* fix(schema): preserve SystemOne image inputs
Assisted-by: OpenAI
* test(schema): follow Ginkgo conventions for decision inputs
Assisted-by: OpenAI
* feat(llama-cpp): dispatch native decisions through Score
Upgrade the stock dependency and reconcile Score/TTS patches. Reuse native decision parsing, tasks, formatting and response-reader cleanup; preserve ordinary scoring admission and guard older dependencies.
Assisted-by: OpenAI
* refactor(systemone): share request and model validation
Assisted-by: OpenAI:gpt-5
* fix(systemone): preserve HTTP wire-byte validation limit
Keep structural validation separate from the serialized internal request bound so HTML escaping cannot reject valid HTTP payloads.
Assisted-by: OpenAI:gpt-5
* feat(systemone): bound images and account native decisions
Preserve public wire limits independently from router serialization. Reject unsupported NER images, map native request/capability errors, and stamp explicit usage once. Advertise decisions for stock llama-cpp.
Assisted-by: OpenAI
* fix(systemone): record usage on registered native route
Exercise real registration and billing with a mock native backend. Reject empty native responses, malformed image URLs, trailing JSON, and wire overflow including whitespace.
Assisted-by: OpenAI
* feat(router): add lazy native decision transport
Bind named models through internal ModelSystemOne calls with shared validation and bounded abandoned operations. Remove request and echoed-error contents from decision traces.
Assisted-by: OpenAI:gpt-5
* feat(router): classify overlapping policies with native decisions
Ask independent noul questions, validate probabilities and preserve first-superset routing. Wire the central factory with config-sensitive invalidation and cancellation-safe resolution. Document native framing and bounded operation limits.
Assisted-by: OpenAI:gpt-5
* feat(gallery): add pinned Julia-1 native decision model
Add a separate text-only llama-cpp Q8 entry with pinned Apache-2.0 source provenance and checksum. Installed using the gallery installer and exercised choice, score and noul on CPU.
Assisted-by: OpenAI
* test(router): verify native decisions through central factory
Add an opt-in real-model Ginkgo integration covering the native Go loader and C++ transport, token usage, independent overlapping labels, and candidate selection. Document owned-server execution and the intentionally non-quality threshold.
Assisted-by: Codex:gpt-5
* fix(llama-cpp): align upstream pin and preserve decision signatures
Advance to bed0a856 without losing the automated upstream bump. Detect full-request fill_task support at compile time and forward every question for Nimble framing while retaining the earlier native signature. Preserve reconciled SCORE/TTS patches; add standalone compatibility coverage.
Assisted-by: Codex:gpt-5
* feat(gallery): add native decision family defaults
Pin Laya, Kev-4B, lev, OpenJev and Nimble artifacts. Verify Laya/Kev/lev gallery installs and CPU contracts on both native pins; clearly mark OpenJev/Nimble runtime validation pending and their noncommercial licenses.
Assisted-by: OpenAI
* docs(decisions): clarify integrated Nimble prerequisite
Record the exact combined backend pin while retaining pending OpenJev and Nimble installation/runtime validation status.
Assisted-by: Codex:gpt-5
* fix(gallery): indent native decision model sequences
Match repository yamllint indentation for Laya, Kev, lev and OpenJev list fields. Parsed gallery data is unchanged; reproduce CI gallery lint failure before the whitespace-only fix and pass the same command afterward.
Assisted-by: Codex:gpt-5
* docs(decisions): record OpenJev and Nimble CPU validation
Record gallery installation, checksum/metadata verification and multiquestion native smoke results on bed0a856. Retain noncommercial and text-only limitations without accuracy or deterministic-output claims.
Assisted-by: OpenAI
* fix(ui): expose native Decisions router classifiers
Select classifier models using metadata-driven capability routing, retain tuned thresholds, and validate native decision selections before saving. Cover both native backends and create/save/reopen in the real React editor.
Assisted-by: Codex:gpt-5
* fix(router): exclude aliases from native decision discovery
Check the originally named config before advertising native Decisions eligibility. Retain target capability inheritance for ordinary generation aliases. Exercise the actual capabilities endpoint with native models on both backends, aliases, and disabled models.
Assisted-by: Codex:gpt-5
* feat(systemone): share bounded multimodal input validation
Preserve text wire limits while admitting bounded PNG/JPEG decision input. Share collection and header validation across internal and public callers and keep the native runner response budget independent.
Assisted-by: OpenAI:API-assistant
* fix(systemone): bound admission lifetimes and validate complete images
Retain shared admission leases through actual work completion, including abandoned internal operations. Decode bounded image pixels, cap public native responses before usage stamping, and preserve oversized malformed text status precedence.
Assisted-by: OpenAI:API-assistant
* fix(router): classify images before media fetching
Preserve ordered structured probes for native decisions. Defer OpenAI
media preparation until routing selects the served model, so rejected
decision URLs cannot trigger downloads before shared validation.
Guard direct image collection with context-aware shared admission.
Keep text classifiers and embedding caches from discarding image input.
Retain fail-closed classifier configuration and runtime fallback policy.
Add middleware, typed-content, admission, cancellation and cache tests.
Assisted-by: OpenAI:API-assistant
* fix(router): bound extraction before serialization
Check probe budgets before copying text or marshaling message state.
Count JSON escaping so oversized internal inputs fail before allocation.
Preserve typed Anthropic blocks through selected-model conversion and
fallback. Keep retry coverage in Ginkgo without global test registration.
Assisted-by: OpenAI
* fix(router): bound supported probe serialization
Arbitrary structs can bypass the probe budget through pointer marshalers,
string tags, and promoted fields. Accept concrete chat schema types and
plain JSON values instead of emulating arbitrary struct serialization.
