754 Commits

Author SHA1 Message Date
LocalAI [bot]
a39591f144 realtime: honor output_modalities to skip TTS in text-only mode (#9838)
* realtime: honor output_modalities to skip TTS in text-only mode

The emulated realtime pipeline previously ignored the OpenAI Realtime spec
field output_modalities and always synthesized TTS. Add resolveOutputModalities
+ modalitiesContainAudio helpers and gate the TTS / ResponseOutputAudio*
emission so a client requesting ["text"] gets only ResponseOutputText* events.

This lets thin clients (e.g. thing5-poc) cache TTS on the client side while
still using the realtime WS for VAD + STT + LLM + tool-call parsing.

Assisted-by: Claude:claude-opus-4-7

* realtime: plumb response-level output_modalities and echo on session

Follow-up to the previous commit:
- Resolve response.create's output_modalities at the gate so a per-response
  override of an audio session is honored (the test asserted this contract
  but the production call site was passing nil).
- Mirror OutputModalities in the RealtimeSession echo so session.update
  round-trips the client-supplied value, matching MaxOutputTokens's pattern.

Assisted-by: Claude:claude-opus-4-7

* realtime: silence errcheck on deferred os.Remove of TTS file

CI's errcheck flagged the pre-existing `defer os.Remove(audioFilePath)`
inside the audio-emission block (now wrapped by the modality gate). Wrap
the call in a closure that explicitly discards the error — the canonical
Go pattern for "I want to defer a cleanup whose error I genuinely don't
care about."

Assisted-by: Claude:claude-opus-4-7 golangci-lint

---------

Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-15 12:39:47 +02:00
LocalAI [bot]
c33d36b870 fix(ollama): guard nil filter in galleryop.ListModels (#9817) (#9836)
The Ollama /api/tags handler passes a nil filter to galleryop.ListModels.
When ModelsPath contains any non-skipped loose file the function then
calls filter(name, nil) and panics, which Echo surfaces to clients as
"Server disconnected without sending a response" - the exact failure
Home Assistant's Ollama integration reports against LocalAI.

Mirror the nil guard already present in
ModelConfigLoader.GetModelConfigsByFilter so every caller is safe, and
add a regression test that exercises the loose-file path with a nil
filter.

Assisted-by: claude:claude-opus-4-7 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-15 10:07:50 +02:00
massy_o
745473cbe6 Validate video image URLs before download (#9819)
Signed-off-by: massy-o <telitos000@gmail.com>
2026-05-14 15:07:17 +02:00
LocalAI [bot]
8af963bdd9 fix(streaming): comply with OpenAI usage / stream_options spec (#9815)
* fix(streaming): comply with OpenAI usage / stream_options spec (#8546)

LocalAI emitted `"usage":{"prompt_tokens":0,...}` on every streamed
chunk because `OpenAIResponse.Usage` was a value type without
`omitempty`. The official OpenAI Node SDK and its consumers
(continuedev/continue, Kilo Code, Roo Code, Zed, IntelliJ Continue)
filter on a truthy `result.usage` to detect the trailing usage chunk;
LocalAI's zero-but-non-null usage on every intermediate chunk made
that filter swallow every content chunk and surface an empty chat
response while the server log looked successful.

Changes:

- `core/schema/openai.go`: `Usage *OpenAIUsage \`json:"usage,omitempty"\``
  so intermediate chunks no longer carry a `usage` key. Add
  `OpenAIRequest.StreamOptions` with `include_usage` to mirror OpenAI's
  request field.
- `core/http/endpoints/openai/chat.go` and `completion.go`: keep using
  the `Usage` struct field as an in-process channel for the running
  cumulative, but strip it before JSON marshalling. When the request
  set `stream_options.include_usage: true`, emit a dedicated trailing
  chunk with `"choices": []` and the populated usage (matching the
  OpenAI spec and llama.cpp's server behavior).
- `chat_emit.go`: new `streamUsageTrailerJSON` helper; drop the
  `usage` parameter from `buildNoActionFinalChunks` since chunks no
  longer carry usage.
- Update `image.go`, `inpainting.go`, `edit.go` to wrap their Usage
  values with `&` for the new pointer field.
- UI: send `stream_options:{include_usage:true}` from the React
  (`useChat.js`) and legacy (`static/chat.js`) chat clients so the
  token-count badge keeps populating now that the server is
  spec-compliant.

Tests:

- New `chat_stream_usage_test.go` pins the spec invariants:
  intermediate chunks have no `usage` key, the trailer JSON has
  `"choices":[]` and a populated `usage`, and `OpenAIRequest` parses
  `stream_options.include_usage`.
- Update `chat_emit_test.go` to reflect that finals no longer embed
  usage.

Verified against the live LocalAI instance: before the fix Continue's
filter logic swallowed 16/16 token chunks; with the new shape it
yields 4/5 and routes usage through the dedicated trailer chunk.

Fixes #8546

Assisted-by: Claude:opus-4.7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(streaming): silence errcheck on usage trailer Fprintf

The new spec-compliant `stream_options.include_usage` trailer writes
were flagged by errcheck since they're new code (golangci-lint runs
new-from-merge-base on master); the surrounding `fmt.Fprintf` data:
writes are grandfathered. Drop the return values explicitly to match
the linter's contract without adding a nolint shim.

Assisted-by: Claude:opus-4.7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-14 08:53:46 +02:00
Tai An
67c34bbb96 fix(middleware): parse OpenAI-spec tool_choice in /v1/chat/completions (#9559)
* fix(middleware): parse OpenAI-spec tool_choice in /v1/chat/completions

Follows up on #9526 (the 3-site setter fix) by addressing the remaining
clause in #9508 — string mode and OpenAI-spec specific-function shape both
silently failed in the /v1/chat/completions parsing path.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(middleware): restore LF endings and cover tool_choice parsing with specs

The previous commit on this branch saved core/http/middleware/request.go
with CRLF line endings, ballooning the diff against master to 684 / 651
for what is in reality a ~50-line parsing change. Restore LF (matches
.editorconfig end_of_line = lf).

Add 11 Ginkgo specs under "SetModelAndConfig tool_choice parsing
(chat completions)" that parallel the existing MergeOpenResponsesConfig
specs from #9509. They drive the full middleware chain (SetModelAndConfig
+ SetOpenAIRequest) and assert:

  * "required"  -> ShouldUseFunctions=true, no specific name
  * "none"      -> ShouldUseFunctions=false (tools disabled per OpenAI spec)
  * "auto"      -> default, tools available, no specific name
  * {type:function, function:{name:X}}  (spec)    -> X is forced
  * {type:function, name:X}             (legacy)  -> X is forced
  * nested wins when both forms are present
  * malformed shapes (no type, wrong type, no name, empty name) are no-ops

Update the inline comment on the string case to describe the actual
mechanism: "none" reaches SetFunctionCallString("none") downstream and
is then honored by ShouldUseFunctions() returning false. Before this PR
json.Unmarshal([]byte("none"), &functions.Tool{}) failed silently, so
"none" was ignored - making "none" actually work is a real behavior fix
this PR brings.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4-7 [Claude Code]

* fix(middleware): preserve pre-#9559 support for JSON-string-encoded tool_choice

Some non-spec clients send tool_choice as a JSON-encoded string of an
object form, e.g. "{\"type\":\"function\",\"function\":{\"name\":\"X\"}}".
The pre-#9559 code accepted this by accident: its case string: branch
ran json.Unmarshal([]byte(content), &functions.Tool{}), which succeeded
for that double-encoded shape even though it failed for the legitimate
plain string modes "auto" / "none" / "required".

The first version of this PR routed every string straight to
SetFunctionCallString as a mode, which fixed the plain-string cases but
silently regressed the double-encoded one (funcs.Select("{...}") returns
nothing). Restore the fallback: when a string looks like a JSON object,
try parsing it as a tool_choice map first; fall through to mode-string
handling only when no usable name comes out.

Factor the map-name extraction into a small helper
(extractToolChoiceFunctionName) so the string-fallback and the regular
map case go through identical code, and accept both the OpenAI-spec
nested shape and the legacy/Anthropic flat shape from either entry
point.

Add 3 Ginkgo specs covering the double-encoded case (nested form, legacy
form, and the fall-through when the JSON has no usable name).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4-7 [Claude Code]

* test(middleware): silence errcheck on AfterEach os.RemoveAll

The new tool_choice parsing tests added a second AfterEach that calls
os.RemoveAll(modelDir) without checking the error; errcheck flagged it.
Suppress with the standard _ = idiom. The pre-existing AfterEach on the
earlier Describe still elides the check the same way it did before -
leaving that untouched to keep this commit minimal.

Assisted-by: Claude:opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-14 00:14:38 +02:00
LocalAI [bot]
ab01ed1a3e fix(agentpool): close truncate-then-read race in agent_jobs.json persistence (#9811)
* fix(agentpool): close truncate-then-read race in agent_jobs.json persistence

Three call sites wrote and read agent_jobs.json (and agent_tasks.json)
through three independent mutexes:

  - AgentJobService.ExecuteJob spawns go saveJobs(job) -> fileJobPersister
    holding p.mu
  - AgentJobService.SaveJobsToFile holding service.fileMutex
  - AgentJobService.LoadJobsFromFile on a separate service instance holding
    a different service.fileMutex

Nothing serialized those mutexes, and both writers used os.WriteFile, which
opens O_TRUNC. A reader landing between the truncate and the write saw a
zero-byte file and surfaced as `unexpected end of JSON input` at offset 0.
The macOS tests-apple job started hitting this consistently once the path
filter was removed from .github/workflows/test.yml and the file-mode race
test ran on every push (run 25823124797 was the first observed failure).

Two changes close the window:

1. fileJobPersister.saveTasksToFile / saveJobsToFile now write to a
   same-directory temp file and os.Rename to the final path. rename(2) is
   atomic on POSIX, so concurrent readers see either the prior contents or
   the new contents and never a zero-byte window. The helper Syncs before
   close so a crash mid-write leaves either the old file intact or the temp
   behind (cleaned up on next save).

2. AgentJobService.{Load,Save}{Tasks,Jobs}{FromFile,ToFile} are collapsed
   to thin wrappers around fileJobPersister, removing the duplicate write
   path and the redundant service.fileMutex / service.tasksFile /
   service.jobsFile fields. Within a single service all task/job I/O now
   serializes on the persister's mutex; the atomic rename handles the
   cross-instance case the tests exercise.

Adds a regression test that hammers SaveJobsToFile and LoadJobsFromFile
concurrently for 500ms across two service instances on the same paths.
On master this reproduces `unexpected end of JSON input` on Linux within
~500ms; with the fix the suite ran -until-it-fails for 30s (54 attempts,
all green).

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(agentpool): route service flush/load through JobPersister interface

The first cut of the race fix made AgentJobService.{Save,Load}{Tasks,Jobs}*
type-assert s.persister to *fileJobPersister so they could reach the
unexported saveTasksToFile / saveJobsToFile helpers. That defeats the
JobPersister interface: the service is back to reasoning about a concrete
implementation instead of an abstraction.

Promote the bulk-flush operations to the interface as FlushTasks / FlushJobs:

  - fileJobPersister.FlushTasks/FlushJobs call the existing private helpers
    (atomic temp+rename writes from the prior commit).
  - dbJobPersister.FlushTasks/FlushJobs are no-ops because SaveTask/SaveJob
    are already write-through to the database.

The service's four file-named methods now talk only to the interface:
LoadTasks/LoadJobs read through s.persister.LoadTasks/LoadJobs, and the
Save side calls FlushTasks/FlushJobs. The "FromFile"/"ToFile" suffixes
stay for backward compat with user_services.go and the existing tests,
but they no longer claim a file-only contract.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-13 23:58:43 +02:00
Adira
c2fe0a6475 fix(http): honor X-Forwarded-Prefix when proxy strips the prefix (#9614)
* fix(http): honor X-Forwarded-Prefix when proxy strips the prefix

Closes #9145.

Two related issues kept the React UI from loading when a reverse proxy
rewrites a sub-path with prefix-stripping (e.g. Caddy `handle_path`):

1. `BaseURL` only computed a prefix from the path StripPathPrefix had
   removed, so when the proxy strips the prefix before forwarding, the
   request arrives without it and the base URL was returned without a
   prefix. Extract a `BasePathPrefix` helper and add an
   `X-Forwarded-Prefix` header fallback so the prefix is recovered.
2. `<base href>` only changes how relative URLs resolve; the build
   emits path-absolute references like `/assets/...` and
   `/favicon.svg`, which still resolve against the origin and bypass
   the proxy prefix. Rewrite those references in the served
   `index.html` so the browser requests them through the proxy.

Adds unit coverage for `BaseURL` with a pre-stripped path and an
end-to-end test for the proxy-stripped scenario.

Assisted-by: Claude:claude-opus-4-7

* fix(http): gate X-Forwarded-Prefix through SafeForwardedPrefix in BasePathPrefix

BasePathPrefix consumed X-Forwarded-Prefix directly, so a value the
codebase elsewhere rejects (e.g. "//evil.com") slipped through and was
interpolated into the SPA index.html — both into the path-absolute asset
URL rewrite in serveIndex (turning "/assets/..." into "//evil.com/assets/...",
a protocol-relative URL that loads JS from a foreign origin) and into
<base href>. Route the header through the existing SafeForwardedPrefix
validator that StripPathPrefix and prefixRedirect already use, and
HTML-escape the prefix before injecting it into the asset rewrite as
defense in depth against attribute breakout.

Tests cover //evil.com, backslashes, control chars, CR/LF and a missing
leading slash; the integration test asserts an unsafe prefix can't poison
asset URLs.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7-1m [Read] [Edit] [Bash]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-13 21:59:33 +02:00
LocalAI [bot]
b4fdb41dcc fix(distributed): cascade-clean stale node_models rows + filter routing by healthy status (#9754)
* fix(distributed): cascade-clean stale node_models on drain and filter routing by healthy status

Stale node_models rows (state="loaded") were surviving past the healthy
state of their owning node, causing /embeddings (and other inference
paths) to dispatch to a backend whose process was gone or drained. The
downstream symptom in a live cluster was pgvector rejecting inserts
with "vector cannot have more than 16000 dimensions (SQLSTATE 54000)"
because the misbehaving backend silently returned a malformed
(oversized) tensor; the Models page showed the model as "running"
without an associated node, like a stale entry, even though the node
was no longer visible in the Nodes view.

Two changes here, plus a third in a follow-up commit:

- MarkDraining now cascade-deletes node_models rows for the affected
  node, mirroring MarkOffline. Drains are explicit operator actions —
  the box has been intentionally taken out of rotation — so clearing
  the rows stops the Models UI from misreporting and prevents the
  routing layer from picking those rows if scheduling logic is ever
  relaxed. In-flight requests already hold their gRPC client through
  Route() and finish normally; the only observable effect is a
  non-fatal IncrementInFlight warning, acceptable for a drain.

  MarkUnhealthy is deliberately left status-only: it fires from
  managers_distributed / reconciler on a single nats.ErrNoResponders
  with no retry, so a transient NATS hiccup must not nuke every loaded
  model and force a full reload on recovery.

- FindAndLockNodeWithModel's inner JOIN now filters on
  backend_nodes.status = healthy in addition to node_models.state =
  loaded. The previous version relied on the second node-fetch step to
  reject non-healthy nodes, but a concurrent reader could still pick
  the same stale row in the same window. Belt-and-braces.

- DistributedConfig.PerModelHealthCheck renamed to
  DisablePerModelHealthCheck and inverted at the call site so
  per-model gRPC probing is on by default. The probe (now made
  consecutive-miss aware in a follow-up commit) independently health-
  checks each model's gRPC address and removes stale node_models rows
  when the backend has crashed even though the worker's node-level
  heartbeat is still arriving.

  Migration: the field had no CLI flag, env var binding, or YAML key
  in tree (only the bare struct field), so there is no user-facing
  migration. Anything constructing DistributedConfig in code needs to
  drop the assignment (default now does the right thing) or invert it.

Assisted-by: Claude:claude-opus-4-7 go-vet go-test golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(distributed): require consecutive misses before per-model probe removes a row

The per-model gRPC probe used to remove a node_models row on a single
failed health check. With the per-model probe now on by default, that
made any 5-second gRPC blip (network jitter, a long-running request
hogging the worker's gRPC server thread, brief GC pause) trigger a
full reload of the affected model — too eager for production.

Require perModelMissThreshold (3) consecutive failed probes before
removal. At the default 15s tick a model must be unreachable for ~45s
before reap; a single successful probe in between resets the streak.
Per-(node, model, replica) state tracked under a mutex on the monitor.

If the removal call itself fails, the miss counter is left in place
so the next tick retries rather than starting the streak over.

Tests:
- removes stale model via per-model health check after consecutive
  failures (replaces the single-shot expectation)
- preserves model row when an intermittent failure is followed by a
  success (covers the reset-on-success path and verifies the counter
  reset by failing twice more without crossing threshold)
- newTestHealthMonitor initializes the misses map so direct-construct
  test helpers don't nil-map-panic in the probe path

Assisted-by: Claude:claude-opus-4-7 go-vet go-test golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-13 21:57:50 +02:00
Richard Palethorpe
0245b33eab feat(realtime): Add Liquid Audio s2s model and assistant mode on talk page (#9801)
* feat(liquid-audio): add LFM2.5-Audio any-to-any backend + realtime_audio usecase

Wires LiquidAI's LFM2.5-Audio-1.5B as a self-contained Realtime API model:
single engine handles VAD, transcription, LLM, and TTS in one bidirectional
stream — drop-in alternative to a VAD+STT+LLM+TTS pipeline.

Backend
- backend/python/liquid-audio/ — new Python gRPC backend wrapping the
  `liquid-audio` package. Modes: chat / asr / tts / s2s, voice presets,
  Load/Predict/PredictStream/AudioTranscription/TTS/VAD/AudioToAudioStream/
  Free and StartFineTune/FineTuneProgress/StopFineTune. Runtime monkey-patch
  on `liquid_audio.utils.snapshot_download` so absolute local paths from
  LocalAI's gallery resolve without a HF round-trip. soundfile in place of
  torchaudio.load/save (torchcodec drags NVIDIA NPP we don't bundle).
- backend/backend.proto + pkg/grpc/{backend,client,server,base,embed,
  interface}.go — new AudioToAudioStream RPC mirroring AudioTransformStream
  (config/frame/control oneof in; typed event+pcm+meta out).
- core/services/nodes/{health_mock,inflight}_test.go — add stubs for the
  new RPC to the test fakes.

Config + capabilities
- core/config/backend_capabilities.go — UsecaseRealtimeAudio, MethodAudio
  ToAudioStream, UsecaseInfoMap entry, liquid-audio BackendCapability row.
- core/config/model_config.go — FLAG_REALTIME_AUDIO bitmask, ModalityGroups
  membership in both speech-input and audio-output groups so a lone flag
  still reads as multimodal, GetAllModelConfigUsecases entry, GuessUsecases
  branch.

Realtime endpoint
- core/http/endpoints/openai/realtime.go — extract prepareRealtimeConfig()
  so the gate is unit-testable; accept realtime_audio models and self-fill
  empty pipeline slots with the model's own name (user-pinned slots win).
- core/http/endpoints/openai/realtime_gate_test.go — six specs covering nil
  cfg, empty pipeline, legacy pipeline, self-contained realtime_audio,
  user-pinned VAD slot, and partial legacy pipeline.

UI + endpoints
- core/http/routes/ui.go — /api/pipeline-models accepts either a legacy
  VAD+STT+LLM+TTS pipeline or a realtime_audio model; surfaces a
  self_contained flag so the Talk page can collapse the four cards.
- core/http/routes/ui_api.go — realtime_audio in usecaseFilters.
- core/http/routes/ui_pipeline_models_test.go — covers both code paths.
- core/http/react-ui/src/pages/Talk.jsx — self-contained badge instead of
  the four-slot grid; rename Edit Pipeline → Edit Model Config; less
  pipeline-specific wording.
- core/http/react-ui/src/pages/Models.jsx + locales/en/models.json — new
  realtime_audio filter button + i18n.
- core/http/react-ui/src/utils/capabilities.js — CAP_REALTIME_AUDIO.
- core/http/react-ui/src/pages/FineTune.jsx — voice + validation-dataset
  fields, surfaced when backend === liquid-audio, plumbed via
  extra_options on submit/export/import.

Gallery + importer
- gallery/liquid-audio.yaml — config template with known_usecases:
  [realtime_audio, chat, tts, transcript, vad].
- gallery/index.yaml — four model entries (realtime/chat/asr/tts) keyed by
  mode option. Fixed pre-existing `transcribe` typo on the asr entry
  (loader silently dropped the unknown string → entry never surfaced as a
  transcript model).
- gallery/lfm.yaml — function block for the LFM2 Pythonic tool-call format
  `<|tool_call_start|>[name(k="v")]<|tool_call_end|>` matching
  common_chat_params_init_lfm2 in vendored llama.cpp.
- core/gallery/importers/{liquid-audio,liquid-audio_test}.go — detector
  matches LFM2-Audio HF repos (excludes -gguf mirrors); mode/voice
  preferences plumbed through to options.
- core/gallery/importers/importers.go — register LiquidAudioImporter
  before LlamaCPPImporter.
- pkg/functions/parse_lfm2_test.go — seven specs for the response/argument
  regex pair on the LFM2 pythonic format.

Build matrix
- .github/backend-matrix.yml — seven liquid-audio targets (cuda12, cuda13,
  l4t-cuda-13, hipblas, intel, cpu amd64, cpu arm64). Jetpack r36 cuda-12
  is skipped (Ubuntu 22.04 / Python 3.10 incompatible with liquid-audio's
  3.12 floor).
- backend/index.yaml — anchor + 13 image entries.
- Makefile — .NOTPARALLEL, prepare-test-extra, test-extra,
  docker-build-liquid-audio.

Docs
- .agents/plans/liquid-audio-integration.md — phased plan; PR-D (real
  any-to-any wiring via AudioToAudioStream), PR-E (mid-audio tool-call
  detector), PR-G (GGUF entries once upstream llama.cpp PR #18641 lands)
  remain.
- .agents/api-endpoints-and-auth.md — expand the capability-surface
  checklist with every place a new FLAG_* needs to be registered.

Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(realtime): function calling + history cap for any-to-any models

Three pieces, all on the realtime_audio path that just landed:

1. liquid-audio backend (backend/python/liquid-audio/backend.py):
   - _build_chat_state grows a `tools_prelude` arg.
   - new _render_tools_prelude parses request.Tools (the OpenAI Chat
     Completions function array realtime.go already serialises) and
     emits an LFM2 `<|tool_list_start|>…<|tool_list_end|>` system turn
     ahead of the user history. Mirrors gallery/lfm.yaml's `function:`
     template so the model sees the same prompt shape whether served
     via llama-cpp or here. Without this the backend silently dropped
     tools — function calling was wired end-to-end on the Go side but
     the model never saw a tool list.

