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fix/distributed-companion-path
984 Commits
| Author | SHA1 | Message | Date | |
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Ettore Di Giacinto
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1df5a3ef7f |
fix(model-artifacts): keep the companion option present on a remote load, even unresolved
Follow-up to the companion-persistence fix. On a live distributed cluster the managed base_model companion option still failed to reach the remote worker (nvidia-thor) even with the companion resolved-and-persisted in the config: the backend logged "Downloading required files for meituan-longcat/LongCat-Video" and failed "base_model must point to a LongCat-Video checkpoint". Symlinking the companion into place did not help (the option was simply absent from the worker's LoadModel), while an explicit absolute base_model in options: worked as a control. Trace of where the remote ModelOptions is built and whether the companion is present there: - The *pb.ModelOptions the worker's LoadModel consumes is built on the CONTROLLER by grpcModelOpts (core/backend/options.go) -> withCompanionArtifactOptions, set as gRPCOptions, and sent by direct gRPC via FileStagingClient.LoadModel. It is NOT rebuilt on the worker. The reconciler's replica scale-up instead replays a Postgres-stored proto blob, which already carries whatever grpcModelOpts produced. - withCompanionArtifactOptions is the ONLY builder of ModelOptions.Options in the tree, and it emits base_model iff the config's companion artifact has Resolved != nil. Staging preserves the option and derives the worker ModelPath as the nested per-model staged root, so a resolved companion resolves under it without a download (verified end to end; the path-nesting angle is a red herring here). So the option is absent only when the config the loader is serving from carries the companion WITHOUT a resolved snapshot (its resolved state not reaching the serving config, e.g. a peer-replica reload from local disk or a config loaded before resolution). In that state the old code emitted NOTHING for the companion, and longcat-video fell back to its OWN hardcoded default (BASE_MODEL_ID), which is exactly the observed download-and-fail. Fix: an unresolved-but-declared companion no longer vanishes. It now falls back to its DECLARED source repository id, so the backend fetches the artifact the config actually asked for instead of a hardcoded default; the resolved snapshot path (the staged, no-download fast path) is still preferred whenever the companion is resolved, so the single-node and healthy distributed paths are unchanged. The fallback logs a warning naming the artifact and repo, and the router now logs the exact option strings crossing to the worker at debug, so a recurrence is diagnosable in one load instead of by inference. Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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Ettore Di Giacinto
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bb2ed02cca |
fix(model-artifacts): persist companion artifacts, not just the primary
A managed model can declare companion artifacts (LongCat-Video-Avatar-1.5
pulls its tokenizer, text encoder and VAE from the separate LongCat-Video
base repo via a target: companion artifact). preloadOne resolves the whole
set in memory, but the binding written back to disk carried only the
primary: persistArtifactBinding marshalled []Spec{result.Spec} and replaced
the entire artifacts: list with it, silently dropping every companion.
In a single process the loss is invisible because the in-memory config keeps
the companion. It bites on the next controller restart: the config reloads
from the mangled file with the primary alone, so withCompanionArtifactOptions
finds no resolved companion and synthesizes no base_model option. The remote
longcat-video backend then never receives base_model, falls back to
BASE_MODEL_ID and downloads the repo itself ("Downloading required files for
meituan-longcat/LongCat-Video"), failing the load with "base_model must point
to a LongCat-Video checkpoint".
This is why an explicit base_model:<path> added to the config options works
where the managed companion does not: an explicit option lives in options:,
which is never rewritten, while the managed companion lives in artifacts:,
which the binding overwrote.
Persist the full resolved set (primary + every companion), and widen
bindingNeedsPersistence to compare the whole artifact list so a companion
resolving for the first time still triggers a write. The single-node path is
unaffected: there the in-memory config already carried the companion, and the
staging/ModelPath resolution for a remote worker (nested per-model staged
root, #10949) is unchanged and already correct once the option is generated.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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mudler's LocalAI [bot]
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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>
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mudler's LocalAI [bot]
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f317da7c0f |
fix(galleryop): make admitted operations queryable and survive a failed op (#11044)
Two lifecycle defects observed on a 2-replica distributed cluster. The install endpoints mint a job UUID, hand the operation to an unbuffered channel, and answer HTTP 200 immediately. The gallery worker is a single goroutine that processes operations serially, and the first status write happens inside modelHandler/backendHandler — i.e. only once the worker actually starts the work. An operation queued behind a running install therefore had no status at all: GET /models/jobs/<uuid> answered "could not find any status for ID" and GET /models/jobs did not list it, so the endpoint reported success for work nothing could observe. On the paths that sent directly rather than from a goroutine, the same unbuffered channel blocked the HTTP handler for the whole duration of the in-flight install, which is how a replica came to accept no /models/apply at all while /readyz stayed green. Admission now goes through EnqueueModelOp/EnqueueBackendOp, which publish a "queued" status before handing the operation over, so a job ID is queryable from the instant it is handed out. Delivery selects on the operation's context, so cancelling a still-queued operation releases the delivery goroutine instead of stranding it on a send that will never be received, and an operation the worker never accepts becomes a terminal failure rather than a silent leak. The worker also had no panic containment. A panic in any handler propagated out of the single consumer goroutine and killed the process, taking every queued operation with it; it is now contained to the operation that caused it. The two ignored galleryStore.Create errors are logged, and the model and backend delete endpoints now run under the same ID they hand back — they previously ran under an empty ID and returned a status URL for a job that could never have a status. Second, an operation orphaned by a controller replaced mid-download kept reporting phase=downloading, processed=false, error=none while nothing was downloading. The PostgreSQL side does recover on its own (FindDuplicate ignores rows untouched for 30 minutes and CleanStale marks them failed), but the reaper only ever corrected the database. The in-memory statuses map that GET /models/jobs/<id> and /api/operations actually read was never corrected, so every replica kept serving the frozen tick indefinitely. ReapStaleOperations now reconciles the in-memory copy with the reap. Note that operation ownership is still not tracked: gallery_operations has a FrontendID column that nothing writes, so a live operation and one whose owner died are distinguished only by a 30-minute staleness timeout. Narrowing that window needs a lease/heartbeat mechanism and is out of scope here. Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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ff299df453 |
perf(http): gzip responses, cache hashed assets, bound the trace endpoints (#11056)
Three measured HTTP-layer regressions on a live deployment, fixed together
because they all shape the bytes on the wire.
1. No compression. The server sent no Content-Encoding regardless of what
the client asked for, confirmed with curl straight at 127.0.0.1:8080 so
it was not an ingress artefact. Adds gzip middleware, on by default and
configurable via LOCALAI_DISABLE_HTTP_COMPRESSION and
LOCALAI_HTTP_COMPRESSION_MIN_LENGTH (default 1024 bytes so tiny bodies
are not wastefully wrapped). Streaming routes are skipped explicitly:
an SSE Accept header, a WebSocket upgrade, and the completion / SSE /
log-tail path prefixes, because whether a completion request streams is
decided by the request body, which the middleware runs too early to see.
Already-compressed formats (woff2, png, mp4, ...) are skipped too; gzip
made those marginally larger. Measured over the embedded React build:
JS+CSS 2815 KB raw to 808 KB gzipped (3.48x).
2. No cache headers on content-hashed assets. Vite hashes the filenames,
so a given /assets/ URL can never change content, yet they shipped with
no Cache-Control, ETag or Last-Modified, and the browser re-fetched the
whole bundle on every navigation with no conditional request available.
/assets/* now carries public, max-age=31536000, immutable. index.html
stays no-cache so a deploy is picked up, and the unhashed locale JSONs
get a short TTL rather than the immutable one.
3. Unbounded trace endpoints. /api/traces returned 21,033,606 bytes in
4.65s and /api/backend-traces 3,471,682 bytes in 1.50s, and the admin
UI polls both every few seconds. The ring buffer holds up to 1024
entries, each embedding full input_text payloads. Both list endpoints
now take limit / offset / full, default to 50 entries, and strip the
heavy fields (request and response bodies plus headers for API traces,
body and data for backend traces) unless full=true. Every trace gets a
process-lifetime ID and GET /api/traces/{id} and
/api/backend-traces/{id} serve the full record, which is what the UI
fetches when a row is expanded. The list body stays a JSON array;
paging metadata rides in X-Total-Count, X-Trace-Offset and
X-Trace-Limit. Reproducing the live shape in a test, the polled payload
goes from 21,131,097 bytes to 7,201 bytes.
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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mudler's LocalAI [bot]
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248e1ef9a2 |
fix(worker): never reuse a backend process whose directory a reinstall replaced (#11029)
A backend reinstall could poison every subsequent model load on a worker
node until the worker process was restarted.
gallery.InstallBackend (and gallery.UpgradeBackend) replace a backend by
renaming the live directory to `<name>.install-backup`, moving the staged
directory into place, then deleting the backup. A working directory
follows the inode across a rename, so a backend process that outlives
that swap ends up with a deleted inode as its CWD, and every getcwd(2)
in it fails with ENOENT.
Observed on a Jetson Thor worker in distributed mode after two
successive reinstalls of cuda13-nvidia-l4t-arm64-longcat-video-development.
A later model load failed with:
rpc error: code = Internal desc = failed to load LongCat model: [Errno 2] No such file or directory
The backend's own traceback shows it dying while importing torch, before
touching any model file:
backend.py line 142 in LoadModel
backend.py line 300 in _import_torch
torch/_library/custom_ops.py lib._register_fake(...)
torch/library.py:183 caller_module = inspect.getmodule(frame)
inspect.py:1013 f = getabsfile(module)
inspect.py:983 return os.path.normcase(os.path.abspath(_filename))
<frozen posixpath>, line 415, in abspath
FileNotFoundError: [Errno 2] No such file or directory
os.path.abspath calls os.getcwd() for a relative path. Scanning /proc
inside the worker container found the deleted CWD directly:
pid 23467 CWD DELETED: /backends/cuda13-nvidia-l4t-arm64-longcat-video-development.install-backup (deleted)
Restarting the worker container cleared it (dead CWD count 1 -> 0).