Budget escaped direct prompts before marshaling so raw length cannot hide
serialized expansion. Preserve runtime fallback and reject oversized
input before invoking the decision runner.
Add Ginkgo allocation, boundary, and marshaler invocation regressions.
Six-package tests, three-package race tests, and full-T2 delta lint pass.
Assisted-by: OpenAI:GPT-5 golangci-lint
* feat(decisions): enable bounded OpenJev images
Validate native decision images before permissive media parsing and pixel
allocation. Require both decision image support and a vision projector;
missing or audio-only projectors cannot silently become text decisions.
Pin the OpenJev Q8 projector and document its license and disk footprint.
Add native safety tests, canonical limit parity, gallery and load-option
checks, and a reproducible CPU direct-RPC contrasting-image smoke.
Assisted-by: OpenAI:GPT-5
* fix(decisions): reject incomplete image streams
stb accepts corrupt PNG Adler checksums and truncated JPEG scans.
Use bounded zlib validation and strict libjpeg decoding before parsing.
Keep dimension and aggregate pixel checks ahead of decoder allocations.
Wire decoder dependencies into native builds and runtime packaging.
Add regressions for appended EOI and embedded marker bypasses.
Assisted-by: OpenAI:GPT-5
* fix(ci): gate native decision image validation
Run the decoder security tests outside the stdlib-only native suite.
Fetch vendor headers at the backend pin and provision decoder dependencies.
Gate Go limit parity and production CMake wiring without model downloads.
Assisted-by: OpenAI:GPT-5
* test(decisions): cover multimodal public API paths
Exercise shared image contracts through the registered HTTP routes and
external mock backend. Add opt-in cached gallery installation and real
OpenJev image decisions through SystemOne and both routing APIs.
Assisted-by: Codex:gpt-5
* test(decisions): assert isolation and cache bypass
Observe external RPC calls and compare complete classifier history.
Winner-only and cache-miss checks could hide dropped history or cache use.
Give real inference its own application and model directory so shared
backend mappings and loaded processes cannot affect mixed suite order.
Assisted-by: OpenAI:ChatGPT
* test(decisions): isolate fixture globals
Disable optional global services in the isolated HTTP fixture and register
cleanup before setup assertions. Verify meter provider identity survives
fixture creation and destruction.
Snapshot observed usage before assertions so failures cannot retain the
mutex. Require a successful usage stamp before checking error responses.
Assisted-by: Codex:gpt-5 golangci-lint
* fix(application): honor optional telemetry controls
Skip failover gauge registration when metrics are disabled. Register
against the application meter rather than looking up the global provider.
Allow embedders to retain the bounded routing log without billing stats.
Keep the existing default when stats are disabled. The isolated HTTP
fixture uses this option without losing its native router assertions.
Assisted-by: Codex:gpt-5 golangci-lint
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(schema): validate portable speaker profiles
Add the versioned profile schema for explicit speaker enrollment.
Validate compatibility against separately supplied loaded-encoder metadata.
Reject unusable speakers, invalid vectors, and inconsistent clean spans.
This slice does not change HTTP routes, backend integration, or the UI.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet): export profiles with transcripts
Export opt-in speaker profiles and trusted encoder metadata.
Replay registrations by ID so duplicate display names keep independent
vectors.
Use one profile-capable diarization for slots, names, and clean spans.
Assign timestamped ASR words to those slots without a second diarization.
Preserve legacy opt-out and no-ASR behavior, and propagate failures.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(audio): enroll portable speaker profiles
Gate profile exports with voice-recognition permission and validate
registration against metadata from the loaded encoder. Preserve audio
enrollment and independent registrations with duplicate display names.
Exclude diarization and registration exchanges before API trace capture
so persisted traces cannot retain profile vectors or JSON audio.
Defer candidate dimensions to trusted loaded metadata. Sort candidates
by registration ID so incompatible profiles cannot suppress legacy voices
through registry iteration order. Keep portable identity checks closed
when trusted metadata is unavailable.
Test persisted traces, explicit slot zero, and selection through offline
and live transport. Document privacy and the ephemeral registry lifecycle.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): remember speakers from diarization
Add a Studio page for diarization and opt-in speaker profiles. Preview
clean intervals from the original recording before explicit registration.
Join profiles by raw speaker labels, preserve duplicate names, and relabel
turns only after a successful save. Discard stale results when the model
or recording changes. Share registration metadata with voice management
without storing vectors or recordings from this flow.
Document permissions and the global, ephemeral registry. Cover enrollment,
permissions, previews, and asynchronous races with mocked Playwright tests.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: clarify HTTP speaker enrollment support
Replace the stale enrollment limitation with the current HTTP workflow.
Distinguish native transport from explicit registration and link its docs.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(parakeet): pin merged speaker profile support
Use the merged commit from mudler/parakeet.cpp#80.
Its tree matches the previously accepted native pin.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: add diarization enrollment setup example
Connect the existing gallery modes to the speaker enrollment workflow.
Show installation, private profile export, explicit raw-slot registration,
and later recognition without another export.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(blog): explain diarization speaker profiles
Put the diarization walkthrough on the LocalAI website in the feature PR.
Cover the three gallery modes, explicit enrollment, and privacy limits.
Link setup instructions and keep availability conditional on feature support.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(blog): focus diarization on everyday use
Explain what users can do with recordings before the setup steps.
Replace the technical walkthrough with a short Studio guide and link
readers to the existing reference for model names and developer use.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(blog): lead with speaker capabilities
Present speaker recognition through everyday uses and a short UI flow.
Keep technical reference details in the existing documentation.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(diarization): satisfy Go lint checks
Avoid copying protobuf message state when extending backend status, check the multipart reader close result, and document the focused testing.T lint exemptions.