2. Realtime history cap (core/http/endpoints/openai/realtime.go):
   - Session grows MaxHistoryItems int; default picked by new
     defaultMaxHistoryItems(cfg) — 6 for realtime_audio models (LFM2.5
     1.5B degrades quickly past a handful of turns), 0/unlimited for
     legacy pipelines composing larger LLMs.
   - triggerResponse runs conv.Items through trimRealtimeItems before
     building conversationHistory. Helper walks the cut left if it
     would orphan a function_call_output, so tool result + call pairs
     stay intact.
   - realtime_gate_test.go: specs for defaultMaxHistoryItems and
     trimRealtimeItems (zero cap, under cap, over cap, tool-call pair
     preservation).

3. Talk page (core/http/react-ui/src/pages/Talk.jsx):
   - Reuses the chat page's MCP plumbing — useMCPClient hook,
     ClientMCPDropdown component, same auto-connect/disconnect effect
     pattern. No bespoke tool registry, no new REST endpoints; tools
     come from whichever MCP servers the user toggles on, exactly as
     on the chat page.
   - sendSessionUpdate now passes session.tools=getToolsForLLM(); the
     update re-fires when the active server set changes mid-session.
   - New response.function_call_arguments.done handler executes via
     the hook's executeTool (which round-trips through the MCP client
     SDK), then replies with conversation.item.create
     {type:function_call_output} + response.create so the model
     completes its turn with the tool output. Mirrors chat's
     client-side agentic loop, translated to the realtime wire shape.

UI changes require a LocalAI image rebuild (Dockerfile:308-313 bakes
react-ui/dist into the runtime image). Backend.py changes can be
swapped live in /backends/<id>/backend.py + /backend/shutdown.

Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(realtime): LocalAI Assistant ("Manage Mode") for the Talk page

Mirrors the chat-page metadata.localai_assistant flow so users can ask the
realtime model what's loaded / installed / configured. Tools are run
server-side via the same in-process MCP holder that powers the chat
modality — no transport switch, no proxy, no new wire protocol.

Wire:
- core/http/endpoints/openai/realtime.go:
  - RealtimeSessionOptions{LocalAIAssistant,IsAdmin}; isCurrentUserAdmin
    helper mirrors chat.go's requireAssistantAccess (no-op when auth
    disabled, else requires auth.RoleAdmin).
  - Session grows AssistantExecutor mcpTools.ToolExecutor.
  - runRealtimeSession, when opts.LocalAIAssistant is set: gate on admin,
    fail closed if DisableLocalAIAssistant or the holder has no tools,
    DiscoverTools and inject into session.Tools, prepend
    holder.SystemPrompt() to instructions.
  - Tool-call dispatch loop: when AssistantExecutor.IsTool(name), run
    ExecuteTool inproc, append a FunctionCallOutput to conv.Items, skip
    the function_call_arguments client emit (the client can't execute
    these — it doesn't know about them). After the loop, if any
    assistant tool ran, trigger another response so the model speaks the
    result. Mirrors chat's agentic loop, driven server-side rather than
    via client round-trip.

- core/http/endpoints/openai/realtime_webrtc.go: RealtimeCallRequest
  gains `localai_assistant` (JSON omitempty). Handshake calls
  isCurrentUserAdmin and builds RealtimeSessionOptions.

- core/http/react-ui/src/pages/Talk.jsx: admin-only "Manage Mode"
  checkbox under the Tools dropdown; passes localai_assistant: true to
  realtimeApi.call's body, captured in the connect callback's deps.

Mirroring chat's pattern means the in-process MCP tools surface "just
works" for the Talk page without exposing a Streamable-HTTP MCP endpoint
(which was the alternative). Clients with their own MCP servers can
still use the existing ClientMCPDropdown path in parallel; the realtime
handler distinguishes them by AssistantExecutor.IsTool() at dispatch
time.

Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(realtime): render Manage Mode tool calls in the Talk transcript

Previously the realtime endpoint only emitted response.output_item.added
for the FunctionCall item, and Talk.jsx's switch ignored the event — so
server-side tool runs were invisible in the UI. The model would speak
the result but the user had no way to see what tool was actually
called.

realtime.go: after executing an assistant tool inproc, emit a second
output_item.added/.done pair for the FunctionCallOutput item. Mirrors
the way the chat page displays tool_call + tool_result blocks.

Talk.jsx: handle both response.output_item.added and .done. Render
FunctionCall (with arguments) and FunctionCallOutput (pretty-printed
JSON when possible) as two transcript entries — `tool_call` with the
wrench icon, `tool_result` with the clipboard icon, both in mono-space
secondary-colour. Resets streamingRef after the result so the next
assistant text delta starts a fresh transcript entry instead of
appending to the previous turn.

Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* refactor(realtime): bound the Manage Mode tool-loop + preserve assistant tools

Fallout from a review pass on the Manage Mode patches:

- Bound the server-side agentic loop. triggerResponse used to recurse on
  executedAssistantTool with no cap — a model that kept calling tools
  would blow the goroutine stack. New maxAssistantToolTurns = 10 (mirrors
  useChat.js's maxToolTurns). Public triggerResponse is now a thin shim
  over triggerResponseAtTurn(toolTurn int); recursion increments the
  counter and stops at the cap with an xlog.Warn.

- Preserve Manage Mode tools across client session.update. The handler
  used to blindly overwrite session.Tools, so toggling a client MCP
  server mid-session silently wiped the in-process admin tools. Session
  now caches the original AssistantTools slice at session creation and
  the session.update handler merges them back in (client names win on
  collision — the client is explicit).

- strconv.ParseBool for the localai_assistant query param instead of
  hand-rolled "1" || "true". Mirrors LocalAIAssistantFromMetadata.

- Talk.jsx: render both tool_call and tool_result on
  response.output_item.done instead of splitting them across .added and
  .done. The server's event pairing (added → done) stays correct; the
  UI just doesn't need to inspect both phases of the same item. One
  switch case instead of two, no behavioural change.

Out of scope (noted for follow-ups): extract a shared assistant-tools
helper between chat.go and realtime.go (duplication is small enough
that two parallel implementations stay readable for now), and an i18n
key for the Manage Mode helper text (Talk.jsx doesn't use i18n
anywhere else yet).

Assisted-by: claude-code:claude-opus-4-7-1m [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* ci(test-extra): wire liquid-audio backend smoke test

The backend ships test.py + a `make test` target and is listed in
backend-matrix.yml, so scripts/changed-backends.js already writes a
`liquid-audio=true|false` output when files under backend/python/liquid-audio/
change. The workflow just wasn't reading it.

- Expose the `liquid-audio` output on the detect-changes job
- Add a tests-liquid-audio job that runs `make` + `make test` in
  backend/python/liquid-audio, gated on the per-backend detect flag

The smoke covers Health() and LoadModel(mode:finetune); fine-tune mode
short-circuits before any HuggingFace download (backend.py:192), so the
job needs neither weights nor a GPU. The full-inference path remains
gated on LIQUID_AUDIO_MODEL_ID, which CI doesn't set.

The four new Go test files (core/gallery/importers/liquid-audio_test.go,
core/http/endpoints/openai/realtime_gate_test.go,
core/http/routes/ui_pipeline_models_test.go, pkg/functions/parse_lfm2_test.go)
are already picked up by the existing test.yml workflow via `make test` →
`ginkgo -r ./pkg/... ./core/...`; their packages all carry RunSpecs entries.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-13 21:57:27 +02:00
LocalAI [bot]
a57e73691d fix(ollama): accept prompt alias on /api/embed for Ollama parity (#9780)
Ollama's embedding endpoint accepts both `input` and `prompt` as the
input string value (see ollama/ollama docs/api.md#generate-embeddings).
LocalAI only accepted `input`, which broke client libraries that send
the `prompt` form.

Add `Prompt` to OllamaEmbedRequest and have GetInputStrings fall back
to it when Input is unset. Input still wins when both are provided.

Fixes #9767.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-12 17:21:20 +02:00
dependabot[bot]
a689100d61 chore(deps): bump the npm_and_yarn group across 1 directory with 3 updates (#9728)
Bumps the npm_and_yarn group with 3 updates in the /core/http/react-ui directory: [fast-uri](https://github.com/fastify/fast-uri), [hono](https://github.com/honojs/hono) and [ip-address](https://github.com/beaugunderson/ip-address).


Updates `fast-uri` from 3.1.0 to 3.1.2
- [Release notes](https://github.com/fastify/fast-uri/releases)
- [Commits](https://github.com/fastify/fast-uri/compare/v3.1.0...v3.1.2)

Updates `hono` from 4.12.14 to 4.12.18
- [Release notes](https://github.com/honojs/hono/releases)
- [Commits](https://github.com/honojs/hono/compare/v4.12.14...v4.12.18)

Updates `ip-address` from 10.1.0 to 10.2.0
- [Commits](https://github.com/beaugunderson/ip-address/commits)

---
updated-dependencies:
- dependency-name: fast-uri
  dependency-version: 3.1.2
  dependency-type: indirect
  dependency-group: npm_and_yarn
- dependency-name: hono
  dependency-version: 4.12.18
  dependency-type: indirect
  dependency-group: npm_and_yarn
- dependency-name: ip-address
  dependency-version: 10.2.0
  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>
2026-05-12 09:54:38 +02:00
LocalAI [bot]
bc3fb16105 feat(ollama): report model capabilities + details on /api/tags and /api/show (#9766)
Ollama-compatible clients (Open WebUI, Enchanted, ollama-grid-search,
etc.) rely on the `capabilities` list and `details.{parameter_size,
quantization_level,families}` fields returned by /api/tags and
/api/show to decide which models are eligible for a given task --
for example to filter the "embedding model" picker. Upstream Ollama
returns these; LocalAI's compat layer was leaving them empty, so
embedding models were silently rejected by clients that only allow
chat models for chat and only allow embedding models for embeddings.

This wires up the existing config signals already present in
ModelConfig:

- modelCapabilities() derives the Ollama capability strings from the
  config: "embedding" (FLAG_EMBEDDINGS), "completion" (FLAG_CHAT /
  FLAG_COMPLETION), "vision" (explicit KnownUsecases bit or MMProj /
  multimodal template / backend media marker), "tools" (auto-detected
  ToolFormatMarkers, JSON/Response regex, XML format, grammar
  triggers), "thinking" (ReasoningConfig with reasoning not disabled)
  and "insert" (presence of a completion template).
- modelDetailsFromModelConfig() now fills families, parameter_size
  and quantization_level. The latter two are parsed from the GGUF
  filename via regex -- conservative tokens only (Q*/IQ*/F16/F32/BF16
  and \d+(\.\d+)?[BM] surrounded by separators) so we don't accidentally
  match "Qwen3" as "3B".
- modelInfoFromModelConfig() exposes general.architecture and
  general.context_length in the new ShowResponse.model_info map.

Note: HasUsecases(FLAG_VISION) cannot be used directly -- GuessUsecases
has no FLAG_VISION case and returns true at the end for any chat model.
hasVisionSupport() instead reads KnownUsecases explicitly plus MMProj /
template / media-marker signals.

Tests are written first (TDD) using Ginkgo/Gomega -- DescribeTable for
the capability mapping (embedding-only, chat, vision, thinking, tools
via markers, tools via JSON regex, no-capability rerank) plus
integration tests against ShowModelEndpoint that round-trip JSON
through a real ModelConfigLoader populated from a temp YAML file.

Fixes #9760.


Assisted-by: Claude Code:claude-opus-4-7

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-12 00:16:19 +02:00
LocalAI [bot]
d892e4af80 feat: add ds4 backend (DeepSeek V4 Flash) with tool calls, thinking, KV cache (#9758)
* test(e2e-backends): allow BACKEND_BINARY for native-built backends

Adds an escape hatch for hardware-gated backends (e.g. ds4) where the
model is too large for Docker build context. When BACKEND_BINARY points
at a run.sh produced by 'make -C backend/cpp/<name> package', the suite
skips docker image extraction and drives the binary directly.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(e2e-backends): validate BACKEND_BINARY basename + log actual source

Two follow-ups from the cbcf5148 code review:

- BACKEND_BINARY now requires a path whose basename is `run.sh`. Without
  this check, `filepath.Dir(binary)` silently discarded the filename, so
  pointing the env var at an arbitrary binary failed later with a
  confusing assertion that named a path the user never typed.
- The "Testing image=..." debug line printed an empty string when the
  binary path was used, hiding the actual source in CI logs. The line
  now reports whichever of BACKEND_IMAGE / BACKEND_BINARY is in effect
  as `src=...`.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): scaffold ds4 backend dir

Adds prepare.sh, run.sh, and a .gitignore. CMakeLists, Makefile, and the
implementation arrive in follow-up commits.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): add backend Makefile

Drives ds4's upstream Makefile to produce engine .o files (CUDA on Linux
when BUILD_TYPE=cublas, Metal on Darwin, otherwise CPU debug path), then
invokes CMake on our wrapper.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): add CMakeLists for grpc-server

Generates protoc stubs from backend.proto, links grpc-server.cpp +
dsml_parser.cpp + dsml_renderer.cpp + kv_cache.cpp against pre-built
ds4 engine .o files. DS4_GPU=cuda|metal|cpu selects the backend.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): grpc-server skeleton + module stubs

The minimum that links: Backend service with Health + Free; other RPCs
default to UNIMPLEMENTED. Stub headers/sources for dsml_parser,
dsml_renderer, and kv_cache are in place so CMake links cleanly even
before those modules ship.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): implement LoadModel

Opens engine + creates session sized to ContextSize (default 32768).
Backend is compile-time: CPU when DS4_NO_GPU, Metal on __APPLE__, else
CUDA. MTP/speculative options are accepted via ModelOptions.Options[]
(mtp_path, mtp_draft, mtp_margin). kv_cache_dir option is captured into
g_kv_cache_dir for the cache module (Task 19 wires it in).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): implement TokenizeString

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): implement Predict (plain text)

Tool calls + thinking-mode split arrive in Task 13 once dsml_parser is in.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): implement PredictStream (plain text)

ChatDelta + reasoning/tool_calls split arrives in Task 14.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): implement Status RPC

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): add DSML streaming parser

Classifies raw model-emitted token text into CONTENT / REASONING /
TOOL_START / TOOL_ARGS / TOOL_END events. Markers it watches for are the
literal DSML strings rendered by ds4_server.c's prompt template
(<|DSML|tool_calls>, <|DSML|invoke name=...>, <think>, etc.) - these are
plain text the model emits, not special tokens.

Partial markers split across token chunks are buffered until a full marker
or a definitively-not-a-marker '<' is observed. RandomToolId() generates
the API-side tool call id (call_xxx) that exact-replay would key on.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(backend/cpp/ds4): split hex escapes in DSML markers + add cstring/cstdio includes

C++ \x hex escapes have no length cap. '\x9cD' was read as a single escape
producing byte 0xCD, eating the 'D'. The markers were never actually matching
the DSML text the model emits. Split each escape with adjacent string literal
concatenation so the byte sequence is exactly EF BD 9C 44 (|D) at runtime.

Also adds <cstring> and <cstdio> includes (libstdc++ 13 does not transitively
expose std::strlen / std::snprintf via <string>).

The local plan file (uncommitted) was also updated with the same fixes so
Task 16's dsml_renderer.cpp does not re-introduce the bug.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): wire DsmlParser into Predict (ChatDelta)

Non-streaming Predict now emits one ChatDelta carrying content,
reasoning_content, and tool_calls[] parsed from the model's DSML output.
Reply.message still carries the raw model bytes for backends that prefer
the regex fallback path.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): wire DsmlParser into PredictStream

Per-token ChatDelta writes: content/reasoning_content go incrementally,
tool_calls emit TOOL_START as one delta (id + name) followed by
TOOL_ARGS deltas with incremental JSON. The Go-side aggregator
(pkg/functions/chat_deltas.go) reassembles them.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): chat template + reasoning_effort mapping

UseTokenizerTemplate=true + Messages -> ds4_chat_begin / append /
assistant_prefix. PredictOptions.Metadata['enable_thinking'] and
['reasoning_effort'] map to ds4_think_mode (DS4_THINK_HIGH default;
'max'/'xhigh' -> DS4_THINK_MAX; disabled -> DS4_THINK_NONE).

Tool-call rendering for assistant turns with tool_calls JSON arrives in
the next commit (dsml_renderer).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): render assistant tool_calls + tool results to DSML

Closes the round-trip: when an OpenAI client sends a multi-turn chat
where prior turns contain tool_calls or role=tool messages, build_prompt
serializes them back to the DSML shape the model was trained on. Mirrors
ds4_server.c's prompt renderer; uses nlohmann::json for parsing the
OpenAI tool_calls payload.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): disk KV cache module

Dir-based cache keyed by SHA1(rendered prompt prefix). File format:
'DS4G' magic + version + ctx_size + prefix_len + prefix + payload_bytes
+ ds4_session_save_payload output. NOT bit-compatible with ds4-server's
KVC files - that interop is a follow-up plan. LoadLongestPrefix walks
the dir picking the longest stored prefix that prefixes the incoming
prompt.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): wire KvCache into Predict/PredictStream

LoadModel reads 'kv_cache_dir' from ModelOptions.Options[], passes it to
g_kv_cache.SetDir. Each Predict/PredictStream computes a render text for
the request, tries LoadLongestPrefix to recover state, then Saves the
new state after generation. ds4_session_sync handles the live-cache
fast path internally, so the disk cache only matters for cold-starts
and cross-session reuse.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): add package.sh

Linux: bundles libc + ld + libstdc++ + libgomp + GPU runtime libs into
package/lib so the FROM scratch image boots without a host libc.
Darwin is handled by scripts/build/ds4-darwin.sh which uses otool -L.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(backend/cpp/ds4): rename namespace ds4_backend -> ds4cpp

ds4.h defines 'typedef enum {...} ds4_backend' which collides with our
C++ 'namespace ds4_backend' anywhere a TU includes both. kv_cache.h
includes ds4.h directly and surfaces the conflict immediately; other
TUs would hit it once gRPC dev headers are available.

Renames the C++ namespace to ds4cpp across all wrapper files and the
plan, leaving the upstream ds4 typedef untouched.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend): add Dockerfile.ds4

Single-stage builder (CUDA devel image for cublas, ubuntu:24.04 for cpu)
-> FROM scratch with packaged grpc-server + bundled runtime libs.
nlohmann-json3-dev is required for dsml_renderer's JSON handling.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(make): wire backend/cpp/ds4 + ds4-darwin into root Makefile

BACKEND_DS4 entry + generate-docker-build-target eval + docker-build-ds4
in docker-build-backends + .NOTPARALLEL guards. Also adds the
backends/ds4-darwin target which delegates to scripts/build/ds4-darwin.sh
(landed in Task 24).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* ci: add backend-matrix entries for ds4 (cpu + cuda13, per-arch)

Two entries per build (amd64 + arm64) so backend-merge-jobs assembles a
multi-arch manifest. Skipping cuda12 - ds4 was validated against CUDA 13.
Darwin Metal is handled outside this matrix by backend_build_darwin.yml.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/index): add ds4 meta + image entries

cpu + cuda13 x latest + master. Darwin Metal builds publish under
ds4-darwin via the existing llama-cpp-darwin OCI pipeline.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(scripts/build): add ds4-darwin.sh

Native macOS/Metal build for the ds4 backend. Mirrors llama-cpp-darwin.sh:
make grpc-server -> otool -L for dylib bundling -> OCI tar that
'local-ai backends install' consumes via the backends/ds4-darwin
Makefile target.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* ci(darwin): build ds4-darwin in backend_build_darwin

Adds a 'Build ds4 backend (Darwin Metal)' step that runs the
backends/ds4-darwin Makefile target on the macOS runner.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(import): auto-detect ds4 weights via DS4Importer

Adds core/gallery/importers/ds4.go which matches on the antirez/deepseek-v4-gguf
repo URI and the DeepSeek-V4-Flash-*.gguf filename pattern. Registered before
LlamaCPPImporter so ds4 weights route to backend: ds4 instead of falling
through to llama-cpp.

Also lists ds4 in /backends/known so the /import-model UI surfaces it as a
manual choice for users who want to force the backend on a non-canonical URI.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(gallery): add deepseek-v4-flash-q2 (ds4 backend)

One-click install of the q2 weights with backend: ds4.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* docs(.agents): add ds4-backend.md

Documents the backend shape, DSML state machine, thinking-mode mapping,
disk KV cache, build matrix (cpu/cuda13/Darwin), and the BACKEND_BINARY
hardware-validation path.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(backend/cpp/ds4): pass UBUNTU_VERSION + arch env vars to install-base-deps

The .docker/install-base-deps.sh script needs UBUNTU_VERSION (defaults to
2404), TARGETARCH, SKIP_DRIVERS, and APT_MIRROR/APT_PORTS_MIRROR exported
into the environment so it can pick the right cuda-keyring / cudss / nvpl
debs and apt mirrors. Dockerfile.ds4 was declaring some of the ARGs but not
re-exporting them via ENV. Mirrors Dockerfile.llama-cpp's pattern.

Without this fix 'make docker-build-ds4 BUILD_TYPE=cublas CUDA_MAJOR_VERSION=13'
failed at:
  /usr/local/sbin/install-base-deps: line 120: UBUNTU_VERSION: unbound variable

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/index): add Metal image entries for ds4

Adds metal-ds4 + metal-ds4-development image entries pointing at
quay.io/go-skynet/local-ai-backends:{latest,master}-metal-darwin-arm64-ds4
(built by scripts/build/ds4-darwin.sh on macOS arm64 runners), plus the
'metal' and 'metal-darwin-arm64' capability mappings on the ds4 meta and
ds4-development variant.

Closes a gap from the initial Task 23 landing - the Darwin Metal build
script and CI workflow step were already wired (Tasks 24-25), but the
gallery had no image entry for users to install the Metal variant.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(ci): use ubuntu:24.04 base for ds4 cuda13 matrix entries

The initial Task 22 matrix landing used base-image: 'nvidia/cuda:13.0.0-devel-ubuntu24.04'
which clashes with install-base-deps.sh's cuda-keyring step:

  E: Conflicting values set for option Signed-By regarding source
     https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/sbsa/

The canonical pattern (llama-cpp, ik-llama-cpp, turboquant) uses plain
'ubuntu:24.04' + 'skip-drivers: false' so install-base-deps installs CUDA
from scratch via its own keyring setup. Adopting that here.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(backend/cpp/ds4): drop install-base-deps.sh dependency

The .docker/install-base-deps.sh pipeline is built around the llama-cpp
needs: NVIDIA keyring + cuda-toolkit apt + gRPC-from-source build at
/opt/grpc. For ds4 we don't need any of that:
- CUDA: nvidia/cuda:13.0.0-devel-ubuntu24.04 ships /usr/local/cuda
  ready to go; install-base-deps's keyring step then conflicts with
  the pre-installed Signed-By.
- gRPC: ds4's grpc-server.cpp only links against grpc++; system
  libgrpc++-dev (apt) is sufficient, no source build needed.