Python backends import torch lazily inside LoadModel, so such a survivor
still answers HealthCheck and keeps its gRPC port. It looks healthy and
only detonates when a model is actually loaded through it.
The install paths already stop running processes before replacing the
directory (installBackend's force branch, upgradeBackend, backend.delete),
but they resolve them by name. That bookkeeping reaps nothing whenever
the recorded name no longer resolves into the install's identity set: a
legacy entry with an empty backendName, backendIdentity degraded to
name-only matching after a ListSystemBackends failure, or an earlier
reinstall having already rewritten the metadata.json that carries the
alias. Any of those leaves a live process whose directory is about to be
unlinked, and nothing downstream notices, because the reuse gate checks
liveness and name -- and the name is precisely what does not change
across a reinstall.
Record the directory each supervised process runs out of, plus that
directory's identity at spawn time, and compare with os.SameFile before
reusing the process. This needs none of the name bookkeeping to have
been correct. Both reuse gates are covered: processMatchesBackend (the
install fast path) and startBackend's own already-running branch, which
now force-stops such a survivor so the fresh spawn chdirs into the newly
installed directory. Processes with no recorded directory are accepted,
so a rollout does not restart every running backend once.
This matters more with #11024 pending: making GPU backends visible to
the upgrade checker will have AutoUpgradeBackends fan upgrades out to
worker nodes at scale, and every one of those is a reinstall. Left as
is, a rare manual-upgrade footgun becomes a fleet-wide one.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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mudler's LocalAI [bot]
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7a8db9b1f1 |
fix(ollama): set ContextSize via the embedded LLMConfig so the package builds (#11049)
The num_ctx clamping specs added in #11032 construct their fixture with
`config.ModelConfig{ContextSize: &existing}`, but ContextSize is not a
direct field of ModelConfig: it belongs to LLMConfig, which ModelConfig
embeds inline. Go allows reading a promoted field but not setting one in
a composite literal, so the test file has never compiled:
helpers_internal_test.go:33:31: unknown field ContextSize in struct
literal of type "github.com/mudler/LocalAI/core/config".ModelConfig
This broke `make lint` on master from
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dependabot[bot]
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f92410b20b |
chore(deps): bump fast-uri from 3.1.2 to 3.1.4 in /core/http/react-ui in the npm_and_yarn group across 1 directory (#11043)
chore(deps): bump fast-uri Bumps the npm_and_yarn group with 1 update in the /core/http/react-ui directory: [fast-uri](https://github.com/fastify/fast-uri). Updates `fast-uri` from 3.1.2 to 3.1.4 - [Release notes](https://github.com/fastify/fast-uri/releases) - [Commits](https://github.com/fastify/fast-uri/compare/v3.1.2...v3.1.4) --- updated-dependencies: - dependency-name: fast-uri dependency-version: 3.1.4 dependency-type: indirect dependency-group: npm_and_yarn ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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mudler's LocalAI [bot]
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54f531f452 |
fix(mcp): bound MCP session connect so an unreachable server can't hang the widget (#10880) (#10884)
Establishing an MCP session held the session-cache mutex across client.Connect with no per-connect timeout. An unreachable remote server (bounded only by the 360s httpClient timeout) or a stdio server whose initialize handshake never completes therefore blocked the caller and, because the mutex was held, every other MCP request for that model too. In the UI this shows up as the MCP "Servers" widget spinning forever. It is most visible for cloud-proxy models: their chat path bails out before the MCP tool block, so it never warms the session cache in the background. The widget's /v1/mcp/servers/<model> call is then the first and only code that connects synchronously, in the request foreground. The session, once established, stays bound to the shared context (it is cancelled later via the cached cancel func on eviction/shutdown), so we can't pass a WithTimeout context to Connect: firing the timeout would tear a healthy session down, and cancelling the shared context would also kill sibling servers that already connected. Instead connectMCP runs Connect on the shared context in a goroutine and stops waiting after the discovery timeout, returning an error for that one server without disturbing the others. A stalled goroutine is reaped when the model's sessions are cancelled. Applied to both SessionsFromMCPConfig and NamedSessionsFromMCPConfig. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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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>
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Tai An
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d7020708f2 |
fix(completions): reject empty PromptStrings in streaming to avoid index-out-of-range panic (#11028)
* fix(completions): reject empty PromptStrings in streaming to avoid index-out-of-range panic The streaming branch of CompletionEndpoint only guarded len(config.PromptStrings) > 1 before unconditionally reading config.PromptStrings[0]. A completion request whose prompt field is an empty array, an array of non-strings, or omitted leaves PromptStrings with length 0, so PromptStrings[0] panics with index out of range and crashes the handler goroutine. Guard for exactly one prompt string instead, returning a clean error for the 0-length case as well as the pre-existing multi-prompt case. Signed-off-by: Tai An <antai12232931@outlook.com> * fix(completions): return 400 for malformed streaming prompt Reject streaming completion requests whose prompt does not resolve to exactly one string (omitted prompt, empty array, or a multi-element array) with an HTTP 400 before writing any SSE headers, instead of returning a plain error that Echo surfaces as a 500. Extract the guard into validateStreamingPromptStrings and cover the three reported payloads with a regression test. Fixes #11021 Signed-off-by: Tai An <antai12232931@outlook.com> --------- Signed-off-by: Tai An <antai12232931@outlook.com> |
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Tai An
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bf19758e05 |
fix(ollama): cap num_ctx so it cannot wrap negative when cast to int32 (#11032)
* fix(ollama): cap num_ctx so it cannot wrap negative when cast to int32 applyOllamaOptions copied a client-supplied options.num_ctx straight into cfg.ContextSize with only a > 0 check. That value is later cast to int32 before it reaches the backend (core/backend/options.go), so a num_ctx above math.MaxInt32 silently wrapped into a negative context size that was then sent to the LoadModel gRPC call. Both /api/chat and /api/generate share applyOllamaOptions, so both endpoints were affected. Cap num_ctx at math.MaxInt32 so the later cast stays positive, and add internal regression coverage for the overflow, in-range, and unset cases. num_ctx remains an intentional user override, so this does not re-impose the hardware-aware auto context clamp; that policy choice is left to maintainers. Fixes #11022 Signed-off-by: Tai An <antai12232931@outlook.com> * fix(ollama): clamp num_ctx to model context ceiling, not just int32 Per review on #11032: capping only at math.MaxInt32 still let an unauthenticated request replace the hardware/model-derived context limit with ~2.1B tokens, so a real backend could attempt a catastrophic KV-cache allocation. Treat any existing positive cfg.ContextSize as the server ceiling and clamp num_ctx down to it (smaller values still honored), while retaining the int32-safe bound when no smaller ceiling exists. Shared by /api/chat and /api/generate via applyOllamaOptions. Add regression coverage proving num_ctx=2,000,000,000 cannot replace an existing 4096/8192 ceiling. Signed-off-by: Tai An <antai12232931@outlook.com> --------- Signed-off-by: Tai An <antai12232931@outlook.com> |
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mudler's LocalAI [bot]
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a4a181d2f7 |
fix(distributed): count staging verification as progress, not as a stall (#11026)
Testing the progress-based cold-load deadline on the live cluster surfaced a false positive. The stall window observed UPLOAD bytes only, but the staging path has a phase that does real work while moving zero upload bytes: the resumable-upload verify phase. When a shard is already present on the worker from an earlier attempt, the frontend HEADs it, hashes the local copy to confirm it matches, and skips the transfer. Staging a 70 GB model with 56 GB already staged: 17:27:34 INFO Upload skipped (file already exists with matching hash) ... 17:28:20 INFO Upload skipped (file already exists with matching hash) ... 17:29:07 INFO Upload skipped (file already exists with matching hash) ... ... six-plus consecutive minutes, no bytes uploaded at all ~45s per skipped ~4 GB shard. That is correct and desirable - it is what makes resume work - but it was indistinguishable from a stall. At 45s per shard it sits inside the 5m window, so the run in flight was fine; the problem is the 600 GB scale this machinery exists to enable, where one shard can plausibly hash for longer than the window. The guard would then fire during verification of a transfer that is working perfectly. Verified mechanism: probeExisting() HEADs the worker and then calls downloader.CalculateSHA(). The staging progress callback is only consulted inside doUpload(), which the skip path never reaches, so observeLoadProgress was called zero times for the whole verify phase. Verification exposed a second, worse bug in the same path: CalculateSHA consults no context at all. An expired cold load kept hashing to completion, compared the hashes, and returned success - reporting a file as staged on a dead load. The failure only surfaced on the NEXT file, whose HEAD died immediately. That is exactly the shape of the red test here, which fails on shard 3. Fix: hash in 1 MiB chunks via hashFileWithActivity(), ticking the cold-load deadline per chunk and checking ctx per chunk. A successful HEAD also counts, since a 200 with a content hash proves the worker is serving right now. Counting hash progress does not make a dead transfer look alive: hashing is bounded, terminating work proportional to file size, in probeExisting it runs only after a HEAD proved the worker was up, and the 24h absolute cap still bounds the whole hold. The alternative of simply widening the window was rejected - it would reintroduce the size cliff this work removes. Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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2b61e4bc1d |
fix(upgrade-check): don't filter upgrade candidates by controller capability (#11024)
CheckUpgradesAgainst resolved gallery entries through AvailableBackends, which drops every entry the *local* host cannot run. In distributed mode the host running the check is a CPU-only controller while the GPU backends live on worker nodes, so FindGalleryElement returned nil for every cuda/rocm/l4t entry and those backends were silently skipped. Measured on a live cluster: GET /backends reported 48 installed backends, POST /backends/upgrades/check evaluated 5 — all of them plain or cpu-prefixed. The 43 skipped were all hardware-specific builds. As a result cuda13-nvidia-l4t-arm64-longcat-video-development stayed at sha256:0b8dc851 while the registry tag held sha256:38dae6ff, and a cuDNN packaging fix sat unnoticed on a GPU worker for two days. Every name looked up here is already installed somewhere in the cluster, so hardware compatibility was decided at install time; re-deciding it against the controller is wrong. Switch both CheckUpgradesAgainst and UpgradeBackend to AvailableBackendsUnfiltered. Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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dependabot[bot]
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4ce67ccb84 |
chore(deps): bump body-parser from 2.2.2 to 2.3.0 in /core/http/react-ui in the npm_and_yarn group across 1 directory (#11016)
chore(deps): bump body-parser Bumps the npm_and_yarn group with 1 update in the /core/http/react-ui directory: [body-parser](https://github.com/expressjs/body-parser). Updates `body-parser` from 2.2.2 to 2.3.0 - [Release notes](https://github.com/expressjs/body-parser/releases) - [Changelog](https://github.com/expressjs/body-parser/blob/master/HISTORY.md) - [Commits](https://github.com/expressjs/body-parser/compare/v2.2.2...v2.3.0) --- updated-dependencies: - dependency-name: body-parser dependency-version: 2.3.0 dependency-type: indirect dependency-group: npm_and_yarn ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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mudler's LocalAI [bot]
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b700a78ae4 |
fix(distributed): make the cold-load hold scale with progress, not wall-clock (#11019)
A 70 GB video checkpoint (longcat-video-avatar-1.5) could not be loaded on a
distributed cluster. The request failed with HTTP 500 after 1499.98s - exactly
the 25m00s cold-load ceiling - while staging was demonstrably healthy: 26 of 57
files and 39 GB transferred at a sustained ~26 MB/s, zero errors, no stalls. It
was not wedged, it was killed by a timer.