Assisted-by: nib:gpt-5.6-sol
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The usecase describes what a model can do, and the category is the Decisions
API. SystemOne stays as the wire contract: the /v1/systemone routes, the
Score RPC question_type and the swagger tag are unchanged. The usecase,
flag, auth feature, UI label, gallery tags and docs page are now decisions.
Assisted-by: Claude Code:claude-sonnet-5-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
The React UI read every non-media attachment with file.text(). For a PDF
that decodes the binary bytes as UTF-8, so the model received raw
"%PDF ... stream ... endobj" noise instead of the document. The legacy
Alpine UI ran pdf.js; that step was not ported when the React UI
replaced it, but both file pickers still advertise .pdf.
Add a shared readAttachmentText helper that routes PDFs through
pdfjs-dist and reads other files as before. pdf.js and its worker load
on first use, so the main bundle does not grow. A PDF that cannot be
parsed or has no text layer (scanned, encrypted, damaged) is rejected
with a toast instead of being attached as an empty or garbage file.
Cover the chat and home paths with Playwright specs that build a real
PDF in the test.
Assisted-by: Claude Code:claude-sonnet-5-5 [playwright] [eslint]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ci: bump Hugo from 0.146.3 to 0.166.0
The hugo-theme-relearn submodule was bumped to 9.1.x in #12096,
which requires Hugo >= 0.165.0. The pinned 0.146.3 broke the docs
site build with a template error in alias.html that could not
evaluate the Locale field on langs.Language.
Bump HUGO_VERSION to 0.166.0 (latest stable) to satisfy the
theme minimum and resolve the alias.html template error.
Assisted-by: nib:claude-sonnet-4.5 [bash] [read] [edit]
* feat(distributed): report worker version and show models in node inspector
Workers now send their LocalAI build version and git commit at
registration. The controller stores them on BackendNode and exposes
them through the existing node list/detail API responses.
The node inspector side pane now fetches and renders the list of
loaded models (name, state, in-flight) instead of showing only a
count, matching what the node detail page already displays.
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat: return 429 when backends are saturated
When backends are at capacity (per-model max_concurrent or the
process-wide --max-concurrent-backend-requests ceiling), the response
was 503. The OpenAI SDK, litellm, and most agent harnesses key on 429
for rate-limit backoff and treat 503 as a hard error.
Both saturation paths now return 429 with the existing Retry-After
header and type: "rate_limit_error" in the JSON body. The per-model
admission middleware keeps admission_rejected as the code field so
existing alerts that match on it still fire.
Non-saturation 503s are unchanged: model cold-loading (with progress
body), model-load failure cooldown, PII detector fail-closed, and
classifier unavailable. These mean "not ready" rather than "busy".
Assisted-by: AGENT:regolo/glm5.2 [TOOL]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: return 503 when scheduler has no available nodes
When the scheduler cannot find any healthy node to serve a model —
all nodes are full and eviction cannot free a slot, or a node_selector
excludes every candidate — the error fell through to 500. A 500 tells
clients something is broken when the condition is transient and
retryable.
The router now wraps these errors with a new ErrNoAvailableNodes
sentinel. The HTTP error handler maps it to 503 via applyNoAvailableNodes,
following the same pattern as applyBackendAdmission (429). Unrelated
scheduler errors (DB timeouts, registry lookups) still return 500.
Three return sites are wrapped:
- resolveSelectorCandidates: selector matches zero healthy nodes
- scheduleNewModel eviction-busy: all models have in-flight requests
- scheduleNewModel eviction-failed: eviction itself errored
The existing scheduleAndLoad wrapper ("no available nodes: %w") preserves
the sentinel through the chain via errors.Is, as does ModelRouterAdapter.
Assisted-by: AGENT:regolo/glm5.2 [TOOL]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(http): use Ginkgo for admission tests
Replace forbidden testing.T calls with Ginkgo and Gomega so the lint
check accepts the admission handler tests.
Assisted-by: Codex:GPT-6 forbidigo
* fix(middleware): show the recorded status for admission rejections
The admission audit row now records 429, but the Middleware page still
printed a hard-coded 503. Read the status from the event, and update
the two package comments that still said 503.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Editing a failover chain now shows its state, the target serving it,
and a per-target health table under the editor header. The strip reads
GET /api/failover and follows /api/failover/events, with a 15 s re-list
to cover SSE reconnect gaps. Admins can pin a target or unpin the chain
after a confirmation.
Assisted-by: Claude:claude-opus-5-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Warm local targets are pinned in the watchdog and preloaded. Switches
and target health are exported as metrics, skipped attempts as traces.
Assisted-by: Claude:claude-opus-5-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
On a single-node install nothing in Operate listed the models loaded on
this machine or let an admin stop one. The System page that did was
retired in #11548, and its replacements (the Nodes workbench) only work
in distributed mode. The Nodes page also mis-detected single-node mode:
the cluster routes are not registered there, so /api/nodes answers 404,
but only 503 was treated as "distributed off", which sent every
single-node install to the empty worker-registration card. The rail hid
the entry anyway.
Nodes route on a single node becomes "This machine":
- the Nodes page's VRAM / RAM / CPU / models-disk gauges, fed from this
host by mapping /api/resources onto the worker heartbeat fields
- a memory bar splitting host RAM by running model
- a running-models table (backend, RSS, CPU share, uptime, PID) with
search, sorting, logs and a confirmed Stop
- the distributed setup behind an "Add machines" button
The Operate overview gains a "Running now" preview (heaviest five, with
Stop) on single node and a pointer to Nodes > Running models on a
cluster. The rail shows "This machine" in Runtime with a running count.