Replaced the install-base-deps invocation in Dockerfile.ds4 with a
direct 'apt-get install libgrpc++-dev libprotobuf-dev protobuf-compiler-grpc
nlohmann-json3-dev cmake build-essential pkg-config git'. Matrix entries
back to nvidia/cuda base + skip-drivers=true so install-base-deps would
no-op even if some downstream tooling calls it.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(backend/cpp/ds4): correct proto accessors + alias grpc::Status as GStatus

Two compile bugs caught by the docker build:

1. proto::Message uses snake_case accessors. The build_prompt loop called
   m.toolcalls() / m.toolcallid() - the protoc-generated names are
   m.tool_calls() / m.tool_call_id(). Plan-text bug propagated to the
   wrapper.

2. The Status RPC method shadowed the 'using grpc::Status' alias, so any
   later method declaration using Status as a return type failed to parse
   ('Status does not name a type' starting at LoadModel). Solution: alias
   grpc::Status as GStatus instead, with no 'using' clause that would
   conflict. All RPC method declarations and return-statement constructions
   now use GStatus.

Pre-existing code reviewer flagged the Status-shadow concern as 'minor'
in the original Task 10 commit; it turned out to be a real compile blocker
under libstdc++ 13 once the surrounding methods were filled in.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(backend/cpp/ds4): preserve TOOL_ARGS content in dsml_parser Flush

When the model emitted a parameter value that arrived in the same buffer
as the surrounding tool_call markers (e.g. the buffered tail after a
literal '</think>' opened the model output), the parser deferred all
buffered bytes to Flush() because looks_like_prefix() always returns
true while buf starts with '<'. Flush() then drained the buffer as
plain CONTENT/REASONING regardless of parser state, so the bytes
between the parameter open and close markers were classified as
CONTENT instead of TOOL_ARGS.

Symptom: the model emitted

  <|DSML|parameter name="location" string="true">Paris, France</|DSML|parameter>

and the assembled tool_call arguments came out as {"location":""} -
the opener and closer were emitted into the args stream but the
"Paris, France" content went to the assistant message instead.

Fix:

1. Flush() now uses the same state-aware emit logic as DrainPlain:
   PARAM_VALUE bytes become TOOL_ARGS (json-escaped when string),
   THINK bytes become REASONING, TEXT bytes become CONTENT, and
   INVOKE / TOOL_CALLS structural whitespace is discarded.

2. looks_like_prefix() restricts its leading-'<' fallback to buffers
   that have not yet seen a '>'. Without that change, char-by-char
   feeds would discard the '<' of '<|DSML|invoke name="..."' once
   the marker prefix length was reached but the closing quote/'>'
   were still in flight.

Verified with a standalone harness that runs the failing input three
ways (single Feed, split-after-'>', and char-by-char) and aggregates
TOOL_ARGS for tool index 0: all three now produce
{"location":"Paris, France"}.

Assisted-by: Claude:opus-4.7 [Read,Edit,Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(backend/cpp/ds4): use ds4_session_sync + manual generation loop for KV persistence

ds4_engine_generate_argmax() is a self-contained helper that doesn't take or
update a ds4_session - it manages its own internal state. Our Predict and
PredictStream methods created g_session via ds4_session_create() but then
called ds4_engine_generate_argmax(), so g_session's KV state never advanced.
ds4_session_payload_bytes(g_session) returned 0 and the disk KV cache save
correctly rejected with 'session has no valid checkpoint to save'.

Switch both RPCs to the proper session API:
  ds4_session_sync(g_session, &prompt, ...)
  loop:
    int token = ds4_session_argmax(g_session)
    if token == eos: break
    emit(token)
    ds4_session_eval(g_session, token, ...)

After the loop the session has a real checkpoint and ds4_session_save_payload
writes the KV state to disk. Verified end-to-end on a DGX Spark GB10: three
.kv files (15-30 MB each) are written when BACKEND_TEST_OPTIONS sets
kv_cache_dir, and the e2e tool-call assertion still passes.

Also added stderr diagnostics to KvCache (enabled/disabled at SetDir; per-save
path + payload_bytes + result) so future failures are visible instead of
silent. The 'wrote ok' lines are low-volume - one per Predict/PredictStream
when the cache is enabled - and skipped entirely when the option is unset.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): use ds4_session_eval_speculative_argmax when MTP loaded

Wires MTP (Multi-Token Prediction) speculative decoding into the manual
generation loop in both Predict and PredictStream. When the upstream MTP
weights are loaded via 'mtp_path:' option AND we're on CUDA / Metal,
ds4_engine_mtp_draft_tokens() returns >0 and we switch the inner loop to
ds4_session_eval_speculative_argmax(), which can accept N>1 tokens per
verifier step. When MTP is not loaded (no option, CPU backend, or weights
absent), we fall through to the simple ds4_session_argmax + ds4_session_eval
path with no behavior change.

Validated on a DGX Spark GB10 with the optional MTP GGUF
(DeepSeek-V4-Flash-MTP-Q4K-Q8_0-F32.gguf, ~3.6 GB). LoadModel logs
'ds4: MTP support model loaded ... (draft=2)' on stderr.

Caveat per upstream README: 'currently provides at most a slight speedup,
not a meaningful generation-speed win'. Wired now mainly to track the
upstream API; bigger speedups arrive when ds4 improves the speculative path.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(backend/cpp/ds4): honor PredictOptions sampling with DSML-aware override

Mirrors ds4_server.c:7102-7115 sampling-policy semantics on the LocalAI
gRPC side. The generation loop now consults compute_sample_params() per
token to pick the effective (temperature, top_k, top_p, min_p), based on:

  1. Request defaults: PredictOptions.temperature / .topk / .topp / .minp
  2. Thinking-mode override: when enable_thinking != false, force T=1.0,
     top_k=0, top_p=1.0, min_p=0.0 (creativity for the reasoning pass and
     the trailing content)
  3. DSML structural override: when DsmlParser::IsInDsmlStructural()
     returns true (we are between tool-call markers but NOT in a param
     value payload), force T=0.0 so protocol bytes parse cleanly

When the effective temperature is 0, we keep using ds4_session_argmax +
MTP speculative path (matches ds4-server's gate that only enables MTP for
greedy positions). When > 0, we call ds4_session_sample(s, T, ...) with
a per-thread RNG seeded from system_clock and fall back to single-token
ds4_session_eval.

New public method on DsmlParser: IsInDsmlStructural() encodes which states
need protocol-byte determinism. PARAM_VALUE is excluded (payload uses user
sampling); TEXT and THINK are excluded (no tool-call context to protect).

Verified on the DGX Spark GB10: the e2e suite still passes with all 5
specs including tools, and the Predict output now varies between runs
(creative sampling active) while the tool-call args remain a clean
'{"location":"Paris, France"}' because the parser-state check forces
greedy on the structural bytes.

UX note: thinking mode is ON by default (matching ds4-server). Users who
want deterministic output should set Metadata.enable_thinking = false.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(gallery): add sha256 to deepseek-v4-flash-q2 entry

Per HF LFS metadata for antirez/deepseek-v4-gguf:
  size: 86720111200 bytes (~80.76 GiB)
  sha256: 31598c67c8b8744d3bcebcd19aa62253c6dc43cef3b8adf9f593656c9e86fd8c

LocalAI's downloader verifies sha256 when present, so users who install
deepseek-v4-flash-q2 from the gallery get integrity-checked weights and
the partial-download issue (an 81 GB file is easy to truncate) becomes
recoverable instead of silently producing a broken backend.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-11 22:15:47 +02:00
Ettore Di Giacinto
3568b2819d fix(gallery): keep auto-upgrade off non-dev backends when -development is installed (#9736)
A `-development` backend variant (e.g. `cuda12-llama-cpp-development`)
shares its `alias` with the stable counterpart and is meant to be a
drop-in replacement via ListSystemBackends alias resolution. Two paths
in the auto-upgrade flow let the stable variant slip back in on top of
the user's explicit dev pick:

1. ListSystemBackends emits a synthetic alias row keyed by the alias
   name that re-uses the chosen concrete's metadata pointer. In
   distributed mode, the worker's handleBackendList serialised that
   row over NATS as `{Name: <alias>, URI: <dev URI>, Digest: <dev>}`
   — the frontend can't reconstruct the alias relationship, and the
   wire-rebuilt row then carried `Metadata.Name = <alias>` and
   resolved against an unrelated gallery entry on the next upgrade
   check.
2. CheckUpgradesAgainst happily iterated the synthetic row in
   single-node too. Today the duplicate gallery lookup is harmless
   because both rows share the same `Metadata.Name`, but any gallery
   change that gives a meta backend a version, or any concrete
   sharing its alias with a dev counterpart, would surface a phantom
   non-dev upgrade and auto-upgrade would install it — shadowing the
   dev one through alias-token preference.

Two layered fixes:

- `core/services/worker/lifecycle.go` (`handleBackendList`): drop
  rows where the map key differs from `b.Metadata.Name`. Concrete
  and meta entries always have `key == Metadata.Name`; only synthetic
  aliases violate it. Workers now report only what's actually on disk;
  the per-node UI listing and CheckUpgrades both stop seeing phantoms.
- `core/gallery/upgrade.go` (`CheckUpgradesAgainst`): iterate by key,
  skip rows where `key != Metadata.Name` (belt-and-suspenders for any
  caller-supplied installed set), and apply the dev-aware rule —
  build a set of installed `Metadata.Name`s and drop any non-dev
  candidate `X` whose `X-<devSuffix>` counterpart is installed. Uses
  the configured dev suffix from `getFallbackTagValues(systemState)`.

Manual `POST /api/backends/upgrade/<name>` is unaffected: it goes
straight through `bm.UpgradeBackend(name)` without consulting the
suppression list, so users who genuinely want the stable variant
upgraded can still trigger it explicitly.

Tests in core/gallery/upgrade_test.go cover three cases under
"CheckUpgradesAgainst (distributed)": dev-only installed → only the
dev surfaces; both variants installed → dev still wins; synthetic
alias row is ignored. Generic backend names are used to avoid the
capability filter dropping cuda-prefixed entries on a CPU-only host.

Assisted-by: Claude:claude-opus-4-7

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-09 18:20:00 +02:00
Richard Palethorpe
670259ce43 chore: Security hardening (#9719)
* fix(http): close 0.0.0.0/[::] SSRF bypass in /api/cors-proxy

The CORS proxy carried its own private-network blocklist (RFC 1918 + a
handful of IPv6 ranges) instead of using the same classification as
pkg/utils/urlfetch.go. The hand-rolled list missed 0.0.0.0/8 and ::/128,
both of which Linux routes to localhost — so any user with FeatureMCP
(default-on for new users) could reach LocalAI's own listener and any
other service bound to 0.0.0.0:port via:

  GET /api/cors-proxy?url=http://0.0.0.0:8080/...
  GET /api/cors-proxy?url=http://[::]:8080/...

Replace the custom check with utils.IsPublicIP (Go stdlib IsLoopback /
IsLinkLocalUnicast / IsPrivate / IsUnspecified, plus IPv4-mapped IPv6
unmasking) and add an upfront hostname rejection for localhost, *.local,
and the cloud metadata aliases so split-horizon DNS can't paper over the
IP check.

The IP-pinning DialContext is unchanged: the validated IP from the
single resolution is reused for the connection, so DNS rebinding still
cannot swap a public answer for a private one between validate and dial.

Regression tests cover 0.0.0.0, 0.0.0.0:PORT, [::], ::ffff:127.0.0.1,
::ffff:10.0.0.1, file://, gopher://, ftp://, localhost, 127.0.0.1,
10.0.0.1, 169.254.169.254, metadata.google.internal.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(downloader): verify SHA before promoting temp file to final path

DownloadFileWithContext renamed the .partial file to its final name
*before* checking the streamed SHA, so a hash mismatch returned an
error but left the tampered file at filePath. Subsequent code that
operated on filePath (a backend launcher, a YAML loader, a re-download
that finds the file already present and skips) would consume the
attacker-supplied bytes.

Reorder: verify the streamed hash first, remove the .partial on
mismatch, then rename. The streamed hash is computed during io.Copy
so no second read is needed.

While here, raise the empty-SHA case from a Debug log to a Warn so
"this download had no integrity check" is visible at the default log
level. Backend installs currently pass through with no digest; the
warning makes that footprint observable without changing behaviour.

Regression test asserts os.IsNotExist on the destination after a
deliberate SHA mismatch.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(auth): require email_verified for OIDC admin promotion

extractOIDCUserInfo read the ID token's "email" claim but never
inspected "email_verified". With LOCALAI_ADMIN_EMAIL set, an attacker
who could register on the configured OIDC IdP under that email (some
IdPs accept self-supplied unverified emails) inherited admin role:

  - first login:  AssignRole(tx, email, adminEmail) → RoleAdmin
  - re-login:     MaybePromote(db, user, adminEmail) → flip to RoleAdmin

Add EmailVerified to oauthUserInfo, parse email_verified from the OIDC
claims (default false on absence so an IdP that omits the claim cannot
short-circuit the gate), and substitute "" for the role-decision email
when verified=false via emailForRoleDecision. The user record still
stores the unverified email for display.

GitHub's path defaults EmailVerified=true: GitHub only returns a public
profile email after verification, and fetchGitHubPrimaryEmail explicitly
filters to Verified=true.

Regression tests cover both the helper contract and integration with
AssignRole, including the bootstrap "first user" branch that would
otherwise mask the gate.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(cli): refuse public bind when no auth backend is configured

When neither an auth DB nor a static API key is set, the auth
middleware passes every request through. That is fine for a developer
laptop, a home LAN, or a Tailnet — the network itself is the trust
boundary. It is not fine on a public IP, where every model install,
settings change, and admin endpoint becomes reachable from the
internet.

Refuse to start in that exact configuration. Loopback, RFC 1918,
RFC 4193 ULA, link-local, and RFC 6598 CGNAT (Tailscale's default
range) all count as trusted; wildcard binds (`:port`, `0.0.0.0`,
`[::]`) are accepted only when every host interface is in one of those
ranges. Hostnames are resolved and treated as trusted only when every
answer is.

A new --allow-insecure-public-bind / LOCALAI_ALLOW_INSECURE_PUBLIC_BIND
flag opts out for deployments that gate access externally (a reverse
proxy enforcing auth, a mesh ACL, etc.). The error message lists this
plus the three constructive alternatives (bind a private interface,
enable --auth, set --api-keys).

The interface enumeration goes through a package-level interfaceAddrsFn
var so tests can simulate cloud-VM, home-LAN, Tailscale-only, and
enumeration-failure topologies without poking at the real network
stack.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* test(http): regression-test the localai_assistant admin gate

ChatEndpoint already rejects metadata.localai_assistant=true from a
non-admin caller, but the gate was open-coded inline with no direct
test coverage. The chat route is FeatureChat-gated (default-on), and
the assistant's in-process MCP server can install/delete models and
edit configs — the wrong handler change would silently turn the LLM
into a confused deputy.

Extract the gate into requireAssistantAccess(c, authEnabled) and pin
its behaviour: auth disabled is a no-op, unauthenticated is 403,
RoleUser is 403, RoleAdmin and the synthetic legacy-key admin are
admitted.

No behaviour change in the production path.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* test(http): assert every API route is auth-classified

The auth middleware classifies path prefixes (/api/, /v1/, /models/,
etc.) as protected and treats anything else as a static-asset
passthrough. A new endpoint shipped under a brand-new prefix — or a
new path that simply isn't on the prefix allowlist — would be
reachable anonymously.

Walk every route registered by API() with auth enabled and a fresh
in-memory database (no users, no keys), and assert each API-prefixed
route returns 401 / 404 / 405 to an anonymous request. Public surfaces
(/api/auth/*, /api/branding, /api/node/* token-authenticated routes,
/healthz, branding asset server, generated-content server, static
assets) are explicit allowlist entries with comments justifying them.

Build-tagged 'auth' so it runs against the SQLite-backed auth DB
(matches the existing auth suite).

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* test(http): pin agent endpoint per-user isolation contract

agents.go's getUserID / effectiveUserID / canImpersonateUser /
wantsAllUsers helpers are the single trust boundary for cross-user
access on agent, agent-jobs, collections, and skills routes. A
regression there is the difference between "regular user reads their
own data" and "regular user reads anyone's data via ?user_id=victim".

Lock in the contract:
  - effectiveUserID ignores ?user_id= for unauthenticated and RoleUser
  - effectiveUserID honours it for RoleAdmin and ProviderAgentWorker
  - wantsAllUsers requires admin AND the literal "true" string
  - canImpersonateUser is admin OR agent-worker, never plain RoleUser

No production change — this commit only adds tests.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(downloader): drop redundant stat in removePartialFile

The stat-then-remove pattern is a TOCTOU window and a wasted syscall —
os.Remove already returns ErrNotExist for the missing-file case, so trust
that and treat it as a no-op.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(http): redact secrets from trace buffer and distribution-token logs

The /api/traces buffer captured Authorization, Cookie, Set-Cookie, and
API-key headers verbatim from every request when tracing was enabled. The
endpoint is admin-only but the buffer is reachable via any heap-style
introspection and the captured tokens otherwise outlive the request.
Strip those header values at capture time. Body redaction is left to a
follow-up — the prompts are usually the operator's own and JSON-walking
is invasive.

Distribution tokens were also logged in plaintext from
core/explorer/discovery.go; logs forward to syslog/journald and outlive
the token. Redact those to a short prefix/suffix instead.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(auth): rate-limit OAuth callbacks separately from password endpoints

The shared 5/min/IP limit on auth endpoints is right for password-style
flows but too tight for OAuth callbacks: corporate SSO funnels many real
users through one outbound IP and would trip the limit. Add a separate
60/min/IP limiter for /api/auth/{github,oidc}/callback so callbacks are
bounded against floods without breaking shared-IP deployments.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(gallery): verify backend tarball sha256 when set in gallery entry

GalleryBackend gained an optional sha256 field; the install path now
threads it through to the existing downloader hash-verify (which already
streams, verifies, and rolls back on mismatch). Galleries without sha256
keep working; the empty-SHA path still emits the existing
"downloading without integrity check" warning.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* test(http): pin CSRF coverage on multipart endpoints

The CSRF middleware in app.go is global (e.Use) so it covers every
multipart upload route — branding assets, fine-tune datasets, audio
transforms, agent collections. Pin that contract: cross-site multipart
POSTs are rejected; same-origin / same-site / API-key clients are not.
Also pins the SameSite=Lax fallback path the skipper relies on when
Sec-Fetch-Site is absent.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(http): XSS hardening — CSP headers, safe href, base-href escape, SVG sandbox

Several closely related XSS-prevention changes spanning the SPA shell, the
React UI, and the branding asset server:

- New SecurityHeaders middleware sets CSP, X-Content-Type-Options,
  X-Frame-Options, and Referrer-Policy on every response. The CSP keeps
  script-src permissive because the Vite bundle relies on inline + eval'd
  scripts; tightening that requires moving to a nonce-based policy.

- The <base href> injection in the SPA shell escaped attacker-controllable
  Host / X-Forwarded-Host headers — a single quote in the host header
  broke out of the attribute. Pass through SecureBaseHref (html.EscapeString).

- Three React sinks rendering untrusted content via dangerouslySetInnerHTML
  switch to text-node rendering with whiteSpace: pre-wrap: user message
  bodies in Chat.jsx and AgentChat.jsx, and the agent activity log in
  AgentChat.jsx. The hand-rolled escape on the agent user-message variant
  is replaced by the same plain-text path.

- New safeHref util collapses non-allowlisted URI schemes (most
  importantly javascript:) to '#'. Applied to gallery `<a href={url}>`
  links in Models / Backends / Manage and to canvas artifact links —
  these come from gallery JSON or assistant tool calls and must be treated
  as untrusted.

- The branding asset server attaches a sandbox CSP plus same-origin CORP
  to .svg responses. The React UI loads logos via <img>, but the same URL
  is also reachable via direct navigation; this prevents script
  execution if a hostile SVG slipped past upload validation.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(http): bound HTTP server with read-header and idle timeouts

A net/http server with no timeouts is trivially Slowloris-able and leaks
idle keep-alive connections. Set ReadHeaderTimeout (30s) to plug the
slow-headers attack and IdleTimeout (120s) to cap keep-alive sockets.

ReadTimeout and WriteTimeout stay at 0 because request bodies can be
multi-GB model uploads and SSE / chat completions stream for many
minutes; operators who need tighter per-request bounds should terminate
slow clients at a reverse proxy.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* test(auth): pin PUT /api/auth/profile field-tampering contract

The handler uses an explicit local body struct (only name and avatar_url)
plus a gorm Updates(map) with a column allowlist, so an attacker posting
{"role":"admin","email":"...","password_hash":"..."} can't mass-assign
those fields. Lock that down with a regression test so a future
"let's just c.Bind(&user)" refactor breaks loudly.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(services): strip directory components from multipart upload filenames

UploadDataset and UploadToCollectionForUser took the raw multipart
file.Filename and joined it into a destination path. The fine-tune
upload was incidentally safe because of a UUID prefix that fused any
leading '..' to a literal segment, but the protection is fragile.
UploadToCollectionForUser handed the filename to a vendored backend
without sanitising at all.

Strip to filepath.Base at both boundaries and reject the trivial
unsafe values ("", ".", "..", "/").

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(react-ui): validate persisted MCP server entries on load

localStorage is shared across same-origin pages; an XSS that lands once
can poison persisted MCP server config to attempt header injection or
to feed a non-http URL into the fetch path on subsequent loads.
Validate every entry: types must match, URL must parse with http(s)
scheme, header keys/values must be control-char-free. Drop anything
that doesn't fit.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(http): close X-Forwarded-Prefix open redirect

The reverse-proxy support concatenated X-Forwarded-Prefix into the
redirect target without validation, so a forged header value of
"//evil.com" turned the SPA-shell redirect helper at /, /browse, and
/browse/* into a 301 to //evil.com/app. The path-strip middleware had
the same shape on its prefix-trailing-slash redirect.

Add SafeForwardedPrefix at the middleware boundary: must start with
a single '/', no protocol-relative '//' opener, no scheme, no
backslash, no control characters. Apply at both consumers; misconfig
trips the validator and the header is dropped.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(http): refuse wildcard CORS when LOCALAI_CORS=true with empty allowlist

When LOCALAI_CORS=true but LOCALAI_CORS_ALLOW_ORIGINS was empty, Echo's
CORSWithConfig saw an empty allow-list and fell back to its default
AllowOrigins=["*"]. An operator who flipped the strict-CORS feature
flag without populating the list got the opposite of what they asked
for. Echo never sets Allow-Credentials: true so this isn't directly
exploitable (cookies aren't sent under wildcard CORS), but the
misconfiguration trap is worth closing. Skip the registration and warn.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(auth): zxcvbn password strength check with user-acknowledged override

The previous policy was len < 8, which let through "Password1" and the
rest of the credential-stuffing corpus. LocalAI has no second factor
yet, so the bar needs to sit higher.

