93 Commits

Author	SHA1	Message	Date
Richard Palethorpe	49ef40a187	feat(classifier/VAD): support voice control on low power devices (#10804) ... * 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>	2026-07-29 12:50:22 +02:00
mudler's LocalAI [bot]	878a0d00a1	fix(distributed): reaper reaps live backends, ghost model stubs, in_flight leak, sidecar staging runaway (#11142) ... * 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>	2026-07-27 18:36:31 +02:00
mudler's LocalAI [bot]	6584db992f	fix(nodes): never schedule a model onto a node that cannot store it (#11054) ... * 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>	2026-07-23 00:03:21 +02:00
mudler's LocalAI [bot]	01fca9c9b2	fix(distributed): scale the remote model-load deadline with checkpoint size (#11030) ... 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>	2026-07-22 09:30:23 +02:00
mudler's LocalAI [bot]	f01038f479	fix(modelartifacts): stage each writer's artifact in its own partial tree (#10995) ... 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>	2026-07-20 23:07:43 +02:00
mudler's LocalAI [bot]	65bdbc4ee3	fix(http): make /readyz reflect startup readiness, plus gitignore and coverage-ratchet fixes (#10989) ... * 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>	2026-07-20 21:45:27 +02:00
mudler's LocalAI [bot]	fb4c61d1c9	fix(distributed): configurable remote model-load timeout, and reap the load when it times out (#10948) ... * 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>	2026-07-19 12:01:48 +02:00
Tai An	45b8047736	fix(p2p): serialize access to p2pCtx/p2pCancel (#10839) (#10861) ... 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>	2026-07-17 09:02:05 +02:00
LocalAI [bot]	c1a891662c	refactor(settings): single declarative registry for runtime settings (fixes the #10845 bug class) (#10864) ... * 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>	2026-07-16 22:39:59 +02:00
LocalAI [bot]	bbe018c1a0	feat(bonsai): PrismML llama.cpp fork backend + Bonsai/Ternary-Bonsai gallery models (#10834) ... 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>	2026-07-16 10:09:14 +02:00
Tai An	808312b4b9	fix(watchdog): guard StopWatchdog with watchdogMutex to prevent double close (#10841) (#10859) ... 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>	2026-07-16 09:40:29 +02:00
Tai An	688f904a10	fix(runtime-settings): apply persisted threads/context_size/f16 at startup (#10853) ... 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>	2026-07-16 08:52:11 +02:00
LocalAI [bot]	3601174ce0	fix(distributed): make per-node backend upgrade actually upgrade (#10838) ... * 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>	2026-07-15 09:16:55 +02:00
LocalAI [bot]	bcc41219f7	feat: materialize Hugging Face model artifacts (#10825) ... * feat(config): add model artifact source contract Assisted-by: Codex:GPT-5 [Codex] * feat(downloader): add authenticated raw-byte progress Assisted-by: Codex:GPT-5 [Codex] * feat(huggingface): resolve immutable snapshot manifests Assisted-by: Codex:GPT-5 [Codex] * feat(models): add artifact storage primitives Assisted-by: Codex:GPT-5 [Codex] * feat(models): materialize pinned Hugging Face snapshots Assisted-by: Codex:GPT-5 [Codex] * feat(models): bind managed snapshots at runtime Assisted-by: Codex:GPT-5 [Codex] * feat(gallery): materialize model artifacts during install Assisted-by: Codex:GPT-5 [Codex] * feat(gallery): declare managed Hugging Face artifacts Assisted-by: Codex:GPT-5 [Codex] * feat(models): preload managed model artifacts Assisted-by: Codex:GPT-5 [Codex] * fix(gallery): retain shared artifact caches on delete Assisted-by: Codex:GPT-5 [Codex] * feat(models): report artifact acquisition progress Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): load managed models from ModelFile Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): load staged speech model snapshots Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): use staged snapshots in engine backends Assisted-by: Codex:GPT-5 [Codex] * test(distributed): cover staged artifact snapshots Assisted-by: Codex:GPT-5 [Codex] * docs: explain managed model artifacts Assisted-by: Codex:GPT-5 [Codex] * docs: add product design context Assisted-by: Codex:GPT-5 [Codex] * feat(ui): show model artifact download progress Assisted-by: Codex:GPT-5 [Codex] * Eagerly materialize Hugging Face artifacts Materialize HF-backed model references as managed GGUF artifacts during load, with lazy download retained only as fallback. Assisted-by: Codex:GPT-5 [shell] * Refactor HF downloads through a shared executor Assisted-by: Codex:GPT-5 [shell] * drop 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>	2026-07-15 01:09:33 +02:00
LocalAI [bot]	4056283aa4	[voice] feat: add managed voice cloning profiles (#10799) ... * 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>	2026-07-13 09:54:46 +02:00
LocalAI [bot]	40c29db8c4	fix(logs): capture backend logs by default in single mode (#10742) ... 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>	2026-07-08 12:13:52 +00:00
LocalAI [bot]	97175f4b5a	feat(model): debounce model loads after a failure to stop retry-storms (#10728) ... 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>	2026-07-07 20:55:24 +00:00
Richard Palethorpe	eb32cd9073	feat(realtime): eager blocking pipeline warm-up + /backend/load API (#10662) ... Realtime sessions previously lazy-loaded each pipeline sub-model (VAD, transcription, LLM, TTS) on first use, so every cold session paid a per-request model-load stall and load errors only surfaced mid-stream. Warm the whole pipeline eagerly and blockingly at session start (including the voice-gate speaker-recognition model, which an enforced gate blocks each utterance on; compaction's summary_model stays lazy since it only runs off the response path): - Add backend.PreloadModel / PreloadModelByName as the single load path for every modality (no transcription special-case; backend-omitted configs are deprecated). - The realtime session blocks on Model.Warmup and returns a model_load_error to the client if any stage fails to load; updateSession warms in the background. Opt out per pipeline with pipeline.disable_warmup, exposed as a UI toggle via the config-metadata registry. Add a LocalAI-native POST /backend/load (and /v1/backend/load) that pre-loads a model -- expanding realtime pipelines into their sub-models -- as the inverse of /backend/shutdown. There is one preload engine (backend.PreloadStages): the realtime Warmup methods, /backend/load and the --load-to-memory startup flag all use it, so --load-to-memory now also expands pipeline models and records load-failure traces. Pipeline sub-model alias resolution is likewise shared (ModelConfigLoader.LoadResolvedModelConfig). Surface the endpoint everywhere an admin manages models: - MCP admin tool load_model (httpapi + inproc clients, safety/catalog prompts, catalog/dispatch tests). - "Load into memory" action in the React models UI. - Swagger regenerated; docs moved to the general backend-monitor page since it is not realtime-specific. Fix a Traces UI crash ("json: unsupported value: -Inf"): audio-snippet RMS/peak now floor at a finite dBFS, and backend-trace data is sanitized to drop non-finite floats before marshaling. The sanitizer is copy-on-write -- it runs on every RecordBackendTrace, so containers are only re-allocated on the paths that actually changed. Migrate core/http/openresponses_test.go onto the prebuilt mock-backend the rest of the http suite already uses -- it was the last spec still pointing at a real HuggingFace model, so it 404'd wherever no vision backend was built -- and fix its item_reference specs to send the spec's "id" field instead of "item_id", which the handler never accepted. Assisted-by: Claude:claude-opus-4-8 Claude Code Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-07-03 18:00:37 +02:00
LocalAI [bot]	6eea3ef2ac	fix(backends): make backend install ops idempotent unless forced (#10643) ... * fix(backends): make backend install ops idempotent unless forced POST /backends/apply hardcoded force=true through LocalBackendManager.InstallBackend, so applying an already-installed backend re-downloaded and re-extracted the whole artifact every time. API clients that ensure a backend exists at startup paid a full OCI image pull on every boot. Backend install ops now default to non-forced — an installed, runnable backend short-circuits (the orphaned-meta reinstall path in InstallBackendFromGallery is preserved) — and reinstall stays available: - ManagementOp gains a Force field; the local manager passes it through instead of hardcoding true. - /backends/apply accepts an optional "force" boolean in the body. - The React UI install route keeps forcing, since its button doubles as the explicit "Reinstall backend" action. Distributed installs already behaved this way (workers skip when the binary exists unless force is set); this aligns single-node behavior. Assisted-by: Claude:claude-fable-5 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(backends): don't force-reinstall LOCALAI_EXTERNAL_BACKENDS on boot The startup loop for LOCALAI_EXTERNAL_BACKENDS runs InstallExternalBackend for each listed backend on every boot, and its gallery-name path hardcoded force=true — so every start re-downloaded and re-extracted each listed backend's OCI image even when it was installed and runnable. Supervising apps that list several backends paid several full OCI pulls per launch. Give InstallExternalBackend an explicit force parameter (it only affects the gallery-name fallback; URI installs always write) and pass: - false from the boot loop and `local-ai backends install` (idempotent ensure — `backends upgrade` is the refresh path), - op.Force from the local manager's external-URI op, - the request's force on the worker install path and true on its upgrade path (behavior unchanged). Assisted-by: Claude:claude-fable-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>	2026-07-02 19:16:29 +02:00
LocalAI [bot]	29001a88c1	fix(distributed): don't let a dead worker pin the model-load advisory lock (#10600) ... * fix(distributed): don't let a dead worker pin the model-load advisory lock In distributed mode a chat request could fail with: failed to route model with internal loader: routing model ...: loading model ...: advisorylock: acquiring lock <id>: ERROR: canceling statement due to lock timeout (SQLSTATE 55P03) Root cause is two independent defects in the cross-replica model-load path: 1. SmartRouter.Route holds a per-model PostgreSQL advisory lock for the whole cold-load sequence, which includes installBackendOnNode -> InstallBackend, a NATS request-reply with a 15m deadline (DefaultBackendInstallTimeout) that ignored ctx. When the chosen worker died mid-install, the holder sat on the lock for up to 15m. The detached loadCtx (WithoutCancel) had no deadline, so nothing capped the hold. 2. The acquiring statement, pg_advisory_lock(), is subject to any deployment global lock_timeout. A common operator setting (e.g. 10s) aborts the wait with SQLSTATE 55P03, so every other replica's request for that model hard -errored instead of waiting for the in-progress load and reusing it. For the ~15m window the model was effectively unroutable. Fixes: - advisorylock.WithLockCtx (postgres): SET lock_timeout = 0 on its dedicated connection (RESET before it returns to the pool) so the Go context, not a deployment-wide GUC, governs how long we wait. Waiters now block and then re-check, reusing the model another replica just loaded. - SmartRouter: bound the detached loadCtx with a single ModelLoadCeiling so the lock is always released in bounded time even if a sub-step wedges. Default is the configured backend.install deadline + 10m (staging + LoadModel margin), so a legitimately slow load is never cut. - installBackendOnNode: use singleflight.DoChan + select on ctx.Done() so the install wait honors cancellation; the ceiling can then actually free a caller pinned behind a dead worker. The shared install still coalesces via singleflight. Reproduced both defects as failing tests first (a real 55P03 against a testcontainer with a short lock_timeout; a wedged install that blocks Route) and confirmed green. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * fix(distributed): bound advisory-lock wait instead of disabling lock_timeout Setting lock_timeout = 0 to override a deployment's short global lock_timeout meant "wait forever" server-side. Safe for SmartRouter.Route (its loadCtx now carries the model-load ceiling) but unsafe for the schema-migration callers that pass context.Background(): a holder whose session never releases would hang them indefinitely. Derive the server-side lock_timeout from the caller's context instead: its remaining budget plus a margin (so the Go context's cancellation still wins with a clean error and the server bound is only a backstop), or a finite 30m backstop when the context has no deadline. Never zero - "wait forever" is no longer possible, while a deployment's hostile short lock_timeout is still overridden so legitimate cross-replica waits don't fail with 55P03. Added a spec proving a deadline-less waiter gives up at the (shrunk) backstop rather than hanging. 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> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>	2026-07-02 09:52:51 +02:00
LocalAI [bot]	fd8cebd0b3	fix(watchdog): persist UI-saved Check Interval across restarts (#10601) (#10605) ... fix(watchdog): persist a UI-saved Check Interval across restarts (#10601) The watchdog Check Interval saved via /api/settings reverted to 500ms on every restart, while the idle/busy timeouts persisted correctly. Root cause: NewApplicationConfig baseline-defaulted WatchDogInterval to 500ms, whereas the idle/busy timeouts default to 0. The startup loader (loadRuntimeSettingsFromFile) applies a persisted runtime_settings.json value only when the field is still at its zero default - its heuristic for "this wasn't set by an env var". Because the interval was always 500ms at that point, the loader never read the persisted value back, so the saved interval was silently discarded on each boot. Fix: drop the non-zero baseline default so the interval behaves like the sibling timeouts (0 = unset). The effective 500ms default is now supplied at the watchdog layer: WithWatchdogInterval ignores a non-positive value so DefaultWatchDogOptions' 500ms is preserved (and a 0 interval can never turn the watchdog loop into a busy spin). Also mirror the interval in the live config file watcher alongside idle/busy, and report the real 500ms default (not the stale "2s") from ToRuntimeSettings. 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>	2026-06-30 17:48:14 +02:00
Richard Palethorpe	5d0c43ec6e	feat(realtime): Semantic VAD EOU token (#10444) ... * feat(realtime): EOU-driven semantic_vad turn detection Add a `semantic_vad` turn-detection mode to the realtime API that feeds the transcription model live and decides "the user finished speaking" from the `<EOU>` end-of-utterance token rather than from silence alone. When EOU fires the turn commits immediately (~0.3s); otherwise it falls back to an eagerness-scaled silence threshold (low/med/high = 8/4/2s). Plumbing, bottom to top: - proto: `AudioTranscriptionLive` bidirectional RPC (config-first oneof, mono float PCM @16k, ready-ack / Unimplemented degrade signal) plus `TranscriptResult.eou` for the unary retranscribe gate. - pkg/grpc: client/server/base/embed scaffolding for the bidi stream, modeled on AudioTransformStream; release stream conns on terminal Recv. - parakeet-cpp: live transcription RPC with per-C-call engine locking (one live stream per turn, finalize+free at commit); bump parakeet.cpp to ABI v5 — incremental StreamingMel (no more quadratic per-feed mel recompute that delayed EOU on long turns) and the <EOU>/<EOB> split; strip the literal <EOU>/<EOB> from offline text and set Eou. - core/backend: LiveTranscriptionSession wrapper + pipeline `turn_detection:` config block (type/eagerness/retranscribe). - realtime: semantic_vad integration — live input captions streamed as transcription deltas while the user speaks, EOU-immediate commit with eagerness fallback, optional retranscribe gate (batch re-decode must also end in <EOU> to confirm), clause synthesis off the LLM token callback, and per-turn live-transcription / model_load telemetry. - UI: show the realtime pipeline components as a vertical list. Docs and tests included; opt-in via the pipeline YAML or per-session `session.update`. Non-streaming STT backends degrade to silence-only. Assisted-by: Claude Code:claude-opus-4-8 [Read] [Edit] [Write] [Bash] Assisted-by: Claude Code:claude-fable-5 [Read] [Edit] [Bash] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(realtime): explicit formally-verified state machines + parakeet streaming driver The realtime API had several implicit state machines whose state was inferred from scattered booleans, channels, and five separate mutexes, leaving illegal/inconsistent states reachable. Make them explicit and keep the implementation in step with a formal design; rework the parakeet streaming backend along the same lines. Realtime state machines (M1-M5). Each is a sealed sum-type State/Event/Effect with a total, pure Next(state,event)->(state,[]effect) behind a single-writer Coordinator: M1 conncoord connection lifecycle: VAD toggle + once-only teardown (replaces vadServerStarted + a `done` channel closed from two sites). M2 turncoord turn detection: collapses speechStarted and the live-stream "turn open" flag into one state, so discardTurn can no longer desync them and suppress the next onset. M3 respcoord response coordination: serializes the dual-writer start/cancel so at most one response is live; one response.done per response.create. M4 compactcoord conversation compaction: single-flight (replaces the `compacting atomic.Bool` CAS). M5 ttscoord TTS pipeline: open->closing->closed, idempotent wait(), rejects enqueue-after-close (was a silent drop). The Coordinator/Sink/Next plumbing — only the sealed types and Next differed per machine — is extracted once into core/http/endpoints/openai/coordinator as a generic Coordinator[S,E,F]; each machine keeps its public API via type aliases, so no sink, call-site, or test moved. Hierarchy. session_lifecycle.fizz models M1 as the parent region with its children (M2/M3/M4) as one statechart and asserts ChildrenDieWithParent (conn torn => all children terminal, none start after teardown). respcoord and compactcoord gain an absorbing Terminated state + Shutdown event; conncoord's teardown drives the children terminal. This closes a compaction teardown gap: a fire-and-forget compaction could outlive a torn session — compactionSink now takes a session-scoped cancellable context + WaitGroup and joins the in-flight summarize+evict on shutdown. Formal verification. formal-verification/ holds one authoritative FizzBee spec per machine plus the composition spec, each with an always-assertion and a documented one-line edit that makes the checker fail (verified non-vacuous). scripts/realtime-conformance.sh is fail-closed: all Go conformance suites under -race AND a model-check of every .fizz spec; a missing FizzBee is a hard error (only the loud REALTIME_CONFORMANCE_SKIP_FIZZBEE=1 bypasses it, never in CI). FizzBee is pinned by sha256 and installed via scripts/install-fizzbee.sh into .tools/ (gitignored). Wired as make test-realtime-conformance, a CI workflow, and a pre-commit path filter. Go conformance tests are Ginkgo/Gomega (per the repo's forbidigo lint): transition tables + fixed-seed property walks + concurrent/-race specs, no rapid dependency. Design map: docs/design/realtime-state-machines.md. Parakeet streaming backend. The same treatment applied to the parakeet-cpp streaming paths: - AudioTranscriptionStream returns codes.Unimplemented for non-streaming models instead of decoding offline and emitting it as one delta + final. A client that asked for streaming learns the model cannot stream rather than receiving a batch result shaped like a stream. New grpcerrors.StreamTranscriptionUnsupported carries that signal; the HTTP /v1/audio/transcriptions stream path surfaces it as an SSE error event. Mirrors AudioTranscriptionLive, which already did this. - utteranceBoundary (boundary.go): a single definition of the end-of-utterance latch, replacing three open-coded finalEou toggles. Modelled as a two-valued type so illegal states are unrepresentable. - Shared decode driver (driver.go): streamFeedResult (one per-feed event) + feedChunk (hides the ABI v4 JSON vs text-only split) + feedSlices + flushTail. The feed loop is written once. - AudioTranscriptionLive becomes a bidi adapter: it streams the per-feed {delta,eou,eob,words} the realtime turn detector consumes and a terminal FinalResult carrying only Text. Segments/duration/eou are offline-only and no longer produced (nor read) on the live path; liveTraceState drops the terminal eou and keeps the per-feed eou_events count. - AudioTranscriptionStream + streamJSON merge into one driver-based function; streamSegmenter is generalized to the unified event with a text-only fallback that preserves the legacy (no-words) library's per-utterance segmentation. Verified: build/vet/gofumpt clean, golangci-lint 0 issues, all coordinator and parakeet packages under -race, the fail-closed conformance gate green, and make test-realtime (12 e2e WS+WebRTC). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-06-30 09:01:22 +02:00