ModelLoadCeilingFor covers node selection, backend install, file staging and the
remote LoadModel. Install and load carry their own budgets; staging was covered
only by a FIXED 5-minute margin. But staging time is bytes over bandwidth, not a
constant: 70 GB at 26 MB/s needs ~45m against a 25m ceiling, so the failure is
deterministic for any sufficiently large model rather than a flake. Simply
raising the constant moves the cliff to the next model size - the deployment
target here is checkpoints of 600 GB and beyond.
The ceiling's real purpose is that "a wedged worker can never pin the lock
indefinitely". Progress, not elapsed time, is what distinguishes a wedged worker
from a large one. The hold is now a deadline that extends whenever the transfer
reports bytes and expires a 5-minute stall window after they stop:
- A large model transferring fine continues, for hours if needed.
- A worker that died mid-transfer still fails within the stall window.
Progress is observed at byte level on the transfer itself, via the existing
staging progress callback. Per-file completion would be too coarse - a single
600 GB shard would be indistinguishable from a stall for hours. The observation
point is back-pressured by the socket, so it reflects the network rather than
local disk reads. Observation is coarsened to one timer touch per stall/20 so
the per-read callback stays cheap.
The base budget (unchanged, and still derived from the install and load
timeouts) continues to cover the steps that report no progress, so
LOCALAI_NATS_MODEL_LOAD_TIMEOUT keeps working exactly as before. An absolute
cap of 24h bounds the hold even while progress keeps arriving, so a peer
trickling bytes forever cannot pin the advisory lock; 600 GB at the measured
26 MB/s is ~6.5h, so the cap sits far above any legitimate transfer.
Also fixes the incoherent layering the same error exposed: the resumable upload
carried a 1h retry budget nested inside the 25m ceiling, so the inner budget was
unreachable and the message still blamed it ("failed after 1 attempts within
1h0m0s budget") while the 25m parent was the actual killer. The upload now
adopts the caller's deadline when there is one, and applies its fixed budget
only when nothing above bounded it - which also stops a fixed 1h from
reintroducing the size cliff under the now-extendable parent.
This is the successor to #10968, where a hardcoded 5-minute LoadModel gRPC
timeout was replaced by this derived ceiling. Fixing the inner timeout exposed
the outer ceiling as the new binding constraint.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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dependabot[bot]
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2a8eb5a04b |
chore(deps): bump the npm_and_yarn group across 1 directory with 5 updates (#11011)
Bumps the npm_and_yarn group with 5 updates in the /core/http/react-ui directory: | Package | From | To | | --- | --- | --- | | [dompurify](https://github.com/cure53/DOMPurify) | `3.4.0` | `3.4.11` | | [hono](https://github.com/honojs/hono) | `4.12.18` | `4.12.31` | | [qs](https://github.com/ljharb/qs) | `6.15.0` | `6.15.3` | | [react-router](https://github.com/remix-run/react-router/tree/HEAD/packages/react-router) | `7.13.1` | `7.18.1` | | [undici](https://github.com/nodejs/undici) | `7.25.0` | `7.28.0` | Updates `dompurify` from 3.4.0 to 3.4.11 - [Release notes](https://github.com/cure53/DOMPurify/releases) - [Commits](https://github.com/cure53/DOMPurify/compare/3.4.0...3.4.11) Updates `hono` from 4.12.18 to 4.12.31 - [Release notes](https://github.com/honojs/hono/releases) - [Commits](https://github.com/honojs/hono/compare/v4.12.18...v4.12.31) Updates `qs` from 6.15.0 to 6.15.3 - [Changelog](https://github.com/ljharb/qs/blob/main/CHANGELOG.md) - [Commits](https://github.com/ljharb/qs/compare/v6.15.0...v6.15.3) Updates `react-router` from 7.13.1 to 7.18.1 - [Release notes](https://github.com/remix-run/react-router/releases) - [Changelog](https://github.com/remix-run/react-router/blob/react-router@7.18.1/packages/react-router/CHANGELOG.md) - [Commits](https://github.com/remix-run/react-router/commits/react-router@7.18.1/packages/react-router) Updates `undici` from 7.25.0 to 7.28.0 - [Release notes](https://github.com/nodejs/undici/releases) - [Commits](https://github.com/nodejs/undici/compare/v7.25.0...v7.28.0) --- updated-dependencies: - dependency-name: dompurify dependency-version: 3.4.11 dependency-type: direct:production dependency-group: npm_and_yarn - dependency-name: hono dependency-version: 4.12.31 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: qs dependency-version: 6.15.3 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: react-router dependency-version: 7.18.1 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: undici dependency-version: 7.28.0 dependency-type: indirect dependency-group: npm_and_yarn ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> |
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mudler's LocalAI [bot]
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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> |
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mudler's LocalAI [bot]
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0eb8a1188d |
fix(worker): give the worker a real health endpoint and a mode-aware HEALTHCHECK (#10999)
fix(worker): give the worker a real health endpoint (#10987) The image bakes in a single HEALTHCHECK that curls http://localhost:8080/readyz, but the same image also runs `local-ai worker`, which serves HTTP on the gRPC base port minus one and never binds 8080. Every worker container was therefore permanently `unhealthy` (43 consecutive failures observed on a production node), which is worse than having no healthcheck: a genuinely broken worker and a perfectly good one both report `unhealthy`, so the signal carries no information and orchestration that keys on it misbehaves. The worker already served /readyz on that port via the file-transfer server, but as a constant 200 — it only proved the listener was bound, which is precisely the failure mode at issue. Readiness now tracks the live NATS connection: all of a worker's actual work (backend lifecycle events, inference dispatch, file staging) arrives over NATS, so a worker whose link is dead is up and useless. Registration is already implied, since the server only starts after registration succeeds. This reports something the controller cannot already see. The node registry's status/last_heartbeat is fed by an HTTP heartbeat to the frontend, a different network path from NATS — a worker can keep heartbeating while its NATS connection is dead and still look healthy in the registry. /healthz stays a constant 200: liveness must not follow readiness, or a NATS blip becomes a cluster-wide restart storm. The HEALTHCHECK is now a script that derives its endpoint from the mode the container is actually running plus the env vars that configure the bind address, so a frontend moved off 8080 with LOCALAI_ADDRESS (broken the same way) and a worker on a non-default base port are both probed correctly. Modes with no HTTP surface (agent-worker, one-shot commands) report healthy rather than false-unhealthy. HEALTHCHECK_ENDPOINT remains as an explicit override, so the workaround shipped in docker-compose.distributed.yaml keeps working; both overrides in that file are now unnecessary and have been removed. Also fixes the latent --start-period gap. Since #10949 a frontend's startup preload materializes HuggingFace artifacts before the HTTP server binds (31 GB observed on a live cluster), so a healthy replica can legitimately fail probes for a long time. --start-period is Docker's knob for exactly this: failures inside it leave the container `starting` instead of burning retries, and it ends early on the first success, so a generous 60m costs a fast-starting container nothing. --timeout drops from 10m to 10s — it is a per-probe deadline, and a localhost curl that has not answered in 10s is itself the fault being detected. Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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d7e04dcc32 |
fix(openresponses): make responses visible and cancellable across replicas (#11000)
In distributed mode the Open Responses store is process-local: a sync.OnceValue over a map behind an RWMutex. With several frontend replicas behind a round-robin load balancer, every request that lands on a replica other than the creator misses. Measured on a live 2-replica cluster (#10993): the same response id returns 200 on the creating replica and 404 on its peer, and a cancel on the peer returns 404 without ever invoking CancelFunc, so generation runs to completion on the other replica while the caller is told the response does not exist. previous_response_id chaining fails through the same lookup. Split the state by what can actually cross a process boundary: - Replicated: response metadata (request, response resource, owner, expiry, stream/background flags) via syncstate.SyncedMap, the same component finetune, quantization and agent tasks already use. A local miss in Get/FindItem now falls back to it and returns a read-only remote view, so polling and chaining resolve on any replica. - Delegated: cancellation. context.CancelFunc is a function pointer and exists only in the creating process, so a cancel that lands elsewhere is broadcast on responses.<id>.cancel and applied by whichever replica holds the function. The broadcast is fire-and-forget rather than request/reply: if the owner crashed or was scaled down nobody answers, and the handler must not block on a reply that will never come. The replicated status moves to cancelled either way, which is truthful, since a dead owner's generation died with its process. - Refused: streaming resume. The resume buffer is a byte log plus a live notification channel and cannot be replicated without shipping every token over the bus. A resume that reaches the wrong replica now returns HTTP 409 naming the owning replica via the new ErrResponseNotLocal, instead of an empty event list that looks like a finished stream. It is deliberately distinct from ErrOffsetLost, which means the owner's buffer evicted the requested events. Standalone deployments never call EnableDistributed and keep exactly the previous process-local behaviour. Fixes #10993 Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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a4bab71f27 |
gallery: remove duplicated entries and lint against them recurring (#10996)
gallery: remove duplicated entries and lint against them coming back gallery/index.yaml declared eight names twice: deepseek-r1-distill-llama-8b, llama3.2-3b-enigma, qwen3-asr-0.6b, qwen3-asr-1.7b, qwopus-glm-18b-merged, voice-en-us-kathleen-low, whisper-large-q5_0 and whisper-small-q5_1. FindGalleryElement resolves a reference by returning the first match, so in every pair the second copy was unreachable: it could not be installed, could not be selected as a variant target, and could not be corrected, because any edit to it went to a copy nobody reads. A reference to such a name is also ambiguous to anything reasoning over the catalog, which is why the variant proposal job refuses to propose against them. Each pair was compared both as parsed entries and as raw text, and all eight were byte-identical apart from position. None of the sixteen blocks defines a YAML anchor or pulls one in with a merge key, so nothing was reachable only through a deleted block, and no entry named a removed copy as a variant target. Removing the second copy of each therefore changes no behaviour: the parsed set loses exactly eight entries and every surviving entry is field-for-field unchanged. The removal is textual, by line range, so the diff is pure deletions rather than a reflow of forty thousand lines. checkNoDuplicateEntryNames is the rule that keeps them out, added beside the existing gallery invariants and reporting in the same style. checkSingleVariantClaim closes the adjacent gap in the same place. VariantParents resolves a build claimed by two parents by taking the first in gallery order and calls that deterministic "for a gallery the linter would reject", but nothing rejected it: the invariant was held by curation alone. Now it is a rule, and the comment describes something real. No target is doubly claimed today, so the rule is green on arrival. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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2f33ad6669 |