Backend, additive only:
- /system: each loaded model carries a `process` block (pid, rss_bytes,
memory_percent, cpu_percent, started_at). A sampler keeps one gopsutil
handle per PID so CPU is the share since the previous poll rather than
the lifetime average; it is omitted on the first reading.
- /api/resources: host `cpu` and models-path `disk`, the same readings
workers send in their heartbeat.
Also fixes the fleet tables widening the page on phones: the headers'
absolutely positioned sr-only labels escaped the scroll wrapper.
Assisted-by: Claude:claude-opus-5 [Playwright]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The global ::selection used --color-primary-light (14% primary), which
composites to about 1.1:1 against the dark page ground — selected text
was nearly indistinguishable from unselected. Give selection its own
token in both palettes and align the CodeMirror themes with the same
strengths.
Assisted-by: Claude:claude-fable-5
Signed-off-by: Plamen K. Kosseff <p.kosseff@gmail.com>
* fix(vulkan): preserve host ICD discovery for packaged backends
Add bundled Mesa manifests through VK_ADD_DRIVER_FILES instead of replacing the system driver list. Merge inherited and model-specific additive paths while preserving explicit operator overrides, with regression coverage.
Assisted-by: Codex:gpt-5 golangci-lint
Assisted-by: Codex:gpt-5.6-sol
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(3d): add Kimodo CPU and Vulkan animation backend
Introduce a distinct animation capability and model-described 3D operations, with a typed /3d/animate API, RPC transport, distributed media staging, permissions, and tracing.
Add a persistent kimodo.cpp adapter, skeleton GLB export, CPU/Vulkan packages, model and backend galleries, importer support, CI builds, and documentation. Adapt Studio inputs to each model and provide real-time skeleton playback, seeking, and history.
Cover backend validation, packaging, API behavior, importer inventories, distributed staging, and Studio workflows. Validate real-model CPU/Vulkan generation and deploy the integration to the local QA instance.
Assisted-by: Codex:gpt-5 golangci-lint
Assisted-by: Codex:gpt-5.6-sol
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(kimodocpp): adopt monolithic encoders and resident inference
Update upstream for resident weights, packed execution paths, and cached motion graphs. Default to all 32 text layers while retaining configurable streaming and legacy bundle support.
Use monolithic Q8_0 encoders by default and offer all six published quantizations through the gallery and importer. Refresh pinned hashes, tests, and documentation; remove the obsolete thread patch and ensure cached source checkouts follow the upstream pin.
Validated CPU and Vulkan generation, lower-bit streaming, gallery/importer suites, packaging, lint, and cold/warm Studio generation on localai-dev.
Assisted-by: Codex:gpt-5 golangci-lint
Assisted-by: Codex:gpt-5.6-sol
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
The node detail redesign moved backend operations into an action menu.
Four existing specs still search for the removed direct buttons, so the
UI E2E workflow fails consistently on master.
Open the backend action menu before checking or activating its items.
Assisted-by: Codex:gpt-5
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The node restructure hid backend logs and split related controls
across inconsistent layouts.
Restore contextual log actions and align the detail page with the
fleet dashboard. Make multi-node selection clear and accessible.
Assisted-by: Codex:gpt-5 Playwright ESLint
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Agent Status replaced the chat route and unmounted its EventSource. Any response still in flight could then disappear from the conversation.\n\nOpen status in a separate tab so the chat keeps its live connection until the response completes.\n\nAssisted-by: Codex:gpt-5 [eslint]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Saved profiles previously resolved to one audio path and transcript, so
cloning backends could not use several examples of one personality.
Store ordered audio and transcript pairs while preserving the legacy
first-reference fields. Fish Speech and audio.cpp receive all pairs,
including on distributed workers. Other backends retain their
single-reference behavior.
Assisted-by: Codex:gpt-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
The API mock also matched navigation to /app/tts and returned a WAV download instead of the React page. Let non-POST requests reach the test server.
Assisted-by: Codex:gpt-5 [Playwright]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
TTS instructions add a second textarea to the page. Target the speech input by its placeholder so the history test does not depend on the page having one textarea.
Assisted-by: Codex:gpt-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Let studio users guide speech delivery for backends that support request instructions. Blank guidance stays out of requests and media history.
Assisted-by: Codex:gpt-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
fix(ui): preserve decoded route parameters
React Router already decodes dynamic path segments before exposing them through useParams. Decoding those values again crashes pages for names containing a literal percent sign and mutates escape-like substrings.
Use route parameters as-is, encode the model editor API path at the outbound boundary, and cover all affected pages with Playwright.
Fixes#11882
Assisted-by: Codex:gpt-5 eslint playwright
Signed-off-by: QiuLG <l237455523@outlook.com>
When no sampled candidate fits GPU memory, ranking falls back to the
oversized pool and labels its first model Best fit. Keep GPU picks within
the existing 95% budget and hide the section when no candidate qualifies.
Remove static GPU starter picks so Home cannot reintroduce the same error.
Add browser regressions for both sections and document the empty result.
CPU fallback behavior stays unchanged.
Assisted-by: Codex:gpt-6 [Codex]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Web Chat Settings left the System Prompt field empty but still treated a
blank/whitespace value as an explicit system turn. That satisfied
tokenizer chat templates' messages[0].role == system check and suppressed
the model YAML system_prompt on fresh chats.
Omit empty/whitespace system messages in the React and Alpine UIs, strip
them server-side, and inject config.SystemPrompt for tokenizer-template
models when the request has no real system turn.
Fixes#11834
Signed-off-by: lei_lei <96427312+leilei3167@users.noreply.github.com>
Node placement and replica rules could only name a model, so an operator
who pinned "llama3" to the GPU tier had to rewrite the rule whenever a
different model took over that job. An alias already gives a stable name
for whichever model serves it, and a rule on that name makes it a
deployment slot: repoint the alias and the placement follows.