LocalAI [bot]	f3d829e2ef	feat(distributed): add LOCALAI_DISTRIBUTED_SHARED_MODELS to skip staging on shared volumes (#10556) (#10566) ... In distributed mode, even when the frontend and workers share the same models directory via a shared volume mount, starting a model on a worker re-staged (re-downloaded) it: stageModelFiles always uploads model files into a tracking-key-namespaced subdir on the worker, and the staging probe only checks that staged location, so a file already present on the shared volume at the canonical path was never reused. Add a config switch LOCALAI_DISTRIBUTED_SHARED_MODELS (default false). When enabled, the operator asserts that all nodes mount the SAME models directory at the SAME path, so staging is unnecessary: the frontend's absolute model paths are already valid on the worker. In that mode stageModelFiles returns the cloned opts unchanged without uploading, leaving the path fields pointing at their canonical absolute paths so the worker loads them directly from the shared volume. The value is plumbed from DistributedConfig through SmartRouterOptions into the SmartRouter. Docs and docker-compose.distributed.yaml updated. 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>	2026-06-28 01:23:07 +02:00
LocalAI [bot]	d7d7721eae	feat(distributed): SyncedMap component + migrate finetune/quant/agent-tasks to cross-replica state (#10542) ... * feat(distributed): add SyncedMap cross-replica in-memory state component Introduce core/services/syncstate.SyncedMap[K,V]: a thread-safe in-memory map that keeps itself consistent across frontend replicas via NATS, with an optional pluggable durable Store and hydrate-from-source convergence. Several features keep process-local state surfaced to the API (finetune/quant jobs, agent tasks, model configs) and each hand-wired the same in-memory + NATS broadcast + read-through-store legs - or forgot to, reintroducing cross-replica staleness. SyncedMap makes that consistency a configuration choice: - local writes mutate the map, write through the Store, then broadcast a delta; - the apply path is memory-only and never re-publishes or re-writes the Store (structural echo-loop guard, mirroring galleryop.mergeStatus); - on Start and on NATS reconnect the map re-hydrates from the source (Store, else Loader); an optional periodic Reconcile repairs silent drift; - standalone mode (nil NATS client) is a strict in-memory no-op. Reconnect re-hydrate is wired via a new *messaging.Client.OnReconnect callback, consumed through an optional type-assertion so MessagingClient stays minimal. Adds messaging.SubjectSyncStateDelta and a reusable testutil.FakeBus (synchronous in-process MessagingClient with wildcard matching) for adopter tests. Component only; service migrations follow in subsequent commits. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * refactor(finetune): back jobs with SyncedMap for cross-replica consistency FineTuneService kept jobs in a process-local map and, although it wrote them to Postgres, ListJobs/GetJob never read the store back and the wired natsClient was never used - so in distributed mode a job created on one replica was invisible to the others. Replace the map and the dead client with a syncstate.SyncedMap keyed by job ID, value *schema.FineTuneJob (the exact REST shape, so responses are unchanged). - Add a Store adapter (core/services/finetune/syncstore.go) over FineTuneStore, plus FineTuneStore.ListAll (global hydrate; per-user List kept) and an idempotent Upsert (create-or-update; Create alone fails on dup key). - Writes go through SyncedMap.Set/Delete (write-through + broadcast); reads use List/Get. The on-disk state.json path becomes the standalone Loader, keeping single-node restart recovery (stale->stopped / exporting->failed fixups). - Fold SetNATSClient/SetFineTuneStore into NewFineTuneService; app.go passes the distributed NATS client + store when distributed, nil otherwise. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * refactor(agentpool): back agent tasks with SyncedMap for cross-replica consistency AgentJobService.ListTasks read the process-local tasks map only, while ListJobs already read through the DB persister + dispatcher NATS - so in distributed mode a task created on one replica was invisible to the others. Back tasks with a syncstate.SyncedMap keyed by task ID (value schema.Task, the exact REST shape); jobs are left untouched. - Store adapter (task_syncstore.go) over the existing JobPersister (LoadTasks/SaveTask/DeleteTask); reads svc.persister/userID live so a persister swap needs no rebuild. No new persister methods required. - Task reads -> SyncedMap.List/Get; create/update -> Set (write-through + broadcast); delete -> Delete. The file persister now owns its own task set so the write-through path does not re-enter the SyncedMap lock (deadlock guard). - The distributed NATS client is not available at construction (start() precedes initDistributed), so it is injected via SetTaskSyncNATS, which rebuilds the still-empty map before Start/hydrate. Wired at the main, restart, and per-user (UserServicesManager) distributed sites. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * refactor(quantization): back jobs with SyncedMap + durable QuantStore QuantizationService kept jobs in a process-local map persisted only to a local state.json, so in distributed mode jobs were neither visible across replicas nor durable cluster-wide. Back jobs with a syncstate.SyncedMap keyed by job ID (value *schema.QuantizationJob, the exact REST shape). - New distributed.QuantStore (GORM, table quantization_jobs) mirroring FineTuneStore: Create/Get/ListAll/Upsert(idempotent)/Delete, registered for AutoMigrate via distributed.InitStores (Stores.Quant). - New adapter (quantization/syncstore.go) over QuantStore implementing syncstate.Store, with record<->schema conversion. - Reads go through List/Get, writes through Set/Delete (write-through + broadcast); state.json is kept as the standalone Loader for single-node restart recovery (stale-job fixups preserved). - app.go passes the distributed NATS client + QuantStore when distributed, nil otherwise; Start/Close lifecycle mirrors finetune. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * fix(syncstate): annotate gosec G118 false positive on lifeCtx gosec flagged the WithCancel in Start as "cancellation function not called" because the returned cancel is stored on the struct rather than called/deferred in scope. It is invoked in Close (covered by tests), and lifeCtx must outlive Start to drive the reconnect/reconcile goroutines. Suppress the verified false positive with a justified #nosec G118. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * test(distributed): e2e two-replica SyncedMap sync over real NATS + Postgres Adds the real-infrastructure counterpart to the fake-bus unit tests, in the existing distributed e2e suite (testcontainers NATS + PostgreSQL). Two SyncedMap instances stand in for two frontend replicas - each with its OWN NATS connection to a shared server and a SHARED Postgres store (the distributed-mode invariant) - and assert, over the wire: - a create on replica A is observed by replica B; - an update and a delete propagate A -> B (delete prunes, which a reload cannot); - a late-joining replica recovers a job it never received a delta for, via store hydrate on Start (the at-most-once gap a fake bus cannot exercise); - a local Set is written through to the shared Postgres store. 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>	2026-06-27 23:23:51 +02:00
LocalAI [bot]	64150ca7ab	fix(distributed): broadcast admin model-config changes across replicas (#10540) ... In distributed mode the admin model endpoints (/models/edit, /models/import, /models/toggle-state and the PATCH config-json endpoint) wrote the YAML to the shared models dir but reloaded only the local replica's in-memory ModelConfigLoader. With multiple frontend replicas behind one service, a save landed on whichever replica handled the request; peers kept serving their stale in-memory view, so a load-balanced request was a coin-flip between old and new config (a created alias visible on one replica and missing on the other, an edited alias target diverging, etc.). The NATS cache-invalidation channel (SubjectCacheInvalidateModels + OnModelsChanged) already existed for the gallery install/delete path; these admin endpoints simply never published on it. Wire them up via a new GalleryService.BroadcastModelsChanged helper (no-op in standalone mode). Also fix delete propagation: LoadModelConfigsFromPath is additive and never drops an entry whose file is gone, so the subscriber hook (which only reloaded from disk) could not propagate a removal. ApplyRemoteChange now honors the event op - pruning the element on "delete" and reloading otherwise - and shuts down any running instance of the affected model so the new config takes effect. This closes the same latent gap on the gallery delete path. 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>	2026-06-27 01:36:57 +02:00
Richard Palethorpe	e1994579f8	fix(pii): load default detectors at startup + add LOCALAI_PII_DEFAULT_DETECTORS (#10474) ... pii_default_detectors was applied to the live config only by a live POST /api/settings (ApplyRuntimeSettings) — neither the startup loader nor the config file watcher read it back. So after a restart the persisted default detectors were dropped, and the cloud-proxy MITM listener (which resolves each intercept host's detectors once at start via ResolvePIIPolicy) came up with an empty set and forwarded intercepted traffic unredacted, even though the MITM model had pii.enabled:true and the defaults were on disk. Request-side default redaction broke the same way. - startup.go: loadRuntimeSettingsFromFile now applies pii_default_detectors, before startMITMIfConfigured, with env > file precedence. - config_file_watcher.go: apply pii_default_detectors on live file edits, matching the existing env-guard pattern used for the other fields. - settings endpoint: rebuild the MITM listener when pii_default_detectors changes (its per-host detector map is frozen at listener start), not only on a mitm_listen change — so toggling a default detector takes effect on cloud-proxy traffic immediately. - new LOCALAI_PII_DEFAULT_DETECTORS env var / CLI flag (WithPIIDefaultDetectors) so the default detector set can be pinned at boot for immutable deployments. Assisted-by: Claude:claude-opus-4-8 Claude-Code Signed-off-by: Richard Palethorpe <io@richiejp.com> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>	2026-06-24 11:08:57 +02:00
Richard Palethorpe	63bcbf6c12	fix(pii): post-merge review fixes + live NER e2e for the privacy-filter tier (#10401) ... * fix(pii): post-merge review fixes + live NER e2e for the privacy-filter tier Follow-up to the NER tier engine (#10360), already on master. This carries only the incremental review fixes and tests that postdate that merge — the feature itself is not re-introduced. Review fixes: - openai_completion.go: remove the dead `elem >= 0` conjunct in applyAnyText (the `elem < 0` guard above already returns). - application.go: collapse ResolvePIIPolicy's inline re-implementation of PIIIsEnabled to a single cfg.PIIIsEnabled() call (sole source of the "explicit pii.enabled wins, else cloud-proxy default" rule) and return true past the !enabled guard where it is provable. - pattern.go: hoist the triple `appConfig != nil && EnableTracing` check in patternDetector.Detect into one local. - grammar.go: MaxQuantifier was 4096, but Go's regexp/syntax rejects repeat bounds above 1000 at Parse time, so walk()'s {n,m} guard could never fire — dead code shadowed by the parser. Lower it to 512 so a bound in (512,1000] is rejected here with an actionable error; >1000 still fails closed via Parse. Specs pin the relationship so the guard can't silently revert. - PatternListEditor.jsx: clamp a directly-typed negative min_len to >=0 and force the DOM value back when clamping (min={0} only constrained the spinner, so a negative reached saved config and silently disabled the length filter). Tests: - piipattern_test.go: MaxQuantifier guard specs (must stay live, not dead). - model-config.spec.js: assert the min_len clamp, and that entity_actions collapses a duplicate group to a single row (map semantics; regression guard against emitting an array that drops a row on save). - tests/e2e-backends: token_classify capability driving the TokenClassify gRPC RPC against the backend image, asserting byte-correct, UTF-8 rune-aligned spans (entity.Text == text[start:end]) at threshold 0. Verified on CPU via `make test-extra-backend-privacy-filter` (3/3 specs). - Makefile: test-extra-backend-privacy-filter wrapper. - tests/e2e: e2e_pii_ner_test.go drives /api/pii/analyze + /api/pii/redact (mask + block) through the full HTTP -> detector -> redactor path; gated on PII_NER_MODEL_GGUF so the default suite is unaffected. - .github/workflows/tests-pii-ner-e2e.yml: path-filtered / nightly CI job running the container harness on CPU. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(gallery): add privacy-filter-nemotron (f16 + q8) GGUF conversions of OpenMed/privacy-filter-nemotron — a fine-grained English PII token-classifier (55 categories / 221 BIOES classes), fine-tuned from openai/privacy-filter on NVIDIA's Nemotron-PII dataset. Sibling to the existing privacy-filter-multilingual entry, trading language breadth for category depth. - privacy-filter-nemotron: F16 reference artifact (~2.8 GB). - privacy-filter-nemotron-q8: Q8_0 quant (~1.64 GB) for RAM-constrained / edge use; description notes the size/speed tradeoff and to validate on your own data (a single dropped span is a PII leak). Both run on the privacy-filter backend with known_usecases [token_classify] and a default mask policy (min_score 0.5); operators add per-category entity_actions as needed. sha256s taken from the HF repo's LFS object ids. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-06-22 18:26:19 +02:00
LocalAI [bot]	569d9bbd9e	fix(distributed): broadcast file-staging progress across replicas (#10440) ... File-staging progress lived only in the SmartRouter's in-memory StagingTracker on the replica performing the transfer. In a multi-replica deployment behind a round-robin load balancer, a /api/operations poll that lands on any other replica saw no staging row, so the progress ("processing file ... Total ... Current ...") flickered in and out as polls rotated between frontends. Mirror the pattern already used for gallery-install progress: the origin replica broadcasts staging ticks over NATS (SubjectStagingProgress, a new staging.<model>.progress subject), and peers merge them via ApplyRemote (SubscribeBroadcasts on the wildcard). Byte-level ticks are leading-edge debounced (~1/s); Start/FileComplete/Complete always publish. A locally-owned op stays authoritative so the origin's own echo and stray peer events can't clobber it, and mirrored remote ops expire after a TTL so a missed Done event can't leave a phantom row. The UI read path (StagingTracker.GetAll) is unchanged. 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>	2026-06-22 09:28:07 +02:00
Leoy	b50b1fe418	feat(watchdog): add size-aware LRU eviction mode (#9527) ... * feat(watchdog): add size-aware LRU eviction mode When the model count hits the LRU limit or the memory reclaimer fires, evict the largest model by on-disk file size first rather than the least-recently-used one. For GGUF models the file size is a reliable proxy for GPU/RAM footprint, so evicting the largest candidate maximises freed memory per eviction round while keeping small utility models (embeddings, classifiers, rerankers) resident. Changes: - `pkg/model/watchdog.go`: add `sizeAwareEviction` flag and `modelSizes map[string]int64` to `WatchDog`; sort candidates by `sizeBytes` desc (LRU time as tiebreaker) when the flag is set; add `RegisterModelSize`, `SetSizeAwareEviction`, `GetSizeAwareEviction` - `pkg/model/watchdog_options.go`: add `WithSizeAwareEviction` option - `pkg/model/initializers.go`: stat model file after load and call `RegisterModelSize` so size data is available before the first eviction - `core/config/application_config.go`, `runtime_settings.go`: add `SizeAwareEviction` field and `WithSizeAwareEviction` app option; expose via `ToRuntimeSettings` / `ApplyRuntimeSettings` for the `POST /api/settings` live-reload path - `core/cli/run.go`: add `--size-aware-eviction` flag / `LOCALAI_SIZE_AWARE_EVICTION` env var - `core/application/startup.go`, `watchdog.go`: wire the new option through to `NewWatchDog` - `pkg/model/watchdog_test.go`: 5 new specs — option enable, dynamic toggle, largest-first ordering, equal-size LRU tiebreaker, no-size fallback to LRU, and size-map cleanup on eviction Closes #9375 Signed-off-by: supermario_leo <leo.stack@outlook.com> * refactor(watchdog): use vram estimation scaffolding for model size Replace the brittle os.Stat(modelFile) approach with a proper call to pkg/vram, which handles multi-file models (DownloadFiles, MMProj) and all weight file types, not just single GGUF files. - Add estimateModelSizeBytes() in core/backend/options.go that collects all weight file URIs from the model config, resolves them to file:// URIs, and calls vram.Estimate() with the shared DefaultCachedSizeResolver (15-min TTL cache avoids redundant stat calls on repeated loads) - Thread the result through via a new WithModelSizeBytes() loader option - In initializers.go, consume the pre-computed size instead of calling os.Stat; if no size was supplied (e.g. for external/router-dispatched models) the registration is simply skipped Signed-off-by: supermario_leo <leo.stack@outlook.com> * refactor(watchdog): use EstimateModel with HF fallback for size estimation Switch estimateModelSizeBytes from calling vram.Estimate directly to the unified vram.EstimateModel entry point, which adds automatic fallbacks: file-based GGUF metadata → HF API → size string. Also extract the HuggingFace repo ID from model URIs (huggingface://, hf://, https://huggingface.co/ and org/model short-form) and pass it as ModelEstimateInput.HFRepo, so models not yet downloaded locally can still get a size estimate via the HF API. Addresses @mudler's review feedback: "better to rely on EstimateModel and pass by the HF URL of the model extracted from the URI". Signed-off-by: supermario_leo <leo.stack@outlook.com> * feat(webui): add Size-Aware Eviction toggle to settings page The size-aware eviction setting was wired through the CLI flag and the RuntimeSettings live-reload path (POST /api/settings) but had no handle on the React settings page, so it could not be toggled from the UI. Add a Size-Aware Eviction toggle to the Watchdog section, next to the existing Force Eviction When Busy / LRU eviction handles. The settings page loads and saves the whole RuntimeSettings object, so the new size_aware_eviction key is picked up with no extra plumbing. Addresses @mudler's review feedback: the application config setting should land on the same UI settings page as the other handles. Signed-off-by: supermario_leo <leo.stack@outlook.com> --------- Signed-off-by: supermario_leo <leo.stack@outlook.com>	2026-06-21 17:17:04 +02:00
LocalAI [bot]	2e734bf560	fix(downloader): stall timeout, resume-safe cancel, and stale-partial reaping (#10406) ... * fix(downloader): stall timeout, resume-safe cancel, and stale-partial reaping Large model installs would hang forever or never finish. Three defects in the HTTP download path, all hit by big GGUF pulls over a slow or flaky link: 1. No stall timeout. The shared download client sets no body deadline (correct for streaming) but also no read-idle timeout, and the transport's IdleConnTimeout does not cover an in-flight body read. A silently-dropped TCP connection (no FIN/RST) blocked the body Read forever, freezing an install at N bytes until an external reaper killed it. Add an idle-timeout reader that closes the body after a window of zero progress (DownloadStallTimeout, default 60s), turning an indefinite hang into a fast, retryable error. A read that returns data resets the clock, so a slow-but-steady transfer is unaffected. 2. Cancellation deleted the partial. On context.Canceled the code removed the .partial file, so any frontend restart (deploy, OOM) mid-download wiped all progress and the retry restarted from zero. At slow egress, files larger than the restart interval never completed. Keep the .partial on cancel so the next attempt resumes via Range. 3. Partials leaked. Cleanup only ran on the context-cancel path, never on a stall or a SIGKILL/OOM, so abandoned .partial files accumulated and could fill the models volume. Add CleanupStalePartialFiles and reap partials older than 24h on startup. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * fix(downloader): discard the .partial on a deliberate user cancel Review follow-up. The previous commit kept the .partial on every cancellation so restarts could resume, but that also left a dangling partial when a user *intentionally* cancelled an install — the file lingered until the 24h reaper. Distinguish the two: cancel the gallery operation's context with a cause (downloader.ErrUserCancelled) so the download layer can tell a deliberate abort (discard the partial) from an incidental one such as a shutdown/restart (keep it for resume). Detect cancellation via the context rather than the returned error, because an HTTP request cancelled with a cause surfaces the cause error, not context.Canceled. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-8 [Claude Code] * fix(downloader): resolve gosec G122 in CleanupStalePartialFiles CI's code-scanning (gosec) flagged G122 (symlink TOCTOU) for the os.Remove call inside the filepath.WalkDir callback. Collect the stale paths during the walk and delete them afterwards instead of mutating the tree from inside the callback. Behavior is unchanged; the existing specs still pass. 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>	2026-06-19 21:35:21 +02:00