fix(modelartifacts): treat CIFS EACCES as lock contention, not failure (#10986)
flock(2) on CIFS/SMB returns EACCES when another client holds the lock: the kernel maps STATUS_LOCK_NOT_GRANTED and STATUS_FILE_LOCK_CONFLICT to -EACCES and never produces EWOULDBLOCK on that path. gofrs/flock only recognises EWOULDBLOCK as contention, so TryLockContext returned a bare "permission denied" and Ensure aborted. Both replicas then fell back to legacy loading, which makes the worker download the whole repo in-band inside LoadModel and blow the remote-load deadline. Replace TryLockContext with an explicit wait loop over a new Locker interface, classifying EWOULDBLOCK/EAGAIN/EACCES/EBUSY as contention. EACCES is ambiguous at the syscall boundary but not here: the lock file is already open O_CREATE|O_RDWR, so a real permission problem would have failed the open with an *fs.PathError, and flock(2) documents no EACCES on Linux at all. The wait is bounded (DefaultLockWait, overridable via WithLockWait), so even a misclassification degrades to a delay. On timeout the committed result is re-checked before reporting the new ErrLockContended, so a peer that finished the work still wins. Locker also exists so the contention path is testable without a network filesystem: nothing in CI can make flock(2) return EACCES on demand. Raise the fallback to error for a managedArtifactBackends backend, via a shared config.LogArtifactFallback used by both call sites. For those backends the legacy path is not graceful degradation, and the operator otherwise sees only a timeout with no causal link. The fallback stays non-fatal. Drop the os.Chmod(layout.Lock, 0o600) after acquisition: flock.New already creates the file 0600, and the chmod was gratuitous risk on a nounix mount that ignores modes. Fixes #10981 Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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1cd7d63c7b |
fix(distributed): reject wrong-model requests on the remaining modalities (#10990)
#10970 gave the four PredictOptions RPCs a model-identity check so a backend reached through a stale distributed route rejects the request instead of answering from whatever model it holds (#10952). Every other modality shares that exposure: the route is cached by host:port, a worker can recycle a stopped backend's port for another model's backend, and a liveness-only probe cannot tell a stale row from a valid one. Extends the same mechanism to the 21 remaining request messages that reach a backend through the router, using the pattern #10970 established rather than a parallel one: - proto: ModelIdentity on each modality request message. - controller: populated from ModelConfig.Model at the call site that also builds ModelOptions, so load-time and request-time values are equal by construction. - backends: one generic guard in pkg/grpc/server.go (27 Go backends), the method set in backend/python/common (36 Python backends), llama-cpp (AudioTranscription/Stream, Rerank, Score) and privacy-filter (TokenClassify). - reconcile already drops the stale row on IsModelMismatch; no change. TTSRequest and SoundGenerationRequest get a SEPARATE ModelIdentity field rather than reusing their existing `model`: FileStagingClient rewrites `model` to a worker-local path, so comparing it would reject valid requests in exactly the configuration this guards. AudioEncode/AudioDecode are deliberately left unguarded: the opus codec backend is loaded from a literal rather than a ModelConfig, so no value carries the equality guarantee the comparison depends on. The four bidirectional stream RPCs are out of scope; they bypass reconcile. Empty means skip on both sides, so an old controller, an old backend, and the bare request structs in tests/e2e-backends all keep working. Assisted-by: Claude Code:claude-opus-4-8 [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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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> |
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mudler's LocalAI [bot]
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83a0f16a21 |
feat(gallery): let one gallery entry offer several builds of the same model (#10943)
* feat(system): expose raw detected capability for model meta resolution Model meta gallery entries express hardware fallback through candidate ordering rather than a capability map, so they need the undecorated detected capability string without Capability's default/cpu fallback chain. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor(system): drop duplicate capability accessor, cover DetectedCapability ReportedCapability was added with a body identical to the existing DetectedCapability. Keep one accessor and move the specs onto it, since DetectedCapability had no direct coverage of its no-fallback behavior. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(vram): parse IEC binary size suffixes (KiB..PiB) ParseSizeString accepted only SI suffixes, so a "20GiB" floor was rejected outright. Model and VRAM sizes are conventionally quoted in IEC units, and silently reading GiB as GB would understate a floor by about 7%. Purely additive: these inputs previously returned an unknown-suffix error. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add Candidate type for meta model entries Candidate is one option in a meta entry's ordered variant list. It names a concrete gallery entry and declares when that entry suits the host. EffectiveMinVRAM resolves the VRAM floor, letting an authored min_vram win over a nightly-inferred one. An unparseable floor errors instead of being treated as absent: swallowing a typo would turn a constrained candidate into an unconstrained one and select a too-large variant rather than fail loudly. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add hardware-aware model variant resolver Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): allow gallery model entries to declare variant candidates A gallery entry with a non-empty candidates list is a meta entry: it names an ordered list of concrete entries and resolves to the first one the host can satisfy, instead of describing model files directly. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): resolve meta model entries to hardware-appropriate variants at install Meta gallery entries carry an ordered candidate list; at install time the first candidate the host satisfies is resolved and its payload installed under the meta's name, so the model keeps a stable name regardless of which variant backs it. The resolution is recorded in the installed gallery config so a reinstall honors a prior pin and operators can see the backing variant. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(gallery): key meta pin recall on the installed name and detach resolved entries Six review findings on the meta-entry install path. Pin recall was keyed on the gallery entry name while applyModel writes the record under the install name (req.Name when supplied), so a meta installed under a custom name with a pin lost that pin on reinstall and was silently re-resolved onto a different variant, possibly swapping its backend. Compute the install name with applyModel's own precedence before the recall. ResolveMetaModel returned a shallow struct copy, so the resolved entry's Overrides aliased the gallery entry's map and the install path's in-place mergo merge wrote the caller's request into the shared catalog. Detach Overrides, ConfigFile, AdditionalFiles, URLs and Tags. Not exploitable today only because this path re-unmarshals the gallery per call, which is a property nobody should have to rely on. Also: overlay the meta's name onto the persisted config for meta installs so the gallery file no longer records the variant's name; move the pinned-VRAM warning below the variant validation so a pin naming a nonexistent entry does not warn about VRAM before failing for an unrelated reason; and stop seeding config.URLs in the config_file branch, which duplicated every declared URL. Add seven network-free specs driving InstallModelFromGallery with a meta entry: variant payload wins over the meta's legacy url fallback, the resolution record round-trips to disk, a pin is recorded and honored on reinstall including under a custom install name, and the resolved entry does not alias the gallery's maps. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(gallery): deep-copy meta overrides and make two specs functional ResolveMetaModel detached the resolved entry's Overrides and ConfigFile with maps.Clone, which only copies the top level. Gallery overrides are nested in practice (parameters.model is near-universal) and the install path merges the caller's request with mergo.WithOverride, which recurses into nested maps and overwrites them in place, so the gallery entry's own inner maps were still reachable and still got rewritten by the last caller to install. Copy both maps all the way down instead, recursing through the container shapes a YAML decoder produces. ConfigFile is not mutated on the install path today, but it carries the same kind of nested payload and leaving it shallowly cloned would invite the bug back. Also fix two specs that passed whether or not their target fix was present: - "does not write the caller's overrides back into the gallery entry" re-read the catalog from disk, which re-unmarshals fresh structs and so cannot observe in-memory aliasing. It now asserts against the in-memory gallery entry and drives the real mergo merge. - "round-trips the resolution record to disk under the meta's name" asserted a name that is already correct in the config_file branch. It now drives the url branch via a file:// fixture, where the meta-name overlay actually applies. Both were verified red by reverting their fix. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(gallery): lint meta model entry invariants in index.yaml Adds Ginkgo specs that parse the shipped gallery/index.yaml and enforce the invariants that keep meta entries safe: a legacy url fallback equal to the final candidate's url, references only to existing non-meta entries, a min_vram floor on every candidate but the last-resort one, a capability drawn only from the vocabulary the system can report, and descending VRAM floors within a capability group. The capability check is the only compensating control for a typo there. Candidate matching is a case-sensitive exact comparison against SystemState.DetectedCapability(), so an unknown value never matches and falls through silently instead of erroring. The vocabulary therefore mirrors the raw return set of getSystemCapabilities(), which notably excludes "cpu": that is a fallback key inside Capability(capMap) on the meta backend path, never a reported capability. A CPU-only host reports "default". These pass vacuously until the pilot meta entry lands; the guard is intentionally in place before the thing it guards. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test(gallery): close coverage gaps in the meta entry lint The ordering invariant grouped candidates by capability and asserted floors descend within a group. A candidate with an EMPTY capability matches every host, so it does not belong in its own group: it dominates every later candidate whose floor is at or above its own, across capability groups. Track a running minimum floor over the unconditional candidates instead, which subsumes the old same-group check for the empty capability. Every spec skipped non-meta entries, so with zero meta entries in the index all five bodies were no-ops. Aligning GalleryModel.IsMeta() with GalleryBackend.IsMeta(), whose semantics are deliberately opposite, would have made all of them pass while checking nothing. Extract each invariant into a helper over a slice of entries returning the violations it finds, and cover those helpers with synthetic fixtures so the logic stays tested at zero meta entries. The index-driven specs are now a thin application of already proven logic. Also assert the index parses non-empty, report every violation in one run rather than aborting on the first, and parse the index once for the suite. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ci(gallery): add nightly denormalization of meta model candidates Fills the read-only backend, quantization and inferred_min_vram fields on meta gallery candidates and opens a PR, modeled on the existing checksum_checker job. Computing these needs network access, so it happens nightly rather than at install time. An authored min_vram is never modified: a human who measured a real load knows more than a pre-download estimate does. The index is rewritten via yaml.Node rather than a document round-trip. A full round-trip reflows all ~26k lines of gallery/index.yaml, which would bury the computed values and make the nightly PR unreviewable. The rewrite touches only the three derived keys, so authored styling survives and a run that computes nothing leaves the file untouched. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ci): keep the gallery denormalize diff reviewable and self-healing The nightly denormalization job edits YAML nodes instead of round-tripping structs so its PR stays small enough for a human to review, but the write path undid that: yaml.Marshal re-encoded the node tree at yaml.v3's default 4-space indent and dropped the leading document marker, reflowing roughly 6000 lines around the handful of real changes. Encode through yaml.NewEncoder at the index's authored 2-space indent and restore the header. A write that changes three fields now changes three lines. Stale inferred_min_vram values were also never cleared. Both skip paths (an authored min_vram is present, or the candidate is the last resort) returned before touching the field, so a candidate that gained a floor or became the last resort after a reorder kept an inferred value that EffectiveMinVRAM reported as a real constraint, failing the meta lint with no way for the job to self-heal. Clear the field before both skips. The workflow discarded a whole night's work on any single failure: the program exits 1 when a candidate cannot be estimated, which aborted the job before the PR step, so one unreachable candidate blocked every other refresh indefinitely. Capture the status, open the PR with what was computed, mark the PR body as partial, and fail the run afterwards so the problem still surfaces. Also preserve the index's existing file mode instead of forcing 0644, and drop the redundant //go:build ignore tag, since Go already skips dot directories and the sibling modelslist.go carries no tag. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): add nanbeige4.1-3b meta entry with hardware-resolved variants Adds the first real meta entry to the gallery index. It resolves to the Q8_0 build on hosts with at least 6GiB of VRAM and to the Q4_K_M build everywhere else, installing either payload under the stable name nanbeige4.1-3b. The entry carries a url equal to its final candidate's url. LocalAI releases that predate candidates support parse the index non-strictly and drop the key silently, so without that url they would list the entry and install nothing. A regression spec parses the index the way those releases do and asserts every meta entry stays installable for them. Also teaches core/schema/gallery-model.schema.json about candidates. The schema sets additionalProperties: false at the top level, so an author following CONTRIBUTING.md and adding the yaml-language-server comment would otherwise get a validation error on this entry. Assisted-by: Claude:claude-opus-4-8 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(gallery): make candidate entries complete, installable entries Reworks hardware-resolved gallery variants after a design pivot. There is no longer a separate "meta" entry kind. A gallery entry is a normal, complete entry that may additionally carry candidates:, a list of hardware-gated upgrades over itself, and the entry is itself the last-resort candidate. The previous design relied on a bare url: as the fallback for LocalAI releases that predate candidates support. That fallback is empty in practice: none of the 80 gallery/*.yaml files carry a top-level files:, and 1216 of 1281 index entries carry their payload in the index entry itself, so a url alone yields a config template with nothing to download. Since every released LocalAI reads gallery/index.yaml live from master, merging a payload-less entry would have shown every existing user a model that installs to a broken state. Making the entry its own base candidate removes the problem at the root: old clients drop the candidates key and install the entry exactly as they do today. Resolution order is now explicit pin, then capability plus VRAM over the declared upgrades, then the entry itself. The entry ALWAYS installs: when its own min_vram or capability is unmet the installer warns and installs it anyway, because there is nothing below it and refusing would make the gallery behave worse the newer the client is. A pin naming the entry's own name is valid and is how an operator declines an upgrade. IsMeta() becomes HasCandidates(), ResolveMetaModel becomes ResolveVariant, and the persisted meta_name record key becomes entry_name. GalleryBackend.IsMeta() is a separate concept and is untouched. The lint drops the three rules the pivot makes wrong (url equality with the final candidate, no inline payload, unconstrained final candidate) and gains one: the entry's own floor must sit strictly below every candidate's, since a base that outranks a candidate makes that candidate unreachable. The pilot entry is now the existing nanbeige4.1-3b-q4, which gains a 2GiB floor of its own and a single 6GiB upgrade to nanbeige4.1-3b-q8, replacing the separate nanbeige4.1-3b entry added in |
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mudler's LocalAI [bot]
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465d488c90 |
fix(distributed): reject wrong-model requests at the backend (#10970)
fix(distributed): reject wrong-model requests at the backend (#10952) In distributed mode the controller caches a NodeModel row naming a backend's host:port. A worker can recycle a stopped backend's gRPC port for a different model's backend, and probeHealth verifies liveness rather than identity, so the probe succeeds against whatever now occupies the port and the request is dispatched to the wrong backend. The caller gets a silent wrong-model answer. Nothing in the request could catch this: PredictOptions had no model field, so model identity crossed the wire only in ModelOptions.Model at LoadModel time, and the cached-hit path issues no LoadModel. Every backend's "model not loaded" guard checks a nil handle, which a process holding a different model passes, so the stale row was never dropped either. Add PredictOptions.ModelIdentity and enforce it at the point of use: - The controller populates it in gRPCPredictOpts from ModelConfig.Model, the same expression ModelOptions feeds to model.WithModel and therefore the same value the backend received as ModelOptions.Model. Both are read from one config value in one function, so they are equal by construction and the comparison cannot false-reject. - Backends compare it against what they loaded and return NOT_FOUND with a fixed sentinel. Enforced in pkg/grpc/server.go (27 Go backends), an interceptor in backend/python/common (all 36 Python backends, no per-backend change), and the llama-cpp / ik-llama-cpp / ds4 C++ servers. That is every backend with real exposure: kokoros answers all four RPCs with unimplemented and privacy-filter implements none of them. - The router's reconcile drops the stale replica row on a mismatch, so the next request reloads somewhere correct. Empty means "skip the check" on both sides: a controller that predates the field sends nothing, a backend loaded by such a controller has nothing to compare, and the C++ server synthesizes PredictOptions internally for ASR. That keeps upgrades working in both directions. Scoped to the four PredictOptions RPCs. TTSRequest.model and SoundGenerationRequest.model are deliberately NOT validated: FileStagingClient already rewrites them to worker-local absolute paths, so in distributed mode they already differ from the load-time value and comparing them would reject valid requests. IsModelMismatch requires both the NOT_FOUND code and the sentinel, unlike the neighbouring helpers which accept either. insightface's Embedding returns NOT_FOUND "no face detected" on a PredictOptions RPC, and a code-only check would drop a healthy replica row on every faceless image. Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Nandana Dileep
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b5e4413eab |
feat: add MiniMax-M3 model support (#10837)
Adds inference parameter defaults for the minimax-m3 model family and includes a vendored patch of upstream llama.cpp PR #24523 to recognize the minimax-m3 architecture. Once the upstream PR merges, the patch can be removed and LLAMA_VERSION bumped normally. Changes: - backend/cpp/llama-cpp/patches/0001-add-minimax-m3-support.patch: vendored patch from ggml-org/llama.cpp#24523 (Preliminary MiniMax-M3 support). Applied by prepare.sh during the build; keeps the pinned LLAMA_VERSION pointing at the latest upstream tag. - core/config/inference_defaults.json: add minimax-m3 family entry (temperature=1.0, top_p=0.95, top_k=40, min_p=0.01, repeat_penalty=1.0, matching the existing minimax defaults) and register it in the patterns list before the shorter minimax-m2.7 entry for correct longest-match-first ordering. Upstream: depends on ggml-org/llama.cpp#24523 Closes: https://github.com/mudler/LocalAI/issues/10820 Signed-off-by: Nandana Dileep <110280757+nandanadileep@users.noreply.github.com> |
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mudler's LocalAI [bot]
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e55cc3e2a7 |
fix(worker): bound the gRPC port allocator and stop leaking dead backends' ports (#10968)