A rule keeps the name the operator chose. Reads resolve that name through
the config loader to the model the rule governs, so the reconciler counts,
schedules and trims replicas of the target, and the router finds an
alias-keyed rule from the target it is already routing. An alias that
resolves to nothing governs nothing loadable, so the reconciler skips it
and the write paths refuse it.
A replica is shared by every name that resolves to it, so only one rule
can decide where it runs. The REST and MCP write paths reject a rule whose
target another rule already governs. A pair that arrives some other way,
such as a seed file or an alias repointed onto a model that already has a
rule, resolves in favour of the rule named after the model itself and then
the oldest, and the rest are listed as shadowed.
The eviction guard is the exception: it matches rules to replicas in raw
SQL inside a locking transaction and cannot resolve an alias. It reads a
stored target that the reconciler refreshes each tick, and falls back to
the rule's own name when that target is empty.
Assisted-by: Claude:claude-opus-5 golangci-lint eslint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(ui): move node labels into the scheduling selector field
The scheduling page kept a node-label browser open above the rules
whether or not anyone was writing one, while the field that actually
needs labels, the rule's node selector, was two bare text inputs with no
hint of what the cluster reports.
The browser is gone. The selector's key input now completes against the
label keys the cluster uses, and the value input offers only the values
that key takes. The roster already loads for the page, so the
suggestions cost no request, and a roster that fails to load costs the
admin the hints and nothing else.
Suggestions stay suggestions: a key no node reports yet still commits as
typed, which is how an admin writes a rule before labelling the nodes
for it.
Assisted-by: Claude:claude-opus-5 golangci-lint eslint playwright
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): size model fit against the cluster, not the frontend
The models page asked the frontend how much memory a model may occupy.
In distributed mode the frontend is usually a GPU-less pod while every
model runs on a worker, so a fleet of GPU nodes was told it could only
run the smallest CPU build. The variant picker's fits flag and its
auto-selection came from the same place, as did the hardware
recommendations.
The registry now reports the largest single healthy backend node. The
largest node, not the fleet total: a model loads into one node, so four
16GB workers are not a home for a 40GB model. An operator-set VRAM
budget caps a node's contribution, because the scheduler refuses a load
above that ceiling anyway, and a GPU node beats a CPU node holding more
system RAM.
GET /api/resources and GET /api/models carry this as an additional
cluster object. Their aggregate and ram fields keep reporting the
frontend's own hardware, which is what the resource monitor shows.
Variant selection judges backends against the union of the capabilities
present in the cluster, the way backend discovery already did.
Every path degrades to the local host: no cluster object in single-node
mode, and none when the registry cannot be read, so a hiccup narrows the
answer back to single-node behaviour rather than marking the whole
catalog too large.
The verdicts now name the node they belong to, since a model fits
somewhere or nowhere.
Assisted-by: Claude:claude-opus-5 golangci-lint eslint playwright
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vram): persist remote probe metadata
The startup warmer repeated remote size and GGUF metadata probes after every restart because both caches lived only in memory. Store successful HTTP probes for 24 hours so frequent restarts reuse the prior results.
Bound the cache, reject invalid records, and purge it when gallery data changes. Local model files continue to bypass persistence.
Assisted-by: Codex:gpt-5
* fix(vram): check temporary file cleanup
The lint gate rejects the unchecked cleanup call in the persistent cache writer.
Assisted-by: Codex:gpt-5.6 [golangci-lint]
* fix(vram): make persistent cache optional
Remote metadata probes can transfer enough data that operators need
control over disk reuse and startup warming. Gallery autoload now gates
both behaviors, and the runtime setting applies changes immediately.
Assisted-by: Codex:gpt-5
* fix(ui): expose gallery startup pre-warm
The existing gallery autoload setting also gates the startup metadata warmer. Name both effects in Settings so operators can find the requested boot control.
Assisted-by: Codex:gpt-5
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix: GHSA-qwww-vcr4-c8h2 security vulnerability
Automated dependency upgrade by OrbisAI Security
Signed-off-by: anupamme <mediratta@gmail.com>
* fix: upgrade react-router-dom to 7.18.2 to fully remediate GHSA-qwww-vcr4-c8h2
The prior fix pinned react-router@7.18.2 directly but left react-router-dom
at ^7.18.1, which bun resolved to 7.18.1. That package bundles its own
react-router@7.18.1 sub-dep, leaving the vulnerable version in bun.lock
via the react-router-dom/react-router scoped resolution. Pinning
react-router-dom to 7.18.2 and regenerating the lockfile removes all
7.18.1 resolutions.
Assisted-by: Claude Code:claude-sonnet-4-6
Signed-off-by: Anupam Mediratta <mediratta@gmail.com>
---------
Signed-off-by: anupamme <mediratta@gmail.com>
Signed-off-by: Anupam Mediratta <mediratta@gmail.com>
The V8 coverage build inlines every dynamic import, so the stale chunk tests cannot intercept a page chunk. Run those tests against the normal code-split bundle and exclude them from the inlined coverage pass.
Assisted-by: Codex:gpt-5
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
A deploy replaces the whole content-hashed asset set at once. A tab
holding an older index.html, or one whose request lands on a replica
that the rollout has not swapped yet, asks for a page chunk the server
no longer has. The dynamic import rejects and React Router's default
error boundary replaces the app with "Unexpected Application Error!"
until someone reloads by hand.