Add ValidatePasswordStrength using github.com/timbutler/zxcvbn (an
actively-maintained fork of the trustelem port; v1.0.4, April 2024):
- min 12 chars, max 72 (bcrypt's truncation point)
- reject NUL bytes (some bcrypt callers truncate at the first NUL)
- require zxcvbn score >= 3 ("safely unguessable, ~10^8 guesses to
  break"); the hint list ["localai", "local-ai", "admin"] penalises
  passwords built from the app's own branding

zxcvbn produces false positives sometimes (a strong-looking password
that happens to match a dictionary word) and operators occasionally
need to set a known-weak password (kiosk demos, CI rigs). Add an
acknowledgement path: PasswordPolicy{AllowWeak: true} skips the
entropy check while still enforcing the hard rules. The structured
PasswordErrorResponse marks weak-password rejections as Overridable
so the UI can surface a "use this anyway" checkbox.

Wired through register, self-service password change, and admin
password reset on both the server and the React UI.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(react-ui): drop HTML5 minLength on new-password inputs

minLength={12} on the new-password input let the browser block the
form submit silently before any JS or network call ran. The browser
focused the field, showed a brief native tooltip, and that was that —
no toast, no fetch, no clue. Reproducible by typing fewer than 12
chars on the second password change of a session.

The JS-level length check in handleSubmit already shows a toast and
the server rejects with a structured error, so the HTML5 attribute
was redundant defence anyway. Drop it.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(react-ui): bundle Geist fonts locally instead of fetching from Google

The new CSP correctly refused to apply styles from
fonts.googleapis.com because style-src is locked to 'self' and
'unsafe-inline'. Loosening the CSP would defeat its purpose; the
right fix is to stop reaching out to a third-party CDN for fonts on
every page load.

Add @fontsource-variable/geist and @fontsource-variable/geist-mono as
npm deps and import them once at boot. Drop the <link rel="preconnect">
and external stylesheet from index.html.

Side benefit: no third-party tracking via Referer / IP on every UI
load, no failure mode when offline / behind a captive portal.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(react-ui): refresh i18n strings to reflect 12-char password minimum

The translations still said "at least 8 characters" everywhere — the
client-side toast on a too-short password change told the user the
wrong floor. Update tooShort and newPasswordPlaceholder /
newPasswordDescription across all five locales (en, es, it, de,
zh-CN) to match the real ValidatePasswordStrength rule.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(auth): make password length-floor overridable like the entropy check

The 12-char minimum was a policy choice, not a technical invariant —
only "non-empty", "<= 72 bytes", and "no NUL bytes" are real bcrypt
constraints. Treating length-12 as a hard rule was inconsistent with
the entropy check (already overridable) and friction for use cases
where the account is just a name on a session, not a security
boundary (single-user kiosk, CI rig, lab demo).

Restructure ValidatePasswordStrength:
- Hard rules (always enforced): non-empty, <= MaxPasswordLength, no NUL byte
- Policy rules (skipped when AllowWeak=true): length >= 12, zxcvbn score >= 3

PasswordError now marks password_too_short as Overridable too. The
React forms generalised from `error_code === 'password_too_weak'` to
`overridable === true`, and the JS-side preflight length checks were
removed (server is source of truth, returns the same checkbox flow).

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-08 16:25:45 +02:00
LocalAI [bot]
e5d7b84216 fix(distributed): split NATS backend.upgrade off install + dedup loads (#9717)
* feat(messaging): add backend.upgrade NATS subject + payload types

Splits the slow force-reinstall path off backend.install so it can run on
its own subscription goroutine, eliminating head-of-line blocking between
routine model loads and full gallery upgrades.

Wire-level Force flag on BackendInstallRequest is kept for one release as
the rolling-update fallback target; doc note marks it deprecated.

Assisted-by: Claude:claude-sonnet-4-6
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(distributed/worker): add per-backend mutex helper to backendSupervisor

Different backend names lock independently; same backend serializes. This
is the synchronization primitive used by the upcoming concurrent install
handler — without it, wrapping the NATS callback in a goroutine would
race the gallery directory when two requests target the same backend.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(distributed/worker): run backend.install handler in a goroutine

NATS subscriptions deliver messages serially on a single per-subscription
goroutine. With a synchronous install handler, a multi-minute gallery
download would head-of-line-block every other install request to the
same worker — manifesting upstream as a 5-minute "nats: timeout" on
unrelated routine model loads.

The body now runs in its own goroutine, with a per-backend mutex
(lockBackend) protecting the gallery directory from concurrent operations
on the same backend. Different backend names install in parallel.

Backward-compat: req.Force=true is still honored here, so an older master
that hasn't been updated to send on backend.upgrade keeps working.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(distributed/worker): subscribe to backend.upgrade as a separate path

Slow force-reinstall now lives on its own NATS subscription, so a
multi-minute gallery pull cannot head-of-line-block the routine
backend.install handler on the same worker. Same per-backend mutex
guards both — concurrent install + upgrade for the same backend
serialize at the gallery directory; different backends are independent.

upgradeBackend stops every live process for the backend, force-installs
from gallery, and re-registers. It does not start a new process — the
next backend.install will spawn one with the freshly-pulled binary.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(distributed): add UpgradeBackend on NodeCommandSender; drop Force from InstallBackend

Master now sends to backend.upgrade for force-reinstall, with a
nats.ErrNoResponders fallback to the legacy backend.install Force=true
path so a rolling update with a new master + an old worker still
converges. The Force parameter leaves the public Go API surface
entirely — only the internal fallback sets it on the wire.

InstallBackend timeout drops 5min -> 3min (most replies are sub-second
since the worker short-circuits on already-running or already-installed).
UpgradeBackend timeout is 15min, sized for real-world Jetson-on-WiFi
gallery pulls.

Updates the admin install HTTP endpoint
(core/http/endpoints/localai/nodes.go) to the new signature too.

router_test.go's fakeUnloader does not yet implement the new interface
shape; Task 3.2 will catch it up before the next package-level test run.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(distributed): update fakeUnloader for new NodeCommandSender shape

InstallBackend lost its force bool param (Force is not part of the public
Go API anymore — only the internal upgrade-fallback path sets it on the
wire). UpgradeBackend gained a method. Fake records both call slices and
provides an installHook concurrency seam for upcoming singleflight tests.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(distributed): cover UpgradeBackend's new subject + rolling-update fallback

Task 3.1 changed the master to publish UpgradeBackend on the new
backend.upgrade subject; the existing UpgradeBackend tests scripted the
old install subject and so all 3 began failing as expected. Updates them
to script SubjectNodeBackendUpgrade with BackendUpgradeReply.

Adds two new specs for the rolling-update fallback:
  - ErrNoResponders on backend.upgrade triggers a backend.install
    Force=true retry on the same node.
  - Non-NoResponders errors propagate to the caller unchanged.

scriptedMessagingClient gains scriptNoResponders (real nats sentinel) and
scriptReplyMatching (predicate-matched canned reply, used to assert that
the fallback path actually sets Force=true on the install retry).

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(distributed): coalesce concurrent identical backend.install via singleflight

Six simultaneous chat completions for the same not-yet-loaded model were
observed firing six independent NATS install requests, each serializing
through the worker's per-subscription goroutine and amplifying queue
depth. SmartRouter now wraps the NATS round-trip in a singleflight.Group
keyed by (nodeID, backend, modelID, replica): N concurrent identical
loads share one round-trip and one reply.

Distinct (modelID, replica) keys still fire independent calls, so
multi-replica scaling and multi-model fan-out are unaffected.

fakeUnloader gains a sync.Mutex around its recording slices to keep
concurrent test goroutines race-clean.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(e2e/distributed): drop force arg from InstallBackend test calls

Two e2e test call sites still passed the trailing force bool that was
removed from RemoteUnloaderAdapter.InstallBackend in 9bde76d7. Caught
by golangci-lint typecheck on the upgrade-split branch (master CI was
already green because these tests don't run in the standard test path).

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(distributed): extract worker business logic to core/services/worker

core/cli/worker.go grew to 1212 lines after the backend.upgrade split.
The CLI package was carrying backendSupervisor, NATS lifecycle handlers,
gallery install/upgrade orchestration, S3 file staging, and registration
helpers — all distributed-worker business logic that doesn't belong in
the cobra surface.

Move it to a new core/services/worker package, mirroring the existing
core/services/{nodes,messaging,galleryop} pattern. core/cli/worker.go
shrinks to ~19 lines: a kong-tagged shim that embeds worker.Config and
delegates Run.

No behavior change. All symbols stay unexported except Config and Run.
The three worker-specific tests (addr/replica/concurrency) move with
the code via git mv so history follows them.

Files split as:
  worker.go        - Run entry point
  config.go        - Config struct (kong tags retained, kong not imported)
  supervisor.go    - backendProcess, backendSupervisor, process lifecycle
  install.go       - installBackend, upgradeBackend, findBackend, lockBackend
  lifecycle.go     - subscribeLifecycleEvents (verbatim, decomposition is
                     a follow-up commit)
  file_staging.go  - subscribeFileStaging, isPathAllowed
  registration.go  - advertiseAddr, registrationBody, heartbeatBody, etc.
  reply.go         - replyJSON
  process_helpers.go - readLastLinesFromFile

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(distributed/worker): decompose subscribeLifecycleEvents into per-event handlers

The 226-line subscribeLifecycleEvents method packed eight NATS subscriptions
inline. Each grew context-shaped doc comments mixed with subscription
plumbing, making it hard to read any one handler without scrolling past the
others. Extract each handler into its own method on *backendSupervisor; the
subscriber becomes a thin 8-line dispatcher.

No behavior change: each method body is byte-equivalent to its corresponding
inline goroutine + handler. Doc comments that were attached to the inline
SubscribeReply calls migrate to the new method godocs.

Adding the next NATS subject is now a 2-line patch to the dispatcher plus
one new method, instead of grafting onto a monolith.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-08 16:24:54 +02:00
LocalAI [bot]
2be07f61da feat(whisper): honor client cancellation via ggml abort_callback (#9710)
* refactor(transcription): propagate request ctx through ModelTranscription*

Replaces context.Background() with the HTTP request ctx so client
disconnects start cancelling the gRPC call. No backend-side abort wiring
yet — that comes in a later commit. Pure plumbing.

Assisted-by: Claude:claude-haiku-4-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(cli): pass ctx to backend.ModelTranscription

Follow-up to e65d3e1f which threaded ctx through ModelTranscription
but missed the CLI caller. CLI commands have no request-scoped ctx,
so context.Background() is correct here.

Assisted-by: Claude:claude-haiku-4-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(audio): propagate request ctx into TTS, sound-gen, audio-transform

Same ctx-plumbing pattern applied to the rest of the audio path. CLI
callers use context.Background() since there is no request scope; HTTP
callers use c.Request().Context().

Assisted-by: Claude:claude-haiku-4-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(backend): propagate request ctx into biometric, detection, rerank, diarization paths

Replaces remaining context.Background() sites in core/backend with the
caller's ctx. After this commit, every core/backend/*.go entry point
threads the request ctx end-to-end to the gRPC client.

Assisted-by: Claude:claude-haiku-4-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(grpc): plumb ctx through AIModel.AudioTranscription{,Stream}

Adds context.Context as first parameter to the AIModel interface methods
that wrap whisper-style transcription. Server-side gRPC handler now
forwards the per-RPC ctx (server-streaming uses stream.Context()).
Whisper, Voxtral, vibevoice-cpp, and sherpa-onnx accept the parameter;
none uses it yet — the actual cancellation primitive lands in the next
commit so this is pure plumbing.

Assisted-by: Claude:claude-sonnet-4-6
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(whisper): add abort_callback hook in the C++ bridge

Installs a std::atomic<int> flag, wires it into
whisper_full_params.abort_callback, and exposes a set_abort(int) C
symbol so Go can flip the flag from a goroutine watching the request
context. transcribe() now distinguishes abort (return 2) from real
whisper_full failure (return 1).

Assisted-by: Claude:claude-haiku-4-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(whisper): register set_abort symbol in the purego loader

Adds the Go-side binding for the new C export so the next commit can
call CppSetAbort(1) from a watcher goroutine on ctx.Done().

Assisted-by: Claude:claude-haiku-4-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(whisper): honor ctx cancellation and return codes.Canceled

A watcher goroutine watches ctx.Done() during AudioTranscription and
calls CppSetAbort(1) on cancel. whisper_full sees abort_callback return
true at the next compute graph step, returns non-zero, and the bridge
returns 2 -> AudioTranscription maps that to codes.Canceled.

Adds an opt-in test (gated on WHISPER_MODEL_PATH / WHISPER_AUDIO_PATH)
that asserts cancellation latency under 5s and proves the abort flag
resets cleanly so the next transcription succeeds.

Assisted-by: Claude:claude-sonnet-4-6
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(whisper): join the cancel watcher goroutine before returning

Follow-up to 85edf9d2. The previous commit used `defer close(done)` and
called the watcher "joined synchronously" — but close() only signals,
it does not block until the goroutine exits. That left a window where
a late CppSetAbort(1) from a cancelled call could land on the next
call, after its C-side g_abort reset but before whisper_full() began
polling the abort callback, corrupting the second transcription.

Switch to a sync.WaitGroup join so wg.Wait() blocks until the watcher
has actually returned from its select.

Assisted-by: Claude:claude-sonnet-4-6
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(whisper): short-circuit pre-cancelled ctx in AudioTranscription

If ctx is already Done() at entry, return codes.Canceled immediately
instead of running the full transcription. The C-side g_abort reset
happens at the start of transcribe() and would otherwise overwrite a
watcher-set abort flag from an already-cancelled ctx, producing a
spurious successful transcription on a request the client has already
abandoned.

Assisted-by: Claude:claude-haiku-4-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(tests/distributed): update testLLM mock for new AudioTranscription signature

Phase B (93c48e19) added context.Context to AIModel.AudioTranscription
but missed the testLLM mock in tests/e2e/distributed. CI golangci-lint
caught it: *testLLM did not implement grpc.AIModel because the method
signature lacked the ctx parameter, which broke the distributed test
suite compilation and cascaded through every backend-build job that
runs `go build ./...`.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(whisper): port cancellation test to Ginkgo/Gomega

Project policy (.agents/coding-style.md, enforced by golangci-lint
forbidigo) is that all Go tests must use Ginkgo v2 + Gomega — no
stdlib testing patterns (t.Skip, t.Fatalf, etc.). Convert the
cancellation test to a Describe/It block with Skip(...) for env
gating and Expect/HaveOccurred for assertions.

Same coverage: cancel mid-flight returns codes.Canceled within 5s and
a follow-up transcription succeeds, proving the C-side g_abort flag
resets cleanly.

Assisted-by: Claude:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-08 01:44:47 +02:00
LocalAI [bot]
595b6fd22d feat(api/transcription): include segments + duration + language on stream done event (#9709)
streamTranscription previously emitted a done event with just `text`,
matching the OpenAI streaming spec exactly. Streaming clients that need
per-utterance timings or audio duration had to fall back to the
non-streaming JSON path — and that path is exactly the one that trips
on ResponseHeaderTimeout when whisper requests queue behind each other
on a SingleThread backend.

Extend the done event to additively carry `language`, `duration`, and
a `segments` array (id, start, end, text — start/end as float seconds,
matching TranscriptionSegmentSeconds). Empty / zero values are still
omitted; spec-compliant clients ignore the new fields.

This unblocks notary's streaming Transcribe (companion change in the
notary repo) so it produces the same TranscriptionResult shape as the
JSON path while sidestepping the queue-induced header timeouts.


Assisted-by: Claude:claude-opus-4-7 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-07 17:28:26 +02:00
LocalAI [bot]
447c186089 fix(distributed): make backend upgrade actually re-install on workers (#9708)
* fix(distributed): make backend upgrade actually re-install on workers

UpgradeBackend dispatched a vanilla backend.install NATS event to every
node hosting the backend. The worker's installBackend short-circuits on
"already running for this (model, replica) slot" and returns the
existing address — so the gallery install path was skipped, no artifact
was re-downloaded, no metadata was written. The frontend's drift
detection then re-flagged the same backends every cycle (installedDigest
stays empty → mismatch → "Backend upgrade available (new build)") while
"Backend upgraded successfully" landed in the logs at the same time.
The user-visible symptom: clicking "Upgrade All" silently does nothing
and the same N backends sit on the upgrade list forever.

Two coupled fixes, one PR:

1. Force flag on backend.install. Add `Force bool` to
   BackendInstallRequest and thread it through NodeCommandSender ->
   RemoteUnloaderAdapter. UpgradeBackend (and the reconciler's pending-op
   drain when retrying an upgrade) sets force=true; routine load events
   and admin install endpoints keep force=false. On the worker, force=true
   stops every live process that uses this backend (resolveProcessKeys
   for peer replicas, plus the exact request processKey), skips the
   findBackend short-circuit, and passes force=true into
   gallery.InstallBackendFromGallery so the on-disk artifact is
   overwritten. After the gallery install completes, startBackend brings
   up a fresh process at the same processKey on a new port.

2. Liveness check on the fast path. installBackend's "already running"
   branch read getAddr without verifying the process was alive, so a
   gRPC backend that died without the supervisor noticing left a stale
   (key, addr) entry. The reconciler then dialed that address, got
   ECONNREFUSED, marked the replica failed, retried install — and the
   supervisor said "already running addr=…" again. Loop forever, exactly
   what we observed on a node whose llama-cpp process had died but whose
   supervisor record persisted. Verify s.isRunning(processKey) before
   trusting getAddr; if the entry is stale, stopBackendExact cleans up
   and we fall through to a real install.

Backwards-compatible: the new Force field is omitempty, older workers
ignore it (their default behavior matches force=false). The signature
change on NodeCommandSender.InstallBackend is internal-only.

Verified: unit tests in core/services/nodes pass (108s suite). The
pre-existing core/backend build break (proto regen pending for
word-level timestamps) blocks core/cli and core/http/endpoints/localai
package tests but is unrelated to this change.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* test(e2e/distributed): pass force=false to adapter.InstallBackend

NodeCommandSender.InstallBackend gained a final force bool in the
upgrade-force commit; the e2e distributed lifecycle tests still called
the old 8-arg signature and broke compilation. These tests exercise the
routine install path (single replica, default behavior), so force=false
preserves their existing semantics.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-07 17:28:14 +02:00
LocalAI [bot]
cec5c4fdfc fix(http): make handler-error status visible in access log + transcription errors (#9707)
* fix(http): log accurate status code when handler returns error

The custom xlog access-log middleware in API() reads res.Status
*before* Echo's central HTTPErrorHandler runs, so when a handler
returns an error without writing a response (e.g.
TranscriptEndpoint's `return err` on backend failure) the status
field stays at its default 200. The logged line then claims
status=200 while the client receives 500 — silently hiding every
500/503/etc. that bubbles up through Echo's error handler.

Mirror echo.DefaultHTTPErrorHandler's status derivation when
err != nil and the response hasn't been committed: default to 500,
upgrade to *echo.HTTPError.Code if applicable. The logged status now
matches what the client actually sees, so failed transcription
requests stop appearing as 200 in the access log.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(transcription): log underlying error before returning 500 to client

ModelTranscriptionWithOptions surfaces real failures — gRPC errors
from a remote node, model load problems, ffmpeg conversion crashes —
but TranscriptEndpoint just did `return err`, so Echo turned it into
a 500 with a generic body and the original error was lost. Operators
chasing transcription failures across distributed mode were left
with "upstream returned 500" on the client and zero context anywhere
in the frontend's logs.

Add an xlog.Error before returning, recording model name, the staged
audio path, and the underlying error. Combined with the access-log
status fix, a failing transcription now leaves an audit trail (real
status code in the access line, real cause in an Error line) instead
of vanishing.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-07 17:27:45 +02:00
LocalAI [bot]
392fc9ce3d fix(auth): cascade user deletion across all owned data on PostgreSQL (#9702)
* fix(auth): cascade user deletion across all owned data on PostgreSQL

Deleting a user from the admin UI in distributed mode (PostgreSQL auth
DB) returned "user not found" even when the user clearly existed. The
old handler ignored result.Error and only checked RowsAffected, so a
foreign-key constraint violation surfaced as a misleading 404.

Two issues drove this:

1. invite_codes.created_by / used_by reference users(id) but the
   InviteCode model declared the FKs without ON DELETE CASCADE. On
   PostgreSQL the engine therefore rejected the user delete with NO
   ACTION whenever the user had ever issued or consumed an invite. On
   SQLite (default in single-node mode) FKs are not enforced, so the
   bug never appeared there.
2. Several owned tables were never cleaned up regardless of dialect:
   user_permissions and quota_rules relied on CASCADE that does not
   fire under SQLite, and usage_records have no FK at all and were
   left orphaned in every dialect.

Introduce auth.DeleteUserCascade which runs the full cleanup in a
single transaction: drop invites authored by the user, NULL used_by on
invites they consumed (preserves the audit trail), and explicitly wipe
sessions, API keys, permissions, quota rules, and usage metrics before
deleting the user. The in-memory quota cache is invalidated after
commit so a recreated user with the same id never sees stale entries.
The HTTP handler now maps the helper's errors to proper status codes —
real failures surface as 500 with the cause instead of being swallowed
as "not found".

Add Ginkgo regression coverage in core/http/auth/users_test.go and
core/http/routes/auth_test.go covering invite cleanup, used_by
null-out, full data wipe, and the FK-enforced original failure mode
(via PRAGMA foreign_keys=ON to mirror PostgreSQL behavior on SQLite).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* chore(deps): bump LocalAGI/LocalRecall — pull in go-fitz PDF extraction

Pulls LocalAGI@main (facd888) and LocalRecall@v0.6.0. The latter
swaps PDF text extraction from dslipak/pdf to gen2brain/go-fitz
(libmupdf bindings) and wraps it in a 60s goroutine timeout —
previously certain PDFs (broken xref tables, encrypted, image-only
without OCR) would hang indefinitely inside r.GetPlainText() and
poison the upload queue.

Pure dep bump, no LocalAI source changes. Indirect graph picks up
go-fitz + purego + ffi; drops dslipak/pdf.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 08:28:58 +02:00
LocalAI [bot]
22ff86d64f fix(distributed): round-robin replicas of the same model (#9695)
FindAndLockNodeWithModel previously ordered candidate replicas by
in_flight ASC, available_vram DESC. The primary key is correct, but the
tiebreaker meant that whenever in_flight tied — the common case at low
to moderate concurrency where requests don't overlap — the node with
the largest available VRAM won every pick. With autoscaling placing
replicas of the same model on multiple nodes, the fattest GPU node
ended up taking nearly all the load while the others sat idle.

Insert last_used ASC between the two existing tiers. last_used is
already refreshed inside the same transaction that increments in_flight
(and by TouchNodeModel on cache hits in the router), so the
"oldest-used" replica naturally rotates through the candidate set —
strict round-robin without a schema change. available_vram DESC is
demoted to a final tiebreaker for cold starts where last_used is
identical across replicas.

Placement queries (FindNodeWithVRAM, FindLeastLoadedNode, and the
*FromSet variants) have the same fattest-GPU bias on tiebreakers but
are higher-cost to fix consistently. Deferred to a follow-up so the
routing fix can land first — for the user-observed symptom routing was
the dominant cause anyway.

Test: registry_test.go adds a focused spec that loads three replicas
on three nodes with 24/16/8 GB VRAM and asserts each is picked at
least twice across 9 in_flight-tied calls.


Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash] [Grep]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 19:40:54 +02:00
Richard Palethorpe
969005b2a1 feat(gallery): Speed up load times and clean gallery entries (#9211)
* feat: Rework VRAM estimation and use known_usecases in gallery

Signed-off-by: Richard Palethorpe <io@richiejp.com>
Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]

* chore(gallery): regenerate gallery index and add known_usecases to model entries

Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-06 14:51:38 +02:00
LocalAI [bot]
6d56bf98fe feat(importers): add vibevoice-cpp importer for GGUF bundles (#9685)
Routes mudler/vibevoice.cpp-models and similar repos to the vibevoice-cpp
backend. Detects via repo name ("vibevoice.cpp"/"vibevoice-cpp"), file
listing (vibevoice-*.gguf + tokenizer.gguf), or preferences.backend
override. Defaults to the realtime TTS model; preferences.usecase=asr
selects the ASR/diarization variant. Bundles the required tokenizer.gguf
and (for TTS) a voice prompt, emitting the Options[] entries the backend
expects. Registered ahead of VibeVoiceImporter so the C++ bundles aren't
swallowed by the older Python-backend substring match.


Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Write] [Bash]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 13:33:10 +02:00
LocalAI [bot]
70cf8ac546 fix(backend): resolve relative draft_model paths against the models dir (#9680)
* fix(backend): resolve relative draft_model paths against the models dir

The main model file and mmproj are joined with the configured models
directory before reaching the backend, but draft_model was sent
verbatim. With a relative draft_model in the YAML config, llama.cpp
opens the path from the backend process's CWD and fails with "No such
file or directory", forcing users to hard-code an absolute path.

Mirror the existing mmproj resolution: if draft_model is relative,
join it with modelPath. Absolute paths are passed through unchanged.

Adds an e2e regression test against the mock backend that asserts the
main model file, mmproj, and draft_model all arrive at the backend
resolved to absolute paths.

Closes #9675

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7-1m [Read] [Edit] [Bash] [Write]

* fix(backend): always join draft_model with models dir (drop IsAbs shortcut)

The previous commit kept absolute draft_model paths intact via an
IsAbs check. That left a path-traversal vector open: a user-supplied
YAML config could set draft_model to /etc/passwd (or any other host
file the backend process can read) and the path would be sent through
unchanged.

filepath.Join cleans the leading slash from absolute components, so
joining unconditionally — the way mmproj already does — keeps the
result rooted at the configured models directory regardless of input.

Adds a second e2e spec that feeds an absolute draft_model into the
mock backend and asserts the path is clamped under modelsPath.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7-1m [Read] [Edit] [Bash]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 00:58:38 +02:00
Andreas Egli
af83518532 feat: support word-level timestamps for faster-whisper (#9621)
Signed-off-by: Andreas Egli <github@kharan.ch>
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2026-05-06 00:32:52 +02:00
Ettore Di Giacinto
75fba9e03f fix(distributed): scope Upgrade All to nodes that have the backend installed (#9678)
In distributed mode the React UI's "Upgrade All" button fanned every
detected outdated backend out to every healthy backend node, including
nodes that never had that backend installed. On heterogeneous clusters
this surfaced as platform errors (e.g. mac-mini-m4 asked to upgrade
cpu-insightface-development, which has no darwin/arm64 variant) and left
forever-retrying pending_backend_ops rows.

DistributedBackendManager.UpgradeBackend now queries ListBackends()
first, builds the target node-ID set from SystemBackend.Nodes, and only
fans out to those nodes — every per-node primitive
(adapter.InstallBackend, the pending-ops queue, BackendOpResult) is
unchanged. enqueueAndDrainBackendOp gains an optional targetNodeIDs
allowlist; Install/Delete keep their fan-to-everyone semantics by
passing nil. If no node reports the backend installed, UpgradeBackend
now returns a clear "not installed on any node" error instead of
producing a stuck queue.

Adds Ginkgo coverage for the smart fan-out: backend on a subset of
nodes goes only to those nodes; backend on no node returns the new
error and never sends a NATS install request.


Assisted-by: Claude:claude-opus-4-7 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-06 00:28:41 +02:00
Richard Palethorpe
8e43842175 feat(vllm, distributed): tensor parallel distributed workers (#9612)
* feat(vllm): build vllm from source for Intel XPU

Upstream publishes no XPU wheels for vllm. The Intel profile was
silently picking up a non-XPU wheel that imported but errored at
engine init, and several runtime deps (pillow, charset-normalizer,
chardet) were missing on Intel -- backend.py crashed at import time
before the gRPC server came up.

Switch the Intel profile to upstream's documented from-source
procedure (docs/getting_started/installation/gpu.xpu.inc.md in
vllm-project/vllm):

  - Bump portable Python to 3.12 -- vllm-xpu-kernels ships only a
    cp312 wheel.
  - Source /opt/intel/oneapi/setvars.sh so vllm's CMake build sees
    the dpcpp/sycl compiler from the oneapi-basekit base image.
  - Hide requirements-intel-after.txt during installRequirements
    (it used to 'pip install vllm'); install vllm's deps from a
    fresh git clone of vllm via 'uv pip install -r
    requirements/xpu.txt', swap stock triton for
    triton-xpu==3.7.0, then 'VLLM_TARGET_DEVICE=xpu uv pip install
    --no-deps .'.
  - requirements-intel.txt trimmed to LocalAI's direct deps
    (accelerate / transformers / bitsandbytes); torch-xpu, vllm,
    vllm_xpu_kernels and the rest come from upstream's xpu.txt
    during the source build.
  - requirements.txt: add pillow + charset-normalizer + chardet --
    used by backend.py and missing on the Intel install profile.
  - run.sh: 'set -x' so backend startup is visible in container
    logs (the gRPC startup error path was previously opaque).

Also adds a one-line docs example for engine_args.attention_backend
under the vLLM section, since older XE-HPG GPUs (e.g. Arc A770)
need TRITON_ATTN to bypass the cutlass path in vllm_xpu_kernels.

Tested end-to-end on an Intel Arc A770 with Qwen2.5-0.5B-Instruct
via LocalAI's /v1/chat/completions.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(vllm): add multi-node data-parallel follower worker

vLLM v1's multi-node story is one process per node sharing a DP
coordinator over ZMQ -- the head runs the API server with
data_parallel_size > 1 and followers run `vllm serve --headless ...`
with matching topology. Today LocalAI can already configure DP on the
head via the engine_args YAML map, but there's no way to bring up the
follower nodes -- so the head sits waiting for ranks that never
handshake.

Add `local-ai p2p-worker vllm`, mirroring MLXDistributed's structural
precedent (operator-launched, static config, no NATS placement). The
worker:

  - Optionally self-registers with the frontend as an agent-type node
    tagged `node.role=vllm-follower` so it's visible in the admin UI
    and operators can scope ordinary models away via inverse
    selectors.
  - Resolves the platform-specific vllm backend via the gallery's
    "vllm" meta-entry (cuda*, intel-vllm, rocm-vllm, ...).
  - Runs vLLM as a child process so the heartbeat goroutine survives
    until vLLM exits; forwards SIGINT/SIGTERM so vLLM can clean up its
    ZMQ sockets before we tear down.
  - Validates --headless + --start-rank 0 is rejected (rank 0 is the
    head and must serve the API).

Backend run.sh dispatches `serve` as the first arg to vllm's own CLI
instead of LocalAI's backend.py gRPC server -- the follower speaks
ZMQ directly to the head, there is no LocalAI gRPC on the follower
side. Single-node usage is unchanged.

Generalises the gallery resolution helper into findBackendPath()
shared by MLX and vLLM workers; extracts ParseNodeLabels for the
comma-separated label parsing both use.

Ships with two compose recipes (`docker-compose.vllm-multinode.yaml`
for NVIDIA, `docker-compose.vllm-multinode.intel.yaml` for Intel
XPU/xccl) plus `tests/e2e/vllm-multinode/smoke.sh`. Both vendors are
supported (NCCL for CUDA/ROCm, xccl for XPU) but mixed-vendor DP is
not -- PyTorch's process group requires every rank to use the same
collective backend, and NCCL/xccl/gloo don't interoperate.

Out of scope (deferred): SmartRouter-driven placement of follower
ranks via NATS backend.install events, follower log streaming through
/api/backend-logs, tensor-parallel across nodes, disaggregated
prefill via KVTransferConfig.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* test(vllm): CPU-only end-to-end test for multi-node DP

Adds tests/e2e/vllm-multinode/, a Ginkgo + testcontainers-go suite
that brings up a head + headless follower from the locally-built
local-ai:tests image, bind-mounts the cpu-vllm backend extracted by
make extract-backend-vllm so it's seen as a system backend (no gallery
fetch, no registry server), and asserts a chat completion across both
DP ranks. New `make test-e2e-vllm-multinode` target wires the docker
build, backend extract, and ginkgo run together; BuildKit caches both
images so re-runs only rebuild what changed. Tagged Label("VLLMMultinode")
so the existing distributed suite isn't pulled along.

Two pre-existing bugs surfaced by the test:

1. extract-backend-% (Makefile) failed for every backend, because all
   backend images end with `FROM scratch` and `docker create` rejects
   an image with no CMD/ENTRYPOINT. Fixed by passing
   --entrypoint=/run.sh -- the container is never started, only
   docker-cp'd, so the path doesn't have to exist; we just need
   anything that satisfies the daemon's create-time validation.

2. backend/python/vllm/run.sh's `serve` shortcut for the multi-node DP
   follower exec'd ${EDIR}/venv/bin/vllm directly, but uv bakes an
   absolute build-time shebang (`#!/vllm/venv/bin/python3`) that no
   longer resolves once the backend is relocated to BackendsPath.
   _makeVenvPortable's shebang rewriter only matches paths that
   already point at ${EDIR}, so the original shebang slips through
   unchanged. Fixed by exec-ing ${EDIR}/venv/bin/python with the script
   as an argument -- Python ignores the script's shebang in that case.

The test fixture caps memory aggressively (max_model_len=512,
VLLM_CPU_KVCACHE_SPACE=1, TORCH_COMPILE_DISABLE=1) so two CPU engines
fit on a 32 GB box. TORCH_COMPILE_DISABLE is currently mandatory for
cpu-vllm: torch._inductor's CPU-ISA probe runs even with
enforce_eager=True and needs g++ on PATH, which the LocalAI runtime
image doesn't ship -- to be addressed in a follow-up that bundles a
toolchain in the cpu-vllm backend.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(vllm): bundle a g++ toolchain in the cpu-vllm backend image

torch._inductor's CPU-ISA probe (`cpu_model_runner.py:65 "Warming up
model for the compilation"`) shells out to `g++` at vllm engine
startup, regardless of `enforce_eager=True` -- the eager flag only
disables CUDA graphs, not inductor's first-batch warmup. The LocalAI
CPU runtime image (Dockerfile, unconditional apt list) does not ship
build-essential, and the cpu-vllm backend image is `FROM scratch`,
so any non-trivial inference on cpu-vllm crashes with:

  torch._inductor.exc.InductorError:
    InvalidCxxCompiler: No working C++ compiler found in
    torch._inductor.config.cpp.cxx: (None, 'g++')

Bundling the toolchain in the CPU runtime image would bloat every
non-vllm-CPU deployment and force a single GCC version on backends
that may want clang or a different version. So this lives in the
backend, gated to BUILD_TYPE=='' (the CPU profile).

`package.sh` snapshots g++ + binutils + cc1plus + libstdc++ + libc6
(runtime + dev) + the math libs cc1plus links (libisl/libmpc/libmpfr/
libjansson) into ${BACKEND}/toolchain/, mirroring /usr/... layout. The
unversioned binaries on Debian/Ubuntu are symlink chains pointing into
multiarch packages (`g++` -> `g++-13` -> `x86_64-linux-gnu-g++-13`,
the latter in `g++-13-x86-64-linux-gnu`), so the package list resolves
both the version and the arch-triplet variant. Symlinks /lib ->
usr/lib and /lib64 -> usr/lib64 are recreated under the toolchain
root because Ubuntu's UsrMerge keeps them at /, and ld scripts
(`libc.so`, `libm.so`) hardcode `/lib/...` paths that --sysroot
re-roots into the toolchain.

The unversioned `g++`/`gcc`/`cpp` symlinks are replaced with wrapper
shell scripts that resolve their own location at runtime and pass
`--sysroot=<toolchain>` and `-B <toolchain>/usr/lib/gcc/<triplet>/<ver>/`
to the underlying versioned binary. That's how torch's bare `g++ foo.cpp
-o foo` invocation finds cc1plus (-B), system headers (--sysroot), and
the bundled libstdc++ (--sysroot, --sysroot is recursive into linker).

`run.sh` adds the toolchain bin dir to PATH and the toolchain's
shared-lib dir to LD_LIBRARY_PATH -- everything else (header search,
linker search, executable search) is encapsulated in the wrappers.
No-op for non-CPU builds, the dir doesn't exist there.

The cpu-vllm image grows by ~217 MB. Tradeoff is acceptable -- cpu-vllm
is already a niche profile (few users compared to GPU vllm) and the
alternative is a backend that crashes at first inference unless the
operator manually sets TORCH_COMPILE_DISABLE=1, which silently disables
all torch.compile optimizations.

Drops `TORCH_COMPILE_DISABLE=1` from tests/e2e/vllm-multinode -- the
smoke now exercises the real compile path through the bundled toolchain.
Test runtime is +20s for the warmup compile, still <90s end to end.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(vllm): scope jetson-ai-lab index to L4T-specific wheels via pyproject.toml

The L4T arm64 build resolves dependencies through pypi.jetson-ai-lab.io,
which hosts the L4T-specific torch / vllm / flash-attn wheels but also
transparently proxies the rest of PyPI through `/+f/<sha>/<filename>`
URLs. With `--extra-index-url` + `--index-strategy=unsafe-best-match`
uv would pick those proxy URLs for ordinary PyPI packages —
anthropic/openai/propcache/annotated-types — and fail when the proxy
503s. Master is hitting the same bug on its own l4t-vllm matrix entry.

Switch the l4t13 install path to a pyproject.toml that marks the
jetson-ai-lab index `explicit = true` and pins only torch, torchvision,
torchaudio, flash-attn, and vllm to it via [tool.uv.sources]. uv won't
consult the L4T mirror for anything else, so transitive deps fall back
to PyPI as the default index — no exposure to the proxy 503s.

`uv pip install -r requirements.txt` ignores [tool.uv.sources], so the
l4t13 branch in install.sh now invokes `uv pip install --requirement
pyproject.toml` directly, replacing the old requirements-l4t13*.txt
files. Other BUILD_PROFILEs continue using libbackend.sh's
installRequirements and never read pyproject.toml.

Local resolution test (x86_64, dry-run) confirms uv hits the L4T
index for torch and falls through to PyPI for everything else.

Assisted-by: claude-code:claude-opus-4-7-1m [Read] [Edit] [Bash] [Write]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-06 00:22:50 +02:00
Ettore Di Giacinto
e86ade54a6 feat(api): add /v1/audio/diarization endpoint with sherpa-onnx + vibevoice.cpp (#9654)
* feat(api): add /v1/audio/diarization endpoint with sherpa-onnx + vibevoice.cpp

Closes #1648.

OpenAI-style multipart endpoint that returns "who spoke when". Single
endpoint instead of the issue's three-endpoint sketch (refactor /vad,
/vad/embedding, /diarization) — the typical client wants one call, and
embeddings can land later as a sibling without breaking this surface.

Response shape borrows from Pyannote/Deepgram: segments carry a
normalised SPEAKER_NN id (zero-padded, stable across the response) plus
the raw backend label, optional per-segment text when the backend bundles
ASR, and a speakers summary in verbose_json. response_format also accepts
rttm so consumers can pipe straight into pyannote.metrics / dscore.

Backends:

* vibevoice-cpp — Diarize() reuses the existing vv_capi_asr pass.
  vibevoice's ASR prompt asks the model to emit
  [{Start,End,Speaker,Content}] natively, so diarization is a by-product
  of the same pass; include_text=true preserves the transcript per
  segment, otherwise we drop it.

* sherpa-onnx — wraps the upstream SherpaOnnxOfflineSpeakerDiarization
  C API (pyannote segmentation + speaker-embedding extractor + fast
  clustering). libsherpa-shim grew config builders, a SetClustering
  wrapper for per-call num_clusters/threshold overrides, and a
  segment_at accessor (purego can't read field arrays out of
  SherpaOnnxOfflineSpeakerDiarizationSegment[] directly).

Plumbing: new Diarize gRPC RPC + DiarizeRequest / DiarizeSegment /
DiarizeResponse messages, threaded through interface.go, base, server,
client, embed. Default Base impl returns unimplemented.

Capability surfaces all updated: FLAG_DIARIZATION usecase,
FeatureAudioDiarization permission (default-on), RouteFeatureRegistry
entries for /v1/audio/diarization and /audio/diarization, audio
instruction-def description widened, CAP_DIARIZATION JS symbol,
swagger regenerated, /api/instructions discovery map updated.

Tests:

* core/backend: speaker-label normalisation (first-seen → SPEAKER_NN,
  per-speaker totals, nil-safety, fallback to backend NumSpeakers when
  no segments).

* core/http/endpoints/openai: RTTM rendering (file-id basename, negative
  duration clamping, fallback id).

* tests/e2e: mock-backend grew a deterministic Diarize that emits
  raw labels "5","2","5" so the e2e suite verifies SPEAKER_NN
  remapping, verbose_json speakers summary + transcript pass-through
  (gated by include_text), RTTM bytes content-type, and rejection of
  unknown response_format. mock-diarize model config registered with
  known_usecases=[FLAG_DIARIZATION] to bypass the backend-name guard.

Docs: new features/audio-diarization.md (request/response, RTTM example,
sherpa-onnx + vibevoice setup), cross-link from audio-to-text.md, entry
in whats-new.md.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(diarization): correct sherpa-onnx symbol name + lint cleanup

CI failures on #9654:

* sherpa-onnx-grpc-{tts,transcription} and sherpa-onnx-realtime panicked
  at backend startup with `undefined symbol: SherpaOnnxDestroyOfflineSpeakerDiarizationResult`.
  Upstream's actual symbol is SherpaOnnxOfflineSpeakerDiarizationDestroyResult
  (Destroy in the middle, not the prefix); the rest of the diarization
  surface follows the same naming pattern. The mismatched name made
  purego.RegisterLibFunc fail at dlopen time and crashed the gRPC server
  before the BeforeAll could probe Health, taking down every sherpa-onnx
  test job — not just the diarization-related ones.

* golangci-lint flagged 5 errcheck violations on new defer cleanups
  (os.RemoveAll / Close / conn.Close); wrap each in a `defer func() { _ = X() }()`
  closure (matches the pattern other LocalAI files use for new code, since
  pre-existing bare defers are grandfathered in via new-from-merge-base).

* golangci-lint also flagged forbidigo violations: the new
  diarization_test.go files used testing.T-style `t.Errorf` / `t.Fatalf`,
  which are forbidden by the project's coding-style policy
  (.agents/coding-style.md). Convert both files to Ginkgo/Gomega
  Describe/It with Expect(...) — they get picked up by the existing
  TestBackend / TestOpenAI suites, no new suite plumbing needed.

* modernize linter: tightened the diarization segment loop to
  `for i := range int(numSegments)` (Go 1.22+ idiom).

Verified locally: golangci-lint with new-from-merge-base=origin/master
reports 0 issues across all touched packages, and the four mocked
diarization e2e specs in tests/e2e/mock_backend_test.go still pass.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(vibevoice-cpp): convert non-WAV input via ffmpeg + raise ASR token budget

Confirmed end-to-end against a real LocalAI instance with vibevoice-asr-q4_k
loaded and the multi-speaker MP3 sample at vibevoice.cpp/samples/2p_argument.mp3:
both /v1/audio/transcriptions and /v1/audio/diarization now succeed and
return correctly attributed speaker turns for the full clip.

Two latent issues surfaced once the diarization endpoint actually exercised
the backend with a non-trivial input:

1. vv_capi_asr only accepts WAV via load_wav_24k_mono. The previous code
   passed the uploaded path straight through, so anything that wasn't
   already a 24 kHz mono s16le WAV failed at the C side with rc=-8 and
   the very unhelpful "vv_capi_asr failed". prepareWavInput shells out
   to ffmpeg ("-ar 24000 -ac 1 -acodec pcm_s16le") in a per-call temp
   dir, matching the rate the model was trained on; both AudioTranscription
   and Diarize now route through it. This is the same shape sherpa-onnx
   uses (utils.AudioToWav), but vibevoice needs 24 kHz rather than 16 kHz
   so we don't reuse that helper.

2. The C ABI's max_new_tokens defaults to 256 when 0 is passed. That's
   fine for a five-second clip but not for anything past ~10 s — vibevoice
   stops mid-JSON, the parse fails, and the caller sees a hard error.
   Pass a much larger budget (16 384 ≈ ~9 minutes of speech at the
   model's ~30 tok/s rate); generation stops at EOS so this is a cap
   rather than a target.

3. As a defensive belt-and-braces, mirror AudioTranscription's existing
   "fall back to a single segment if the model emits non-JSON text"
   pattern in Diarize, so partial / unusual model output never produces
   a 500. This kept the endpoint usable while diagnosing (1) and (2),
   and is the right behaviour to keep.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(vibevoice-cpp): pass valid WAVs through directly so ffmpeg is not required at runtime

Spotted by tests-e2e-backend (1.25.x): the previous fix forced every
incoming audio file through `ffmpeg -ar 24000 ...`, which meant the
backend container — which does not ship ffmpeg — failed even for the
existing happy path where the caller already uploads a WAV. The
container-side error was:

    rpc error: code = Unknown desc = vibevoice-cpp: ffmpeg convert to
    24k mono wav: exec: "ffmpeg": executable file not found in $PATH

Reading vibevoice.cpp's audio_io.cpp, `load_wav_24k_mono` uses drwav and
already accepts any PCM/IEEE-float WAV at any sample rate, downmixes
multi-channel input to mono, and resamples to 24 kHz internally. So the
only inputs that genuinely need an external converter are non-WAV
formats (MP3, OGG, FLAC, ...).

Detect WAVs by RIFF/WAVE magic at bytes 0..3 / 8..11 and pass them
straight through with a no-op cleanup; everything else still goes
through ffmpeg with the same 24 kHz mono s16le target. The result:

* Container builds without ffmpeg keep working for WAV uploads
  (the e2e-backends fixture is jfk.wav at 16 kHz mono s16le).
* MP3 and other non-WAV inputs still get the new ffmpeg conversion
  path so the diarization endpoint stays useful.
* If the caller uploads a non-WAV but ffmpeg isn't on PATH, the
  surfaced error is still descriptive enough to act on.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(ci): make gcc-14 install in Dockerfile.golang best-effort for jammy bases

The LocalVQE PR (bb033b16) made `gcc-14 g++-14` an unconditional apt
install in backend/Dockerfile.golang and pointed update-alternatives at
them. That works on the default `BASE_IMAGE=ubuntu:24.04` (noble has
gcc-14 in main), but every Go backend that builds on
`nvcr.io/nvidia/l4t-jetpack:r36.4.0` — jammy under the hood — now fails
at the apt step:

    E: Unable to locate package gcc-14

This blocked unrelated jobs:
backend-jobs(*-nvidia-l4t-arm64-{stablediffusion-ggml, sam3-cpp, whisper,
acestep-cpp, qwen3-tts-cpp, vibevoice-cpp}). LocalVQE itself is only
matrix-built on ubuntu:24.04 (CPU + Vulkan), so it doesn't actually
need gcc-14 anywhere else.