The worker's gRPC port allocator grew monotonically with no upper bound: nextPort started at the base port and incremented whenever freePorts was empty, and nothing checked 65535. Past that it handed out integers that cannot be bound, surfacing as an opaque "backend won't start". #10961 estimated this needed ~15,000 concurrent-peak allocations, i.e. effectively unreachable. It is not, because of a second defect: the "process died unexpectedly" branch in startBackend deleted the process map entry without releasing its port at all. That port was leaked, never quarantined and never reused. A crash-looping backend leaks one port per restart, so a backend dying every 30s walks 50051 to 65535 in about five days. The leak, not concurrent peak, is the realistic route to exhaustion. Fixing the leak alone would have been wrong. Releasing that port makes it re-bindable, and the death path is the one teardown path with no request/reply to carry StoppedProcessKeys back to the controller (#10952's eager row removal), so a stale NodeModel row could then resolve to a live listener belonging to a different backend. probeHealth verifies liveness, not identity, so the request is silently misrouted. The 15s port quarantine does not cover this: the only reaper is the per-model health check at ~45s, and it can be disabled outright. The residual was masked only because the port was never rebound. So both are fixed together: - The allocator takes an explicit [basePort, LOCALAI_GRPC_MAX_PORT] range and returns ErrNoFreePort naming the range, the live backend count, the quarantined count, and the knob to raise. Exhaustion is now diagnosable instead of surfacing as an unbindable port. - Released ports carry per-key affinity: a port is offered back to the process key that last held it before any other key. Process keys (modelID#replica) and NodeModel rows (nodeID, modelName, replicaIndex) are isomorphic, so a port that can only be re-bound by its previous owner can only ever be named by that owner's row, which that key's re-registration overwrites. Misrouting to a different model becomes impossible by construction rather than by racing the quarantine timer. Affinity is a preference, not a reservation: under range pressure an owned port is stolen with a warning, because a guaranteed outage is worse than a rare misroute window on a port long out of quarantine. Claiming a port evicts its previous owner's entry, keeping ownership injective over ports so the affinity map can never exceed the range width regardless of how many distinct model keys the worker sees. Ownership also expires. It is only load-bearing while a controller row could still name the port, which the per-model reaper bounds at roughly 45s, so it lapses after five minutes and the port becomes ordinary free space again. Holding it indefinitely would have made every distinct model the worker ever served consume a port permanently: every release path is keyed, so nothing would ever be unowned, the allocator would climb to the end of its range on distinct-key count rather than concurrency, stealing would become routine, and the steal warning would tell operators to widen a range that was not the constraint. With expiry, reaching the steal branch means the worker is genuinely out of concurrent capacity, so that advice is correct when it appears. Closes #10961 Closes #10952 Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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9d82c37f98 |
fix(distributed): backend discovery hid worker-installed backends behind the controller's filesystem (#10967)
fix(distributed): backend discovery hid worker-installed backends Backend discovery endpoints filter on installed-state, which on a distributed controller derives from the controller's own filesystem. A backend lives on the worker node that runs it, so every backend an admin installed on a GPU worker read as "not installed" and vanished from the listing. #10947 fixed the sibling capability filter on the same endpoints, so a fine-tuning-capable GPU worker now made the backend listable while the installed-state filter still dropped it: the dropdown stayed empty. The controller cannot derive this locally, but it already aggregates the per-node view that GET /backends renders, so discovery reuses the active BackendManager rather than growing a second path. Three surfaces shared the root cause and route through the same helper now: - GET /backends/available (Installed is now cluster-wide) - GET /api/fine-tuning/backends - GET /api/quantization/backends The response stays a boolean rather than an installed-on-N-of-M count: per-node install state is already served by GET /backends nodes[], and per-node control by POST /api/nodes/:id/backends/install, so a summary is all these dropdowns need. A nil provider (single-node) leaves the local filesystem as the only source and reproduces today's listing exactly, and a registry error degrades to that same listing instead of blanking the catalog. Assisted-by: Claude:claude-opus-4-8 golangci-lint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
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f735cb24c0 |
fix(worker): reap deleted backends and stop models that live on a worker (#10956)
* fix(worker): reap deleted backends and stop models that live on a worker
Three related backend-lifecycle defects, all reachable from the same
production incident on a Jetson/Thor worker: a deleted backend's gRPC
process survived ~40 minutes with its directory removed from disk, a later
model load was routed to that orphan and failed with a certifi path pointing
into the deleted directory, and the admin could not stop the model because
the frontend reported it as not loaded.
1. backend.delete orphaned the process it claimed to delete
------------------------------------------------------------
s.processes is keyed by `modelID#replicaIndex` (buildProcessKey), so the
backend name never appeared in a key and was recorded nowhere on the
process. backend.delete resolved its target via isRunning/stopBackend, whose
prefix path only matches a bare *modelID* - a delete keyed on a backend name
resolved to zero keys, the stop silently no-op'd, and the files were removed
out from under a live process.
The install fast path then handed that orphan back out: it returns any live
process for the (model, replica) slot without checking which backend started
it, so a reinstalled variant inherited the deleted backend's port.
- Record backendName on backendProcess, threaded installBackend ->
startBackend.
- Add resolveProcessKeysForBackend, matching the recorded name and resolving
alias <-> concrete via ListSystemBackends *before* DeleteBackendFromSystem
erases the metadata that carries the alias. Alias resolution failure
degrades to name-only matching so a delete never fails on it.
- backend.stop goes through resolveStopTargets, which accepts a backend
name, a model name, or an exact modelID#replica key. Its payload field is
named "backend" but is published with all three meanings: the admin UI
sends a backend name, UnloadRemoteModel sends a model name, and the
router's abandoned-load reap (#10948) sends an exact replica key.
Narrowing it to backend names alone would strand the latter two.
backend.delete stays strict - its identifier is unambiguously a backend.
- Gate the install fast path on processMatchesBackend so a slot held by a
different backend is restarted rather than reused. Processes with no
recorded name (pre-upgrade) are accepted, so rollout does not restart
every running backend.
- stopBackendExact reports a real stop failure - the process still being
alive afterwards, which is precisely what finishBackendStop already
detects to keep the entry and its port reserved - and backend.delete no
longer replies success when it knew about a process and could not kill it.
"No process was running" stays a success but is logged, so the orphan case
is visible rather than silent.
2. /backend/shutdown reported a running model as missing
---------------------------------------------------------
ModelLoader.deleteProcess short-circuits on a miss in this replica's
in-memory store. In distributed mode the authoritative record of "is this
model loaded" is the shared node registry: a frontend replica that never
served the model itself (load balancer picked a peer, or the replica
restarted) has no local entry. The remote unload path that pkg/model
documents ("when ShutdownModel is called for a model with no local process,
UnloadRemoteModel is called") sat behind that short-circuit, unreachable in
exactly the case it exists for. #10865 reworked this function but kept the
short-circuit at the top, so the gap survived that refactor.
- deleteProcess consults the remote unloader on a local-store miss, via a
shared unloadRemote helper so this branch and the existing
no-local-process branch both prefer #10865's RemoteModelContextUnloader,
preserving force propagation across the distributed boundary.
- UnloadRemoteModelContext reports ErrRemoteModelNotLoaded when no node has
the model; it previously returned nil, making a no-op stop
indistinguishable from a real one. The converse case (nodes have it, none
could be stopped) already errors since #10865 joined the per-node
failures, so that half of the original fix was dropped as redundant.
- Only when the model is absent locally AND cluster-wide does the endpoint
report not-found, now 404 naming both scopes rather than a bare 500.
- modelNotFoundErr becomes the exported ErrModelNotFound so the HTTP layer
can map it without string matching; watchdog's identity comparison becomes
errors.Is.
3. Coverage for the bounded Free() that #10865 shipped untested
----------------------------------------------------------------
The original branch also bounded the pre-stop Free(), but #10865 landed that
fix first (workerBackendFreeTimeout, applied in both stopBackendExact and
handleModelUnload). That production change is therefore DROPPED here as
superseded - master's version is strictly better, since it also releases the
supervisor mutex across the call and keeps the port reserved until
termination completes.
What #10865 did not ship is a test, and the bound is load-bearing: the
router-side reap in #10948 sends backend.stop for an abandoned load, and
against a wedged backend an unbounded Free would swallow that stop before it
reached the process. Nothing failed if the bound regressed.
The spec stands up a real gRPC backend server whose Free handler never
returns - what a Python backend looks like when its single worker thread
(PYTHON_GRPC_MAX_WORKERS=1 on 37 backends) is occupied by a stuck LoadModel.
A stub socket is not sufficient and was tried first: without a completed
HTTP/2 handshake, gRPC's own ~20s connect timeout ends the call, so that
version passed against the very bug it targets. With the connection READY,
only the caller's deadline can end it, so the spec hangs to its 60s limit if
the timeout is removed and passes with it.
Its fixture process is deliberately never started. go-processmanager v0.1.1
writes Process.pid from readPID() without synchronization, so a live process
races its own monitor goroutine under -race - reproducible with a bare
Run()+Stop() and unrelated to this spec. Since
scripts/model-lifecycle-conformance.sh runs this package with -race and is
fail-closed, starting one would turn that gate red on an upstream defect. An
unstarted process still proves the point: the stop is reached and the slot
released, which is exactly what an unbounded Free prevents.
Verified: make lint (new-from-merge-base origin/master) reports 0 issues;
scripts/model-lifecycle-conformance.sh passes all three stages including the
FizzBee liveness check (1458 states, IsLive: true).