Richard Palethorpe	3fa7b2955c	feat(pii): NER tier engine — privacy-filter.cpp backend + NER-centric PII filter (#10360) ... Squashed feat/pii-ner-tier-engine rebased onto master (was 45 commits; see backup/pii-ner-tier-engine-prerebase). Net change: - privacy-filter.cpp: standalone GGML engine for the openai-privacy-filter PII/NER token classifier, wired as a LocalAI gRPC backend (CPU/CUDA/Vulkan). TokenClassify moves off the patched llama.cpp path onto this backend. - PII filter reworked to be NER-centric (encoder/NER detection tier scanning whole conversations as one document), with a recreated bounded restricted- regex secret-matching pattern detector tier alongside it (per-model pii_detection.builtins / .patterns + core/services/routing/piipattern). - Detection labelled by source (ner vs pattern); backend trace / confidence / debug observability; analyze/redact exposed as a synchronous API. - Instance-wide default detector policy + per-usecase default-on; request filtering extended to completions, embeddings, edits & Ollama. - React UI: NER-centric PII editor, detector-models table, pattern/builtins editor, middleware default-policy UI. - Gallery: privacy-filter-multilingual token-classify model + NER install filter; token_classify known_usecase; batch sized to context for NER models. privacy-filter backend registered in the backend gallery (cpu/vulkan/cuda-13 meta + image entries with a capabilities map) matching its CI matrix jobs, and an /import-model auto-detect importer (PrivacyFilterImporter, narrow privacy-filter GGUF detection) replacing the prior pref-only registration. Reconciled against master's independent evolution: - Dropped master's PIIPatternOverrides feature (global-pattern runtime overrides + /api/pii/patterns API + runtime_settings.json persistence). The per-model NER + pattern-detector design supersedes it; it was built on the global redactor pattern set this branch replaced. - Reverted the llama.cpp Score carry-patch (0006-server-task-type-score): removed the patch and restored master's grpc-server.cpp Score RPC (direct llama_decode, slot-loop bypass) and LLAMA_VERSION pin, plus master's model_config validation forbidding score + chat/completion/embeddings on llama-cpp. token_classify is unaffected (it runs on the privacy-filter backend, not llama-cpp). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-06-18 11:45:22 +01:00
LocalAI [bot]	7637f8cf1b	feat(distributed): declarative per-model scheduling via env/args (#10308) ... * feat(distributed): add SpreadAll column and authoritative scheduling seeding Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): parse declarative model scheduling config (env/file) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): reconcile spread_all to one replica per matching node Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): wire LOCALAI_MODEL_SCHEDULING env/args and startup seeding Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): expose spread_all on the scheduling API endpoint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): add spread-to-all-nodes mode to the scheduling UI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(distributed): document LOCALAI_MODEL_SCHEDULING env/args Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(distributed): clarify replica modes and all-nodes spread in scheduling config 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>	2026-06-13 18:31:06 +02:00
Richard Palethorpe	085fc53bbc	fix(router): production-ready request router + auto-size batch for embedding/rerank (#10104) ... * fix(router): score classifier production-readiness Conversation trimming runs through the classifier model's chat template and trims by exact token count, sized to the model's n_batch which is now scaled to context so long probes can't crash the backend. Missing chat_message templates are a hard error at router build time. Router- facing factories (Embedder/Scorer/Reranker/TokenCounter) re-resolve ModelConfig per call so a model installed post-startup doesn't bind a stub Backend="" config and silently fall into the loader's auto- iterate path. New 'vector_store' backend trace recorded inside localVectorStore on every Search/Insert — including the backend-load-failure path that previously vanished into an xlog.Warn — with outcome tagging (hit/miss/empty_store/backend_load_error/find_error/insert_error/ok). Companion cleanup drops misleading similarity:0 and input_tokens_count:0 from non-hit and text-mode traces. Gallery local-store-development aliases to 'local-store' so the master image satisfies pkg/model.LocalStoreBackend lookups from the embedding cache. Misc: llama-cpp TokenizeString reads the correct 'prompt' JSON key (the original bug); ModelTokenize nil-guard; non-fatal mitm proxy startup; PII 'route_local' renamed to 'allow' with docs/UI in sync; model-editor footer no longer eats the edit area on small screens; several config-editor template/dropdown/section fixes. Tests: e2e router specs (casual/code-hint + long-conversation trim), vector_store trace specs, lazy-factory specs, gallery dev-alias resolution, Playwright trace badge + scroll regression. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(backend): auto-size batch to context for embedding and rerank models Embedding and rerank models pool over the whole input in a single physical batch (n_ubatch). With batch left at the 512 default, the backend rejects longer inputs with "input is too large to process", silently capping a large-context embedder (e.g. 8k/32k) at 512 tokens. Size n_batch to the context for these single-pass usecases, mirroring the existing FLAG_SCORE behaviour; an explicit batch: still wins. Extracts EffectiveContextSize/EffectiveBatchSize from grpcModelOpts so the effective decode window has one home for other callers to reuse. Adds an e2e-aio regression test that embeds a >512-token input. The AIO embedding model is switched to nomic-embed-text-v1.5 (2048 context) because the previous granite model was capped at 512 tokens and could not exercise the larger batch. Assisted-by: claude-code:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(gallery): raise arch-router scoring output cap via parallel:64 Scoring decodes the whole prompt+candidate in a single llama_decode and reads one logit row per candidate token. The vendored llama.cpp server caps causal output rows at n_parallel, so the default of 1 aborts with GGML_ASSERT(n_outputs_max <= cparams.n_outputs_max) on multi-token route labels. Set options: [parallel:64] on both arch-router quant entries to lift the cap; kv_unified (the grpc-server default) keeps the full context per sequence, so this does not split the KV cache. Assisted-by: claude-code:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-06-12 16:21:15 +02:00
LocalAI [bot]	92dea961c2	fix: distributed backend reinstall/upgrade UI stuck on 'reinstalling' (#10214) ... * fix(galleryop): self-evict terminal ops from OpCache.GetStatus The processingBackends map (the UI 'reinstalling' spinner source) only cleared an op when a client polled /api/backends/job/:uid. The Manage-page Reinstall and Upgrade buttons never poll, so completed installs leaked into processingBackends forever and the backend card spun 'reinstalling' even though the install had finished. Evict terminal ops on the list read instead; DeleteUUID already broadcasts the eviction so peer replicas converge. Reproduced on a live 5-node distributed cluster: 5 backends sat in processingBackends with underlying jobs reporting completed:true,progress:100. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(nodes): clear pending backend ops behind offline/draining nodes ListDuePendingBackendOps filters status=healthy, so a backend op queued against a node that went offline (stale heartbeat) or draining (admin action) was never retried, aged out, or deleted - it leaked forever and kept the UI operation spinning. Add DeleteStalePendingBackendOps and run it each reconcile pass: draining nodes are cleared immediately (model rows already purged), offline nodes once their heartbeat is older than a grace window (blip protection). Reproduced on a live cluster: orphaned llama-cpp install rows targeting an offline (nvidia-thor) and a draining (mac-mini-m4) node sat at attempts=0 indefinitely. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(nodes): stream per-node progress during backend upgrade The install dispatch subscribed to a per-op progress subject and streamed per-node download ticks; the upgrade dispatch did a bare 15-minute blocking NATS round-trip with no subscription, so the UI showed progress:0 the whole time (the 'reinstalling but nothing happens' report on a slow node). Thread the op ID through BackendManager.UpgradeBackend -> the distributed manager -> the adapter, and have the adapter subscribe to the per-op progress subject before the request (extracted into a shared subscribeProgress helper reused by install/upgrade/force-fallback). The worker's upgradeBackend now creates the same DebouncedInstallProgressPublisher installBackend uses. An upgrade is a force-reinstall, so it reuses SubjectNodeBackendInstallProgress rather than minting a new subject - no new NATS permission, no new rolling-update compat surface. Reconciler-driven retries pass empty opID/onProgress and stay on the silent path. Reproduced on a live cluster: upgrade of llama-cpp-development on agx-orin-slow sat at progress:0 for 4+ minutes with no per-node feedback. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(galleryop): persist cancellation + periodically reap orphaned ops Two distributed gaps surfaced when a replica was killed mid-upgrade on a live cluster, leaving the backend stuck 'processing' in the UI forever: 1. CancelOperation flipped the in-memory status to cancelled and broadcast a NATS event but never persisted the terminal status. On the next replica restart the still-active row re-hydrated straight back into processingBackends and the UI spun again. It now calls store.Cancel(id) so the cancel survives a restart. 2. CleanStale (which marks abandoned active ops failed) only ran once on startup, so an op orphaned AFTER startup - its owning replica's foreground handler goroutine gone - was never reaped until the next restart. Add GalleryService.ReapStaleOperations and run it on a 15m ticker (CleanStale now returns the reaped count for observability). Neither is covered by the OpCache self-evict fix: an orphaned op never reaches Processed, so it would never self-evict. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(review): address self-review findings on the distributed install fixes Three findings from an adversarial review of this branch: 1. CRITICAL - OpCache.GetStatus crashed under concurrent load. m.Map() returns the live internal map by reference, so deleting from it on the read path was an unsynchronized write to a map four HTTP handlers poll every ~1s -> a 'concurrent map writes' fatal. Rewritten to iterate a Keys() snapshot, build a fresh result map, and apply evictions via the locked DeleteUUID after the loop. Added a -race concurrency regression guard. 2. HIGH - GetStatus evicted failed ops too, hiding them from /api/operations and breaking the dismiss-failed-op flow (the panel keeps Error != nil ops so the admin can read the error and click Dismiss). Eviction now fires only for terminal ops with Error == nil (success/cancelled); failures are retained. 3. MEDIUM - DeleteStalePendingBackendOps missed StatusUnhealthy nodes. A node marked unhealthy on a NATS ErrNoResponders never transitions to offline (health.go skips re-marking it), so its pending ops leaked exactly like the offline case. Unhealthy is now reaped via the same stale-heartbeat grace path (a fresh-heartbeat node is recovering and keeps its op). Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(review-2): don't evict the still-installing soft-path; don't spin on failed ops Second review pass found two issues: 1. MEDIUM (Go) - OpCache.GetStatus evicted the ErrWorkerStillInstalling soft-path op. That op is deliberately Processed=true with no error to show a yellow in-progress state when a worker timed out the NATS round-trip but is still installing in the background; the reconciler confirms the real outcome later. Evicting it (and broadcasting OpEnd + marking the DB completed) hid an install that may still fail. Eviction is now scoped to a clean success (progress 100 + 'completed', matching the job-poll's historical condition) or a cancellation - the soft-path (progress != 100) and failures are kept. 2. MEDIUM (React) - the Backends gallery card rendered ANY operation as an 'Installing...' spinner, so a failed op (now intentionally kept in the list for the OperationsBar error + Dismiss) spun forever. Exclude errored ops from the card spinner, mirroring Models.jsx (isInstalling already excludes op.error). The error + Dismiss still surface in the global OperationsBar. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ui): refresh Manage backends table when an operation settles The Manage backends table fetched installed backends only on mount/after delete and checked upgrades only on tab activation. After a reinstall/upgrade completed neither re-ran, so the installed-version cell and the 'update available' badge stayed stale until the user switched tabs - the op looked like it 'did nothing'. Watch the operations list (via useOperations) and re-fetch installed backends + available upgrades whenever the count settles, mirroring the operations.length watch Backends.jsx already uses. Consolidates the prior tab-activation upgrades check into the same effect. 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>	2026-06-08 10:03:02 +02:00
Richard Palethorpe	3a932a9803	feat(distributed): Add NATS JWT authentication and TLS/mTLS options (#10159) ... * feat(distributed): NATS JWT auth, TLS/mTLS options, and e2e coverage Mint per-node NATS user JWTs at registration when LOCALAI_NATS_ACCOUNT_SEED is set, and connect workers with scoped credentials from the register response. Add optional LOCALAI_NATS_TLS_CA/CERT/KEY for private CA and mTLS alongside tls:// URLs, plus test-e2e-distributed and NatsJWT container e2e specs. Document JWT setup (nats-auth-setup.sh) and TLS env vars in distributed-mode. Assisted-by: Grok:grok grok-build Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(distributed): correct NATS JWT scoping and harden client auth The JWT-auth path added in 46467cc7 had several gaps that fail silently under LOCALAI_NATS_REQUIRE_AUTH: - Agent-worker minted JWTs did not allow the subjects the agent worker actually subscribes to (jobs.mcp-ci.new and nodes.<id>.backend.stop), so MCP-CI jobs and backend-stop session cleanup were silently dropped. Scope the agent permission set to those subjects. - NATS subscription permission violations were swallowed (Subscribe returned a live-but-dead subscription). Confirm subscriptions with a server round-trip so a denial surfaces synchronously, and log async permission errors. - The backend worker connected anonymously when given a JWT without its paired seed; reject the unpaired credential instead. - The documented service-user permissions in nats-auth-setup.sh omitted prefixcache.>, which the frontend publishes and subscribes; add it. Also: add a credential-provider hook to the messaging client (consumed by the follow-up credential-lifecycle change), drop the always-nil error from NatsMessagingOptions, run go mod tidy (jwt/v2 and nkeys are now direct), and gofmt the feature's files. Tests: an agent-JWT e2e spec that connects to the enforcing NATS server and exercises every subscription the agent worker makes, plus permission allow-list coverage unit tests. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(distributed): acquire and auto-refresh worker NATS credentials Workers fetched NATS credentials once at startup, which broke two cases under JWT auth: a worker that registered while still pending admin approval never received a minted JWT (it connected unauthenticated and gave up), and a long-running worker's 24h JWT expired with no way to renew it. Introduce workerregistry.NATSCredentialManager, built on idempotent re-registration (the frontend preserves the node row and mints a fresh JWT each call): - Acquire re-registers through admin approval until the node is approved and credentials are minted (or returns the first success when auth is not required, preserving anonymous-NATS behavior). - RefreshLoop re-registers before the JWT expires (~75% of its lifetime), updating the credentials served to the connection. - Both are bounded (default 100 attempts / consecutive failures) and return an error on exhaustion, so an unapprovable or unrenewable worker exits non-zero and surfaces the problem instead of hanging or drifting toward an expired credential. The messaging client gains WithUserJWTProvider, fetching credentials on each (re)connect so the connection transparently adopts a refreshed JWT when the server expires the old one. RegisterFull exposes the approval status and full response; Register delegates to it. Both the backend worker and the agent worker are wired to this: explicit env credentials are used as-is, minted credentials are acquired-with-wait and refreshed, and a permanent refresh failure shuts the worker down so it restarts and re-acquires. Tests cover Acquire (wait-through-pending, bounded give-up, context cancel), RefreshLoop (refresh-before-expiry, bounded failure, no-expiry exit) and jwtExpiry decoding. Docs updated in distributed-mode.md. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-06-03 19:43:56 +02:00