Make the gcc-14 install conditional on the package being available in
the configured apt repos. On noble: identical behaviour to today (gcc-14
installed, update-alternatives points at it). On jammy: skip the
gcc-14 stanza entirely and let build-essential's default gcc take over,
which is what the other Go backends compile with anyway.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 15:10:13 +02:00
Ettore Di Giacinto
bbcaebc1ef feat(concurrency-groups): per-model exclusive groups for backend loading (#9662)
* feat(concurrency-groups): per-model exclusive groups for backend loading

Adds `concurrency_groups: [...]` to model YAML configs. Two models that share
a group cannot be loaded concurrently on the same node — loading one evicts
the others, reusing the existing pinned/busy/retry policy from LRU eviction.

Layered design:
- Watchdog (pkg/model): per-node correctness floor — on every Load(), evict
  any loaded model that shares a group with the requested one. Pinned skips
  surface NeedMore so the loader retries (and ultimately logs a clear
  warning), instead of silently allowing the rule to be violated.
- Distributed scheduler (core/services/nodes): soft anti-affinity hint —
  scheduleNewModel prefers nodes that don't already host a same-group
  model, falling back to eviction only if every candidate has a conflict.
  Composes with NodeSelector at the same point in the candidate pipeline.

Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy
models running on different nodes is fine. The ConfigLoader is wired into
SmartRouter via a small ConcurrencyConflictResolver interface so the nodes
package keeps a narrow surface on core/config.

Refactors the inner LRU eviction body into a shared collectEvictionsLocked
helper and the loader retry loop into retryEnforce(fn, maxRetries, interval),
so both LRU and group enforcement share busy/pinned/retry semantics.

Closes #9659.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(watchdog): sync pinned + concurrency_groups at startup

The startup-time watchdog setup lives in initializeWatchdog (startup.go),
not in startWatchdog (watchdog.go). The latter is only invoked from the
runtime-settings RestartWatchdog path. As a result, neither
SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot,
so `pinned: true` and `concurrency_groups: [...]` only became effective
after a settings-driven watchdog restart.

Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end:
loading model A in group "heavy", then C with no group (coexists),
then B in group "heavy" now correctly evicts A and leaves [B, C].

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec

CI lint runs new-from-merge-base, so the existing pre-existing
`defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the
one introduced by the concurrency_groups YAML round-trip test is held
to errcheck. Wrap the remove in a closure that discards the error.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 08:42:50 +02:00
Richard Palethorpe
bb033b16a9 feat: add LocalVQE backend and audio transformations UI (#9640)
feat(audio-transform): add LocalVQE backend, bidi gRPC RPC, Studio UI

Introduce a generic "audio transform" capability for any audio-in / audio-out
operation (echo cancellation, noise suppression, dereverberation, voice
conversion, etc.) and ship LocalVQE as the first backend implementation.

Backend protocol:
- Two new gRPC RPCs in backend.proto: unary AudioTransform for batch and
  bidirectional AudioTransformStream for low-latency frame-by-frame use.
  This is the first bidi stream in the proto; per-frame unary at LocalVQE's
  16 ms hop would be RTT-bound. Wire it through pkg/grpc/{client,server,
  embed,interface,base} with paired-channel ergonomics.

LocalVQE backend (backend/go/localvqe/):
- Go-Purego wrapper around upstream liblocalvqe.so. CMake builds the upstream
  shared lib + its libggml-cpu-*.so runtime variants directly — no MODULE
  wrapper needed because LocalVQE handles CPU feature selection internally
  via GGML_BACKEND_DL.
- Sets GGML_NTHREADS from opts.Threads (or runtime.NumCPU()-1) — without it
  LocalVQE runs single-threaded at ~1× realtime instead of the documented
  ~9.6×.
- Reference-length policy: zero-pad short refs, truncate long ones (the
  trailing portion can't have leaked into a mic that wasn't recording).
- Ginkgo test suite (9 always-on specs + 2 model-gated).

HTTP layer:
- POST /audio/transformations (alias /audio/transform): multipart batch
  endpoint, accepts audio + optional reference + params[*]=v form fields.
  Persists inputs alongside the output in GeneratedContentDir/audio so the
  React UI history can replay past (audio, reference, output) triples.
- GET /audio/transformations/stream: WebSocket bidi, 16 ms PCM frames
  (interleaved stereo mic+ref in, mono out). JSON session.update envelope
  for config; constants hoisted in core/schema/audio_transform.go.
- ffmpeg-based input normalisation to 16 kHz mono s16 WAV via the existing
  utils.AudioToWav (with passthrough fast-path), so the user can upload any
  format / rate without seeing the model's strict 16 kHz constraint.
- BackendTraceAudioTransform integration so /api/backend-traces and the
  Traces UI light up with audio_snippet base64 and timing.
- Routes registered under routes/localai.go (LocalAI extension; OpenAI has
  no /audio/transformations endpoint), traced via TraceMiddleware.

Auth + capability + importer:
- FLAG_AUDIO_TRANSFORM (model_config.go), FeatureAudioTransform (default-on,
  in APIFeatures), three RouteFeatureRegistry rows.
- localvqe added to knownPrefOnlyBackends with modality "audio-transform".
- Gallery entry localvqe-v1-1.3m (sha256-pinned, hosted on
  huggingface.co/LocalAI-io/LocalVQE).

React UI:
- New /app/transform page surfaced via a dedicated "Enhance" sidebar
  section (sibling of Tools / Biometrics) — the page is enhancement, not
  generation, so it lives outside Studio. Two AudioInput components
  (Upload + Record tabs, drag-drop, mic capture).
- Echo-test button: records mic while playing the loaded reference through
  the speakers — the mic naturally picks up speaker bleed, giving a real
  (mic, ref) pair for AEC testing without leaving the UI.
- Reusable WaveformPlayer (canvas peaks + click-to-seek + audio controls)
  and useAudioPeaks hook (shared module-scoped AudioContext to avoid
  hitting browser context limits with three players on one page); migrated
  TTS, Sound, Traces audio blocks to use it.
- Past runs saved in localStorage via useMediaHistory('audio-transform') —
  the history entry stores all three URLs so clicking re-renders the full
  triple, not just the output.

Build + e2e:
- 11 matrix entries removed from .github/workflows/backend.yml (CUDA, ROCm,
  SYCL, Metal, L4T): upstream supports only CPU + Vulkan, so we ship those
  two and let GPU-class hardware route through Vulkan in the gallery
  capabilities map.
- tests-localvqe-grpc-transform job in test-extra.yml (gated on
  detect-changes.outputs.localvqe).
- New audio_transform capability + 4 specs in tests/e2e-backends.
- Playwright spec suite in core/http/react-ui/e2e/audio-transform.spec.js
  (8 specs covering tabs, file upload, multipart shape, history, errors).

Docs:
- New docs/content/features/audio-transform.md covering the (audio,
  reference) mental model, batch + WebSocket wire formats, LocalVQE param
  keys, and a YAML config example. Cross-links from text-to-audio and
  audio-to-text feature pages.

Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit Write Agent TaskCreate]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-04 22:07:11 +02:00
LocalAI [bot]
de83b72bb7 fix(distributed): orchestrator resilience — auto-upgrade routing, worker bind-wait, RAG-init crash, log spam (#9657)
* fix(nodes/health): skip stale-marking already-offline nodes

The health monitor re-emitted "Node heartbeat stale" + "Marking stale
node offline" + MarkOffline on every cycle for nodes that were already
in the offline (or unhealthy) state. For an operator-stopped node this
flooded the logs with the same WARN+INFO pair every check interval.

Skip the staleness branch when the node is already StatusOffline /
StatusUnhealthy — the state is already what we'd write, so neither the
log lines nor the DB update carry information.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(worker): wait for backend gRPC bind before replying to backend.install

The backend supervisor used to wait up to 4s (20 × 200ms) for the
backend's gRPC server to answer a HealthCheck, then log a warning and
reply Success with the bind address anyway. On slower nodes (a Jetson
Orin doing first-boot CUDA init, large CGO library load) the gRPC
listener wasn't up yet, so the frontend's first LoadModel dial returned
"connect: connection refused" and the operator chased a phantom network
issue instead of a startup-timing one.

Two changes:

  - Bump the readiness window to 30s. CUDA init on Orin/Thor first boot
    measures in seconds, not milliseconds.
  - On deadline-exceeded, stop the half-started process, recycle the
    port, and return an error with the backend's stderr tail. The
    frontend now gets a real failure with diagnostic context instead of
    a misleading ECONNREFUSED on a downstream dial.

Process death during the wait window keeps its existing fast-fail path.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(distributed): route auto-upgrade through BackendManager + bump LocalAGI/LocalRecall

Two distributed-mode bugs that surfaced together in the orchestrator
logs:

1. Auto-upgrade always failed with "backend not found".

   UpgradeChecker correctly routed CheckUpgrades through the active
   BackendManager (so the frontend aggregates worker state), but the
   auto-upgrade branch right below called gallery.UpgradeBackend
   directly with the frontend's SystemState. In distributed mode the
   frontend has no backends installed locally, so ListSystemBackends
   returned empty and Get(name) failed for every reported upgrade.
   Auto-upgrade now also goes through BackendManager.UpgradeBackend,
   which fans out to workers via NATS.

2. Embedding-load failure on a remote node crashed the orchestrator.

   When RAG init lazily called NewPersistentPostgresCollection and the
   remote embedding worker was unreachable, LocalRecall called
   os.Exit(1) inside the constructor, killing the orchestrator pod.
   LocalRecall now returns errors instead, LocalAGI surfaces them as a
   nil collection, and the existing RAGProviderFromState path returns
   (nil, nil, false) — the same code path the agent pool already takes
   when no RAG is configured. The orchestrator stays up; chat requests
   degrade to "no RAG available" until the embedding worker recovers.

Bumps:
  github.com/mudler/LocalAGI    → e83bf515d010
  github.com/mudler/localrecall → 6138c1f535ab

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 19:09:16 +02:00
Ettore Di Giacinto
a271c72931 fix(react-ui/e2e): scope backendTrigger to <main> so it skips LanguageSwitcher
The LanguageSwitcher added in the i18n PR (#9642) lives in the sidebar
and also uses aria-haspopup="listbox" — same attribute the import-form
SearchableSelect uses. The Batch D / E tests' helper resolved the trigger
with `page.locator('button[aria-haspopup="listbox"]').first()`, which now
returns the language switcher (rendered first in DOM order, in the
sidebar) instead of the backend dropdown.

After clicking the wrong button, getByRole('option', { name: 'llama-cpp' })
naturally never resolves — language options aren't backend names — and
the test times out at 30s.

Scope the locator to the <main className="main-content"> wrapper so only
buttons inside the route's main content area match. The page layout has
the Sidebar outside <main>, so this cleanly excludes it.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 08:58:25 +00:00
Ettore Di Giacinto
ade5fd4b97 fix(react-ui): reflect disabled state on SearchableSelect button
The Backend dropdown is disabled while /backends/known is in flight
(disabled={isSubmitting || backendsLoading} in ImportModel.jsx). Until
now the disabled prop only guarded the internal onClick handler — there
was no `disabled` HTML attribute on the <button>, so the element
remained "actionable" from the outside.

That regressed the import-form-ux Batch D / E Playwright tests after
the i18next-suspense PR (#9642): suspending on the importModel
namespace defers the useEffect that fetches /backends/known, so when
the test calls backendTrigger.click() the button is rendered but
backendsLoading is still true. The click hits the no-op branch,
the dropdown stays closed, and `getByRole('option', { name: 'llama-cpp' })`
times out at 30s.

Surfacing the disabled state on the actual <button> makes Playwright
auto-wait until the dropdown is ready, fixes a11y (screen readers now
announce "disabled"), and removes the button from the tab order while
loading.

Assisted-by: Claude:claude-opus-4-7[1m] [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 08:21:03 +00:00
LocalAI [bot]
170d55c67d fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups (#9652)
* fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups

Two distinct bugs were causing tight retry loops in the distributed scheduler:

1. FindAndLockNodeWithModel ignored the model's NodeSelector. When a model
   was loaded on multiple nodes and only some matched the current selector,
   the function returned the lowest-in_flight node — even one the selector
   excluded. Route()'s post-check then fell through to scheduleNewModel,
   which targeted the matching node where the model was already at
   MaxReplicasPerModel capacity. Eviction couldn't help (the only loaded
   model on that node was the one being requested, and it was busy), so
   every request looped through "evicting LRU" → "all models busy".

   Fix: thread an optional candidateNodeIDs filter through
   FindAndLockNodeWithModel. Route() resolves the selector once via a new
   resolveSelectorCandidates helper and passes the matching IDs to both
   the cached-replica lookup and scheduleNewModel. The same helper
   replaces the inline selector block in scheduleNewModel.

2. ScheduleAndLoadModel (reconciler scale-up path) fell back to
   scheduleNewModel with backendType="" when no replica had ever been
   loaded for a model. The worker rejected the resulting backend.install
   ("backend name is empty") on every reconciler tick (~30s).

   Fix: remove the broken fallback. When GetModelLoadInfo has nothing
   stored, return a clear error instead of firing a doomed NATS install.
   The reconciler's existing scale-up failure log surfaces it once per
   tick; the model auto-replicates as soon as Route() serves it once and
   stores load info.

Also downgrade the post-LoadModel-failure StopGRPC error to Debug — that
cleanup attempt usually hits "model not found" because LoadModel failed
before registering the process, and the outer "Failed to load model"
error already carries the real reason.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]

* test(distributed): cover selector-aware FindAndLockNodeWithModel and reconciler scaleup guard

Two regression tests for the bugs fixed in the previous commit:

1. FindAndLockNodeWithModel — registry-level integration tests verify the
   candidateNodeIDs filter:
   - Returns the included node even when an excluded node has lower
     in_flight (the original selector-mismatch loop scenario).
   - Returns not-found when the model is loaded only on excluded nodes,
     forcing Route() to fall through to a fresh schedule instead of
     reusing the excluded replica.

2. ScheduleAndLoadModel — mock-based test verifies the reconciler scale-up
   path returns an error and does NOT fire backend.install when no replica
   has been loaded yet. fakeUnloader gains an installCalls slice so this
   negative assertion is direct.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 09:42:14 +02:00
Ettore Di Giacinto
87cf736068 feat(react-ui): add multilingual (i18n) support (#9642)
Adds end-to-end internationalization to the React UI with five seed
languages (English, Italian, Spanish, German, Simplified Chinese) and
a sidebar-footer language switcher next to the existing theme toggle.

Library: react-i18next + i18next + i18next-http-backend +
i18next-browser-languagedetector. The detector caches the user's
choice in localStorage (key `localai-language`, mirroring the existing
`localai-theme` convention) and updates the `<html lang>` attribute on
change. fallbackLng is `en`, so any missing translation in another
locale falls back transparently.

Translation files live under `public/locales/<lng>/<ns>.json`. They
ride along with the existing `//go:embed react-ui/dist/*` directive,
but the previous SPA route in core/http/app.go only exposed
`/assets/*` from the embedded React build. This commit generalizes
the asset handler into a `serveReactSubdir(subdir)` helper and adds a
matching `/locales/*` route so i18next-http-backend can fetch the
JSONs at runtime. The http-backend `loadPath` is built via the
existing `apiUrl()` helper so instances served under a sub-path (e.g.
`<base href="/ui/">`) resolve correctly.

Namespaces (13): common, nav, errors, auth, home, models, importModel,
chat, agents, skills, collections, media, admin. Translated UI surfaces
include the sidebar/header/footer chrome, login + account flows, the
Home dashboard (incl. the manage-by-chat assistant CTA), the model
gallery + import flow, the chat experience (Chat.jsx + ChatsMenu),
agents/skills/collections list pages, the studio media tabs (Image,
Video, TTS), and the admin page-headers (Settings incl. its section
nav, Manage, Backends, Traces, Nodes, P2P, Users, Usage). Shared
components (ConfirmDialog, Toast) take their default labels from the
common namespace so callers don't need to pass strings explicitly.

Tooling for incremental adoption is included:
  - `i18next-parser.config.js` + `npm run i18n:extract` to sweep `t()`
    keys into the JSON skeletons.
  - `scripts/translate-locales.mjs` (one-off helper) to bootstrap
    non-English locales from English source via OpenAI or Anthropic
    APIs, with --copy mode as a placeholder fallback. Idempotent;
    preserves existing translations unless --overwrite is passed.

Larger config-driven pages (ModelEditor, Settings deep field forms,
AgentChat/AgentCreate, SkillEdit, CollectionDetails, Talk, Sound,
biometrics, FineTune/Quantize, Users modals, Nodes/P2P install
pickers, BackendLogs, Traces deep filters, Explorer) intentionally
keep their inner content untranslated for now — they fall back to
English via fallbackLng so functionality is unaffected, and the
extracted-strings pattern + the bootstrap script make follow-up
extraction straightforward.

The initial Suspense fallback at the root in main.jsx covers the
first JSON fetch on cold load. A simple `.app-boot-spinner` styled
in App.css provides a non-empty paint while the first namespace
loads.

Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit Write Agent]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-02 22:42:08 +02:00
Ettore Di Giacinto
b1a99436c7 feat(branding): admin-configurable instance name, tagline, and assets (#9635)
Adds a whitelabeling feature so an operator can replace the LocalAI
instance name, tagline, square logo, horizontal logo, and favicon from
the admin Settings page. Defaults fall back to the bundled assets so
existing installs are unaffected.

The public GET /api/branding endpoint is reachable pre-auth so the
login screen can render the configured branding before sign-in.
Mutating routes (POST/DELETE /api/branding/asset/:kind) remain
admin-only. Text fields (instance_name, instance_tagline) ride the
existing /api/settings flow; binary assets get a dedicated multipart
upload route that persists files under DynamicConfigsDir/branding/.

To prevent the Settings page's stale local state from clobbering an
upload on save, UpdateSettingsEndpoint preserves whatever the on-disk
asset filename fields are regardless of the body — /api/branding/asset/*
are the sole writers for those fields.

The MCP catalog gains get_branding and set_branding tools (text fields
only; file upload stays UI-only) plus a configure_branding skill prompt.

While wiring this up, the same restart-loss class of bug surfaced for
several existing fields whose RuntimeSettings entries were never read
by the startup loader. Fix loadRuntimeSettingsFromFile() to load:

  - branding (instance_name, instance_tagline, *_file basenames)
  - auto_upgrade_backends, prefer_development_backends
  - localai_assistant_enabled
  - open_responses_store_ttl
  - the 7 existing AgentPool fields (enabled, default/embedding model,
    chunking sizes, enable_logs, collection_db_path)

Also exposes 3 new AgentPool runtime settings (vector_engine,
database_url, agent_hub_url) via /api/settings + the Settings UI, with
the same load-on-startup wiring. The file watcher's manual-edit path
is intentionally not changed — the in-process API endpoints already
update appConfig directly, so the watcher is redundant for supported
flows and a separate refactor for everything else.

15 TDD specs cover the loader behaviour (1 branding + 11 adjacent + 3
new agent-pool); 2 specs cover the persistence helpers and the
clobber-prevention contract.


Assisted-by: claude-code:claude-opus-4-7

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-02 15:51:36 +02:00
Ettore Di Giacinto
8452068f43 feat(importers): whisper.cpp HF repos pick a quant + nest under whisper/models (#9630)
The WhisperImporter's Import() switch ordered LooksLikeURL ahead of the
HuggingFace branch, so any https://huggingface.co/<owner>/<repo> URI
(e.g. LocalAI-io/whisper-large-v3-it-yodas-only-ggml) hijacked the URL
path. FilenameFromUrl returned the repo slug, the gallery entry pointed
at the HTML repo page, the SHA256 was empty, and the HF file listing
was effectively dead code for HTTPS imports. The HF branch only fired
for huggingface://owner/repo and hf://owner/repo references.

Gate the URL case on a "ggml-*.bin" basename signal — mirroring how
the llama-cpp importer gates on ".gguf" — so direct file URLs still
take the URL path while HF repo URLs fall through to the HF branch.
There the file listing is actually consulted: every ggml-*.bin entry
is collected and one is picked by the new preferences.quantizations
preference (default q5_0; comma-separated for fallback ordering).

Pin the chosen file under whisper/models/<name>/<file> so a single
repo can ship q4_0/q5_0/q8_0 side-by-side without colliding on disk,
matching the llama-cpp/models/<name>/ layout. The fallback when no
preference matches is the last available ggml file, mirroring
llama-cpp's pickPreferredGroup behaviour.

Tests: replace the previous probe spec with positive assertions
against LocalAI-io/whisper-large-v3-it-yodas-only-ggml (default →
ggml-model-q5_0.bin, quantizations=q4_0 → ggml-model-q4_0.bin) plus
two offline specs that build a fake hfapi.ModelDetails to cover the
fallback rule and non-ggml filtering without touching the network.


Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit WebFetch]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-01 12:03:07 +02:00
Ettore Di Giacinto
091eda8d70 feat: react chat redesign (#9616)
* feat(react-ui): redesign chat — popover history, focus on send, density pass

Replace the persistent 260px conversation sidebar with a Cmd/Ctrl+K
popover (ChatsMenu) so the conversation owns the page. Once a chat has
at least one message we auto-collapse the global app rail and fade
non-essential header chrome; Esc gives the user back the full chrome
for the rest of the session.

Move Canvas mode and the MCP dropdown into the input wrapper as mode
chips — they describe what's armed for the next message and now live
where the user composes. The chat header drops to Chats · title ·
ModelSelector · overflow · settings, and an overflow menu carries
admin-only Manage mode along with Info / Edit / Export / Clear.

Density pass: tighter header (40px), smaller avatars with the assistant
left-border accent doing the work, 88% bubble width, modern
field-sizing on the textarea, 32px send/stop buttons.

Empty state now surfaces a Recent strip (top 4 non-empty chats) and a
Cmd+K hint, replacing the discoverability the persistent sidebar used
to provide.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

* feat(react-ui): chat input chips, slimmer menu, focus mode polish

Move Canvas mode and the MCP dropdown into the input wrapper as compact
mode chips — they describe what's armed for the next message and now
sit where the user composes. The MCP popover flips upward when anchored
to the input row so it stays on-screen.

Eliminate the chat header overflow ("…") menu entirely; relocate each
item to its semantic home so users don't have to remember a
miscellany drawer:

- Manage mode toggle → top of the Settings drawer, alongside the
  other sticky chat knobs. The shield next to the title still
  signals state at a glance.
- Model info / Edit config → small admin-only "ⓘ" button next to the
  ModelSelector; the existing model-info panel now hosts the Edit
  config link.
- Export as Markdown → per-row hover action in ChatsMenu, so it works
  for any chat (not just the active one).
- Clear chat history → destructive button at the bottom of the
  Settings drawer.