Assisted-by: Claude:claude-opus-4-8 golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): keep remote unload idempotent, ask presence separately
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zjuzhongwen
|
864c84f48b |
chore: fix some comments to improve readability (#10960)
Signed-off-by: zjuzhongwen <zjuzhongwen@outlook.com> |
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mudler's LocalAI [bot]
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0e0221b0f5 |
fix(vision): probe the media marker for pinned llama.cpp backend variants (#10955)
llama.cpp picks a random per-process media marker (ggml-org/llama.cpp#21962),
so LocalAI renders the prompt with a "<__media__>" sentinel and swaps in the
backend's real marker after probing ModelMetadata.
That probe was gated on an exact match against "llama-cpp", the gallery's meta
backend name. A model config pinning a concrete build ("vulkan-llama-cpp",
"cuda12-llama-cpp", "rocm-llama-cpp", ... and their -development counterparts)
runs the same llama.cpp gRPC server but skipped the probe, so MediaMarker
stayed empty, no substitution happened, and the prompt reached mtmd still
carrying the sentinel. mtmd_tokenize then counted zero markers against one
bitmap and every image request failed with "Failed to tokenize prompt".
The same early return also skipped thinking-mode detection and tool-format
marker extraction, so a pinned variant silently lost reasoning and native
tool-call parsing too.
Add IsLlamaCppBackend, which recognises the whole variant family (plus the
empty auto-detect name, which resolves to llama.cpp) while excluding
ik-llama.cpp, a separate engine that merely shares the suffix.
Fixes #10945
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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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>
|
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mudler's LocalAI [bot]
|
626ae4d51e |
fix(model-artifacts): materialize longcat-video on the controller, and support companion repos (#10949)
* fix(model-artifacts): materialize longcat-video checkpoints on the controller longcat-video loads a checkpoint directory: its backend.py takes request.ModelFile when os.path.isdir(request.ModelFile) and otherwise falls back to snapshot_download. That places it in the same class as transformers/vllm/diffusers/sglang, but the allow-list added in #10910 did not enumerate it, so PrimaryArtifactSpec returned no managed artifact for a bare HuggingFace repo id. The consequence in distributed mode: nothing was acquired on the controller, ModelFileName fell through to the raw repo id, and staging skipped the resulting phantom /models/<owner>/<repo> path. The worker received a blank ModelFile, fell back to request.Model, and downloaded ~83GB from HuggingFace inside the remote LoadModel deadline - so the load could only ever fail with DeadlineExceeded while an abandoned backend process kept downloading. Note this materializes the full repository. The backend restricts its own snapshot_download with allow_patterns, and the avatar repo ships both base_model/ and base_model_int8/ where only one is ever loaded; inferred specs have no way to carry patterns today. Tracked separately. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): warn when staging skips a non-existent model path stageModelFiles logs "Staging model files for remote node" up front, then silently drops any path field that does not exist on the controller. The skip itself is legitimate and must stay: a backend outside managedArtifactBackends that takes a bare HuggingFace repo id gets an optimistically constructed path (ModelFileName falls through to the raw model reference) that was never materialized, and sources its own weights on the worker. Erroring would break those configs. But at debug level the operator is left with a reassuring staging line and no trace of the skip, so a genuine controller-side acquisition gap is indistinguishable from a healthy pass-through - it surfaces much later as a remote LoadModel timeout, on a worker that is quietly downloading tens of gigabytes. Raise the skip to warn and name the field, path, node and tracking key. Behavior is unchanged. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(model-artifacts): allow a config to declare companion artifacts A composed pipeline needs more than one HuggingFace snapshot. LongCat-Video-Avatar-1.5 loads its own transformer but takes the tokenizer, text encoder and VAE from the separate LongCat-Video base repo, so a single-artifact config cannot express it and the backend is left to fetch the second repo itself at load time. Widen the artifact model to target: model plus any number of named target: companion entries. Normalize accepts the new target and constrains a companion name to [a-z0-9][a-z0-9_-]{0,63} because that name is the option key the backend later receives; a companion may not claim primary_file, which only means anything for a load target. ModelConfig.Validate requires exactly one primary and requires it first, since Artifacts[0] is what ModelFileName, size estimation and staging all resolve from. Both acquisition paths now loop instead of touching index 0 alone: preloadOne for an already-installed config, bindPrimaryArtifact for a gallery install. Failure policy differs by provenance. An inferred primary keeps its warn-and-fall-back, because the legacy download path still exists for it. Companions are explicit by construction, so they are all-or-nothing: a config naming one is asserting the backend needs it, and failing at the acquisition boundary is far more legible than a missing-weights error surfacing later inside the backend. The cache key is deliberately unchanged. It hashes source identity only, never name or target, so every already-installed managed model still hits its existing snapshot instead of silently re-downloading. Two specs pin that: one proving a companion and a primary with identical sources agree on the key, and one pinning the digest of a known primary outright. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(model-artifacts): hand resolved companion snapshots to the backend A materialized companion is useless until the backend can find it, and its location is a content-addressed cache key that does not exist until the artifact resolves. A static gallery override cannot carry that, and persisting it into the config YAML would rot the moment a re-resolve produced a new key. Synthesize it instead at load time: each resolved companion becomes "<artifact name>:<snapshot path>" in ModelOptions.Options, reusing the key:value convention backends already parse for options like attention_backend. The value stays relative to the models directory so a remote worker can resolve it under its own ModelPath once staging has rewritten the model root. An option the author set explicitly always wins, so pinning a companion to a local checkout still beats the managed snapshot. longcat-video resolves base_model through ModelPath, the same convention qwen-tts, voxcpm, outetts and ace-step already use for companion assets. Its sibling-directory heuristic is deleted: it looked for a LongCat-Video directory next to the model, which cannot exist under the content addressed .artifacts/huggingface/<key>/snapshot layout, so it was dead code the moment the model became managed. The gallery entry declares both repositories and restricts each with allow_patterns. The avatar repo ships base_model/ and base_model_int8/ and only ever loads one, so fetching the whole repo would roughly double the download. The patterns match the entry's own options (use_distill true, use_int8 default false); enabling use_int8 here also requires adding base_model_int8/**, which is called out in the entry. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(distributed): stage managed artifact trees from the models root Staging anchored the worker's models directory on the primary snapshot whenever a model was managed, so a companion snapshot could not reach the worker at all. frontendModelsDir was derived by stripping the Model relative path off the end of ModelFile. For a managed artifact nothing matches: ModelFile is .artifacts/huggingface/<key>/snapshot while Model stays a bare HuggingFace repo id, so the strip was a no-op and the "models directory" came out as the snapshot itself. Two consequences, both silent. Staging keys lost the .artifacts/huggingface/<key>/snapshot prefix, so two snapshots of one model were indistinguishable on the worker. And a companion, which lives in a sibling snapshot directory outside the primary, fell outside that directory entirely: StagingKeyMapper.Key collapsed its files to bare basenames and resolveOptionPath could not resolve the relative option at all, so it was skipped without a word. Derive the models root from the artifact tree instead when the path runs through it, and compute the worker's ModelPath from the file's path relative to that root rather than from the Model field. The legacy layout is unaffected: where Model really is the relative path, the new derivation reduces to the old one, which a regression spec pins. This deliberately changes an invariant that router_dirstage_test.go pinned: for a managed primary, ModelFile and ModelPath were both the snapshot directory, and staging keys were relative to it. Now ModelFile is the snapshot, ModelPath is the models root above it, and keys keep the full relative path. That spec is updated rather than accommodated, with the reasoning recorded inline, because the old invariant is exactly what made a sibling companion unreachable. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
|
b19afb192a |
fix(distributed): backend discovery hid GPU-only backends behind the controller's capability (#10947)
* fix(backends): list backends runnable on worker nodes in distributed mode GET /backends/available filtered the gallery against the system state of the host serving the request. In a distributed deployment that host is the controller, which typically has no GPU, while the GPUs live on worker nodes. Any meta backend whose capabilities map lacks a "default" (or "cpu") key was therefore dropped from the listing entirely — longcat-video, vllm-omni, ltx-video, parakeet, edgetam and qwentts were invisible in the UI even though installing them by name on a GPU worker worked fine. Workers now report their own meta-backend capability at registration and the controller persists it on the node row. The controller cannot derive it: OS-dependent capabilities (metal, darwin-x86, nvidia-l4t) and the CUDA runtime refinements are only observable on the worker. Nodes registered before this field existed fall back to a coarse capability derived from their GPU vendor and VRAM. Backend discovery then evaluates compatibility as the union over healthy backend nodes, so a backend runnable on any node is offered while one no node can run stays hidden. Each remote capability is evaluated through a capability-pinned system state, otherwise a forced capability on the controller image (LOCALAI_FORCE_META_BACKEND_CAPABILITY or /run/localai/capability) would silently override every worker's verdict. With no registered nodes the listing is byte-for-byte what it was, so single-node deployments are unaffected. Also fixes the same-root-cause misclassification in /api/operations, which used the capability-filtered listing to decide whether an operation was a backend or a model install. A GPU-only backend installing on a worker is still a backend operation on the controller, so that lookup is now unfiltered. Assisted-by: Claude:claude-opus-4-8 golangci-lint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(backends): union worker capabilities in backend discovery Implementation for the specs added in the previous commit, plus the two remaining discovery endpoints. Capability-filtered backend discovery evaluated compatibility against the system state of the host serving the request. In a distributed deployment that host is the controller, which typically has no GPU, while the GPUs live on worker nodes. Any meta backend whose capabilities map lacks a "default" (or "cpu") key was dropped entirely — longcat-video, vllm-omni, ltx-video, parakeet, edgetam and qwentts were invisible in the UI even though installing them by name on a GPU worker worked fine. Workers now report their own meta-backend capability at registration and the controller persists it on the node row. The controller cannot derive it: OS-dependent capabilities (metal, darwin-x86, nvidia-l4t) and the CUDA runtime refinements are only observable on the worker. Nodes registered before this field existed fall back to a coarse capability derived from their GPU vendor and VRAM. Discovery then evaluates compatibility as the union over healthy backend nodes, so a backend runnable on any node is offered while one no node can run stays hidden. Each remote capability is evaluated through a capability-pinned system state, otherwise a forced capability on the controller image (LOCALAI_FORCE_META_BACKEND_CAPABILITY or /run/localai/capability) would silently override every worker's verdict. With no registered nodes the listing is byte-for-byte what it was, so single-node deployments are unaffected. Four surfaces shared this root cause and are all routed through the same helper now: - GET /backends/available - GET /api/fine-tuning/backends - GET /api/quantization/backends - /api/operations backend-vs-model classification, which additionally had no reason to filter by capability at all: a GPU-only backend installing on a worker is still a backend operation on the controller, so that lookup is now unfiltered. Assisted-by: Claude:claude-opus-4-8 golangci-lint Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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Richard Palethorpe
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9c43b2da8f |
fix(model): make backend shutdown model-scoped (#10865)
Avoid holding the global loader lock across backend lifecycle waits and propagate forced shutdown through distributed workers. Track parallel requests with in-flight counters and reserve worker ports until process termination. Add focused race tests and an authoritative FizzBee lifecycle model with a fail-closed conformance target. Assisted-by: Codex:GPT-5 [FizzBee] [Ginkgo] Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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localai-org-maint-bot
|
0389495388 |
fix(webui): use relative asset base so fonts and lazy chunks honor X-Forwarded-Prefix (#10889) (#10904)
The Vite build emitted path-absolute asset URLs (base: '/'). index.html
entry scripts and the favicon were rewritten to include the reverse-proxy
prefix in serveIndex, but two reference kinds are not in index.html and so
bypassed that rewrite:
- CSS `url()` font references (e.g. Font Awesome .woff2), which the browser
resolves relative to the stylesheet and which `<base href>` never affects
- lazily-imported route chunks, whose preload base came from the absolute
Vite base
Under a subpath mount (X-Forwarded-Prefix: /llm/) both were fetched from the
origin root, 404ing — missing-glyph "tofu" icons and broken lazy-loaded pages.