LocalAI [bot]	a44bdb29d4	feat: prefix-cache-aware routing for distributed mode (#10071) ... * feat(radixtree): generic prefix tree skeleton with longest-match Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(radixtree): Insert with path recency refresh and entry cap Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(radixtree): TTL idle-expiry and Evict sweep with branch pruning Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(radixtree): recency-weighted per-value Weight Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(radixtree): Remove all entries for a value Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(radixtree): race-free concurrency smoke test Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(radixtree): reclaim empty branches, RWMutex reads, TTL boundary, empty-key guard Address review findings on the generic prefix tree: - Extract a shared pruneWalk helper parameterized by a shouldClear predicate and use it from Evict, Remove, and the MaxEntries path. Previously evictOldestLocked cleared a victim's value but never removed the now value-less node or its childless ancestors, so internal nodes accumulated under sustained churn at the cap. The MaxEntries path now prunes the victim and its empty ancestors. - DRY: pruneWalk replaces the duplicated logic in the former pruneLocked and Remove's inner closure. - Switch Tree.mu to sync.RWMutex; LongestMatch, Weight and Len take the read lock (RLock) while Insert, Evict and Remove keep the write lock. Confirmed race-clean under go test -race. - Document the strict greater-than TTL boundary on Options.TTL and expired: age exactly equal to TTL is still live. - Guard Insert against an empty key (no-op): the root never holds a value. Adds Ginkgo specs covering MaxEntries eviction, ancestor reclamation, the no-growth-past-cap invariant, the TTL boundary, and empty-key behavior for both Insert and LongestMatch. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(prefixcache): RoutePolicy enum with parse/resolve Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(prefixcache): Config with defaults and validation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(prefixcache): deterministic xxhash prefix-chain extractor Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(prefixcache): pure filter-then-score replica selection Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(prefixcache): Provider interface and radix-tree-backed Index Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * style(prefixcache): gofmt policy enum comment alignment Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(prefixcache): head-first prefix chunking and hoist Weight out of sort Address code-quality review findings in the prefixcache package. Correctness: ExtractChain now chunks from absolute offset 0 with fixed [0,W),[W,2W),... boundaries and caps the chain to the FIRST MaxDepth head blocks. The previous tail-keeping logic shifted the byte offset by a non-window amount once a conversation grew past MaxDepth*WindowBytes, changing every hash each turn and silently breaking cross-turn longest-prefix matching. The reusable KV/prefix cache lives at the head of the prompt, so anchoring at offset 0 makes the chain a true prefix-chain: P and P+suffix share their full leading overlap. Add a regression spec proving cross-turn stability past the cap. Performance: Index.Decide precomputes each candidate's Weight once (decorate-sort-undecorate) instead of calling the O(tree size) Weight inside the O(n log n) sort comparator. Behavior is unchanged. Lint: encode prev with binary.LittleEndian.PutUint64 instead of a manual byte loop, clearing the modernize rangeint finding. Also add a concurrent Decide/Observe/Invalidate spec to exercise Index's documented concurrency safety under go test -race. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(messaging): prefixcache observe/invalidate subjects and payloads Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(prefixcache): NATS sync publish/apply for observe and invalidate Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributedhdr): ctx carrier for prefix-hash chain Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributedhdr): PrefixChainHook indirection for backend-side chain build Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(backend): stash prompt prefix chain on ctx before distributed routing Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(backend): mirror modelID fallback for prefix-chain salt parity Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(nodes): scheduling config columns for prefix-cache routing Add RoutePolicy and per-model balance/prefix-match override columns to ModelSchedulingConfig and include them in the SetModelScheduling upsert DoUpdates list so updates are not dropped on conflict. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(nodes): optional route preference in FindAndLockNodeWithModel Add a RoutePreference type and a new pref parameter so the atomic pick+lock+increment can be biased toward a preferred node without weakening atomicity. A nil preference reproduces the previous ORDER BY behavior exactly. Update the ModelRouter interface, both router.go call sites (pass nil for now; Phase 5 builds the real preference), the test doubles, and the distributed e2e caller. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(prefixcache): make Sync satisfy Provider with Evict Sync.Observe now returns whether the local index treated the assignment as new or extended, and Sync gains an Evict method that delegates to the wrapped index. Together these let SmartRouter hold a single prefixcache.Provider that broadcasts via NATS. Adds a compile-time Provider assertion and an Evict-delegates behavioral test. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(nodes): prefix-cache-aware preference and observe in SmartRouter.Route Add a PrefixProvider + PrefixConfig to SmartRouterOptions/SmartRouter (nil keeps routing byte-for-byte the round-robin floor). On each request Route now calls buildPreference: it reads the prompt prefix chain from ctx (distributedhdr.PrefixChain), resolves the per-model policy/thresholds over the global config, loads candidate replica in-flight via a new registry read LoadedReplicaStats (deduped to one entry per node using the MIN in-flight across that node's replicas), asks the provider to Decide, and runs prefixcache.Select. The chosen node is passed as the RoutePreference to FindAndLockNodeWithModel on all three pick paths (cache hit, locked re-pick, cold scheduleAndLoad), and the served node is recorded via Observe only when the resolved policy is prefix_cache so round-robin models never pollute the tree. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(nodes): invalidate prefix-cache entries on unload and stale removal UnloadModel and both staleness fall-through paths in Route (after a failed gRPC probe and RemoveNodeModel) now call prefixProvider.Invalidate(model, nodeID), guarded by a nil-provider check so the round-robin floor is unchanged. At runtime the provider is the *prefixcache.Sync, so invalidations also broadcast to peer frontends. Adds a test that a previously hot prefix no longer Decides to a node after UnloadModel. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(prefixcache): rolling forced-disturb pressure counter Add a concurrency-safe per-model rolling counter that tracks how many times a request had a usable hot prefix match but the load guard forced it off the warm node. Entries outside the window are dropped lazily on Count so the backing slice stays bounded. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(nodes): autoscale on prefix-cache forced-disturb pressure Wire the rolling forced-disturb counter into the SmartRouter and the ReplicaReconciler. Router: in buildPreference, after Decide + Select, record a forced-disturb when a usable hot prefix match existed (d.HotNodeID != "" and d.MatchRatio >= cfg.MinPrefixMatch) but Select chose a different node (or nothing) because the load guard ruled the warm node out. This is the scale-worthy signal: the cache-warm replica is saturated. It deliberately does not fire for all-unique workloads (no hot match), avoiding false-positive scale-ups. Pressure is optional on SmartRouterOptions; nil keeps the path a no-op. Reconciler: read the same Pressure instance in reconcileModel as an extra scale-up reason, reusing the existing MaxReplicas + ClusterCapacityForModel guards and the UnsatisfiableUntil cooldown that gates the whole method. Pressure never overrides MaxReplicas and never force-evicts; a no-capacity model does not spin. Window and threshold come from prefixcache.Config (PressureWindow default 1m, PressureScaleThreshold default 1) and are configurable via ReplicaReconcilerOptions. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(prefixcache): bound Pressure slice in Record; drop dead reconciler pressureWindow Record now prunes entries older than the rolling window (the same prune Count does), via a shared pruneLocked helper, so a model that takes forced-disturb records but is never Counted (e.g. one with zero loaded replicas the reconciler skips) no longer grows its backing slice unbounded. Also removes the dead pressureWindow struct field and the ReplicaReconcilerOptions.PressureWindow option from the reconciler: they were stored but never read (the window lives inside the *prefixcache.Pressure instance). The scale block now reads pressure.Count once into a local. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(api): prefix-cache fields in scheduling endpoint DTO with validation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): prefix-cache routing controls in node scheduling form Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): wire prefix-cache index, NATS sync, and config Activates prefix-cache-aware routing in distributed mode. Builds the prefixcache Index + NATS-backed Sync + Pressure counter, installs the distributedhdr.PrefixChainHook so core/backend/llm.go attaches a prefix chain per request, subscribes to prefixcache.observe/prefixcache.invalidate to apply peers' events to the local index (no re-broadcast), threads PrefixProvider/PrefixConfig/Pressure into the SmartRouter and Pressure/PressureThreshold into the ReplicaReconciler, and runs a background eviction ticker (every TTL/2) bound to the app context. Enabled by default; --distributed-prefix-cache=false (LOCALAI_DISTRIBUTED_PREFIX_CACHE) opts out and leaves the provider/pressure nil so routing stays round-robin. --distributed-prefix-cache-ttl (LOCALAI_DISTRIBUTED_PREFIX_CACHE_TTL, default 5m) controls entry idle-timeout and eviction cadence. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(nodes): round-robin-floor invariant for prefix-cache routing Drives Select directly: a saturated hot node (in_flight 50 vs 0) is never picked even with a perfect prefix match (round-robin floor holds), while a balanced hot node within the load slack is reused. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(prefixcache): clear branch lint findings and em dashes Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): validate prefix-cache config at startup wiring Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * perf(radixtree): single-walk WeightsFor for batch value weights Add Tree.WeightsFor(values, now) which computes the recency-weighted weight for many values in a single O(N + len(values)) tree traversal, versus calling Weight once per value (O(len(values) * N)). Consumers that score K candidates against the tree under the read lock no longer pay K full walks. Extract the per-entry contribution math into an unexported helper shared by both Weight and WeightsFor so the metric stays identical (DRY). Weight's public behavior is unchanged. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(config): add ModelConfig.ModelID() single source of truth The c.Name fallback to c.Model was duplicated in core/backend/options.go (feeding model.WithModelID) and hand-copied into core/backend/llm.go (the prefix-chain salt). These MUST agree or the prefix-cache salt diverges silently from the id the model loader tracks. Consolidate both into a new config.ModelConfig.ModelID() helper and call it from both sites. Behavior is identical. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * perf(prefixcache): reuse one xxhash.Digest in ExtractChain ExtractChain allocated a fresh xxhash.New() Digest per block (up to MaxDepth per call) and grew the chain slice without preallocation. Reuse a single Digest via Reset() before each block and preallocate the chain to min(nBlocks, MaxDepth). xxhash seed 0 is stateless, so Reset()+Write produces the byte-identical value to a fresh New()+Write. Output hashes are unchanged, preserving the cross-process determinism that peers rely on over NATS. Verified by capturing ExtractChain output for the existing test inputs before and after the refactor: identical. Existing extractor tests pass unchanged. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(prefixcache): drop hot match when matched node is not a candidate; weigh cold candidates in one walk Index.Decide called radixtree.LongestMatch over the whole tree, so the deepest match could be a node that is offline, unloaded, or simply not in the passed candidate set. Honoring that as HotNodeID produced a false forced-disturb signal upstream (buildPreference records pressure when chosen != HotNodeID), making it look like a warm replica was load saturated when it was actually absent. Build the candidate set once and only set HotNodeID/MatchRatio when the matched node is an actual candidate; otherwise fall back to cold placement. A future refinement could ask the tree for the longest match restricted to the candidate nodes (shallower-but-valid) instead of dropping it. Also replace the per-candidate tree.Weight call in the cold-order sort with a single tree.WeightsFor walk, turning O(K*N) under the read lock into O(N + K). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(prefixcache): remove Select's unreachable deterministic fallback buildPreference always passes ColdOrder as a permutation of the full candidate set, so the cold-order loop hits every eligible candidate. The trailing best/bestIF scan was dead. Replace it with a plain "return """ and document that ColdOrder is guaranteed to cover all candidates, so "" means none were eligible. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(nodes): fetch model scheduling config once per Route GetModelScheduling was read three times per request - in resolveSelectorCandidates, buildPreference, and nodeMatchesScheduling - three DB round-trips for one row that is immutable for the life of the request, and not a consistent snapshot. Fetch it once near the top of Route and thread the *ModelSchedulingConfig (may be nil) into all three helpers. scheduleNewModel keeps its own fetch since it runs outside the Route snapshot. Behavior is identical for nil sched. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(autoscale): add Pressure.Reset to consume forced-disturb signal Pressure.Count is non-draining (it prunes only by age), so a single burst of forced-disturbs stays within the rolling window for the whole window and keeps Count >= threshold on every reconciler tick. The reconciler will use Reset to clear a model's events after acting on the signal so a fresh scale-up requires fresh forced-disturbs to accumulate, rather than one burst driving the model toward MaxReplicas. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(autoscale): at most one scale-up per reconcile tick, consume pressure Two autoscale bugs: 1. Over-scaling: the pressure scale-up block read Pressure.Count but never consumed it. With a non-draining counter a single forced-disturb burst kept Count >= threshold across the whole window, firing scaleUp on every tick and pushing the model toward MaxReplicas off one transient burst. After a successful pressure-triggered scale-up the reconciler now calls Pressure.Reset to consume the signal. 2. Double scale-up in one tick: the all-replicas-busy block and the pressure block could both fire in the same reconcileModel pass, each calling scaleUp(+1) against the same `current` read once at the top, so a model that was both busy and over threshold scaled +2 and could overshoot MaxReplicas by one. A scaledUp flag now enforces at most one scaleUp(+1) per tick: the pressure block is skipped if the busy block already scaled, and scale-down is skipped in any tick that scaled up. MinReplicas enforcement, UnsatisfiableUntil backoff, and capacity guards are unchanged. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(nodes): replica-removed chokepoint hook for prefix-cache invalidation Add SetReplicaRemovedHook to NodeRegistry and fire it from both RemoveNodeModel and RemoveAllNodeModelReplicas after a successful delete. This is the single chokepoint every replica-removal path funnels through (router eviction, reconciler scale-down, probe reaper, health-monitor node-down reap, RemoteUnloaderAdapter), so the prefix-cache index can be invalidated by construction rather than wiring each call site individually. The hook is stored in an atomic.Pointer so the startup wiring (setter) and the request/reconcile-time fire are race-free; it is nil-safe when unset. GORM Delete reports no error for a no-op delete, so the hook also fires when nothing was removed; the consumer's Invalidate(model, node) is idempotent so this is harmless. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): invalidate prefix-cache on any replica removal via registry hook Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(prefixcache): single source of truth for threshold bounds Extract ValidateThresholds into prefixcache/config.go so the per-model override validation (nodes.go endpoint) and Config.Validate share one implementation of the numeric bounds (min_prefix_match in [0,1], balance_abs_threshold >= 0, balance_rel_threshold == 0-or->= 1) instead of hard-coding them in two places. The route_policy allow-list stays explicit (not ParsePolicy, which maps typos to Default). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(nodes): preserve prefix-cache settings on partial scheduling update A scheduling POST that omitted route_policy/thresholds (e.g. a min_replicas-only update) full-replaced every column and silently reset the model's previously-configured prefix-cache settings to empty/zero. Make the four prefix-cache request fields pointers so omitted is distinguishable from explicit zero, and merge PATCH-style in SetSchedulingEndpoint: a provided pointer wins, an omitted one preserves the existing config value (zero default when none). Non-prefix fields keep their full-replace PUT semantics. Validation now runs on the resolved values via prefixcache.ValidateThresholds. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(prefixcache): make Invalidate a no-op for uncached models and skip empty broadcasts A registry chokepoint fires Sync.Invalidate(model, nodeID) for every replica removal of every model, including round-robin models that never used the prefix cache. Index.Invalidate previously called tree(model), which lazily created and permanently retained an empty radix tree for any model that ever lost a replica, growing the trees map without bound. Sync.Invalidate also published a NATS PrefixCacheInvalidateEvent on every call, amplifying no-op removals across the cluster. Index.Invalidate now looks the tree up read-only via existingTree and returns without allocating when none exists. The Provider interface is unchanged; Sync gates the broadcast through an optional invalidateExisting(bool) capability type-asserted from the wrapped Index, falling back to the prior always-broadcast behavior for other Provider implementations. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * perf(prefixcache): derive Decide candidacy from WeightsFor and skip trivial sort WeightsFor already returns a map keyed by every requested candidate, so the separate candidates set built to validate the hot match was redundant: a node is a candidate iff it is a key in the weights map. Drop the extra map and gate the hot-match check on weights membership. Also skip the sort when there is at most one candidate, since the input order is already the cold order. Behavior is unchanged. Deferred follow-up: skipping the WeightsFor walk entirely when a hot match wins would need lazy cross-file changes and is out of scope here. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(nodes): fire replica-removed hook on bulk node_models deletes; trim LoadedReplicaStats columns Bulk node-scoped node_models deletes (Register re-register cleanup, MarkOffline, MarkDraining, Deregister) removed rows directly without firing the replica-removed hook, so the prefix-cache index kept pointing at nodes whose models were gone. Capture the DISTINCT model names before each bulk delete and fire fireReplicaRemoved once per model after a successful delete, restoring the single-chokepoint invariant for all removal paths. The pre-query is skipped when no hook is set so the no-hook path stays cheap. Also narrow LoadedReplicaStats to SELECT only node_id and in_flight (the only fields the router consumer reads), dropping the JOIN-side available_vram fetch and unused columns while keeping the []ReplicaCandidate return type unchanged. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(reconciler): consume autoscale signals only on a real scale-up scaleUp was fire-and-forget (void) yet its callers unconditionally consumed the pressure signal (Pressure.Reset) and the MinReplicas hysteresis (ClearUnsatisfiable) right after calling it. If scaleUp added nothing (ScheduleAndLoadModel errored, or no node could be loaded) the saturated warm replica got no new replica AND its accumulated forced-disturb history was wiped, forcing the signal to re-accumulate over a full PressureWindow before the next attempt. Make scaleUp return whether at least one replica was actually scheduled, and gate the side effects on it: - pressure block (2b): set scaledUp and call Pressure.Reset only on success; on failure preserve the signal so the next tick retries off the same accumulated pressure. - busy-burst block (2): set scaledUp from the return value so a failed attempt does not suppress the pressure path or scale-down. - MinReplicas block: call ClearUnsatisfiable only on success so a failed attempt does not reset the unsatisfiable counter. All existing invariants (MaxReplicas, capacity gating, UnsatisfiableUntil cooldown, at-most-one-scale-up-per-tick) are preserved. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(nodes): drop router's redundant prefix-cache Invalidate calls The NodeRegistry removal chokepoint (RemoveNodeModel / RemoveAllNodeModelReplicas) now fires SetReplicaRemovedHook, which invalidates the prefix-cache index. The router was also calling prefixProvider.Invalidate explicitly right after each registry removal on the two stale-replica health-probe fall-throughs in Route and in UnloadModel, so every router-side eviction invalidated twice (double tree-prune + double NATS broadcast). Remove the three redundant explicit Invalidate calls and their empty nil-guards. Each removed call sat immediately after a registry removal that fires the hook, so invalidation is preserved via the chokepoint. Decide/Observe usage is untouched. Re-point the unit test (fake registry fires no hook) to assert the removal chokepoint is exercised on unload instead of the router's direct invalidation. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(prefixcache): broadcast invalidations unconditionally for cross-frontend coherence Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(prefixcache): reject TTL<=0 in Config.Validate (eviction ticker would panic) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(nodes): make capture+delete atomic in bulk node_models removal paths MarkOffline, MarkDraining, and the Register re-register cleanup ran the nodeModelNames SELECT and the bulk node_models DELETE as two separate statements on r.db with no transaction. A SetNodeModel landing between the two was deleted but its replica-removed hook never fired, leaving the prefix-cache index pointing at a removed replica until TTL or candidacy self-heal. Wrap the capture and the delete in a single db.Transaction in each path (mirroring how Deregister already does it). The captured model names are collected into a slice declared outside the closure; the replica-removed hook fires for each only after the transaction commits, so a rollback never invalidates the index for a removal that did not persist. The set of fired hooks now equals exactly the set of node_models rows actually deleted, with no interleaving gap. The status flip in MarkOffline/MarkDraining (setStatus) is a separate, pre-existing operation and routing already filters non-healthy nodes, so it stays outside the transaction; return contracts are unchanged. Deregister was already correct and is untouched. The cheap-path skip (no hook -> skip the SELECT) is preserved. Adds a spec asserting MarkOffline fires hooks for exactly the rows it deletes and leaves no node_models row behind (consistent snapshot). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(nodes): debug logging for prefix-cache routing decisions and observations Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(radixtree): match shared prefixes by valuing every node on insert Insert recorded the value (node id) only on the final node of the key chain, leaving every intermediate prefix node valueless. LongestMatch returns the deepest node that hasValue, so two chains that share a leading block but diverge in the tail never matched: only exact-repeat queries hit. That broke the prefix-cache routing core use cases (shared system prompt, multi-turn extension, volatile tail), all of which rely on prefix matching rather than exact-repeat. Set value/hasValue/lastSeen at every node along the chain so each prefix-block node remembers the node id that served that prefix (SGLang/vLLM-style). The deepest match wins, and the last writer owns a shared prefix node (a recency heuristic: the most recent chain through a block is the one most likely still warm). size now counts valued nodes, which is the intended meaning. Updated radixtree tests to the new semantics: deepest-prefix test uses non-overlapping chains, a new test asserts last-writer-owns-shared-node, Evict/Remove/MaxEntries expectations recomputed for per-prefix-node counting, and a shared-prefix LongestMatch red test added. Added a prefixcache Decide test proving a prefix-only query routes to the warm node. No prefixcache .go logic changed. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(distributed): lock in prefix-cache routing behavior end to end Add a DB-backed e2e spec that drives SmartRouter against a real NodeRegistry (Postgres testcontainer) and the real prefixcache.Index radix-tree provider, using a fake gRPC backend factory so no real inference runs. Covers the five behaviors validated by hand: 1. Cold miss + observe: an unseen prefix chain cold-places and is recorded. 2. Hot-match affinity: the same chain returns to its warm node X. 3. Shared-prefix match: a divergent chain sharing X's leading prefix still routes to X (the radix-tree regression we fixed). 4. Negative control: an unrelated chain is a cold miss, not a false hot match on X. 5. Failover + invalidation: removing X's replica fires the registry chokepoint hook to invalidate the prefix entry, and the chain fails over to surviving node Y and re-homes there. Replaces the need for manual docker-compose re-runs. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(prefixcache): make prefix-cache affinity replica-granular Track prefix-cache affinity per loaded replica (a backend process with its own KV cache) instead of per node, so multiple replicas of the same model on one node each keep distinct affinity and a hot prefix routes back to the exact replica that served it. - radixtree: add RemoveFunc(pred) and reimplement Remove on top of it. - prefixcache: introduce ReplicaKey{NodeID, Replica}; Index/Candidate/ PrefixDecision/Select/Provider now key on ReplicaKey. Add InvalidateNode to drop every replica of a node; Invalidate drops one replica. Select returns (ReplicaKey, bool) and gains a deterministic least-in-flight eligible fallback (tiebreak NodeID then Replica). - messaging: carry Replica on PrefixCacheObserveEvent and PrefixCacheInvalidateEvent (Replica < 0 means all replicas of the node). - Sync delegates + broadcasts with replica; InvalidateNode broadcasts Replica=-1; ApplyInvalidate routes negative replica to InvalidateNode. This is part 1 of 2; the registry/router/wiring consumers are updated separately. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): make prefix-cache routing replica-granular Wire the SmartRouter, NodeRegistry, and distributed startup to the replica-keyed prefixcache API. Affinity is now tracked per replica (each replica is a separate process with its own KV cache), so a prefix served by (node,0) no longer leaks onto the same-node sibling (node,1). - RoutePreference gains PreferredReplica; FindAndLockNodeWithModel locks the EXACT (node_id, replica_index) row, falling through to the default ORDER BY when that replica is not loaded. - SetReplicaRemovedHook now carries replicaIndex; RemoveNodeModel fires the specific replica, RemoveAllNodeModelReplicas and the four bulk node-scoped deletes fire replica<0 (all replicas of the node). - buildPreference builds one Candidate per loaded replica and locks the exact replica the policy chose; observePrefix records the served ReplicaKey at every call site. - distributed.go routes the hook to InvalidateNode (replica<0) or Invalidate(key). - Tests updated to the replica-keyed API plus new coverage: a hot prefix on (node,0) prefers replica 0 over the same-node sibling (router unit + e2e), and FindAndLock locks the exact preferred replica. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): derive prefix chain from messages for tokenizer-template models Prefix-cache-aware routing built its prompt-prefix chain from the rendered prompt string `s` in ModelInference. For models with TemplateConfig.UseTokenizerTemplate the frontend never renders a prompt - the backend tokenizes the structured messages itself - so `s` is empty, the chain is empty, and routing silently falls back to round-robin. That covers the bulk of modern chat models (qwen3, llama3, ...), so the feature effectively never engaged for them. Fall back to messagesPrefixSource(messages): a deterministic, prefix-stable head-first serialization of the conversation (role + content per turn). Two requests sharing a leading system prompt and early turns share a leading byte prefix, which ExtractChain maps to a shared chain prefix - landing both on the same cache-warm replica. The rendered `s` is still preferred when present (higher fidelity for non-template models). Found via the multi-replica-per-node e2e: zero "prefix-cache routing decision" logs despite per-request Route calls, traced to the empty-chain guard. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(distributed): document prefix-cache routing roadmap Add a routing-and-caching roadmap section to the distributed-mode guide, linking the epic (#10063) and the follow-up issues (#10064-#10070) surfaced from a survey of SGLang, vLLM production-stack, Ray Serve, llm-d, AIBrix, and NVIDIA Dynamo. 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>	2026-05-30 23:24:22 +02:00
Richard Palethorpe	fbcd886a47	fix(application): stop backend processes synchronously on shutdown (#10058) ... application.New wires a fire-and-forget goroutine that runs StopAllGRPC + distributed.Shutdown when the app context is cancelled. Callers (tests, CLI signal handler) cancel the context and then exit immediately, so the test binary / process can terminate before that goroutine kills the spawned backend children. go-processmanager sets no Pdeathsig, so the orphans are reparented to init and survive — leaving dozens of stray mock-backend processes after an e2e run. Add Application.Shutdown(), which runs the same cleanup synchronously on the caller's stack and is idempotent via sync.Once. The context-cancel goroutine, the CLI signal handler, and the test suites all call it, so cleanup is deterministic and the duplicated teardown logic collapses to one place. The async goroutine remains as a safety net for callers that forget; sync.Once dedupes the double call. Wire e2e_suite_test and the two mock-backend Contexts in app_test to call Shutdown in their AfterSuite/AfterEach. Assisted-by: Claude:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-05-29 11:40:43 +02:00
LocalAI [bot]	8d6548c0b9	fix(distributed): sync gallery OpCache + caches across frontend replicas (#9983) ... When the LocalAI frontend deployment is scaled past one replica, the UI's /api/operations poll round-robins between pods. Each pod kept the OpCache (galleryID->jobID), OpStatus map, and the post-install in-memory caches (ModelConfigLoader, UpgradeChecker) purely in-process. Reads never consulted PostgreSQL or NATS even though writes already published to PG. Symptoms: - A user installing a model on replica A saw the operation card flicker in and out as the load balancer alternated. - The Models page re-fetched the whole gallery on every flicker because useEffect([operations.length]) re-fires when the count changes. - A chat completion that landed on replica B after the install completed on replica A failed to find the new model — B's ModelConfigLoader was still the old one because nothing told it to reload from disk. - The UpgradeChecker 6-hour cache stayed stale on peer replicas after a backend upgrade, so /api/backends/upgrades kept surfacing an upgrade that had already shipped. Mirror the jobs Dispatcher pattern for gallery ops: - OpCache learns SetMessagingClient/SetGalleryStore + a Start(ctx) that hydrates from PostgreSQL and subscribes to gallery.opcache.{start,end}. Set/SetBackend now upsert cache_key + is_backend_op on the gallery_ operations row and broadcast OpCacheEvent so peers merge it in. The hydrate path uses a new GalleryStore.ListActive() (status in {pending, downloading, processing} and updated within 30 min). - GalleryService.SubscribeBroadcasts wires a SubjectGalleryProgress- Wildcard subscriber that calls a new lock-light mergeStatus into the local statuses map, plus a SubjectGalleryCancelWildcard subscriber that runs the locally-registered cancel func. Hydrate() restores active rows from PostgreSQL on startup so a freshly-started replica is not observably empty mid-install. CancelOperation tolerates the cancel func living on a different replica and publishes anyway. - modelHandler and backendHandler publish on the new SubjectCacheInvalidateModels / SubjectCacheInvalidateBackends after a successful install/delete/upgrade. SubscribeBroadcasts wires peers to refresh: OnModelsChanged (re-runs LoadModelConfigsFromPath) and OnBackendOpCompleted (re-triggers UpgradeChecker). The originating replica reloads inline so it never enters the broadcast handler. - OpStatus.Error (an error interface) flat-marshalled to "{}" over JSON, so a failed install replicated to a peer arrived with a nil error and the UI's failure banner never appeared. Add MarshalJSON/UnmarshalJSON via an opStatusWire shim that round-trips Error as a string. - UpdateStatus and CancelOperation now drop the mutex before publishing to NATS or persisting to PostgreSQL. The wildcard subscriber's mergeStatus loops back into the same service on the publishing replica and would deadlock otherwise; this also prevents future PG round-trips from stalling concurrent readers on every progress tick. Tests cover the OpStatus error round-trip, OpCache propagation through a shared in-memory bus, OpCache PostgreSQL hydration (active-only), GalleryService progress + cancel broadcast, Nodes preservation across a peer's bare progress tick, GalleryService hydration from PG, and the two cache-invalidation broadcasts (models + backends). 44 specs total in galleryop; routes/operations specs and jobs/agents suites still pass. Assisted-by: claude-code:claude-opus-4-7 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>	2026-05-25 17:28:14 +02:00
Richard Palethorpe	6a80e23733	feat(middleware): Model routing, PII filtering, Cloud model proxies (#9802) ... Add a routing middleware stack and a cloud-proxy backend. * cloud-proxy: a Go gRPC backend that forwards OpenAI- and Anthropic-shaped chat requests to upstream providers, with an optional translate mode (OpenAI request -> Anthropic /v1/messages -> OpenAI response) and full tool-calling support. * routing: admission control, content-aware model routing (embedding cache + classifier + rerank + Arch-Router score), PII detection/redaction (regex + NER) with streaming filter and OpenAI/Anthropic adapters, and a per-user/per-key billing recorder backed by GORM or in-memory storage. * middleware: UsageMiddleware records usage via the billing recorder, plus admission, route-model, usage-stamp and trace middlewares. * observability: BackendTrace ring buffer stores full request bodies (capped), MITM proxy emits structured trace events, and router classifier decisions surface at /api/router/decide. * gallery: Arch-Router-1.5B (Q4_K_M and Q8_0). * UI: cloud-proxy model-editor fields, classifier system-prompt and score-normalization config, and a Traces page rendering request bodies. Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash] Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-05-25 09:28:27 +02:00
LocalAI [bot]	a0f3e26245	fix(distributed): make admin backend installs resilient and observable (#9958) ... * feat(distributed): add configurable NATS backend install/upgrade timeouts Adds BackendInstallTimeout and BackendUpgradeTimeout to DistributedConfig with 15m defaults, following the existing MCPToolTimeout / WorkerWaitTimeout pattern. These will replace the hardcoded literals in RemoteUnloaderAdapter so admin-driven backend installs across the cluster survive long OCI image pulls that previously timed out at 3m. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * style(distributed): gofmt alignment after timeout fields Re-aligns the Validate() negative-duration map and the Default* const block so the new BackendInstall/UpgradeTimeout entries do not leave the surrounding columns mis-padded. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(cli): surface LOCALAI_NATS_BACKEND_INSTALL_TIMEOUT and _UPGRADE_TIMEOUT Parses the two new env vars on the run CLI and threads them through the existing AppOption builder so DistributedConfig picks them up. Invalid duration strings now fail loudly at startup rather than silently falling back to the default. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): inject NATS install/upgrade timeouts into RemoteUnloaderAdapter Removes the hardcoded 3m / 15m literals from RemoteUnloaderAdapter and threads in DistributedConfig.BackendInstallTimeoutOrDefault() and BackendUpgradeTimeoutOrDefault() at construction. Install now defaults to 15m (was 3m); cold OCI image pulls on Jetson Wi-Fi routinely blew past the old ceiling. Scripted messaging client captures the timeout so tests can assert the configured value actually reaches the NATS request. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): introduce galleryop.ErrWorkerStillInstalling sentinel When the NATS request-reply for backend.install (or .upgrade) times out the worker is almost always still pulling the OCI image. Wrap the timeout in a typed sentinel so the manager above can distinguish "worker hung" from "worker still working" and leave the pending_backend_ops row in place for the reconciler to confirm via backend.list. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): treat NATS install timeout as in-progress, not failure When a worker times out replying to backend.install but the install is still running on the worker, enqueueAndDrainBackendOp now reports a running_on_worker status and pushes NextRetryAt out by the install timeout so the reconciler does not immediately re-fire another install while the worker is still pulling the image. The pending_backend_ops row stays in place for the next reconciler pass to confirm via backend.list. InstallBackend wraps the result in galleryop.ErrWorkerStillInstalling so callers can branch (galleryop renders yellow in-progress instead of red error). UpgradeBackend uses the same wrap. Adds RemoteUnloaderAdapter.InstallTimeout() so the manager can push NextRetryAt by the configured timeout without reaching into a private field, and NodeRegistry.RecordPendingBackendOpInFlight as the soft cousin of RecordPendingBackendOpFailure. Also includes incidental gofmt-driven struct-field alignment in registry.go on lines unrelated to the change (touched files are re-formatted to canonical form per project policy). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): don't increment Attempts on in-flight install timeout An in-flight timeout (worker still pulling the OCI image) is not a failed attempt, it's a delayed one. Incrementing Attempts let genuinely-progressing slow installs (e.g. 30 GB CUDA images on Wi-Fi) trip the reconciler's maxPendingBackendOpAttempts cap and dead-letter the queue row while the worker was still legitimately working. RecordPendingBackendOpInFlight now only updates LastError and NextRetryAt. Also documents "running_on_worker" in the NodeOpStatus.Status enum comment so Task 6 implementers see the full surface. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(galleryop): surface ErrWorkerStillInstalling as non-error OpStatus When the distributed backend manager returns an error that wraps ErrWorkerStillInstalling, backendHandler now completes the op with a "still installing in background" message rather than marking it as a red failure. Admin UI sees a yellow in-progress state; reconciler confirms completion on its next pass. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(distributed): end-to-end install-timeout-then-reconcile Wires Task 1-6 end-to-end so any seam mismatch surfaces in CI rather than during a real cluster install. NATS times out, the queue row stays alive with running_on_worker status, the worker eventually reports the backend installed via backend.list, the manager surfaces it via ListBackends. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(distributed): document LOCALAI_NATS_BACKEND_INSTALL_TIMEOUT / _UPGRADE_TIMEOUT Add the two new operator-tunable env vars to the Frontend Configuration table in the distributed-mode docs. Explains the 15m default, when to raise it (slow links pulling multi-GB OCI images), and the new "still installing in background" admin-UI state when the round-trip times out but the worker is still working. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): clear pending install rows when backend.list confirms DistributedBackendManager.ListBackends now proactively clears pending_backend_ops install rows whose (nodeID, backend) is reported installed by backend.list. Operator UI updates immediately instead of waiting up to installTimeout (default 15m) for the next reconciler tick after NextRetryAt. Only install rows are cleared; upgrade and delete intents are not satisfied by presence in backend.list and continue to drain through their normal reconciler paths. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(messaging): add BackendInstallProgressEvent wire type and subject New NATS subject nodes.<nodeID>.backend.install.<opID>.progress lets the worker publish transient progress events (file, current/total bytes, percentage, phase) while a long-running install pulls its OCI image. BackendInstallRequest gains an optional OpID field so the worker knows which subject to publish on. Transient pub/sub (not JetStream): the install reply remains ground truth for success/failure; dropped progress events are tolerable. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * style(messaging): drop em-dash from BackendInstallProgress test comment Per project convention (no em-dashes anywhere). Comment substance is unchanged. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): worker publishes debounced install progress over NATS When BackendInstallRequest.OpID is set, the worker's backend.install handler wires a debounced publisher (250ms window) into the gallery download callback. Each tick becomes a BackendInstallProgressEvent on nodes.<nodeID>.backend.install.<opID>.progress; the publisher always emits a final event on Flush so the UI sees the terminal percentage. Old masters that do not set OpID continue to run silent installs: no behavior change for them. Lock ordering: the publisher releases its mutex before calling messaging.Publish so a slow network never stalls the install loop. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): RemoteUnloaderAdapter subscribes to install progress InstallBackend gains opID + onProgress parameters. When both are set, the adapter subscribes to nodes.<nodeID>.backend.install.<opID>.progress BEFORE publishing the install request, decodes each message into the caller's onProgress callback in a goroutine (so a slow callback never stalls the NATS reader thread), and unsubscribes after RequestJSON returns. When onProgress is nil OR opID is empty (the reconciler retry path), subscription is skipped entirely - silent installs cost nothing extra. Subscribe failure is logged at Warn and the install proceeds without progress streaming; the NATS round-trip still owns terminal status. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): forward backend install progress into galleryop OpStatus DistributedBackendManager.InstallBackend now passes the gallery op ID and a progress bridge into the adapter call. Each BackendInstallProgressEvent from the worker becomes a galleryop.ProgressCallback tick - which the existing backendHandler already turns into OpStatus.UpdateStatus, so the admin UI/SSE polling sees per-byte progress for distributed installs without any UI-side change. UpgradeBackend is intentionally left silent for now: its wire request (BackendUpgradeRequest) does not carry OpID, and rolling-update fallback is the rarer path. Will be picked up in a follow-up if the worker upgrade path also gets a progress channel. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(distributed): InstallBackend tolerates silent (pre-Phase-2) workers A worker on pre-Phase-2 code never publishes progress events. The new master subscribes optimistically; this spec pins that a silent worker still produces a green install with no progressCb ticks. The install reply is the source of truth for terminal state; the progress stream is a best-effort UX enrichment. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(distributed): document install progress streaming Note the new nodes.<nodeID>.backend.install.<opID>.progress subject and the silent-worker compatibility behavior so operators know to expect real-time progress and what happens on a mixed-version cluster. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(distributed): note progress-event ordering trade-off in InstallBackend Document near the goroutine dispatch why ordering at the consumer is best-effort, why it rarely matters in practice (worker debounce >> goroutine jitter), and what a future hardening pass would look like (Seq field + stale-by-seq drop). Stops the next reader from accidentally "fixing" the goroutine pool away. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(galleryop): add NodeProgress + OpStatus.Nodes for per-node breakdown Adds the data model the UI needs to render an expandable per-node breakdown of a fanned-out backend install. NodeProgress carries node identity (ID + name), per-node status (queued / running_on_worker / success / error / downloading), the current file + bytes + percentage from the Phase 2 progress stream, and any per-node error. OpStatus.Nodes is the slice the /api/operations handler will surface in a follow-up. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(galleryop): UpdateNodeProgress merges per-node ticks by NodeID GalleryService.UpdateNodeProgress(opID, nodeID, np) merges a NodeProgress into OpStatus.Nodes (keyed by NodeID, no duplicates) and mirrors the latest tick into the aggregate Progress / FileName / DownloadedFileSize / TotalFileSize fields so the legacy single-bar OperationsBar view keeps working unchanged alongside the new per-node breakdown. Concurrent-safe via the existing g.Mutex. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(distributed): write per-node OpStatus entries during install fan-out DistributedBackendManager now accepts a nodeProgressSink and feeds it two streams: 1. enqueueAndDrainBackendOp emits a per-node terminal entry on each status it appends to BackendOpResult (queued, success, error, running_on_worker). The opID is threaded through the function so the sink gets the right gallery op identity. 2. The install apply closure fans each BackendInstallProgressEvent into the sink as a downloading entry, alongside the legacy progressCb path so the aggregate single-bar view stays correct. Production wiring passes the GalleryService (which implements UpdateNodeProgress via Task 2) as the sink. Single-node tests pass nil. DeleteBackend and UpgradeBackend pass an empty opID so the sink path no-ops for ops that aren't gallery-tracked the same way as Install. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(operations): expose per-node breakdown on /api/operations When an operation's OpStatus has Nodes entries (populated by the Phase 4 progress sink wiring), surface them as a "nodes" array on the /api/operations response, sorted by node_name for stable rendering. Backward compatible: legacy clients ignore the field; ops without any node entries (single-node mode, model installs) omit the array entirely thanks to the empty-slice guard. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ui): per-node breakdown in OperationsBar When an install op fans out to more than one worker, the operations bar now shows a "N nodes" chevron that expands into a per-node list. Each row carries the node's status (color-coded pill), the current file being downloaded, byte counts, percentage, and a thin per-node progress bar. Yellow "Worker busy" pill marks running_on_worker status with a tooltip explaining the NATS round-trip timed out but the worker is still installing in the background. Backward compatible: ops without a nodes field (legacy or single-node mode) render as before. State for expand/collapse is local to the component, keyed by jobID/id - reload starts collapsed. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(distributed): document per-node breakdown in the operations bar Adds a short subsection covering the expandable "N nodes" chevron in the OperationsBar admin UI, the meaning of each status pill, and how it relates to the /api/operations nodes array. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(galleryop): UpdateStatus preserves Nodes when caller sends none Real-world bug surfaced by the Phase 4 multi-worker smoke test: the nodes[] array in /api/operations flickered between a single node at a time on a 2-worker install. Root cause: the Phase 2 progress bridge also calls the legacy progressCb -> UpdateStatus(&OpStatus{...}) on every tick. UpdateStatus then overwrote the entire status pointer, wiping the Nodes slice that UpdateNodeProgress had just merged in. Fix: in UpdateStatus, if the incoming op has an empty Nodes slice, carry forward the previous status's Nodes before storing. Callers that explicitly populate Nodes still win (their slice replaces the prior one, no merge across the two code paths). Two regression specs added pinning both directions of the contract. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(distributed): strip implementation details from user-facing docs Trim the new install/upgrade timeout rows and the install-progress sections to focus on what the operator sees and tunes. Drops: - the NATS subject names and pub/sub mechanics - "round-trip" / reconciler / backend.list jargon - /api/operations polling cadence - "pre-2026-05-22" version references Reframes the breakdown text around the admin UI (Operations Bar, chevron, status pills, "Worker busy" tooltip). Implementation context lives in the agent notes and code comments. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(config): move DistributedConfig.Validate flag names to constants The negative-duration check map was a wall of literal kebab-case strings that had to stay in sync with the kong-derived CLI flag names manually. Move them to a Flag* const block alongside the existing Default* block so a rename of either the Go field or the CLI naming convention forces a compile error rather than silent drift. Sole consumer today is Validate; the constants are exported so future operator-facing surfaces (e.g. error messages on other validation paths) can reference them by name instead of repeating the literals. Tests pin both the literal values (so a future "let's just rename this" doesn't accidentally regress the CLI flag) and the negative- duration error message for the new BackendInstall / BackendUpgrade fields. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(distributed): extract NodeStatus and Phase enums to constants Sweep for the same literal-string-as-identifier pattern called out on the Validate flag names: the per-node install status enum ("queued" | "downloading" | "running_on_worker" | "success" | "error") appeared as raw literals across managers_distributed.go (10+ sites, including 3 separate `n.Status == "running_on_worker"` checks), operation.go, and the test suite. Same shape for the Phase enum ("resolving" | "downloading" | "extracting" | "starting") in the worker-side progress publisher. Promote both to exported const blocks: - galleryop.NodeStatus{Queued,Downloading,RunningOnWorker,Success,Error} shared between galleryop.NodeProgress.Status (the wire field) and nodes.NodeOpStatus.Status (the in-process per-node summary) - messaging.Phase{Resolving,Downloading,Extracting,Starting} shared between the worker publisher and any future consumer that needs to switch on phase Tests pin both the literal values (so a future "let's just rename" doesn't silently change the JSON wire) and use the constants in setup (so the producer side stays drift-protected). Wire-format assertions on the /api/operations JSON output keep their literals deliberately, so the constant value can never silently diverge from what the UI receives. Out of scope for this PR (separate cleanup): the finetune and quantization job-status enums have the same anti-pattern with 14+ literal sites each, but predate this PR's work. 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>	2026-05-23 12:35:44 +02:00
LocalAI [bot]	61bf34ea2f	fix(traces): cap captured body size to keep admin Traces UI responsive (#9946) ... The trace middleware buffered the full request and response bodies for every JSON exchange. With a chatty agent-pool RAG workload, /embeddings responses (large vector arrays) accumulated to tens of MB in the in-memory buffer; the admin Traces page would then download and parse 40+ MB on every load and on every 5s auto-refresh, locking the UI in a loading state. Add LOCALAI_TRACING_MAX_BODY_BYTES (default 64 KiB) that caps each captured body. The full payload still flows through to the real client; only the trace copy is bounded. Exchanges record body_truncated and original body_bytes so the dashboard can show that truncation happened. The cap is configurable via env, CLI, and runtime_settings.json. Also unblock recovery: the Traces page now keeps the Clear button enabled while loading, since "buffer too large to render" is exactly when the user needs to clear it. Assisted-by: Claude:claude-opus-4-7 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>	2026-05-22 15:29:24 +02:00
Richard Palethorpe	5d0b549049	feat(gallery): verify backend OCI images with keyless cosign (#9823) ... * feat(gallery): verify backend OCI images with keyless cosign Close a trust gap where a registry compromise or MITM could silently replace a backend image: the gallery YAML tells LocalAI which image to pull, but until now nothing verified the bytes came from our CI. Consumer (pkg/oci/cosignverify): - New package using sigstore-go to verify keyless-cosign signatures. - OCI 1.1 referrers API + new bundle format (no legacy :tag.sig). - Policy fields: Issuer / IssuerRegex / Identity / IdentityRegex / NotBefore. NotBefore is the revocation lever — keyless Fulcio certs are ephemeral so revocation is policy-side; advancing not_before in the gallery YAML invalidates every signature predating the cutoff. - TUF trusted root cached process-wide so N backends from one gallery do 1 fetch, not N. Plumbing: - pkg/downloader: ImageVerifier interface + WithImageVerifier option threaded through DownloadFileWithContext. Verification runs between oci.GetImage and oci.ExtractOCIImage, with digest pinning via pinnedImageRef to close the TOCTOU window. Skips the verifier's HEAD when the ref is already digest-pinned. - core/config: Gallery.Verification YAML block. - core/gallery: backendDownloadOptions builds the verifier from the policy; applied on initial URI, mirrors, and tag fallbacks. - core/gallery/upgrade: the upgrade path now routes through the same options builder. A regression Ginkgo spec pins this contract — without it, UpgradeBackend silently bypassed verification. - core/cli: --require-backend-integrity (LOCALAI_REQUIRE_BACKEND_INTEGRITY) escalates missing policy / empty SHA256 from warn to hard-fail. Producer (.github/workflows/backend_merge.yml): - id-token: write at job scope (PR-fork-safe via existing event gate). - sigstore/cosign-installer@v3 pinned to v2.4.1. - After each docker buildx imagetools create, resolve the manifest list digest and run cosign sign --recursive --new-bundle-format --registry-referrers-mode=oci-1-1 against repo@digest. --recursive signs the index and every per-arch entry, matching how the consumer resolves a tag to a platform-specific manifest before verifying. Rollout: backend/index.yaml has no `verification:` block yet, so this PR is backward-compatible — installs proceed with a warning until the gallery is populated. Strict mode is opt-in. Assisted-by: claude-code:claude-opus-4-7 [Bash] [Edit] [Read] [Write] [WebSearch] [WebFetch] Signed-off-by: Richard Palethorpe <io@richiejp.com> * refactor(gallery): plumb RequireBackendIntegrity through config instead of env The previous implementation re-exported the --require-backend-integrity CLI flag into LOCALAI_REQUIRE_BACKEND_INTEGRITY via os.Setenv, then re-read it in core/gallery via os.Getenv. This leaked process state into the gallery package and made the flag impossible to override per-call or test without touching the env. Add RequireBackendIntegrity to ApplicationConfig (with a matching WithRequireBackendIntegrity AppOption) and thread the bool through every install/upgrade path: InstallBackend, InstallBackendFromGallery, UpgradeBackend, InstallModelFromGallery, InstallExternalBackend, ApplyGalleryFromString/File, startup.InstallModels. Worker subcommands gain the same env-bound flag on WorkerFlags so distributed-worker installs honor it consistently with the worker daemon path. Add a forbidigo lint rule against os.Getenv / os.LookupEnv / os.Environ to keep the env-leak pattern from creeping back. Existing offenders (p2p, config loaders, etc.) are baseline-grandfathered by the existing new-from-merge-base: origin/master setting; targeted path exclusions cover the legitimate cases — kong CLI entry points, backend subprocesses, system capability probes, gRPC AUTH_TOKEN inheritance, test gating env vars. Assisted-by: claude-code:claude-opus-4-7 Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-05-18 08:02:20 +02:00
LocalAI [bot]	b4fdb41dcc	fix(distributed): cascade-clean stale node_models rows + filter routing by healthy status (#9754) ... * fix(distributed): cascade-clean stale node_models on drain and filter routing by healthy status Stale node_models rows (state="loaded") were surviving past the healthy state of their owning node, causing /embeddings (and other inference paths) to dispatch to a backend whose process was gone or drained. The downstream symptom in a live cluster was pgvector rejecting inserts with "vector cannot have more than 16000 dimensions (SQLSTATE 54000)" because the misbehaving backend silently returned a malformed (oversized) tensor; the Models page showed the model as "running" without an associated node, like a stale entry, even though the node was no longer visible in the Nodes view. Two changes here, plus a third in a follow-up commit: - MarkDraining now cascade-deletes node_models rows for the affected node, mirroring MarkOffline. Drains are explicit operator actions — the box has been intentionally taken out of rotation — so clearing the rows stops the Models UI from misreporting and prevents the routing layer from picking those rows if scheduling logic is ever relaxed. In-flight requests already hold their gRPC client through Route() and finish normally; the only observable effect is a non-fatal IncrementInFlight warning, acceptable for a drain. MarkUnhealthy is deliberately left status-only: it fires from managers_distributed / reconciler on a single nats.ErrNoResponders with no retry, so a transient NATS hiccup must not nuke every loaded model and force a full reload on recovery. - FindAndLockNodeWithModel's inner JOIN now filters on backend_nodes.status = healthy in addition to node_models.state = loaded. The previous version relied on the second node-fetch step to reject non-healthy nodes, but a concurrent reader could still pick the same stale row in the same window. Belt-and-braces. - DistributedConfig.PerModelHealthCheck renamed to DisablePerModelHealthCheck and inverted at the call site so per-model gRPC probing is on by default. The probe (now made consecutive-miss aware in a follow-up commit) independently health- checks each model's gRPC address and removes stale node_models rows when the backend has crashed even though the worker's node-level heartbeat is still arriving. Migration: the field had no CLI flag, env var binding, or YAML key in tree (only the bare struct field), so there is no user-facing migration. Anything constructing DistributedConfig in code needs to drop the assignment (default now does the right thing) or invert it. Assisted-by: Claude:claude-opus-4-7 go-vet go-test golangci-lint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): require consecutive misses before per-model probe removes a row The per-model gRPC probe used to remove a node_models row on a single failed health check. With the per-model probe now on by default, that made any 5-second gRPC blip (network jitter, a long-running request hogging the worker's gRPC server thread, brief GC pause) trigger a full reload of the affected model — too eager for production. Require perModelMissThreshold (3) consecutive failed probes before removal. At the default 15s tick a model must be unreachable for ~45s before reap; a single successful probe in between resets the streak. Per-(node, model, replica) state tracked under a mutex on the monitor. If the removal call itself fails, the miss counter is left in place so the next tick retries rather than starting the streak over. Tests: - removes stale model via per-model health check after consecutive failures (replaces the single-shot expectation) - preserves model row when an intermittent failure is followed by a success (covers the reset-on-success path and verifies the counter reset by failing twice more without crossing threshold) - newTestHealthMonitor initializes the misses map so direct-construct test helpers don't nil-map-panic in the probe path Assisted-by: Claude:claude-opus-4-7 go-vet go-test 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>	2026-05-13 21:57:50 +02:00
Richard Palethorpe	969005b2a1	feat(gallery): Speed up load times and clean gallery entries (#9211) ... * feat: Rework VRAM estimation and use known_usecases in gallery Signed-off-by: Richard Palethorpe <io@richiejp.com> Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code] * chore(gallery): regenerate gallery index and add known_usecases to model entries Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com>	2026-05-06 14:51:38 +02:00
Ettore Di Giacinto	bbcaebc1ef	feat(concurrency-groups): per-model exclusive groups for backend loading (#9662) ... * feat(concurrency-groups): per-model exclusive groups for backend loading Adds `concurrency_groups: [...]` to model YAML configs. Two models that share a group cannot be loaded concurrently on the same node — loading one evicts the others, reusing the existing pinned/busy/retry policy from LRU eviction. Layered design: - Watchdog (pkg/model): per-node correctness floor — on every Load(), evict any loaded model that shares a group with the requested one. Pinned skips surface NeedMore so the loader retries (and ultimately logs a clear warning), instead of silently allowing the rule to be violated. - Distributed scheduler (core/services/nodes): soft anti-affinity hint — scheduleNewModel prefers nodes that don't already host a same-group model, falling back to eviction only if every candidate has a conflict. Composes with NodeSelector at the same point in the candidate pipeline. Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy models running on different nodes is fine. The ConfigLoader is wired into SmartRouter via a small ConcurrencyConflictResolver interface so the nodes package keeps a narrow surface on core/config. Refactors the inner LRU eviction body into a shared collectEvictionsLocked helper and the loader retry loop into retryEnforce(fn, maxRetries, interval), so both LRU and group enforcement share busy/pinned/retry semantics. Closes #9659. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(watchdog): sync pinned + concurrency_groups at startup The startup-time watchdog setup lives in initializeWatchdog (startup.go), not in startWatchdog (watchdog.go). The latter is only invoked from the runtime-settings RestartWatchdog path. As a result, neither SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot, so `pinned: true` and `concurrency_groups: [...]` only became effective after a settings-driven watchdog restart. Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end: loading model A in group "heavy", then C with no group (coexists), then B in group "heavy" now correctly evicts A and leaves [B, C]. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec CI lint runs new-from-merge-base, so the existing pre-existing `defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the one introduced by the concurrency_groups YAML round-trip test is held to errcheck. Wrap the remove in a closure that discards the error. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>	2026-05-05 08:42:50 +02:00
