Backend processes shared the host temporary directory, so crashes could leave request images and audio behind until the filesystem filled. Give each process a locked LocalAI-owned runtime, remove scratch on exit, and sweep only marked abandoned runtimes at the next start.
Also close known request error-path leaks in the Python media backends, CrispASR, LongCat Video, and stable-diffusion.cpp.
Assisted-by: Codex:gpt-5
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The device fell back to CPU unless the model config set cuda: true,
while MPS right below was auto-detected — GPU hosts silently rendered
on CPU for any gallery entry missing the flag. Use CUDA whenever torch
reports it available (ROCm builds included), keep cuda: true as an
explicit force, and allow pinning with the device: model option (e.g.
options: ["device:cpu"]). Gallery entries stay untouched.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Plamen K. Kosseff <p.kosseff@gmail.com>
Qwen3-style chat templates append the opening <think> tag to the *prompt*
when thinking is enabled. The model therefore never generates it and emits
only the reasoning text plus the closing </think>.
sglang's ReasoningParser keys off the opening tag:
in_reasoning = self._in_reasoning or self.think_start_token in text
if not in_reasoning:
return StreamingParseResult(normal_text=text)
so with such a template the entire completion — reasoning and answer, the
raw </think> in between — is returned as content and reasoning_content
stays empty, no matter how reasoning_parser is configured.
sglang's own OpenAI server handles this via
force_reasoning = (self.template_manager.force_reasoning
or self._get_reasoning_from_request(request))
This backend has no template manager, so derive the same signal from the
rendered prompt: if it ends with the detector's think_start_token, the tag
was prefilled and the parser is constructed with force_reasoning=True.
Structured decoding is the exception, and it matters: a grammar applies
from the first token, so the model cannot emit the closing tag even though
the template opened the block. The whole completion is schema output and
belongs in content — forcing there files it as reasoning and returns an
empty answer. Measured against a JSON-schema code audit: 10107 characters
of "reasoning", zero content. sglang's own server keeps the two apart for
the same reason; its grammar backend owns the reasoning prefix when a
reasoning parser is configured.
force_reasoning is only passed when it is meant to be True, so detector
defaults (DeepSeek-R1 already defaults to True) are untouched, and a
prompt without a prefilled tag behaves exactly as before — which matters,
because forcing unconditionally makes an answer generated with thinking
off disappear into reasoning_content.
The construction is factored into _new_reasoning_parser() so the streaming
and non-streaming paths, which previously built the parser separately,
cannot drift apart.
Signed-off-by: pos-ei-don <1822533+pos-ei-don@users.noreply.github.com>
With `template.use_tokenizer_template: true` the sglang and vllm backends
render the prompt themselves via `tokenizer.apply_chat_template()`, and they
hand it plain string content. A chat template only emits the model's own media
tokens when the content is a list of parts, so the rendered prompt carries no
`<|vision_start|><|image_pad|><|vision_end|>`. The pixels do reach the engine
(`image_data` / `multi_modal_data`), but both engines locate them by scanning
the prompt for that token, so they are discarded silently: HTTP 200, no
warning, and the model answers as if no image had been attached.
Add `attach_media_parts()` to the shared `python_utils` helper and call it in
both backends: the last user turn is rebuilt as
`[{"type": "image"} * n, {"type": "video"} * n, {"type": "text", ...}]` before
templating, which makes the template emit the placeholders. The pixels keep
travelling out of band exactly as before.
Text-only requests are untouched - with no media the helper returns None and
the original string-content path runs unchanged. If a template cannot iterate
content parts (a text-only model), the parts render is caught and the request
falls back to the previous string-content prompt instead of failing.
Signed-off-by: Tai An <antai12232931@outlook.com>
vLLM's engine-based reasoning parsers derive their initial state from the
chat template kwargs. Qwen3Parser:
chat_kwargs = kwargs.get("chat_template_kwargs", {}) or {}
self.thinking_enabled = chat_kwargs.get("enable_thinking", True)
Constructed as ReasoningParser(tokenizer) the flag defaults to True, so the
parser starts in the REASONING state. A completion produced with thinking
disabled contains no tags at all, and every reasoning parser shape then
reports the whole answer as reasoning:
- engine-based parsers classify it by initial state;
- BaseThinkingReasoningParser hits its documented "may not generate start
token" fallback and returns (model_output, None).
Either way `content = c if c is not None else generated_text` turns that
into a duplicate: a Qwen3 model answering "391" with thinking off comes back
as reasoning_content="391" AND content="391".
Measured against Qwen3.5-MoE on vLLM 0.28, non-streaming:
before thinking on reasoning=202 content="391"
thinking off reasoning="391" content="391" <- duplicated
after thinking on reasoning=192 content="391"
thinking off reasoning="" content="391"
Forward the kwargs the prompt was rendered with, which is what vLLM's own
OpenAI server does; parsers that do not accept the argument keep the plain
constructor.
_split_reasoning() covers the older parser shape, which has no initial state
to set. It only reclassifies when the parser exposes a start/end token pair
and neither the completion nor the prompt ever opened a reasoning block.
Truncated reasoning (block open, end token never arrived) stays reasoning,
and parsers without that token pair are left untouched.
Signed-off-by: pos-ei-don <1822533+pos-ei-don@users.noreply.github.com>
#11772 exempted Temperature from the zero-filter in both backend adapters,
because proto3 has no field presence and an explicit 0 is indistinguishable
from "unset". Seed has exactly the same property and is still filtered:
if proto_field != "Temperature" and value in (None, 0, 0.0, [], False, ""):
continue
A caller pinning `"seed": 0` for a reproducible run therefore gets a random
seed instead, with no error and no log line — the one case where the failure
is invisible precisely because the request looked deliberate.
Both adapters now share a named tuple of fields whose zero is meaningful, so
the next one is added in one place rather than as a second special case.
Deliberately left filtered: top_k, top_p, min_p and the penalties. Their zero
is not a value a caller means — sglang disables top_k with -1, not 0, so
forwarding 0 there would turn a default into an invalid argument.
Verified on the sglang backend (Qwen3.5-MoE, arm64): with the temperature fix
alone, two identical requests at temperature 0 are byte-identical, but pinning
seed 0 has no effect until this change.
Signed-off-by: pos-ei-don <1822533+pos-ei-don@users.noreply.github.com>
The Intel backend installs PyTorch XPU wheels, but Qwen ASR only
checked CUDA and MPS. Every Intel model therefore loaded on the CPU.
Select XPU when available and place the model on xpu:0. Keep the
existing CUDA, MPS, and CPU placement behavior.
Assisted-by: Codex:GPT-5 [apply_patch] [gh]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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]
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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
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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>