The router now reloads the page itself when a chunk fails to load.
index.html is served no-cache, so the reload lands on a self-consistent
asset set. A timestamp in sessionStorage bounds this to one reload per
10 seconds, so a chunk that is genuinely gone reaches the error boundary
instead of looping forever.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-5[1m]
* feat(router): make KNN a first-class classifier with a persisted, curated corpus
Add `classifier: knn` — similarity-weighted voting over labelled
example prompts. Unlike score/colbert it needs no classifier model:
label knowledge lives in a corpus seeded and curated through the
admin API, so routing decisions are deterministic, auditable, and
grounded in graded experience rather than a model's opinion.
Epistemic gate: corpus entries below knn.similarity_threshold cannot
vote; when none clears it the classifier activates no labels and the
router uses the fallback — a prompt unlike all labelled experience is
treated as undecidable, not guessed. Decisions record
nearest_similarity (also on fallback rows) so admins can see how far
the nearest labelled experience was; the Routing tab explains
out-of-corpus fallbacks and shows per-label corpus counts.
Persistence: one JSONL file per router under
<data path>/router-corpus (text, labels, vector, embedder
fingerprint). The file is the source of truth; the local-store index
is rebuilt from it at classifier build time and stays a pure
in-memory index. Entries recorded under a different embedding model
re-embed on load. Also corrects the docs' false claim that
local-store collections persist — the embedding cache never survived
restarts (and still doesn't); the corpus does.
Corpus input is API-only by design (entries may contain example user
content): POST /api/router/{name}/corpus seeds (labels validated
against declared policies, embedded server-side, indexed
immediately), GET .../corpus/stats inspects — label counts only,
entry texts are never returned by any surface — DELETE .../corpus
wipes. Admin-gated like the sibling router endpoints, and exposed as
MCP tools (seed_router_corpus / get_router_corpus_stats /
clear_router_corpus) in both the httpapi and inproc clients with
coverage-test route mappings.
Plumbing: VectorStore gains SearchK (top-K was hardcoded to 1);
local-store gets InsertBatch/Delete as optional fast paths;
RouterConfig gains a knn block (embedding_model, k,
similarity_threshold, vote_threshold, store_name) with meta-registry
fields; the classifier dropdown now offers knn and the
previously-missing colbert; embedding_cache is ignored (with a
warning) for knn — it IS an embedding-KNN lookup; the stale
/api/instructions intelligent-routing entry is rewritten (it
described a classifier that no longer exists); swagger regenerated.
Tests: KNN vote/gate specs with hand-computed vote shares, corpus
manager suite (restart reload without re-embedding, fingerprint
re-embed, dedupe, hostile store names), middleware specs (corpus
routing, gate fallback, config validation, cache-wrap refusal),
corpus endpoint specs pinning the texts-never-returned contract, MCP
catalog + route-mapping gates, and a Playwright spec for corpus
stats and the out-of-corpus decision detail.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(router): name consulted corpus neighbours in knn decisions
Every knn decision (decision log rows and the /api/router/decide
response) now carries neighbors: the K retrieved corpus entries by
descending similarity - including ones below the epistemic gate, which
is what makes fallback decisions diagnosable - each as {id, similarity,
labels}. The id is the entry's content hash (first 8 bytes of the
SHA-256 of its text, hex): stable across reseeds and re-embeds, and
text-free, so an external platform that seeded the corpus can recompute
text->id on its own copy and bucket decisions by corpus region (per-
region reliability accounting) without corpus text ever leaving the
server. A corrupt index payload surfaces as an id-less neighbour at a
real similarity instead of disappearing.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* refactor(router): deduplicate knn plumbing and cut corpus hot-path waste
Post-review cleanup of the knn-first-class-router branch; no behaviour
changes on the API surface.
Reuse/altitude:
- RouterKNNConfig.ResolvedStoreName is now the single source of the
router-corpus-<name> default (was hand-derived in four files).
- corpus.ResolveKNNRouter + corpus.Seed carry the shared model
resolution and seed validation; the REST endpoints and the assistant
MCP client are thin transport adapters over them, with sentinel
errors mapped to HTTP statuses at the echo boundary.
- middleware.NewClassifierDeps assembles the classifier dependency set
once for all five entry points (OpenAI, Anthropic, realtime, decide,
corpus) instead of five hand-copied literals.
- router.AllClassifiers feeds both the status endpoint and the
unknown-classifier error, ending the classifier-list drift.
- Per-classifier requirements moved out of validateRouterPolicies into
their buildClassifier arms; the knn arm owns its embedding_cache
opt-out instead of a name-check in the shared wrap tail.
- adminOnly replaces four inline copies of the admin gate in the
middleware routes.
- localVectorStore.Search delegates to SearchK (identical traces).
Efficiency:
- Manager.Add embeds outside the manager mutex and appends to the
JSONL file (O(new) instead of O(corpus) rewrite); a torn tail from a
crash mid-append is tolerated on read and repaired on next write.
- Stats memoises per store keyed on the file's stat fingerprint and no
longer takes the manager mutex, so the 5s status poll stops parsing
vector-laden JSONL and stops blocking behind seeds.
- KNN Classify decodes each neighbour payload once (was twice) and
builds refs and votes in a single pass with one fallback return.
- Corpus file writes fsync before rename/close.
- The corpus manager is built eagerly in newApplication (sync.Once
dropped); test helper dead branch removed.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(router): bind knn corpus vectors to an embedder fingerprint and fail closed on mismatch
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(mcp): align corpus tool prompts and the mutating-tool safety list
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(proto,backend): report embedding shape from the llama-cpp backend
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(embeddings): Go-side pooling — mean/last/decayed_mean with half-life
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(embeddings): accept chat messages[] and per-request pooling on /v1/embeddings
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(middleware): name the failing fields when post-merge validation 400s
An intermittent post-merge validation failure surfaced as an opaque 400
during integration (pooling scheme mismatch that no client had sent).