LocalAI [bot]	de83b72bb7	fix(distributed): orchestrator resilience — auto-upgrade routing, worker bind-wait, RAG-init crash, log spam (#9657) ... * fix(nodes/health): skip stale-marking already-offline nodes The health monitor re-emitted "Node heartbeat stale" + "Marking stale node offline" + MarkOffline on every cycle for nodes that were already in the offline (or unhealthy) state. For an operator-stopped node this flooded the logs with the same WARN+INFO pair every check interval. Skip the staleness branch when the node is already StatusOffline / StatusUnhealthy — the state is already what we'd write, so neither the log lines nor the DB update carry information. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(worker): wait for backend gRPC bind before replying to backend.install The backend supervisor used to wait up to 4s (20 × 200ms) for the backend's gRPC server to answer a HealthCheck, then log a warning and reply Success with the bind address anyway. On slower nodes (a Jetson Orin doing first-boot CUDA init, large CGO library load) the gRPC listener wasn't up yet, so the frontend's first LoadModel dial returned "connect: connection refused" and the operator chased a phantom network issue instead of a startup-timing one. Two changes: - Bump the readiness window to 30s. CUDA init on Orin/Thor first boot measures in seconds, not milliseconds. - On deadline-exceeded, stop the half-started process, recycle the port, and return an error with the backend's stderr tail. The frontend now gets a real failure with diagnostic context instead of a misleading ECONNREFUSED on a downstream dial. Process death during the wait window keeps its existing fast-fail path. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): route auto-upgrade through BackendManager + bump LocalAGI/LocalRecall Two distributed-mode bugs that surfaced together in the orchestrator logs: 1. Auto-upgrade always failed with "backend not found". UpgradeChecker correctly routed CheckUpgrades through the active BackendManager (so the frontend aggregates worker state), but the auto-upgrade branch right below called gallery.UpgradeBackend directly with the frontend's SystemState. In distributed mode the frontend has no backends installed locally, so ListSystemBackends returned empty and Get(name) failed for every reported upgrade. Auto-upgrade now also goes through BackendManager.UpgradeBackend, which fans out to workers via NATS. 2. Embedding-load failure on a remote node crashed the orchestrator. When RAG init lazily called NewPersistentPostgresCollection and the remote embedding worker was unreachable, LocalRecall called os.Exit(1) inside the constructor, killing the orchestrator pod. LocalRecall now returns errors instead, LocalAGI surfaces them as a nil collection, and the existing RAGProviderFromState path returns (nil, nil, false) — the same code path the agent pool already takes when no RAG is configured. The orchestrator stays up; chat requests degrade to "no RAG available" until the embedding worker recovers. Bumps: github.com/mudler/LocalAGI → e83bf515d010 github.com/mudler/localrecall → 6138c1f535ab 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>	2026-05-04 19:09:16 +02:00
Ettore Di Giacinto	b1a99436c7	feat(branding): admin-configurable instance name, tagline, and assets (#9635) ... Adds a whitelabeling feature so an operator can replace the LocalAI instance name, tagline, square logo, horizontal logo, and favicon from the admin Settings page. Defaults fall back to the bundled assets so existing installs are unaffected. The public GET /api/branding endpoint is reachable pre-auth so the login screen can render the configured branding before sign-in. Mutating routes (POST/DELETE /api/branding/asset/:kind) remain admin-only. Text fields (instance_name, instance_tagline) ride the existing /api/settings flow; binary assets get a dedicated multipart upload route that persists files under DynamicConfigsDir/branding/. To prevent the Settings page's stale local state from clobbering an upload on save, UpdateSettingsEndpoint preserves whatever the on-disk asset filename fields are regardless of the body — /api/branding/asset/* are the sole writers for those fields. The MCP catalog gains get_branding and set_branding tools (text fields only; file upload stays UI-only) plus a configure_branding skill prompt. While wiring this up, the same restart-loss class of bug surfaced for several existing fields whose RuntimeSettings entries were never read by the startup loader. Fix loadRuntimeSettingsFromFile() to load: - branding (instance_name, instance_tagline, *_file basenames) - auto_upgrade_backends, prefer_development_backends - localai_assistant_enabled - open_responses_store_ttl - the 7 existing AgentPool fields (enabled, default/embedding model, chunking sizes, enable_logs, collection_db_path) Also exposes 3 new AgentPool runtime settings (vector_engine, database_url, agent_hub_url) via /api/settings + the Settings UI, with the same load-on-startup wiring. The file watcher's manual-edit path is intentionally not changed — the in-process API endpoints already update appConfig directly, so the watcher is redundant for supported flows and a separate refactor for everything else. 15 TDD specs cover the loader behaviour (1 branding + 11 adjacent + 3 new agent-pool); 2 specs cover the persistence helpers and the clobber-prevention contract. Assisted-by: claude-code:claude-opus-4-7 Signed-off-by: Ettore Di Giacinto <mudler@localai.io>	2026-05-02 15:51:36 +02:00
Ettore Di Giacinto	bcef72b9c1	feat: localai assistant chat modality (#9602) ... * fix(tests): inline model_test fixtures after tests/models_fixtures removal The previous reorg removed tests/models_fixtures/ but core/config/model_test.go still read CONFIG_FILE/MODELS_PATH env vars pointing into that directory, so `make test` failed with "open : no such file or directory" on the readConfigFile spec (the suite ran with --fail-fast and bailed before openresponses_test). Inline the YAMLs (config/embeddings/grpc/rwkv/whisper) directly into the test file, materialise them into a per-test tmpdir via BeforeEach, and drop the env-var lookups. The test no longer depends on Makefile plumbing. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:claude-opus-4-7 [Edit] [Write] [Bash] * refactor(modeladmin): extract model-admin helpers into a service package Lift the bodies of EditModelEndpoint, PatchConfigEndpoint, ToggleStateModelEndpoint, TogglePinnedModelEndpoint and VRAMEstimateEndpoint into core/services/modeladmin so the same logic can be called by non-HTTP clients (notably the in-process MCP server that backs the LocalAI Assistant chat modality, landing in a follow-up commit). The HTTP handlers shrink to thin shells that parse echo inputs, call the matching helper, map typed errors (ErrNotFound, ErrConflict, ErrPathNotTrusted, ErrBadAction, ...) to the existing HTTP status codes, and render the existing response shapes. No REST-surface behaviour change; the existing localai endpoint tests cover the regression net. Adds focused unit tests for each helper against tmp-dir-backed ModelConfigLoader fixtures (deep-merge patch, rename + conflict, path separator guard, toggle/pin enable/disable, sync callback). Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(assistant): LocalAI Assistant chat modality with in-memory MCP server Adds a chat modality, admin-only, that wires the chat session to an in-memory MCP server exposing LocalAI's own admin/management surface as tools. An admin can install models, manage backends, edit configs and check status by chatting; the LLM calls tools like gallery_search, install_model, import_model_uri, list_installed_models, edit_model_config and surfaces the results. Same Go package powers two modes: pkg/mcp/localaitools/ NewServer(client, opts) builds an MCP server that registers the 19-tool admin catalog. The LocalAIClient interface has two impls: - inproc.Client — calls services directly (no HTTP loopback, no synthetic admin API key). Used in-process by the chat handler. - httpapi.Client — calls the LocalAI REST API. Used by the new `local-ai mcp-server --target=…` subcommand to control a remote LocalAI from a stdio MCP host. Tools and their embedded skill prompts are agnostic to which client backs them. Skill prompts are markdown files under prompts/, embedded via go:embed and assembled into the system prompt at server init. Wiring: - core/http/endpoints/mcp/localai_assistant.go — process-wide holder that spins up the in-memory MCP server once at Application start using paired net.Pipe transports, then reuses LocalToolExecutor (no fork) for every chat request that opts in. - core/http/endpoints/openai/chat.go — small branch ahead of the existing MCP block: when metadata.localai_assistant=true, defense-in-depth admin check + executor swap + system-prompt injection. All downstream tool dispatch is unchanged. - core/http/auth/{permissions,features}.go — adds FeatureLocalAIAssistant; gating happens at the chat handler entry plus admin-only `/api/settings`. - core/cli/{run.go,cli.go,mcp_server.go} — LOCALAI_DISABLE_ASSISTANT flag (runtime-toggleable via Settings, no restart), plus `local-ai mcp-server` stdio subcommand. - core/config/runtime_settings.go — `localai_assistant_enabled` runtime setting; the chat handler reads `DisableLocalAIAssistant` live at request entry. UI: - Home.jsx — prominent self-explanatory CTA card on first run ("Manage LocalAI by chatting"); collapses to a compact "Manage by chat" button in the quick-links row once used, persisted via localStorage. - Chat.jsx — admin-only "Manage" toggle in the chat header, "Manage mode" badge, dedicated empty-state copy, starter chips. - Settings.jsx — "LocalAI Assistant" section with the runtime enable toggle. - useChat.js — `localaiAssistant` flag on the chat schema; injects `metadata.localai_assistant=true` on requests when active. Distributed mode: the in-memory MCP server lives only on the head node; inproc.Client wraps already-distributed-aware services so installs propagate to workers via the existing GalleryService machinery. Documentation: `.agents/localai-assistant-mcp.md` is the contributor contract — when adding an admin REST endpoint, also add a LocalAIClient method, an inproc + httpapi impl, a tool registration, and a skill prompt update; the AGENTS.md index links to it. Out of scope (follow-ups): per-tool RBAC granularity for non-admin read-only access; streaming mcp_tool_progress for long installs; React Vitest rig for the UI changes. Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(assistant): extract tool/capability/MiB/server-name constants The MCP tool surface, capability tag set, server-name default, and the chat-handler metadata key were repeated as bare string literals across seven files. Renaming any one required hand-editing every call site and risked code/test/prompt drift. This pulls them into typed constants: - pkg/mcp/localaitools/tools.go — Tool* constants for the 19 MCP tools, plus DefaultServerName. - pkg/mcp/localaitools/capability.go — typed Capability + constants for the capability tag set the LLM passes to list_installed_models. The type rides through LocalAIClient.ListInstalledModels and replaces the triplet of "embed"/"embedding"/"embeddings" with the single CapabilityEmbeddings. - pkg/mcp/localaitools/inproc/client.go — bytesPerMiB constant for the VRAMEstimate byte→MB conversion. - core/http/endpoints/mcp/tools.go — MetadataKeyLocalAIAssistant for the "localai_assistant" request-metadata key consumed by the chat handler. Tool registrations, the test catalog, the dispatch table, the validation fixtures, and the fake/stub clients all reference the constants. The embedded skill prompts under prompts/ keep their bare strings (go:embed markdown can't import Go constants); the existing TestPromptsContain SafetyAnchors guards the alignment. No behaviour change. All tests pass with -race. Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(modeladmin): typed Action for ToggleState/TogglePinned The toggle/pin verbs were bare strings everywhere — handler signatures, service implementations, MCP tool args, the fake/stub clients, the inproc and httpapi LocalAIClient impls, plus 4 test files. A typo in any caller silently fell through to the runtime "must be 'enable' or 'disable'" check. Introduce core/services/modeladmin.Action (string alias) with ActionEnable, ActionDisable, ActionPin, ActionUnpin and a small Valid helper. The compiler now catches mismatches at every boundary; renames ripple through one source of truth. LocalAIClient.ToggleModelState/Pinned signatures change to take modeladmin.Action. The package is brand-new and unreleased so this is a free public-API tightening. Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(assistant): respect ctx cancellation on gallery channel sends InstallModel, DeleteModel, ImportModelURI, InstallBackend and UpgradeBackend all pushed onto galleryop channels with bare sends. If the worker was paused or the buffer full, the chat-handler goroutine blocked forever — the LLM kept polling and the request leaked. Wrap the five sends in a sendModelOp/sendBackendOp helper that selects on ctx.Done() so a cancelled chat completion surfaces context.Canceled back to the LLM instead of hanging. Adds inproc/client_test.go with a pre-cancelled-ctx regression test on InstallModel; the helpers are shared so the same guarantee covers the other four call sites. Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(assistant): graceful shutdown for in-memory holder and stdio CLI Two related leaks: - Application.start() built the LocalAIAssistantHolder but never wired Close() into the graceful-termination chain — the in-memory MCP transport pair stayed alive until process exit, and the goroutines behind net.Pipe() didn't drain. Hook into the existing signals.RegisterGracefulTerminationHandler chain (same pattern as core/http/endpoints/mcp/tools.go:770). - core/cli/mcp_server.go ran srv.Run with context.Background(); a Ctrl-C from the host (Claude Desktop, mcphost, npx inspector) or a SIGTERM from process supervision left the stdio loop reading from a closed pipe. Switch to signal.NotifyContext to surface the signal through ctx and let srv.Run drain. Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(assistant): typed HTTPError + propagate prompt walk error The httpapi client detected "no such job" by substring-matching on the error string ("404", "could not find") — brittle to status-code formatting changes and to LocalAI fixing /models/jobs/:uuid to return a proper 404. Replace with a typed *HTTPError whose Is() method honours errors.Is(err, ErrHTTPNotFound). The 500-with-"could not find" branch stays as a transitional fallback documented in Is(). Same change covers ListNodes' 404 fallback for the /api/nodes endpoint. Adds httptest tests for both 404 and the legacy 500 path, plus a direct errors.Is exposure test so external callers (the standalone stdio CLI host) can match without re-string-parsing. Also tightens prompts.SystemPrompt: panic when fs.WalkDir on the embedded FS fails. The only realistic cause is a build-time //go:embed misconfiguration; serving an empty system prompt to the LLM is much worse than crashing init. TestSystemPromptIncludesAllEmbeddedFiles catches regressions in CI. Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(modeladmin): atomic writes for model config files The five sites that wrote model YAML used os.WriteFile, which opens with O_TRUNC|O_WRONLY|O_CREATE. A crash mid-write left the destination truncated and the model unloadable until manual repair. Pre-existing behaviour inherited from the original endpoint handlers — fix once now that there's a single helper. Adds writeFileAtomic: writes to a sibling temp file, chmods, syncs via Close(), then os.Rename. Same-directory temp keeps the rename atomic on the same filesystem; cleanup runs on every error path so stray temps don't accumulate. No new dependency. Applied to: - ConfigService.PatchConfig - ConfigService.EditYAML (both rename and in-place branches) - mutateYAMLBoolFlag (drives ToggleState + TogglePinned) atomic_test.go covers the happy path plus a read-only-dir failure case that asserts the original file is preserved (skipped on Windows where the chmod trick is POSIX-specific). Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(assistant): prune dead code, mark stub, document conventions Three small cleanups landing together: - Drop the unused errNotImplemented sentinel from inproc/client.go. All five methods that used to return it are wired to modeladmin helpers since the Phase B commit; the package var is dead. - Annotate httpapi.Client.GetModelConfig as a known stub. LocalAI's /models/edit/:name returns rendered HTML, not JSON, so the standalone CLI's get_model_config tool surfaces a clear error to the LLM. A future JSON-only /api/models/config-yaml/:name endpoint is tracked in the agent contract; FIXME points at it. - Extend `.agents/localai-assistant-mcp.md` with a "Code conventions" section that documents the audit-driven rules: tool/Capability/Action constants, errors.Is over substring matching, ctx-aware channel sends, atomic writes, and graceful shutdown. Refresh the file map so it lists tools.go and capability.go and drops the removed tools_bootstrap.go. The tools_models.go diff is a comment-only change explaining why the ModelName empty-string check stays at the tool layer (consistency across LocalAIClient implementations, since the SDK schema validator only enforces presence, not non-empty). Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(assistant): convert test files to ginkgo + gomega The repo convention (per core/http/endpoints/localai/*_test.go, core/gallery/**, etc.) is Ginkgo v2 with Gomega assertions. The tests I introduced for the assistant feature used vanilla testing.T, which made them stand out and stripped the BDD structure the rest of the suite relies on. Convert every test file in the assistant scope to Ginkgo: pkg/mcp/localaitools/ dto_test.go — Describe("DTOs round-trip through JSON") prompts_test.go — Describe("SystemPrompt assembler") server_test.go — Describe("Server tool catalog"), Describe("Tool dispatch"), Describe("Tool error surfacing"), Describe("Argument validation"), Describe("Concurrent tool calls") parity_test.go — Describe("LocalAIClient parity"), hosts the suite's single RunSpecs (the file is package localaitools_test so it can import httpapi without an import cycle; Ginkgo aggregates Describes from both the internal and external test packages into one run). httpapi/client_test.go — Describe("httpapi.Client against the LocalAI admin REST surface"), Describe("ErrHTTPNotFound"), Describe("Bearer token") inproc/client_test.go — Describe("inproc.Client cancellation") core/services/modeladmin/ config_test.go — Describe("ConfigService") with sub-Describes for GetConfig, PatchConfig, EditYAML state_test.go — Describe("ConfigService.ToggleState") pinned_test.go — Describe("ConfigService.TogglePinned") atomic_test.go — Describe("writeFileAtomic") core/http/endpoints/mcp/ localai_assistant_test.go — Describe("LocalAIAssistantHolder") Each package gets a `*_suite_test.go` with the standard `RegisterFailHandler(Fail) + RunSpecs(t, "...")` boilerplate. Helpers that previously took *testing.T (newTestService, writeModelYAML, readMap, sortedStrings, sortGalleries, etc.) drop the *T receiver and use Gomega Expectations directly. tmp dirs come from GinkgoT().TempDir(). No semantic change to test coverage — every original assertion has a direct Gomega counterpart. All suites pass with -race. Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test+docs(assistant): drift detector for Tool ↔ REST route mapping Honest gap from the audit: the parity_test.go suite only checks four methods, and uses the same httpapi.Client for both sides — it asserts stability of the DTO shapes, not equivalence between in-process and HTTP. If a contributor adds an admin REST endpoint without an MCP tool, or a tool without a matching httpapi route, both surfaces silently diverge. Add a coverage test plus stronger docs: - pkg/mcp/localaitools/coverage_test.go introduces a hand-maintained toolToHTTPRoute map: every Tool* constant must list the REST endpoint the httpapi.Client hits (or "(none)" with a documented reason). Two Ginkgo specs assert the map and the published catalog stay in sync — one fails when a Tool is added without a route entry, the other fails when a route entry references a tool that no longer exists. Verified by removing the ToolDeleteModel entry locally; the test fired with a clear message pointing the contributor at the file. Deliberate non-test: we don't enumerate live admin REST routes from here. Walking the route registry requires booting Application; parsing core/http/routes/localai.go is brittle. The "new admin REST endpoint → MCP tool" direction stays a PR checklist item — see below. - AGENTS.md gets a new Quick Reference bullet that calls out the rule and points at the test by name. - .agents/api-endpoints-and-auth.md tightens the existing "Companion: MCP admin tool surface" subsection from "if useful, consider..." to "MUST be considered, with three concrete outcomes (tool added, deliberately skipped with documented reason, or forgot — which breaks the contract)". Adds a checklist item at the bottom of the file's authoritative checklist. Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(assistant): drop duplicate DTOs, surface canonical types Audit feedback: localaitools/dto.go reinvented several types that already existed in the codebase. Replace the duplicates with the canonical types so the LLM-visible wire format stays aligned with the rest of LocalAI by construction (no parallel structs to keep in sync). Removed (and the canonical type now used by the LocalAIClient interface): localaitools.Gallery → config.Gallery localaitools.GalleryModelHit → gallery.Metadata localaitools.VRAMEstimate → vram.EstimateResult Tightened scope: localaitools.Backend → kept, but reduced to {Name, Installed}. ListKnownBackends now returns []schema.KnownBackend (the canonical type already used by REST /backends/known). Kept with documented rationale: localaitools.JobStatus — galleryop.OpStatus has Error error which marshals to "{}". JobStatus is the JSON-friendly mirror. localaitools.Node — nodes.BackendNode carries gorm internals + token hash; we expose only the LLM-relevant fields. ImportModelURIRequest/Response — schema.ImportModelRequest and GalleryResponse are wire-shaped, mine are LLM-shaped (BackendPreference flat, AmbiguousBackend exposed). Side wins: - Drop bytesPerMiB; vram.EstimateResult already carries human-readable display strings (size_display, vram_display) the LLM uses directly. - Drop the handler-private vramEstimateRequest in core/http/endpoints/localai/vram.go and bind directly into modeladmin.VRAMRequest (now JSON-tagged). Both clients pass through these types now where possible (e.g. ListGalleries in inproc.Client is a one-liner returning AppConfig.Galleries; httpapi.Client.GallerySearch decodes straight into []gallery.Metadata). All tests green with -race. Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(assistant): extract REST route paths into named constants httpapi.Client had 18 bare-string path sites scattered across methods. Pull them into pkg/mcp/localaitools/httpapi/routes.go: static paths as package-private constants, dynamic paths as small builders that handle url.PathEscape on segment values. No behaviour change. Drops the now-unused net/url import from client.go since path escaping moved into routes.go alongside the path it applies to. Local-only by design: the server-side registrations in core/http/routes/localai.go remain bare strings. Sharing constants across the pkg/ ↔ core/ boundary would invert the layering today; the existing Tool↔REST drift-detector in coverage_test.go is the safety net for that direction. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-7 [Claude Code] * docs(assistant): align with shipped UI and dropped bootstrap env vars The LocalAI Assistant doc still described the older iteration: - The in-chat toggle was renamed from "Admin" to "Manage" (the badge is now "Manage mode" and the home page exposes a "Manage by chat" CTA). - LOCALAI_ASSISTANT_BOOTSTRAP_MODEL / --localai-assistant-bootstrap-model and the bootstrap_default_model tool were removed — admins pick a model from the existing selector instead, no env-var configuration required. - The shipped tool catalog includes import_model_uri but didn't appear in the doc; bootstrap_default_model appeared but no longer exists. - The Settings → LocalAI Assistant runtime toggle wasn't mentioned as the preferred way to disable without restart. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:claude-opus-4-7 [Claude Code] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>	2026-04-28 19:29:27 +02:00
Ettore Di Giacinto	4906cbad04	feat: add biometrics UI (#9524) ... * feat(react-ui): add Face & Voice Recognition pages Expose the face and voice biometrics endpoints (/v1/face/*, /v1/voice/*) through the React UI. Each page has four tabs driving the six endpoints per modality: Analyze (demographics with bounding boxes / waveform segments), Compare (verify with a match gauge and live threshold slider), Enrollment (register / identify / forget with a top-K matches view), Embedding (raw vector inspector with sparkline + copy). MediaInput supports file upload plus live capture: webcam snap-to-canvas for face, MediaRecorder -> AudioContext -> 16-bit PCM mono WAV transcode for voice (libsndfile on the backend only handles WAV/FLAC/OGG natively). Sidebar gets a new Biometrics section feature-gated on face_recognition / voice_recognition; routes are wrapped in <RequireFeature>. No new dependencies -- Font Awesome icons picked from the Free set. Assisted-by: Claude:Opus 4.7 * fix(localai): accept data URI prefixes with codec/charset params Browser MediaRecorder produces data URIs like data:audio/webm;codecs=opus;base64,... so the pre-';base64,' section can carry multiple parameter segments. The `^data:([^;]+);base64,` regex in pkg/utils/base64.go and core/http/endpoints/localai/audio.go only matched exactly one segment, so recordings straight from the React UI's live-capture tab failed the strip and then tripped the base64 decoder on the leading 'data:' literal, surfacing as "invalid audio base64: illegal base64 data at input byte 4" Widened both regexes to `^data:[^,]+?;base64,` so any number of ';param=value' segments between the mime type and ';base64,' are tolerated. Added a regression test covering the MediaRecorder shape. Assisted-by: Claude:Opus 4.7 * fix(insightface): scope pack ONNX loading to known manifests LocalAI's gallery extracts buffalo_* zips flat into the models directory, which inevitably mixes with ONNX files from other backends (opencv face engine, MiniFASNet antispoof, WeSpeaker voice embedding) and older buffalo pack installs. Feeding those foreign files into insightface's model_zoo.get_model() blows up inside the router -- it assumes a 4-D NCHW input and indexes `input_shape[2]` on tensors that aren't shaped like a face model, raising IndexError mid-load and leaving the backend unusable. The router's dispatch isn't amenable to per-file try/except alone (first-file-wins picks det_10g.onnx from buffalo_l even when the user asked for buffalo_sc -- alphabetical order happens to favour the wrong pack). Instead, ship an explicit manifest of the upstream v0.7 pack contents and scope the glob to that when the requested pack is known. The manifest is small and stable; future packs can be added alongside or fall through to the tolerance loop, which also swallows any remaining IndexError / ValueError from foreign files with a clear `[insightface] skipped` stderr line for diagnostics. Assisted-by: Claude:Opus 4.7 * fix(speaker-recognition): extract FBank features for rank-3 ONNX encoders Pre-exported speaker-encoder ONNX graphs come in two shapes: rank-2 [batch, samples] -- some 3D-Speaker exports, take raw waveform directly. rank-3 [batch, frames, n_mels] -- WeSpeaker and most Kaldi- lineage encoders, expect pre-computed Kaldi FBank. OnnxDirectEngine unconditionally fed `audio.reshape(1, -1)` -- correct for rank-2, IndexError-on-input_shape[3] on rank-3, which surfaced to the UI as "Invalid rank for input: feats Got: 2 Expected: 3" Detect the input rank at session init and run Kaldi FBank (80-dim, 25ms/10ms frames, dither=0.0, per-utterance CMN) before the forward pass when rank>=3. All knobs are configurable via backend options for encoders that deviate from defaults. torchaudio.compliance.kaldi is already in the backend's requirements (SpeechBrain pulls torchaudio in), so no new dependency. Assisted-by: Claude:Opus 4.7 * fix(biometrics): isolate face and voice vector stores Face (ArcFace, 512-D) and voice (ECAPA-TDNN 192-D / WeSpeaker 256-D) biometric embeddings were colliding inside a single in-memory local-store instance. Enrolling one after the other failed with "Try to add key with length N when existing length is M" because local-store correctly refuses to mix dimensions in one keyspace. The registries were constructed with `storeName=""`, which in StoreBackend() is just a WithModel() call. But ModelLoader's cache is keyed on `modelID`, not `model` -- so both registries collapsed to the same `modelID=""` slot and reused the same backend process despite looking isolated on paper. Three complementary fixes: 1. application.go -- give each registry a distinct default namespace ("localai-face-biometrics" / "localai-voice-biometrics"). The comment claimed isolation, now it's actually enforced. 2. stores.go -- pass the storeName as both WithModelID and WithModel so the ModelLoader cache key separates namespaces and the loader spawns distinct processes. 3. local-store/store.go -- drop the Load() `opts.Model != ""` guard. It was there to prevent generic model-loading loops from picking up local-store by accident, but that auto-load path is being retired; the guard now just blocks legitimate namespace isolation. opts.Model is treated as a tag; the per-tuple process isolation upstream handles discrimination. Assisted-by: Claude:Opus 4.7 * fix(gallery): stale-file cleanup and upgrade-tmp directory safety Two related robustness fixes for backend install/upgrade: pkg/downloader/uri.go OCI downloads passed through if filepath.Ext(filePath) != "" ... filePath = filepath.Dir(filePath) which was intended to redirect file-shaped download targets into their parent directory for OCI extraction. The heuristic misfires on directory-shaped paths with a dot-suffix -- gallery.UpgradeBackend uses tmpPath = "<backendsPath>/<name>.upgrade-tmp" and Go's filepath.Ext treats ".upgrade-tmp" as an extension. The rewrite landed the extraction at "<backendsPath>/", which then **overwrote the real install** (backends/<name>/) with a flat-layout file and left a stray run.sh at the top level. The tmp dir itself stayed empty, so the validation step that checked "<tmpPath>/run.sh" predictably failed with "upgrade validation failed: run.sh not found in new backend" Every manual upgrade silently corrupted the backends tree this way. Guard the rewrite behind "target isn't already an existing directory" -- InstallBackend / UpgradeBackend both pre-create the target as a directory, so they get the correct behaviour; existing file-path callers with a genuine dot-extension still get the parent redirect. core/gallery/backends.go InstallBackend's MkdirAll returned ENOTDIR when something at the target path was already a file (legacy dev builds dropped golang backend binaries directly at `<backendsPath>/<name>` instead of nesting them under their own subdir). That permanently blocked reinstall and upgrade for anyone carrying that state, since every retry hit the same error. Detect a pre-existing non-directory, warn, and remove it before the MkdirAll so the fresh install can write the correct nested layout with metadata.json + run.sh. Assisted-by: Claude:Opus 4.7 * fix(galleryop): refresh upgrade cache after backend ops UpgradeChecker caches the last upgrade-check result and only refreshes on the 6-hour tick or after an auto-upgrade cycle. Manual upgrades (POST /api/backends/upgrade/:name) go through the async galleryop worker, which completes the upgrade correctly but never tells UpgradeChecker to re-check -- so /api/backends/upgrades continued to list a just-upgraded backend as upgradeable, indistinguishable from a failed upgrade, for up to six hours. Add an optional `OnBackendOpCompleted func()` hook on GalleryService that fires after every successful install / upgrade / delete on the backend channel (async, so a slow callback doesn't stall the queue). startup.go wires it to UpgradeChecker.TriggerCheck after both services exist. Result: the upgrade banner clears within milliseconds of the worker finishing. Assisted-by: Claude:Opus 4.7 * build: prepend GOPATH/bin to PATH for protogen-go install-go-tools runs `go install` for protoc-gen-go and protoc-gen-go-grpc, which writes them into `go env GOPATH`/bin. That directory isn't on every dev's PATH, and protoc resolves its code-gen plugins via PATH, so the immediately-following protoc invocation fails with "protoc-gen-go: program not found" which in turn blocks `make build` and any `make backends/%` target that depends on build. Prepend `go env GOPATH`/bin to PATH for the protoc invocation so the freshly-installed plugins are found without requiring a shell-profile change. Assisted-by: Claude:Opus 4.7 * refactor(ui-api): non-blocking backend upgrade handler with opcache POST /api/backends/upgrade/:name used to send the ManagementOp directly onto the unbuffered BackendGalleryChannel, which blocked the HTTP request whenever the galleryop worker was busy with a prior operation. The op also didn't show up in /api/operations, so the Backends UI couldn't reflect upgrade progress on the affected row. Register the op in opcache immediately, wrap it in a cancellable context, store the cancellation function on the GalleryService, and push onto the channel from a goroutine so the handler returns right away. Response gains a `jobID` field and a `message` string so clients have a consistent handle regardless of whether the op is queued or running. Pairs with the OnBackendOpCompleted hook added in the galleryop commit — together the UI sees the upgrade start, watches progress via /api/operations, and drops the "upgradeable" flag the moment the worker finishes. Assisted-by: Claude:Opus 4.7	2026-04-24 08:50:34 +02:00
Ettore Di Giacinto	181ebb6df4	feat: voice recognition (#9500) ... * feat(voice-recognition): add /v1/voice/{verify,analyze,embed} + speaker-recognition backend Audio analog to face recognition. Adds three gRPC RPCs (VoiceVerify / VoiceAnalyze / VoiceEmbed), their Go service and HTTP layers, a new FLAG_SPEAKER_RECOGNITION capability flag, and a Python backend scaffold under backend/python/speaker-recognition/ wrapping SpeechBrain ECAPA-TDNN with a parallel OnnxDirectEngine for WeSpeaker / 3D-Speaker ONNX exports. The kokoros Rust backend gets matching unimplemented trait stubs — tonic's async_trait has no defaults, so adding an RPC without Rust stubs breaks the build (same regression fixed by eb01c772 for face). Swagger, /api/instructions, and the auth RouteFeatureRegistry / APIFeatures list are updated so the endpoints surface everywhere a client or admin UI looks. Assisted-by: Claude:claude-opus-4-7 * feat(voice-recognition): add 1:N identify + register/forget endpoints Mirrors the face-recognition register/identify/forget surface. New package core/services/voicerecognition/ carries a Registry interface and a local-store-backed implementation (same in-memory vector-store plumbing facerecognition uses, separate instance so the embedding spaces stay isolated). Handlers under /v1/voice/{register,identify,forget} reuse backend.VoiceEmbed to compute the probe vector, then delegate the nearest-neighbour search to the registry. Default cosine-distance threshold is tuned for ECAPA-TDNN on VoxCeleb (0.25, EER ~1.9%). As with the face registry, the current backing is in-memory only — a pgvector implementation is a future constructor-level swap. Assisted-by: Claude:claude-opus-4-7 * feat(voice-recognition): gallery, docs, CI and e2e coverage - backend/index.yaml: speaker-recognition backend entry + CPU and CUDA-12 image variants (plus matching development variants). - gallery/index.yaml: speechbrain-ecapa-tdnn (default) and wespeaker-resnet34 model entries. The WeSpeaker SHA-256 is a deliberate placeholder — the HF URI must be curl'd and its hash filled in before the entry installs. - docs/content/features/voice-recognition.md: API reference + quickstart, mirrors the face-recognition docs. - React UI: CAP_SPEAKER_RECOGNITION flag export (consumers follow face's precedent — no dedicated tab yet). - tests/e2e-backends: voice_embed / voice_verify / voice_analyze specs. Helper resolveFaceFixture is reused as-is — the only thing face/voice share is "download a file into workDir", so no need for a new helper. - Makefile: docker-build-speaker-recognition + test-extra-backend- speaker-recognition-{ecapa,all} targets. Audio fixtures default to VCTK p225/p226 samples from HuggingFace. - CI: test-extra.yml grows a tests-speaker-recognition-grpc job mirroring insightface. backend.yml matrix gains CPU + CUDA-12 image build entries — scripts/changed-backends.js auto-picks these up. Assisted-by: Claude:claude-opus-4-7 * feat(voice-recognition): wire a working /v1/voice/analyze head Adds AnalysisHead: a lazy-loading age / gender / emotion inference wrapper that plugs into both SpeechBrainEngine and OnnxDirectEngine. Defaults to two open-licence HuggingFace checkpoints: - audeering/wav2vec2-large-robust-24-ft-age-gender (Apache 2.0) — age regression + 3-way gender (female / male / child). - superb/wav2vec2-base-superb-er (Apache 2.0) — 4-way emotion. Both are optional and degrade gracefully when transformers or the model can't be loaded — the engine raises NotImplementedError so the gRPC layer returns 501 instead of a generic 500. Emotion classes pass through from the model (neutral/happy/angry/sad on the default checkpoint); the e2e test now accepts any non-empty dominant gender so custom age_gender_model overrides don't fail it. Adds transformers to the backend's CPU and CUDA-12 requirements. Assisted-by: Claude:claude-opus-4-7 * fix(voice-recognition): pin real WeSpeaker ResNet34 ONNX SHA-256 Replaces the placeholder hash in gallery/index.yaml with the actual SHA-256 (7bb2f06e…) of the upstream Wespeaker/wespeaker-voxceleb-resnet34-LM ONNX at ~25MB. `local-ai models install wespeaker-resnet34` now succeeds. Assisted-by: Claude:claude-opus-4-7 * fix(voice-recognition): soundfile loader + honest analyze default Two issues surfaced on first end-to-end smoke with the actual backend image: 1. torchaudio.load in torchaudio 2.8+ requires the torchcodec package for audio decoding. Switch SpeechBrainEngine._load_waveform to the already-present soundfile (listed in requirements.txt) plus a numpy linear resample to 16kHz. Drops a heavy ffmpeg-linked dep and the codepath we never exercise (torchaudio's ffmpeg backend). 2. The AnalysisHead was defaulting to audeering/wav2vec2-large-robust- 24-ft-age-gender, but AutoModelForAudioClassification silently mangles that checkpoint — it reports the age head weights as UNEXPECTED and re-initialises the classifier head with random values, so the "gender" output is noise and there is no age output at all. Make age/gender opt-in instead (empty default; users wire a cleanly-loadable Wav2Vec2ForSequenceClassification checkpoint via age_gender_model: option). Emotion keeps its working Superb default. Also broaden _infer_age_gender's tensor-shape handling and catch runtime exceptions so a dodgy age/gender head never takes down the whole analyze call. Docs and README updated to match the new policy. Verified with the branch-scoped gallery on localhost: - voice/embed → 192-d ECAPA-TDNN vector - voice/verify → same-clip dist≈6e-08 verified=true; cross-speaker dist 0.76–0.99 verified=false (as expected) - voice/register/identify/forget → round-trip works, 404 on unknown id - voice/analyze → emotion populated, age/gender omitted (opt-in) Assisted-by: Claude:claude-opus-4-7 * fix(voice-recognition): real CI audio fixtures + fixture-agnostic verify spec Two issues surfaced after CI actually ran the speaker-recognition e2e target (I'd curl-tested against a running server but hadn't run the make target locally): 1. The default BACKEND_TEST_VOICE_AUDIO_* URLs pointed at huggingface.co/datasets/CSTR-Edinburgh/vctk paths that return 404 (the dataset is gated). Swap them for the speechbrain test samples served from github.com/speechbrain/speechbrain/raw/develop/ — public, no auth, correct 16kHz mono format. 2. The VoiceVerify spec required d(file1,file2) < 0.4, assuming file1/file2 were same-speaker. The speechbrain samples are three different speakers (example1/2/5), and there is no easy un-gated source of true same-speaker audio pairs (VoxCeleb/VCTK/LibriSpeech are all license- or size-gated for CI use). Replace the ceiling check with a relative-ordering assertion: d(pair) > d(same-clip) for both file2 and file3 — that's enough to prove the embeddings encode speaker info, and it works with any three non-identical clips. Actual speaker ordering d(1,2) vs d(1,3) is logged but not asserted. Local run: 4/4 voice specs pass (Health, LoadModel, VoiceEmbed, VoiceVerify) on the built backend image. 12 non-voice specs skipped as expected. Assisted-by: Claude:claude-opus-4-7 * fix(ci): checkout with submodules in the reusable backend_build workflow The kokoros Rust backend build fails with failed to read .../sources/Kokoros/kokoros/Cargo.toml: No such file because the reusable backend_build.yml workflow's actions/checkout step was missing `submodules: true`. Dockerfile.rust does `COPY . /LocalAI`, and without the submodule files the subsequent `cargo build` can't find the vendored Kokoros crate. The bug pre-dates this PR — scripts/changed-backends.js only triggers the kokoros image job when something under backend/rust/kokoros or the shared proto changes, so master had been coasting past it. The voice-recognition proto addition re-broke it. Other checkouts in backend.yml (llama-cpp-darwin) and test-extra.yml (insightface, kokoros, speaker-recognition) already pass `submodules: true`; this brings the shared backend image builder in line. Assisted-by: Claude:claude-opus-4-7	2026-04-23 12:07:14 +02:00