Commit Graph

310 Commits

Author SHA1 Message Date
Ettore Di Giacinto
076dcdbed8 refactor(realtime): buffer whole message for TTS, drop sentence segmenter
Per review (richiejp): the sentence segmenter pipelined unary TTS by
splitting on ASCII .!?/newline, which does nothing for languages without
those boundaries (CJK/Thai) — there it already degraded to buffering the
whole message anyway.

Replace it with a uniform model: stream the LLM transcript live, buffer the
full message, then synthesize it once. emitSpeech already streams the audio
chunks when the backend implements TTSStream and falls back to a single
unary delta otherwise, so this is real streaming TTS where supported and a
clean whole-message synthesis elsewhere — no per-sentence emulation, no
language assumptions. speechStreamer becomes transcriptStreamer (transcript
deltas only); the whole-message synthesis moves into streamLLMResponse.

Assisted-by: Claude:claude-opus-4-8 go test, golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
9ec1456ec6 fix(realtime): clean TTS temp path before read (gosec G304)
emitSpeech reads the WAV file the TTS backend wrote. The read moved here
from realtime.go, so code-scanning flagged it as a new G304 alert even
though the path is backend-controlled (a temp file), not user input.
Wrap it in filepath.Clean — a real path normalization that also clears
the alert, keeping with the repo's no-#nosec convention.

Assisted-by: Claude:claude-opus-4-8 gosec, golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
cb3609530a fix(realtime): always strip reasoning from spoken output
disable_thinking maps to ReasoningConfig.DisableReasoning=true on the LLM
config, which the backend reads as enable_thinking=false. But the realtime
handler reads that SAME config to drive reasoning extraction, and there
DisableReasoning=true means "skip stripping". PredictConfig() returns this
LLM config, so both the streamed (speechStreamer) and buffered realtime
paths stopped stripping <think>…</think> exactly when disable_thinking was
on — leaking raw reasoning to the client whenever the model ignored the
enable_thinking hint (e.g. lfm2.5).

Add spokenReasoningConfig() which clears DisableReasoning for extraction
(keeping custom tokens/tag pairs) and route both realtime paths through it.
Spoken output now always strips reasoning, independent of the backend
suppression hint.

Assisted-by: Claude:claude-opus-4-8 go test, golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
f48344f2ff fix(realtime): register pipeline streaming/thinking config fields
TestAllFieldsHaveRegistryEntries (core/config/meta) requires every config
field to have a meta registry entry. The four new pipeline fields
(disable_thinking, streaming.{llm,tts,transcription}) had none, failing
tests-linux/tests-apple. Add toggle entries for them.

Also handle the os.Remove return in realtime_speech_test.go to satisfy
errcheck (golangci-lint).

Assisted-by: Claude:claude-opus-4-8 go test, golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
16a5bab71f feat(realtime): wire streamLLMResponse for token-streamed replies
triggerResponseAtTurn takes a streamed path when pipeline.streaming.llm is
set, the turn has no tools, and audio is requested: streamLLMResponse
announces the assistant item, drives the LLM token callback through a
speechStreamer (reasoning-stripped transcript deltas + sentence-piped TTS),
and emits the terminal events. Tool turns and non-streaming pipelines keep
the existing buffered path unchanged, so this is strictly opt-in.

Assisted-by: Claude:claude-opus-4-8 go vet
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
ca23d05c66 feat(realtime): speechStreamer for token-streamed LLM->TTS
emitSpeech now returns raw PCM (caller base64-encodes) so streamed segments
accumulate correctly. speechStreamer consumes streamed LLM tokens: it strips
reasoning via the streaming ReasoningExtractor, emits a transcript delta per
content fragment, and sentence-pipes content into emitSpeech so each sentence
is synthesized as soon as it's ready. Handler wiring (plain-content turns)
follows.

Assisted-by: Claude:claude-opus-4-8 go vet
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
685e4632d7 feat(realtime): pipeline disable_thinking maps to enable_thinking off
applyPipelineThinking forces the LLM's ReasoningConfig.DisableReasoning when
pipeline.disable_thinking is set, which gRPCPredictOpts turns into the
enable_thinking=false backend metadata. Applied at newModel construction on
the per-session LLM config copy, so it doesn't leak to other model users and
needs no realtime-specific request plumbing.

Assisted-by: Claude:claude-opus-4-8 go vet
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
98ed541b22 feat(realtime): streaming transcription text deltas
Add emitTranscription and route commitUtterance through it. With
pipeline.streaming.transcription set it streams each transcript fragment as
a conversation.item.input_audio_transcription.delta via TranscribeStream
then a completed event; otherwise it preserves the single completed-event
unary behaviour. Returns the final transcript for response generation.