Log the model, the request's pooling override, and the merged config's
pooling fields at the failure point so the next occurrence identifies
whether the request or the stored config carried the bad value.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(embeddings): scheme override must not inherit the config's half-life
A model config defaulting to decayed_mean pooling carries
pooling_half_life_tokens; a request overriding the scheme to mean/last
without its own half-life inherited that value, and post-merge
validation rejected the pair the server itself had assembled. Zero the
inherited half-life when the overridden scheme is not decayed_mean; a
request that explicitly pairs a half-life with a non-decayed scheme
still 400s.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix embedding pooling validation and router bounds
Declare backend embedding layouts and reject incompatible pooling modes. Reset local-store dimensions after a full clear, validate KNN thresholds, and add real backend and store integration coverage.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: run local-store integration tests
Build and install the local-store backend in the Linux test job, then run the existing store integration suite so new specs are discovered automatically.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
feat: bound backend admission and expose running traces
Add process-wide backend execution admission without blocking UI or administrative HTTP work. Represent backend operations while they are in flight, surface running traces with immediate log links, and tie streaming admission leases to the gRPC receive lifecycle.
Assisted-by: OpenAI Codex: GPT-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(ui): add installed model lifecycle
Models now owns catalog exploration and installed runtime controls under one canonical route. URL-owned state keeps lifecycle context recoverable through links and browser history.
Assisted-by: Codex:gpt-5 Playwright
* feat(ui): add installed backend lifecycle
Backends split discovery from backend-binary management. The canonical
page now keeps both lifecycle views under one URL-backed shell while it
preserves target-node placement.
Assisted-by: Codex:gpt-5 Playwright
* fix(ui): repair lifecycle state updates
Installed models lost distributed refreshes and kept a deleted selection. Backend searches also stopped tracking URL changes, while batch upgrades stopped after their first error.
Preserve background refreshes and finish each requested batch action. Drive catalog results from URL-backed state without losing full metadata.
Assisted-by: Codex:gpt-5 [Playwright]
* feat(ui): make resource pages canonical
Replace Host navigation with canonical Models and Backends lifecycle routes, preserve legacy management URLs, and surface shared host capacity on the Operate overview.
Assisted-by: Codex:gpt-5 [Playwright]
* feat(ui): complete canonical resource lifecycle
Finish the responsive list-to-detail behavior, remove the retired Host implementation, and keep Explore focused on discovery while Installed owns destructive actions. Update regression coverage, localization, documentation, and development binding for the canonical resource pages.
Assisted-by: Codex:gpt-5 [Playwright]
* docs(ui): record the UI design context
Record the approved users, brand character, and design principles so
future interface work uses the same product direction. Index the context
from the repository's agent instructions.
Assisted-by: Codex:gpt-5
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(advisorylock): set statement_timeout alongside lock_timeout
WithLockCtx already overrides a deployment-wide lock_timeout on its
dedicated connection so a blocking pg_advisory_lock() waits its turn
instead of failing with 55P03. statement_timeout aborts that exact same
statement independently, with SQLSTATE 57014, and was not overridden.
Production roles commonly carry statement_timeout=60s. Any guarded
section longer than that (a cold model load stages for tens of minutes)
therefore killed every concurrent waiter:
advisorylock: acquiring lock 9003261067483446873: ERROR: canceling
statement due to statement timeout (SQLSTATE 57014)
Derive it from the same context budget as lock_timeout, with a matching
RESET so the pooled connection is returned clean.
Assisted-by: Claude Opus 5 [claude-code]
* feat(distributed): add ModelLoadJob, the durable cold-load record
A cold load in distributed mode is a long-running background job, but it
was modelled as a synchronous side effect of an inference request: the
whole of it (backend install, multi-GB staging, checkpoint load) ran
inside the per-model advisory lock. Loading a 35.7 GB GGUF held that lock
for ~20 minutes, so every concurrent request for the same model blocked
on pg_advisory_lock and died at the role's 60s statement_timeout.
Introduce the row that lets the lock shrink to a decision. Exactly one
ModelLoadJob may be active per tracking key; that uniqueness — not the
lifetime of a lock — is what de-duplicates concurrent loaders across
replicas. ClaimLoadJob does its read-then-write under the advisory lock
and nothing else: no network, file or gRPC I/O inside the guarded
section, so a claim costs milliseconds no matter how long the resulting
load takes.
LastProgress is a heartbeat rather than a byte counter. A checkpoint load
legitimately moves zero bytes for many minutes, so a reaper keyed on byte
movement would reclaim a healthy job mid-load; byte progress stays the
concern of load_deadline.go. A job whose heartbeat stops for longer than
the orphan window is reclaimable, so a replica killed mid-load cannot
wedge a model permanently.
Failed jobs keep their row for a short grace so an immediately-following
request reports the real cause instead of silently starting a fresh load
of a model that just failed.
No caller yet — the router moves onto this in the next commit.
Assisted-by: Claude Opus 5 [claude-code]
* refactor(distributed): run cold loads as jobs, outside the advisory lock
Route wrapped the entire cold load — node selection, backend install,
multi-GB staging and the remote LoadModel — in the per-model advisory
lock. The lock's job is to de-duplicate concurrent loaders, a decision
that takes milliseconds; holding it for the tens of minutes the resulting
work takes is what turned a dedup mechanism into a cluster-wide outage
for that model.
Split it into a claim and a run. The claim is the only thing left inside
the lock. The run is a background job owned by the claiming replica and
bounded by the same progress-extended deadline as before; every other
request for that model — local or on another replica — attaches as a
waiter and is served the moment the model is ready, with no duplicate
load and no lock contention.