Make the Sidebar listen to its own `sidebar-collapse` event so the
chat's focus mode actually shrinks the rail (it previously only
flipped the layout class, leaving the sidebar element at full width
and overlapping the chat). Drop the focus-mode toast — the visual
shift is enough; the toast was noise.

Define `--color-text-tertiary` in both themes; without it metadata
text (recent strip timestamps and a few other sites) was inheriting
the platform default, which read as black on the dark surface.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

* fix(model/log-store): close merged channel exactly once; clean up Remove

Two latent races in BackendLogStore.Subscribe could panic under load
(distributed e2e test triggered "send on closed channel" at
backend_log_store.go:288):

1. The aggregated path closed the merged channel `ch` from two
   places — the fan-in waiter goroutine (after all source channels
   drained) and unsubscribe(). When unsubscribe ran while a fan-in
   goroutine was mid-flight on `ch <- line`, the close beat the send
   and the runtime panicked. Now `ch` is closed by exactly one
   goroutine: the waiter that observes all fan-in goroutines finish.
   unsubscribe() only closes the per-buffer source channels — the
   for-range in each fan-in goroutine then exits naturally and the
   waiter takes care of the merged close.

2. Remove() closed every subscriber channel but didn't delete the
   entries from the subscribers map, so a concurrent unsubscribe()
   would call close() again on the already-closed channel
   ("close of closed channel"). Clear the map entry while closing.

Add a regression test that hammers AppendLine concurrently with
Subscribe + unsubscribe + Remove; the race detector catches both
classes of regression.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

* test(model/log-store): port backend log store tests to ginkgo

Bring backend_log_store_test.go in line with the rest of pkg/model
(loader_test, watchdog_test, store_test): same external test package
(`model_test`), same ginkgo + gomega imports, same Describe/It
nesting around the public API. Behaviour is unchanged — the four
existing scenarios plus the unsubscribe race regression all run as
specs under the existing `TestModel` suite.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-29 22:33:26 +02:00
Richard Palethorpe
4916f8c880 feat(vllm): expose AsyncEngineArgs via generic engine_args YAML map (#9563)
* feat(vllm): expose AsyncEngineArgs via generic engine_args YAML map

LocalAI's vLLM backend wraps a small typed subset of vLLM's
AsyncEngineArgs (quantization, tensor_parallel_size, dtype, etc.).
Anything outside that subset -- pipeline/data/expert parallelism,
speculative_config, kv_transfer_config, all2all_backend, prefix
caching, chunked prefill, etc. -- requires a new protobuf field, a
Go struct field, an options.go line, and a backend.py mapping per
feature. That cadence is the bottleneck on shipping vLLM's
production feature set.

Add a generic `engine_args:` map on the model YAML that is
JSON-serialised into a new ModelOptions.EngineArgs proto field and
applied verbatim to AsyncEngineArgs at LoadModel time. Validation
is done by the Python backend via dataclasses.fields(); unknown
keys fail with the closest valid name as a hint.
dataclasses.replace() is used so vLLM's __post_init__ re-runs and
auto-converts dict values into nested config dataclasses
(CompilationConfig, AttentionConfig, ...). speculative_config and
kv_transfer_config flow through as dicts; vLLM converts them at
engine init.

Operators can now write:

  engine_args:
    data_parallel_size: 8
    enable_expert_parallel: true
    all2all_backend: deepep_low_latency
    speculative_config:
      method: deepseek_mtp
      num_speculative_tokens: 3
    kv_cache_dtype: fp8

without further proto/Go/Python plumbing per field.

Production defaults seeded by hooks_vllm.go: enable_prefix_caching
and enable_chunked_prefill default to true unless explicitly set.

Existing typed YAML fields (gpu_memory_utilization,
tensor_parallel_size, etc.) remain for back-compat; engine_args
overrides them when both are set.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* chore(vllm): pin cublas13 to vLLM 0.20.0 cu130 wheel

vLLM's PyPI wheel is built against CUDA 12 (libcudart.so.12) and won't
load on a cu130 host. Switch the cublas13 build to vLLM's per-tag cu130
simple-index (https://wheels.vllm.ai/0.20.0/cu130/) and pin
vllm==0.20.0. The cu130-flavoured wheel ships libcudart.so.13 and
includes the DFlash speculative-decoding method that landed in 0.20.0.

cublas13 install gets --index-strategy=unsafe-best-match so uv consults
both the cu130 index and PyPI when resolving — PyPI also publishes
vllm==0.20.0, but with cu12 binaries that error at import time.

Verified: Qwen3.5-4B + z-lab/Qwen3.5-4B-DFlash loads and serves chat
completions on RTX 5070 Ti (sm_120, cu130).

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* ci(vllm): bot job to bump cublas13 vLLM wheel pin

vLLM's cu130 wheel index URL is itself version-locked
(wheels.vllm.ai/<TAG>/cu130/, no /latest/ alias upstream), so a vLLM
bump means rewriting two values atomically — the URL segment and the
version constraint. bump_deps.sh handles git-sha-in-Makefile only;
add a sibling bump_vllm_wheel.sh and a matching workflow job that
mirrors the existing matrix's PR-creation pattern.

The bumper queries /releases/latest (which excludes prereleases),
strips the leading 'v', and seds both lines unconditionally. When the
file is already on the latest tag the rewrite is a no-op and
peter-evans/create-pull-request opens no PR.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* docs(vllm): document engine_args and speculative decoding

The new engine_args: map plumbs arbitrary AsyncEngineArgs through to
vLLM, but the public docs only covered the basic typed fields. Add a
short subsection in the vLLM section explaining the typed/generic
split and showing a worked DFlash speculative-decoding config, with
pointers to vLLM's SpeculativeConfig reference and z-lab's drafter
collection.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2026-04-29 00:49:28 +02:00
Ettore Di Giacinto
bcef72b9c1 feat: localai assistant chat modality (#9602)
* fix(tests): inline model_test fixtures after tests/models_fixtures removal

The previous reorg removed tests/models_fixtures/ but core/config/model_test.go
still read CONFIG_FILE/MODELS_PATH env vars pointing into that directory, so
`make test` failed with "open : no such file or directory" on the readConfigFile
spec (the suite ran with --fail-fast and bailed before openresponses_test).

Inline the YAMLs (config/embeddings/grpc/rwkv/whisper) directly into the test
file, materialise them into a per-test tmpdir via BeforeEach, and drop the
env-var lookups. The test no longer depends on Makefile plumbing.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Edit] [Write] [Bash]

* refactor(modeladmin): extract model-admin helpers into a service package

Lift the bodies of EditModelEndpoint, PatchConfigEndpoint,
ToggleStateModelEndpoint, TogglePinnedModelEndpoint and
VRAMEstimateEndpoint into core/services/modeladmin so the same logic can
be called by non-HTTP clients (notably the in-process MCP server that
backs the LocalAI Assistant chat modality, landing in a follow-up commit).

The HTTP handlers shrink to thin shells that parse echo inputs, call the
matching helper, map typed errors (ErrNotFound, ErrConflict,
ErrPathNotTrusted, ErrBadAction, ...) to the existing HTTP status codes,
and render the existing response shapes. No REST-surface behaviour change;
the existing localai endpoint tests cover the regression net.

Adds focused unit tests for each helper against tmp-dir-backed
ModelConfigLoader fixtures (deep-merge patch, rename + conflict, path
separator guard, toggle/pin enable/disable, sync callback).

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(assistant): LocalAI Assistant chat modality with in-memory MCP server

Adds a chat modality, admin-only, that wires the chat session to an
in-memory MCP server exposing LocalAI's own admin/management surface as
tools. An admin can install models, manage backends, edit configs and
check status by chatting; the LLM calls tools like gallery_search,
install_model, import_model_uri, list_installed_models, edit_model_config
and surfaces the results.

Same Go package powers two modes:

  pkg/mcp/localaitools/

    NewServer(client, opts) builds an MCP server that registers the
    19-tool admin catalog. The LocalAIClient interface has two impls:

    - inproc.Client — calls services directly (no HTTP loopback,
      no synthetic admin API key). Used in-process by the chat handler.
    - httpapi.Client — calls the LocalAI REST API. Used by the new
      `local-ai mcp-server --target=…` subcommand to control a remote
      LocalAI from a stdio MCP host.

    Tools and their embedded skill prompts are agnostic to which client
    backs them. Skill prompts are markdown files under prompts/, embedded
    via go:embed and assembled into the system prompt at server init.

Wiring:

  - core/http/endpoints/mcp/localai_assistant.go — process-wide holder
    that spins up the in-memory MCP server once at Application start
    using paired net.Pipe transports, then reuses LocalToolExecutor
    (no fork) for every chat request that opts in.

  - core/http/endpoints/openai/chat.go — small branch ahead of the
    existing MCP block: when metadata.localai_assistant=true,
    defense-in-depth admin check + executor swap + system-prompt
    injection. All downstream tool dispatch is unchanged.

  - core/http/auth/{permissions,features}.go — adds
    FeatureLocalAIAssistant; gating happens at the chat handler entry
    plus admin-only `/api/settings`.

  - core/cli/{run.go,cli.go,mcp_server.go} —
    LOCALAI_DISABLE_ASSISTANT flag (runtime-toggleable via Settings, no
    restart), plus `local-ai mcp-server` stdio subcommand.

  - core/config/runtime_settings.go — `localai_assistant_enabled`
    runtime setting; the chat handler reads `DisableLocalAIAssistant`
    live at request entry.

UI:

  - Home.jsx — prominent self-explanatory CTA card on first run
    ("Manage LocalAI by chatting"); collapses to a compact
    "Manage by chat" button in the quick-links row once used,
    persisted via localStorage.
  - Chat.jsx — admin-only "Manage" toggle in the chat header,
    "Manage mode" badge, dedicated empty-state copy, starter chips.
  - Settings.jsx — "LocalAI Assistant" section with the runtime
    enable toggle.
  - useChat.js — `localaiAssistant` flag on the chat schema; injects
    `metadata.localai_assistant=true` on requests when active.

Distributed mode: the in-memory MCP server lives only on the head node;
inproc.Client wraps already-distributed-aware services so installs
propagate to workers via the existing GalleryService machinery.

Documentation: `.agents/localai-assistant-mcp.md` is the contributor
contract — when adding an admin REST endpoint, also add a LocalAIClient
method, an inproc + httpapi impl, a tool registration, and a skill
prompt update; the AGENTS.md index links to it.

Out of scope (follow-ups): per-tool RBAC granularity for non-admin
read-only access; streaming mcp_tool_progress for long installs;
React Vitest rig for the UI changes.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): extract tool/capability/MiB/server-name constants

The MCP tool surface, capability tag set, server-name default, and the
chat-handler metadata key were repeated as bare string literals across
seven files. Renaming any one required hand-editing every call site and
risked code/test/prompt drift.

This pulls them into typed constants:

- pkg/mcp/localaitools/tools.go — Tool* constants for the 19 MCP tools,
  plus DefaultServerName.
- pkg/mcp/localaitools/capability.go — typed Capability + constants for
  the capability tag set the LLM passes to list_installed_models. The
  type rides through LocalAIClient.ListInstalledModels and replaces the
  triplet of "embed"/"embedding"/"embeddings" with the single
  CapabilityEmbeddings.
- pkg/mcp/localaitools/inproc/client.go — bytesPerMiB constant for the
  VRAMEstimate byte→MB conversion.
- core/http/endpoints/mcp/tools.go — MetadataKeyLocalAIAssistant for the
  "localai_assistant" request-metadata key consumed by the chat handler.

Tool registrations, the test catalog, the dispatch table, the validation
fixtures, and the fake/stub clients all reference the constants. The
embedded skill prompts under prompts/ keep their bare strings (go:embed
markdown can't import Go constants); the existing TestPromptsContain
SafetyAnchors guards the alignment.

No behaviour change. All tests pass with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(modeladmin): typed Action for ToggleState/TogglePinned

The toggle/pin verbs were bare strings everywhere — handler signatures,
service implementations, MCP tool args, the fake/stub clients, the
inproc and httpapi LocalAIClient impls, plus 4 test files. A typo in
any caller silently fell through to the runtime "must be 'enable' or
'disable'" check.

Introduce core/services/modeladmin.Action (string alias) with
ActionEnable, ActionDisable, ActionPin, ActionUnpin and a small Valid
helper. The compiler now catches mismatches at every boundary; renames
ripple through one source of truth.

LocalAIClient.ToggleModelState/Pinned signatures change to take
modeladmin.Action. The package is brand-new and unreleased so this is
a free public-API tightening.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): respect ctx cancellation on gallery channel sends

InstallModel, DeleteModel, ImportModelURI, InstallBackend and
UpgradeBackend all pushed onto galleryop channels with bare sends. If the
worker was paused or the buffer full, the chat-handler goroutine blocked
forever — the LLM kept polling and the request leaked.

Wrap the five sends in a sendModelOp/sendBackendOp helper that selects
on ctx.Done() so a cancelled chat completion surfaces context.Canceled
back to the LLM instead of hanging.

Adds inproc/client_test.go with a pre-cancelled-ctx regression test on
InstallModel; the helpers are shared so the same guarantee covers the
other four call sites.

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): graceful shutdown for in-memory holder and stdio CLI

Two related leaks:

- Application.start() built the LocalAIAssistantHolder but never wired
  Close() into the graceful-termination chain — the in-memory MCP
  transport pair stayed alive until process exit, and the goroutines
  behind net.Pipe() didn't drain. Hook into the existing
  signals.RegisterGracefulTerminationHandler chain (same pattern as
  core/http/endpoints/mcp/tools.go:770).

- core/cli/mcp_server.go ran srv.Run with context.Background(); a
  Ctrl-C from the host (Claude Desktop, mcphost, npx inspector) or a
  SIGTERM from process supervision left the stdio loop reading from a
  closed pipe. Switch to signal.NotifyContext to surface the signal
  through ctx and let srv.Run drain.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): typed HTTPError + propagate prompt walk error

The httpapi client detected "no such job" by substring-matching on the
error string ("404", "could not find") — brittle to status-code
formatting changes and to LocalAI fixing /models/jobs/:uuid to return a
proper 404. Replace with a typed *HTTPError whose Is() method honours
errors.Is(err, ErrHTTPNotFound). The 500-with-"could not find" branch
stays as a transitional fallback documented in Is().

Same change covers ListNodes' 404 fallback for the /api/nodes endpoint.

Adds httptest tests for both 404 and the legacy 500 path, plus a
direct errors.Is exposure test so external callers (the standalone
stdio CLI host) can match without re-string-parsing.

Also tightens prompts.SystemPrompt: panic when fs.WalkDir on the
embedded FS fails. The only realistic cause is a build-time //go:embed
misconfiguration; serving an empty system prompt to the LLM is much
worse than crashing init. TestSystemPromptIncludesAllEmbeddedFiles
catches regressions in CI.

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(modeladmin): atomic writes for model config files

The five sites that wrote model YAML used os.WriteFile, which opens
with O_TRUNC|O_WRONLY|O_CREATE. A crash mid-write left the destination
truncated and the model unloadable until manual repair. Pre-existing
behaviour inherited from the original endpoint handlers — fix once now
that there's a single helper.

Adds writeFileAtomic: writes to a sibling temp file, chmods, syncs via
Close(), then os.Rename. Same-directory temp keeps the rename atomic on
the same filesystem; cleanup runs on every error path so stray temps
don't accumulate. No new dependency.

Applied to:
- ConfigService.PatchConfig
- ConfigService.EditYAML (both rename and in-place branches)
- mutateYAMLBoolFlag (drives ToggleState + TogglePinned)

atomic_test.go covers the happy path plus a read-only-dir failure case
that asserts the original file is preserved (skipped on Windows where
the chmod trick is POSIX-specific).

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(assistant): prune dead code, mark stub, document conventions

Three small cleanups landing together:

- Drop the unused errNotImplemented sentinel from inproc/client.go.
  All five methods that used to return it are wired to modeladmin
  helpers since the Phase B commit; the package var is dead.

- Annotate httpapi.Client.GetModelConfig as a known stub. LocalAI's
  /models/edit/:name returns rendered HTML, not JSON, so the standalone
  CLI's get_model_config tool surfaces a clear error to the LLM. A
  future JSON-only /api/models/config-yaml/:name endpoint is tracked in
  the agent contract; FIXME points at it.

- Extend `.agents/localai-assistant-mcp.md` with a "Code conventions"
  section that documents the audit-driven rules: tool/Capability/Action
  constants, errors.Is over substring matching, ctx-aware channel
  sends, atomic writes, and graceful shutdown. Refresh the file map so
  it lists tools.go and capability.go and drops the removed
  tools_bootstrap.go.

The tools_models.go diff is a comment-only change explaining why the
ModelName empty-string check stays at the tool layer (consistency
across LocalAIClient implementations, since the SDK schema validator
only enforces presence, not non-empty).

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(assistant): convert test files to ginkgo + gomega

The repo convention (per core/http/endpoints/localai/*_test.go,
core/gallery/**, etc.) is Ginkgo v2 with Gomega assertions. The tests I
introduced for the assistant feature used vanilla testing.T, which made
them stand out and stripped the BDD structure the rest of the suite
relies on.

Convert every test file in the assistant scope to Ginkgo:

  pkg/mcp/localaitools/
    dto_test.go            — Describe("DTOs round-trip through JSON")
    prompts_test.go        — Describe("SystemPrompt assembler")
    server_test.go         — Describe("Server tool catalog"),
                              Describe("Tool dispatch"),
                              Describe("Tool error surfacing"),
                              Describe("Argument validation"),
                              Describe("Concurrent tool calls")
    parity_test.go         — Describe("LocalAIClient parity"),
                              hosts the suite's single RunSpecs (the file
                              is package localaitools_test so it can
                              import httpapi without an import cycle;
                              Ginkgo aggregates Describes from both the
                              internal and external test packages into
                              one run).
    httpapi/client_test.go — Describe("httpapi.Client against the
                              LocalAI admin REST surface"),
                              Describe("ErrHTTPNotFound"),
                              Describe("Bearer token")
    inproc/client_test.go  — Describe("inproc.Client cancellation")

  core/services/modeladmin/
    config_test.go         — Describe("ConfigService") with sub-Describes
                              for GetConfig, PatchConfig, EditYAML
    state_test.go          — Describe("ConfigService.ToggleState")
    pinned_test.go         — Describe("ConfigService.TogglePinned")
    atomic_test.go         — Describe("writeFileAtomic")

  core/http/endpoints/mcp/
    localai_assistant_test.go — Describe("LocalAIAssistantHolder")

Each package gets a `*_suite_test.go` with the standard
`RegisterFailHandler(Fail) + RunSpecs(t, "...")` boilerplate. Helpers
that previously took *testing.T (newTestService, writeModelYAML,
readMap, sortedStrings, sortGalleries, etc.) drop the *T receiver and
use Gomega Expectations directly. tmp dirs come from GinkgoT().TempDir().

No semantic change to test coverage — every original assertion has a
direct Gomega counterpart. All suites pass with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test+docs(assistant): drift detector for Tool ↔ REST route mapping

Honest gap from the audit: the parity_test.go suite only checks four
methods, and uses the same httpapi.Client for both sides — it asserts
stability of the DTO shapes, not equivalence between in-process and
HTTP. If a contributor adds an admin REST endpoint without an MCP tool,
or a tool without a matching httpapi route, both surfaces silently
diverge.

Add a coverage test plus stronger docs:

- pkg/mcp/localaitools/coverage_test.go introduces a hand-maintained
  toolToHTTPRoute map: every Tool* constant must list the REST endpoint
  the httpapi.Client hits (or "(none)" with a documented reason). Two
  Ginkgo specs assert the map and the published catalog stay in sync —
  one fails when a Tool is added without a route entry, the other fails
  when a route entry references a tool that no longer exists. Verified
  by removing the ToolDeleteModel entry locally; the test fired with a
  clear message pointing the contributor at the file.

  Deliberate non-test: we don't enumerate live admin REST routes from
  here. Walking the route registry requires booting Application;
  parsing core/http/routes/localai.go is brittle. The "new admin REST
  endpoint → MCP tool" direction stays a PR checklist item — see below.

- AGENTS.md gets a new Quick Reference bullet that calls out the rule
  and points at the test by name.

- .agents/api-endpoints-and-auth.md tightens the existing "Companion:
  MCP admin tool surface" subsection from "if useful, consider..." to
  "MUST be considered, with three concrete outcomes (tool added,
  deliberately skipped with documented reason, or forgot — which
  breaks the contract)". Adds a checklist item at the bottom of the
  file's authoritative checklist.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): drop duplicate DTOs, surface canonical types

Audit feedback: localaitools/dto.go reinvented several types that already
existed in the codebase. Replace the duplicates with the canonical types
so the LLM-visible wire format stays aligned with the rest of LocalAI by
construction (no parallel structs to keep in sync).

Removed (and the canonical type now used by the LocalAIClient interface):

  localaitools.Gallery          → config.Gallery
  localaitools.GalleryModelHit  → gallery.Metadata
  localaitools.VRAMEstimate     → vram.EstimateResult

Tightened scope:

  localaitools.Backend          → kept, but reduced to {Name, Installed}.
                                  ListKnownBackends now returns
                                  []schema.KnownBackend (the canonical
                                  type already used by REST /backends/known).

Kept with documented rationale:

  localaitools.JobStatus       — galleryop.OpStatus has Error error which
                                 marshals to "{}". JobStatus is the
                                 JSON-friendly mirror.
  localaitools.Node            — nodes.BackendNode carries gorm internals
                                 + token hash; we expose only the
                                 LLM-relevant fields.
  ImportModelURIRequest/Response — schema.ImportModelRequest and
                                   GalleryResponse are wire-shaped, mine
                                   are LLM-shaped (BackendPreference flat,
                                   AmbiguousBackend exposed).

Side wins:

  - Drop bytesPerMiB; vram.EstimateResult already carries human-readable
    display strings (size_display, vram_display) the LLM uses directly.
  - Drop the handler-private vramEstimateRequest in
    core/http/endpoints/localai/vram.go and bind directly into
    modeladmin.VRAMRequest (now JSON-tagged).

Both clients pass through these types now where possible (e.g.
ListGalleries in inproc.Client is a one-liner returning
AppConfig.Galleries; httpapi.Client.GallerySearch decodes straight into
[]gallery.Metadata).

All tests green with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): extract REST route paths into named constants

httpapi.Client had 18 bare-string path sites scattered across methods.
Pull them into pkg/mcp/localaitools/httpapi/routes.go: static paths as
package-private constants, dynamic paths as small builders that handle
url.PathEscape on segment values.

No behaviour change. Drops the now-unused net/url import from client.go
since path escaping moved into routes.go alongside the path it applies to.

