile==1.6.0rc3`
ModuleNotFoundError: No module named 'wheel_stub'
hint: `cuda-tile` (v1.6.0rc3) was included because `sglang` (v0.5.16)
depends on `flashinfer-python` (v0.6.14) which depends on `cuda-tile`
This is the failure mode requirements-cublas1{2,3}-after.txt already
carries an nvidia-modelopt bound for, arriving through a different
package. install.sh passes a global --prerelease=allow, which is
load-bearing for flash-attn-4, so an unbounded dependency resolves to a
prerelease; cuda-tile 1.6.0rc3's build backend imports wheel_stub without
declaring it in build-system.requires; --no-build-isolation means nothing
provides it, and the build dies.
Nothing in this repo changed. cuda-tile published 1.6.0rc1 and rc3 and
the weekly cron picked them up, which is the drift that job exists to
catch.
Bound the one package rather than dropping the global flag, matching the
existing precedent. 1.5.0 is the newest stable release, so <1.6 takes the
last good one. l4t13 gets the same bound: it installs plain sglang rather
than sglang[all], but flashinfer-python is a dependency of both.
NOT VERIFIED LOCALLY: reproducing this needs a CUDA docker build, which
this machine cannot run. The diagnosis is from the CI log and the
resolver's own hint, and the change follows a fix already proven in these
same files. CI on this PR is the check that matters.
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>
* feat(api): add POST /v1/images/upscale endpoint
Add a new image upscaling endpoint that accepts a source image and
returns an upscaled version. Supports selectable upscaler models
(e.g. realesrgan) and a configurable scale factor (2x or 4x).
- backend.proto: add UpscaleImage RPC and UpscaleImageRequest message
- pkg/grpc: implement UpscaleImage in Backend interface, client, server
and embed shim
- core/backend/upscale.go: new backend helper (mirrors ImageGeneration)
- core/http/endpoints/openai/upscale.go: new multipart/form-data handler
- core/http/routes/openai.go: register POST /v1/images/upscale
- core/http/auth/features.go: gate upscale routes under FeatureImages
- backend/python/diffusers/backend.py: implement UpscaleImage — uses
diffusers upscale pipeline when loaded, falls back to Lanczos resize
* fix(grpc): add UpscaleImage stub to Base backend
All Go backends embedding Base now satisfy the AIModel interface
without needing to implement UpscaleImage explicitly.
* fix(images): complete upscale endpoint integration
Store generated upscales under the served images directory, validate scale factors, document and advertise the endpoint, and add a functional Stable Diffusion x4 gallery model.
Assisted-by: Codex:gpt-5
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
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>
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>
* 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>
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>
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>
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>