Waiters share one broadcast rather than an ordered queue: they all want
the identical outcome, so ordering them would add fairness machinery that
changes no result. The local channel wakes same-replica waiters instantly
and a 2s DB poll is the authority, because a waiter on another replica
has no channel to close. On wake a waiter re-runs the warm path rather
than trusting the signal — the model may have been evicted in between.
A waiter whose client disconnects returns immediately and the job keeps
running; it belongs to the job record, not to the request. A failure is
recorded on the row so every waiter reports the real cause, and the row
survives briefly so the next request does not read "no job" as "not
loading" and start a duplicate load of a model that just failed.
The runner heartbeats the row on a fixed interval whether or not bytes
are moving, which is what keeps a legitimately silent checkpoint load
from being reclaimed as an orphan. Phase (installing/staging/loading) and
placement ride to the heartbeat on the context, the same seam
load_deadline.go already uses, so single-host paths are untouched.
Non-distributed mode (no DB) keeps the inline load exactly as it was.
Assisted-by: Claude Opus 5 [claude-code]
* feat(distributed): bound the wait for a loading model and answer with progress
A request whose model is cold-loading now attaches to the running job and
is served the moment the model is ready. That wait has to be bounded: a
held HTTP request cannot survive real infrastructure, and an ingress or LB
idle timeout kills a twenty-minute request regardless of what LocalAI
does.
New LOCALAI_MODEL_LOAD_WAIT (default 60s) bounds the CALLER, never the
load — the job keeps running either way. On expiry the request gets 503
with Retry-After and a structured body naming the model, the node, the
phase, byte progress and an ETA. The `error` envelope keeps OpenAI
clients working; `loading` is additive so they ignore it.
The ETA comes from the job's own observed rate and is omitted rather than
guessed until enough bytes have moved for that rate to mean anything: a
confidently wrong ETA on a twenty-minute wait is worse than none.
Retry-After is that ETA when known, clamped to [5s, 300s], and the wait
budget otherwise.
LOCALAI_MODEL_LOAD_WAIT=0 waits unbounded, for deployments with no proxy
in front. Zero in the config struct still means "unset, use the default",
so the CLI records the operator's zero as ModelLoadWaitUnbounded rather
than losing the distinction.
The distributed branch of ModelLoader.loadModel wrapped the router's
error with %s, which flattened it to a string. Use %w: the typed error is
what the HTTP layer keys the 503 off.
Assisted-by: Claude Opus 5 [claude-code]
* feat(api): add GET /api/models/{id}/load-status
A client that receives 503 while a model stages onto a worker needs
somewhere to poll. This returns the same `loading` object the 503 carries
— phase, node, byte progress and ETA — or 404 when no load is running.
Read-only and observability-shaped, so it is deliberately neither
admin-gated nor feature-gated: it explains a 503 the caller just
received, and hiding that behind a per-modality feature would make the
explanation for a failed image request depend on chat permissions. It
also gets no MCP tool, since there is nothing here an admin would manage
conversationally.
Registered on the surfaces from .agents/api-endpoints-and-auth.md: the
swagger block (existing `models` tag, so /api/instructions needs no new
area), the endpoint discovery maps in RegisterLocalAIRoutes, regenerated
swagger, and the distributed-mode docs page. No FLAG_* usecase is
involved, so capabilities.js is unchanged.
Assisted-by: Claude Opus 5 [claude-code]
* feat(ui): show cold-load progress in Chat and retry when the model is ready
A chat request for a model that is still staging onto a worker now gets a
503 carrying live progress instead of an error. Render it: the composer
shows the phase (installing / staging / loading), the node, the percent
and the ETA, then polls load-status and re-sends the request the moment
the model is ready.
Reuses the staging progress idiom the page already had rather than
inventing a second one — the two sources are folded into one
loadProgress, with the load job winning because it is authoritative
across frontend replicas and knows the phase, where the staging operation
only knows about a byte transfer this replica happens to be performing.
Waiting is bounded (three send attempts, ~30 min of polling each), so a
load that never finishes still surfaces as an error rather than as a
spinner nobody questions. An aborted generation stops the polling too.
Assisted-by: Claude Opus 5 [claude-code]
* fix(distributed): check warm-path cleanup errors
The router moved legacy cleanup calls onto newly linted lines. Report
cleanup failures while preserving the fallback to a cold load.
Assisted-by: Codex:gpt-5 [golangci-lint]
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(ui): keep agent import action visible
The header hid its full import label after the agent list became non-empty. Hide only the nested file input so users can import more agents.
Assisted-by: Codex:gpt-5
* test(ui): match the agent import label
The Agents page renders the action as Import.
The test searched for Import Agent, so it failed before checking visibility.
Mock the observables request to remove backend timing from the fixture.
Assisted-by: Codex:gpt-5
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(mcp): surface configured server failures
Keep model-configured MCP servers visible when discovery or connection setup fails, propagate status through distributed discovery, and let the Chat UI show actionable errors while retrying unavailable servers.
Add model-editor metadata for remote and stdio configuration and document the expected format, deployment networking boundary, and alternate MCP scopes.
Assisted-by: Codex:gpt-5 Ordino golangci-lint
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* build(compose): match CUDA development image
Configure the API image with the cublas, CUDA 13, auth-tagged build settings used by the local development Makefile invocation, including the 24-way Docker build.
Assisted-by: Codex:gpt-5 Ordino
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* revert: keep host build settings out of compose
The CUDA development deployment is managed from ~/docker/localai, not the repository example Compose file. Restore the generic example and keep machine-specific build settings in the host deployment.
Assisted-by: Codex:gpt-5 Ordino
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(docker): exclude local agent artifacts
Keep Claude worktrees and locally installed verification tools out of the Docker build context. These host-only directories added roughly 1.9 GB to every root image build.
Assisted-by: Codex:gpt-5 Ordino
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