Local-only by design: the server-side registrations in
core/http/routes/localai.go remain bare strings. Sharing constants across
the pkg/ ↔ core/ boundary would invert the layering today; the existing
Tool↔REST drift-detector in coverage_test.go is the safety net for that
direction.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* docs(assistant): align with shipped UI and dropped bootstrap env vars

The LocalAI Assistant doc still described the older iteration:

- The in-chat toggle was renamed from "Admin" to "Manage" (the badge is
  now "Manage mode" and the home page exposes a "Manage by chat" CTA).
- LOCALAI_ASSISTANT_BOOTSTRAP_MODEL / --localai-assistant-bootstrap-model
  and the bootstrap_default_model tool were removed — admins pick a model
  from the existing selector instead, no env-var configuration required.
- The shipped tool catalog includes import_model_uri but didn't appear in
  the doc; bootstrap_default_model appeared but no longer exists.
- The Settings → LocalAI Assistant runtime toggle wasn't mentioned as the
  preferred way to disable without restart.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-28 19:29:27 +02:00
Ettore Di Giacinto
142919fc79 fix(tests): inline model_test fixtures after tests/models_fixtures removal
The previous reorg removed tests/models_fixtures/ but core/config/model_test.go
still read CONFIG_FILE/MODELS_PATH env vars pointing into that directory, so
`make test` failed with "open : no such file or directory" on the readConfigFile
spec (the suite ran with --fail-fast and bailed before openresponses_test).

Inline the YAMLs (config/embeddings/grpc/rwkv/whisper) directly into the test
file, materialise them into a per-test tmpdir via BeforeEach, and drop the
env-var lookups. The test no longer depends on Makefile plumbing.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Edit] [Write] [Bash]
2026-04-28 12:58:49 +00:00
Ettore Di Giacinto
a0317d9926 refactor(tests): split app_test.go, move real-backend coverage to e2e-backends
core/http/app_test.go had grown to 1495 lines exercising three concerns at
once: HTTP-layer integration, real-backend inference (llama-gguf, tts,
stablediffusion, transformers embeddings, whisper), and service logic that
already has unit-level coverage. Each PR paid for 6 backend builds plus
real-model downloads to satisfy a single suite.

Reorg per layer:

- app_test.go (1495 -> 1003 lines) drives the mock-backend binary only.
  Kept: auth, routing, gallery API, file:// import, /system, agent-jobs
  HTTP plumbing, config-file model loading. Deleted real-inference specs
  (llama-gguf chat, ggml completions/streaming, logprobs, logit_bias,
  transcription, embeddings, External-gRPC, Stores duplicate, Model gallery
  Context). Lifted Agent Jobs out of the deleted Stores Context.
- tests/e2e-backends/backend_test.go gains logprobs, logit_bias, and
  no-first-token-dup specs (the latter folded into PredictStream). Two
  new caps gate them so non-LLM backends opt out.
- tests/e2e-aio/e2e_test.go gains a streaming smoke under Context("text")
  to catch container-level streaming regressions.
- tests/models_fixtures/ removed; all fixtures referenced testmodel.ggml.
  app_test.go now writes per-Context inline mock-model YAMLs.

CI:

- test.yml + tests-e2e.yml gain paths-ignore (docs/, examples/, *.md,
  backend/) so docs and backend-only PRs skip them. test.yml drops the
  6-backend Build step plus TRANSFORMER_BACKEND/GO_TAGS=tts; tests-apple
  drops the llama-cpp-darwin build.
- New tests-aio.yml runs the AIO container nightly + on workflow_dispatch
  + master/tags. The tests-e2e-container job moved out of test.yml so PRs
  no longer pay AIO cost.
- New tests-llama-cpp-smoke job in test-extra.yml runs on every PR with
  no detect-changes gate; pulls quay.io/go-skynet/local-ai-backends:
  master-cpu-llama-cpp (no build on PR) and exercises predict/stream/
  logprobs/logit_bias against Qwen3-0.6B. This is the PR-acceptance
  real-backend gate after AIO moved to nightly. The path-gated heavy
  test-extra-backend-llama-cpp wrapper appends the same caps so it
  exercises the moved specs when the backend actually changes.

Makefile:

- Deleted test-models/testmodel.ggml (the wget chain), test-llama-gguf,
  test-tts, test-stablediffusion, test-realtime-models. test target
  drops --label-filter, HUGGINGFACE_GRPC, TRANSFORMER_BACKEND, TEST_DIR,
  FIXTURES, CONFIG_FILE, MODELS_PATH, BACKENDS_PATH; depends on
  build-mock-backend. test-stores keeps a focused entry point and depends
  on backends/local-store. clean-tests also clears the mock-backend
  binary.

Net per typical Go-side PR: ~25min (6 backend builds + tests + AIO) +
~8min e2e drops to ~5min mock-backend test + ~8min e2e + ~5-10min
llama-cpp-smoke (image pulled). Docs and backend-only PRs skip the
always-on workflows entirely.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Edit] [Write] [Bash]
2026-04-27 23:09:20 +00:00
Ettore Di Giacinto
3948b580d2 fix(distributed): worker stopBackend/isRunning resolve bare modelID to replica keys
PR #9583 changed the supervisor's process map key from `modelID` to
`modelID#replicaIndex`, but the NATS lifecycle handlers kept passing
the bare modelID:

* `backend.stop` (subscribeLifecycleEvents): `s.stopBackend(req.Backend)`
  → `s.processes["Qwen3.6-..."]` missed (actual key is "...#0") →
  silent no-op. Admin "Unload model" clicks released VRAM via
  model.unload but left the gRPC process alive on its old port.
  Subsequent chats hit installBackend, found the leftover process,
  reused its address — and the UI reported "no models loaded" while
  the model kept responding.

* `backend.delete` (subscribeLifecycleEvents): same map miss in
  `isRunning(req.Backend)` and `s.stopBackend(req.Backend)` — admin
  "Delete backend" deleted the binary while the process was still
  serving traffic.

Add `resolveProcessKeys(id)`: exact match if `id` is a full processKey
(stopAllBackends iterates the map and passes its own keys);
prefix-match if `id` is bare (NATS handlers); empty if `id` contains
`#` but doesn't match (no spurious fallback when the caller was
explicit). stopBackend and isRunning now call it; stopBackend gets a
new stopBackendExact helper for per-key cleanup.

TDD: regression test fails without the fix (resolveProcessKeys
doesn't exist; map lookup by bare name returns nothing). Tests pass
post-fix.

Reproduced live: registry row count was 0 for the model the user
"Unloaded", chat still served by the leftover worker process.
SmartRouter behavior is correct in itself — it falls through to
scheduleAndLoad when no row exists; the bug was that the leftover
process corrupted the install path.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Bash]
2026-04-27 21:43:15 +00:00
Ettore Di Giacinto
ea1df8945b fix(distributed): preserve UI-added node labels across worker re-register
The register endpoint called SetNodeLabels(req.Labels) — replace-all
semantics — so every worker re-register wiped every label not in the
worker's body. The bug existed since labels were introduced in
PR #9186 (Mar 31), but only triggered for workers that supplied
labels via --node-labels.

PR #9583 (the multi-replica refactor) added an auto-mirrored
`node.replica-slots` label to every worker's registration body, which
made `len(req.Labels) > 0` always true — turning a latent edge-case
bug into a universal one. Operators reported "labels assigned to
node do not persist": labels survived until the next worker restart,
then disappeared.

Fix: iterate req.Labels and call SetNodeLabel (upsert) for each
instead of SetNodeLabels (delete-then-recreate). Worker-managed
labels still refresh on re-register; UI-added labels survive.

Trade-off: an operator who removes a label from --node-labels won't
have it auto-removed from the DB on next register — they can clean it
via the UI. Acceptable, since the alternative (current behavior)
silently destroys operator state.

Regression test added first (TDD): RegisterNodeEndpoint registers a
node, the test simulates a UI add via SetNodeLabel, then re-registers
with a different worker label set; assertion that the UI-added label
survives. Test fails against the broken code, passes against the fix.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Bash]
2026-04-27 21:24:50 +00:00
Ettore Di Giacinto
3280b9a287 fix(distributed): per-replica backend logs (store aggregation + UI)
The multi-replica refactor (PR #9583) changed the worker's process key
from `modelID` to `modelID#replicaIndex`, but the BackendLogStore kept
the bare-modelID lookup. Result: every distributed deployment lost
backend logs in the Nodes UI — single-replica too, since even the
default capacity of 1 produces a `#0` suffix.

Two changes wired together:

* pkg/model: BackendLogStore.GetLines/Subscribe now treat a modelID
  without `#` as a model prefix and merge across all `modelID#N` replica
  buffers (timestamp-sorted for GetLines; fan-in for Subscribe). Calls
  with a full `modelID#N` key resolve exactly. ListModels strips
  replica suffixes and deduplicates so the listing surfaces one entry
  per loaded model.

* react-ui: per-replica log streams as the default. Loaded Models
  table disambiguates each row with a `rep N` pill (only when the node
  hosts >1 replica of a model). Each row's "View logs" link routes to
  the per-replica process key so operators see only that replica's
  output. The logs page renders the replica context as a chip in the
  title and surfaces a segmented control — `Replica 0 / 1 / … / All
  merged` — when the model has multiple replicas; the merged segment
  uses the bare-modelID URL (delegating to the store's prefix
  aggregation) for the side-by-side comparison case. Single-replica
  deployments see no extra UI.

Tests added first (TDD): the regression set in
backend_log_store_test.go reproduces the bug at the exact failure
point — GetLines/ListModels/Subscribe assertions all fail against the
broken code, all pass against the fix. TestSubscribe_PerReplicaFilter
pins the exact-key path so a future change can't silently break it.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Skill:critique] [Skill:audit] [Skill:polish] [Skill:distill]
2026-04-27 20:55:24 +00:00
Ettore Di Giacinto
375bf1929d fix(ui): hide meta-dev backends in System → Backends Development toggle
The Manage view's flagsFor() short-circuited on b.IsMeta and returned
dev=false for every meta backend, so meta-dev entries
(e.g. llama-cpp-development, whisper-development, insightface-development)
leaked through the Development toggle in distributed mode and stayed
visible whether the toggle was on or off. The count chip even
under-reported because those rows were excluded from it.

Drop the IsMeta short-circuit and trust gallery enrichment for both
flags. Production metas (llama-cpp) are tagged isAlias=false /
isDevelopment=false in the gallery so they still pass both toggles;
meta-dev entries carry isDevelopment=true and now correctly hide
alongside concrete dev variants.

Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-27 20:38:20 +00:00
Ettore Di Giacinto
6b63b47f61 feat(distributed): support multiple replicas of one model on the same node (#9583)
* feat(distributed): support multiple replicas of one model on the same node

The distributed scheduler implicitly assumed `(node_id, model_name)` was
unique, but the schema didn't enforce it and the worker keyed all gRPC
processes by model name alone. With `MinReplicas=2` against a single
worker, the reconciler "scaled up" every 30s but the registry never
advanced past 1 row — the worker re-loaded the model in-place every tick
until VRAM fragmented and the gRPC process died.

This change introduces multi-replica-per-node as a first-class concept,
with capacity-aware scheduling, a circuit breaker, and VRAM
soft-reservation. Operators can declare per-node capacity via the worker
flag `--max-replicas-per-model` (mirrored as auto-label
`node.replica-slots=N`) or override per-node from the UI.

* Schema: BackendNode gains MaxReplicasPerModel (default 1) and
  ReservedVRAM. NodeModel gains ReplicaIndex (composite with node_id +
  model_name). ModelSchedulingConfig gains UnsatisfiableUntil/Ticks for
  the reconciler circuit breaker.

* Registry: replica_index threaded through SetNodeModel, RemoveNodeModel,
  IncrementInFlight, DecrementInFlight, TouchNodeModel, GetNodeModel,
  SetNodeModelLoadInfo and the InFlightTrackingClient. New helpers:
  CountReplicasOnNode, NextFreeReplicaIndex (with ErrNoFreeSlot),
  RemoveAllNodeModelReplicas, FindNodesWithFreeSlot,
  ClusterCapacityForModel, ReserveVRAM/ReleaseVRAM (atomic UPDATE with
  ErrInsufficientVRAM), and the unsatisfiable-flag CRUD.

* Worker: processKey now `<modelID>#<replicaIndex>` so concurrent loads
  of the same model land on distinct ports. Adds CLI flag
  --max-replicas-per-model (env LOCALAI_MAX_REPLICAS_PER_MODEL, default 1)
  and emits the auto-label.

* Router: scheduleNewModel filters candidates by free slot, allocates the
  replica index, and soft-reserves VRAM before installing the backend.
  evictLRUAndFreeNode now deletes the targeted row by ID instead of all
  replicas of the model on the node — fixes a latent bug where evicting
  one replica orphaned its siblings.

* Reconciler: caps scale-up at ClusterCapacityForModel so a misconfig
  (MinReplicas > capacity) doesn't loop forever. After 3 consecutive
  ticks of capacity==0 it sets UnsatisfiableUntil for a 5m cooldown and
  emits a warning. ClearAllUnsatisfiable fires from Register,
  ApproveNode, SetNodeLabel(s), RemoveNodeLabel and
  UpdateMaxReplicasPerModel so a new node joining or label changes wake
  the reconciler immediately. scaleDownIdle removes highest-replica-index
  first to keep slots compact.

* Heartbeat resets reserved_vram to 0 — worker is the source of truth
  for actual free VRAM; the reservation is only for the in-tick race
  window between two scheduling decisions.

* Probe path (reconciler.probeLoadedModels and health.doCheckAll) now
  pass the row's replica_index to RemoveNodeModel so an unreachable
  replica doesn't orphan healthy siblings.

* Admin override: PUT /api/nodes/:id/max-replicas-per-model sets a
  sticky override (preserved across worker re-registration). DELETE
  clears the override so the worker's flag applies again on next
  register. Required because Kong defaults the worker flag to 1, so
  every worker restart would have silently reverted the UI value.

* React UI: always-visible slot badge on the node row (muted at default
  1, accented when >1); inline editor in the expanded drawer with
  pencil-to-edit, Save/Cancel, Esc/Enter, "(override)" indicator when
  the value is admin-set, and a "Reset" button to hand control back to
  the worker. Soft confirm when shrinking the cap below the count of
  loaded replicas. Scheduling rules table gets an "Unsatisfiable until
  HH:MM" status badge surfacing the cooldown.

* node.replica-slots filtered out of the labels strip on the row to
  avoid duplicating the slot badge.

23 new Ginkgo specs (registry, reconciler, inflight, health) cover:
multi-replica row independence, RemoveNodeModel of one replica
preserving siblings, NextFreeReplicaIndex slot allocation including
ErrNoFreeSlot, capacity-gated scale-up with circuit breaker tripping
and recovery on Register, scheduleDownIdle ordering, ClusterCapacity
math, ReserveVRAM admission gating, Heartbeat reset, override survival
across worker re-registration, and ResetMaxReplicasPerModel handing
control back. Plus 8 stdlib tests for the worker processKey / CLI /
auto-label.

Closes the flap reproduced on Qwen3.6-35B against the nvidia-thor
worker (single 128 GiB node, MinReplicas=2): the reconciler now caps
the scale-up at the cluster's actual capacity instead of looping.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Read] [Edit] [Bash] [Skill:critique] [Skill:audit] [Skill:polish] [Skill:golang-testing]

* refactor(react-ui/nodes): tighten capacity editor copy + adopt ActionMenu for row actions

* Capacity editor hint trimmed from operator-doc-style ("Sourced from
  the worker's `--max-replicas-per-model` flag. Changing it here makes it
  a sticky admin override that survives worker restarts." → "Saved
  values stick across worker restarts.") and the override-state copy
  similarly compressed. The full mechanic is no longer needed in the UI
  — the override pill carries the meaning and the docs cover the rest.

* Node row actions migrated from an inline cluster of icon buttons
  (Drain / Resume / Trash) to the kebab ActionMenu used by /manage for
  per-row model actions, so dense Nodes tables stay clean. Approve
  stays as a prominent primary button — it's a stateful admission gate,
  not a routine action, and elevating it matches how /manage surfaces
  install-time decisions outside the menu.

* The expanded drawer's Labels section now filters node.replica-slots
  out of the editable label list. The label is owned by the Capacity
  editor above; surfacing it again as an editable label invited
  confusion (the Capacity save would clobber any direct edit).

Both backend and agent workers benefit — they share the row rendering
path, so the action menu and label filter apply to both.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp] [Skill:critique] [Skill:audit] [Skill:polish]

* fix(react-ui/nodes): suppress slot badge on agent workers

Agent workers don't load models, so the per-node replica capacity is
inapplicable to them. Showing "1× slots" on agent rows was a tiny
inconsistency from the unified rendering path — gate the badge on
node_type !== 'agent' so it only appears on backend workers.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp]

* refactor(react-ui/nodes): distill expanded drawer + restyle scheduling form

The expanded node drawer used to stack five panels — slot badge,
filled capacity box, Loaded Models h4+empty-state, Installed Backends
h4+empty-state, Labels h4+chips+form — making routine inspections feel
like a control panel. The scheduling rule form wrapped its mode toggle
as two 50%-width filled buttons that competed visually with the actual
primary action.

* Drawer: collapse three rarely-touched config zones (Capacity,
  Backends, Labels) into one `<details>` "Manage" disclosure (closed by
  default) with small uppercase eyebrow labels for each zone instead of
  parallel h4 sub-headings. Loaded Models stays as the at-a-glance
  headline with a single-line empty hint instead of a boxed empty state.
  CapacityEditor renders flat (no filled background) — the Manage
  disclosure provides framing.

* Scheduling form: replace the chunky 50%-width button-tabs with the
  project's existing `.segmented` control (icon + label, sized to
  content). Mode hint becomes a single tied line below. Fields stack
  vertically with helper text under inputs and a hairline divider above
  the right-aligned Save / Cancel.

The empty drawer collapses from ~5 stacked sections (~280px tall) to
two lines (~80px). The scheduling form now reads as a designed dialog
instead of raw building blocks. Both surfaces now match the typographic
density and weight of the rest of the admin pages.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [chrome-devtools-mcp] [Skill:distill] [Skill:audit] [Skill:polish]

* feat(react-ui/nodes): replace scheduling form's model picker with searchable combobox

The native <select> made operators scroll through every gallery entry to
find a model name. The project already has SearchableModelSelect (used
in Studio/Talk/etc.) which combines free-text search with the gallery
list and accepts typed model names that aren't installed yet — useful
for pre-staging a scheduling rule before the node it'll run on has
finished bootstrapping.

Also drops the now-unused useModels import (the combobox manages the
gallery hook internally).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit]

* refactor(react-ui/nodes): consolidate key/value chip editor + add replica preset chips

The Nodes page was rendering the same key=value chip pattern in two
places with subtly different markup: the Labels editor in the expanded
drawer and (post-distill) the Node Selector input in the scheduling
form. The form's input was also a comma-separated string that operators
were getting wrong.

* Extract <KeyValueChips> as a fully controlled chip-builder. Parent
  owns the map and decides what onAdd/onRemove does — form state for the
  scheduling form, API calls for the live drawer Labels editor. Same
  visuals everywhere; one component to change when polish needs apply.

* Replace the comma-separated Node Selector text input with KeyValueChips.
  Operators were copying syntax from docs and missing commas; the chip
  vocabulary makes the key=value structure self-documenting.

* Add <ReplicaInput>: numeric input + quick-pick preset chips for Min/Max
  replicas. Picked over a slider because replica counts are exact specs
  derived from VRAM math (operator decision, not a fuzzy estimate). The
  chips give one-click access to common values (1/2/3/4 for Min,
  0=no-limit/2/4/8 for Max) without the slider's special-value problem
  (MaxReplicas=0 is categorical, not a position on a continuum).

* Drop the now-unused labelInputs state in the Nodes page (the inline
  label editor's per-node draft state lived there and is now owned by
  KeyValueChips).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Skill:distill]

* test: fix CI fallout from multi-replica refactor (e2e/distributed + playwright)

Two breakages caught by CI that didn't surface in the local run:

* tests/e2e/distributed/*.go — multiple files used the pre-PR2 registry
  signatures for SetNodeModel / IncrementInFlight / DecrementInFlight /
  RemoveNodeModel / TouchNodeModel / GetNodeModel / SetNodeModelLoadInfo
  and one stale adapter.InstallBackend call in node_lifecycle_test.go.
  All updated to pass replicaIndex=0 — these tests don't exercise
  multi-replica behavior, they just need to compile against the new
  signatures. The chip-builder tests in core/services/nodes/ already
  cover the multi-replica logic.

* core/http/react-ui/e2e/nodes-per-node-backend-actions.spec.js — the
  drawer's distill refactor moved Backends inside a "Manage" <details>
  disclosure that's collapsed by default. The test helper expanded the
  node row but never opened Manage, so the per-node backend table was
  never in the DOM. Helper now clicks `.node-manage > summary` after
  expanding the row.

All 100 playwright tests pass locally; tests/e2e/distributed compiles
clean.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:opus-4-7 [Edit] [Bash]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-27 21:20:05 +02:00
Ettore Di Giacinto
3810fe1a1e fix(distributed): worker container healthcheck always unhealthy
The Dockerfile's HEALTHCHECK probes http://localhost:8080/readyz, which
is the OpenAI API server port. When the same image runs as a worker, it
listens on the gRPC base port (50051) and an HTTP file transfer server
on port-1 (50050) — nothing on 8080 — so docker always reports the
container as unhealthy.

Add unauthenticated /readyz and /healthz endpoints to the worker's HTTP
file transfer server, and override HEALTHCHECK_ENDPOINT for worker-1 in
the distributed compose file. Disable the healthcheck for agent-worker
since it is NATS-only and exposes no HTTP server.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-27 13:51:57 +00:00
Ettore Di Giacinto
60549a8a60 feat(react-ui): page-width archetype system + mobile/tablet nav polish
Replace the universal max-width:1200px cap on .page with a four-tier
archetype system (narrow 760, medium 1080, default 1600, wide unbounded)
selected per page based on what its UX actually wants. Data/table pages
fill ultrawide displays; forms cap at reading width; tabbed feature
surfaces breathe.

Mobile/tablet:
- New 640/1024 breakpoint split. Tablets (640-1023) get a persistent
  52px icon rail; below 640 keeps the slide-off drawer.
- Drawer polish: body-scroll lock, Escape to close, focus moves into
  the drawer on open and back to the hamburger on close, aria-hidden
  + inert on main while open.
- Mobile top bar carries hamburger + theme toggle + account avatar
  (44x44 touch targets) so theme/account aren't trapped in the drawer.
- Page-level reflow on phones: page-header column-stacks, filter chips
  scroll horizontally, tables go edge-to-edge, OperationsBar overflows
  rather than wrapping. Honors prefers-reduced-motion.

Manage > Models: drop the toggle column; Enable/Disable joins the
per-row Actions menu alongside Stop/Pin/Edit/Logs/Delete for
consistency with the other action verbs.

Page-width tokens live in theme.css so future tuning is one line.
Removes 7 inline maxWidth workarounds from page roots.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-7 [Edit] [Bash]
2026-04-27 11:51:29 +00:00