Switch Vite to a relative base ('./') so every generated URL resolves against
the file that references it: CSS fonts and route chunks now load from
`/llm/assets/...`, and index.html's now-relative entry refs resolve via the
`<base href>` serveIndex already injects on every response. Root deployments
are unaffected. The existing path-absolute rewrite in app.go still covers the
public `/favicon.svg`.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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mudler's LocalAI [bot]
|
2dade4a9f9 |
fix(model-artifacts): gate inferred artifact materialization by backend (#10910)
The managed-artifact materializer stages a HuggingFace snapshot into a directory (.artifacts/huggingface/<key>/snapshot/). That is the right load target for directory-consuming backends (transformers, vLLM, diffusers, ...), but PrimaryArtifactSpec inferred a managed artifact from ANY HuggingFace-shaped model reference regardless of backend. A single-file backend such as llama.cpp or whisper was therefore handed the snapshot directory instead of the weight file and failed to load it. The /import-model importer already guards this with a backend allow-list (managedArtifactBackends), but the loader-side inference did not. Move the allow-list into core/config as IsManagedArtifactBackend and apply it in PrimaryArtifactSpec: only directory-consuming backends may have an artifact inferred from a bare reference; every other backend stays on the legacy download-to-file path. An explicit artifacts: block still bypasses the gate, where single-file snapshot resolution handles the load path. The importer now shares the same predicate, so both paths agree on which backends auto-materialize. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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localai-org-maint-bot
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279f5b8a93 |
fix(model-artifacts): load single-file HF snapshots from the file, not the directory (#10909)
fix(model-artifacts): load single-file HF snapshots from the file, not the dir The managed Hugging Face artifact materializer (#10825) always pointed backends at the snapshot *directory* (.artifacts/huggingface/<key>/snapshot). For a single-file model reference such as huggingface://nomic-ai/nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf, the GGUF lives *inside* that directory, so llama.cpp was handed a directory and failed with "gguf_init_from_reader: failed to read magic". This has kept the tests-aio job red on master since the feature merged (the embeddings e2e tests could not load text-embedding-ada-002). Record the single file of a one-file snapshot as Resolved.PrimaryFile and have ModelFileName() resolve to snapshot/<PrimaryFile> when it is set. Multi-file snapshots (e.g. transformers repos consumed as a directory) keep pointing at the snapshot directory. PrimaryFile is derived from the resolved contents and is deliberately excluded from the artifact cache key. estimateModelSizeBytes now derives the snapshot directory from the cache key instead of ModelFileName(), so its manifest lookup is unaffected by the file-vs-directory resolution. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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mudler's LocalAI [bot]
|
a89d780707 |
fix(gallery): keep multi-file HF install progress proportional during verify (#10908)
The artifact progress bridge mapped every PhaseVerifying event to a flat 95%. The materializer emits PhaseVerifying once per file (from each file's AfterDownload hook) and downloads run sequentially, so the first small file to finish pinned the bar at 95% - and, because progress is monotonic, it stayed at 95% for the entire remaining download (e.g. a 70GB checkpoint reporting 95% at 410MB / 69.7GB). Track per-file verify proportionally to the running aggregate bytes, the same way downloading does. CurrentBytes already reflects "completed files + this file", so the percentage advances honestly. The flat 95%/99% is now reserved for the genuinely once-per-install Committing/Persisting phases. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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localai-org-maint-bot
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4be6e22b5f |
feat(webui): surface user, client IP and user agent in API traces (#10886, #10887) (#10907)
The Operate → Traces "API Traces" panel already recorded who made each request (user_id/user_name) but never showed it, and did not capture the caller's network identity at all. Operators asked to see the requesting user (#10886) and the client IP + user agent (#10887) so a trace can be attributed to who/what issued it. Backend: add ClientIP and UserAgent to APIExchange and populate them from echo's c.RealIP() (honours X-Forwarded-For / X-Real-IP behind a trusted proxy) and the request's User-Agent header. Both are omitempty and the /api/traces swagger response is map[string]any, so this is additive. UI: add a sortable "User" column to the API traces table and a metadata block (User / Client IP / User Agent) at the top of the expanded row detail. Fields render only when present, so older buffered traces and unauthenticated/local requests degrade cleanly. Adds an e2e spec covering the new column value and the expanded metadata. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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localai-org-maint-bot
|
bf484c5181 |
feat(webui): show date alongside time in the Traces view (#10888) (#10905)
The Operate -> Traces table rendered the request time with the time of day only, so entries that span more than one day were ambiguous. Add a formatDateTime helper (localized date + existing time-with-millis) and use it for the Traces "Time" column, keeping the cell on a single line. The shared formatTimestamp used by the log views is unchanged. Assisted-by: Claude:opus-4.8 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io> |
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futurehua
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d3ea65a112 |
refactor: replace Split in loops with more efficient SplitSeq (#10879)
Signed-off-by: futurehua <futurehua@outlook.com> |
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walcz-de
|
6ccb1130d8 |
fix(agent-ui): reset streamed text at generation boundaries in agent chat (#10664)
One agent turn runs several internal LLM generations (tool selection, reasoning, final answer) that all emit stream_event deltas over the same per-agent SSE channel. The chat page accumulated every 'content' delta into a single live bubble and ignored the 'done' boundary events, so the internal generations' text (e.g. the English tool-selection rationale) merged with — and visually corrupted — the streamed final answer. Reset the accumulated content/reasoning on 'done': each generation gets a clean live bubble, and the authoritative full answer still arrives via the final json_message event as before. Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> |
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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> |
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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> |
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Tai An
|
dc2cc4da43 |
fix(audio-transform): serialize WebSocket writes to avoid concurrent-write panic (#10857)
* fix(audio-transform): serialize WebSocket writes to avoid concurrent-write panic AudioTransformStreamEndpoint writes to the same Gorilla WebSocket connection from two goroutines: the backend-forwarding goroutine emits binary PCM frames (and can call sendWSError on a backend recv error), while the read loop calls sendWSError for malformed mid-stream JSON or a backend send failure. Gorilla WebSocket permits only one concurrent writer, so these writers race and can panic with "concurrent write to websocket connection", resetting the client session; a -race build reports the data race directly. Wrap the connection in a lockedConn that serializes WriteMessage behind a mutex, mirroring the existing lockedConn used by the openresponses WebSocket endpoint. Reads stay on the single read loop, so only writes need the lock. Fixes #10844 Signed-off-by: Tai An <antai12232931@outlook.com> * chore: empty commit to re-trigger checks Signed-off-by: Anai-Guo <antai12232931@anaiguo.com> --------- Signed-off-by: Tai An <antai12232931@outlook.com> Signed-off-by: Anai-Guo <antai12232931@anaiguo.com> Co-authored-by: Anai-Guo <antai12232931@anaiguo.com> |
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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> |
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Tai An
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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> |
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Tai An
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5fe48e4910 |
fix(backend): don't crash the whole process on an invalid cutstrings/extract_regex (#10855)
Finetune() compiled every model cutstrings/extract_regex entry via regexp.Compile
and called xlog.Fatal on failure, which terminates the entire local-ai process.
A single model config with an invalid regex (e.g. cutstrings: ["("]) turns one
/v1/chat/completions request into a process-level denial of service.
Log the compile error and skip the offending pattern instead. The mutex is
released before continuing, and skipping avoids dereferencing the nil regexp
that removing the fatal would otherwise leave behind.
Fixes #10843
Signed-off-by: Tai An <antai12232931@outlook.com>
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