Assisted-by: Claude:claude-opus-4-8 go vet
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
378d6c25cf feat(realtime): route response audio through emitSpeech (streaming TTS)
Replace the inline unary TTS block in the response handler with emitSpeech,
which streams a response.output_audio.delta per backend PCM chunk when
pipeline.streaming.tts is set and otherwise preserves the single-delta unary
behaviour. emitSpeech returns the accumulated base64 audio, stored on the
conversation item as before. Transcript and audio-done events stay in the
handler so later per-segment streaming can reuse emitSpeech.

Assisted-by: Claude:claude-opus-4-8 go vet
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
2c6fdd0570 feat(realtime): emitSpeech with flag-gated streaming TTS
emitSpeech synthesizes a piece of text and forwards audio to the client,
streaming one output_audio.delta per backend PCM chunk when the pipeline
sets streaming.tts, or one delta for the whole utterance otherwise. WebRTC
gets raw PCM (it resamples internally); WebSocket gets base64 PCM at the
session rate. It emits no transcript/audio-done events so a streamed reply
can be split into multiple spoken segments sharing one response.

Adds fakeModel/fakeTransport test doubles for the realtime Model/Transport
interfaces, driving streaming assertions deterministically.

Assisted-by: Claude:claude-opus-4-8 go vet
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
2ba2216ce2 feat(realtime): streaming TTS/transcription methods on Model interface
Add TTSStream and TranscribeStream to the realtime Model interface and
implement them on wrappedModel (delegating to backend.ModelTTSStream /
ModelTranscriptionStream) and transcriptOnlyModel. ttsStream adapts the
backend's WAV-framed stream (44-byte header carrying the sample rate, then
PCM) into raw PCM + sample rate for the realtime transports. Handler wiring
that consumes these (flag-gated) follows.

Assisted-by: Claude:claude-opus-4-8 go vet
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
Ettore Di Giacinto
e0820a11c9 feat(realtime): sentence segmenter for streamed LLM->TTS pipelining
streamSegmenter accumulates streamed LLM tokens and emits complete
sentence/clause segments (terminator+whitespace, or newline) so TTS can
synthesize each segment as it completes instead of waiting for the whole
reply. Pure helper; the streaming handler wiring consumes it next.

Assisted-by: Claude:claude-opus-4-8 go vet
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-05 14:03:36 +00:00
LocalAI [bot]
e837921c2c feat: forward reasoning_effort to the backend so jinja models honor it (#10184)
* feat: forward reasoning_effort to the backend so jinja models honor it

reasoning_effort was only mapped to the binary enable_thinking toggle and
otherwise reached Go-side templates — it was never sent to the backend. So
jinja-templated models whose chat template keys on reasoning_effort (gpt-oss
Harmony, LFM2.5) could not be driven by it: LFM2.5 ignores enable_thinking and
kept emitting <think>.

Forward the effective reasoning_effort to the backend as a chat_template_kwarg
(mirroring enable_thinking) in grpc-server.cpp, and put it in PredictOptions
metadata (gRPCPredictOpts). Add a config-level default: ModelConfig.reasoning_effort
and Pipeline.reasoning_effort, resolved by ModelConfig.ApplyReasoningEffort
(request value overrides config default, none->disable / level->enable, an
operator's reasoning.disable wins). request.go now uses that helper.

Assisted-by: Claude:claude-opus-4-8 go test, golangci-lint
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(realtime): set the pipeline LLM's reasoning_effort

Apply Pipeline.ReasoningEffort to the pipeline's LLM config when the realtime
model is built (per-session copy, overrides the LLM's own reasoning_effort),
and surface the resolved effort on the template input so Go-templated models
get it too. jinja models receive it via the backend metadata. This lets a
realtime pipeline disable thinking on models that only honor reasoning_effort
(e.g. LFM2.5), which enable_thinking can't.

Assisted-by: Claude:claude-opus-4-8 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>
2026-06-05 13:45:43 +00:00
LocalAI [bot]
27e63b9a78 feat(tts): support per-request instructions and params (#10172)
The OpenAI-compatible TTS endpoint accepts an `instructions` field, but it
was silently dropped at the HTTP->gRPC boundary: neither schema.TTSRequest
nor the gRPC TTSRequest proto carried it, so backends could only read such a
value from static YAML options (identical for every request). This blocked
per-line emotion/style and, for Qwen3-TTS VoiceDesign, limited a model config
to a single designed voice.

Plumb a generic per-request instruction string end to end, plus an optional
backend-specific params map:

- proto: add `optional string instructions` and `map<string,string> params`
  to TTSRequest.
- schema: add Instructions (maps OpenAI `instructions`) and Params (LocalAI
  extension) to schema.TTSRequest.
- core: thread both through ModelTTS/ModelTTSStream via a newTTSRequest helper
  that attaches instructions only when non-empty (so backends can fall back to
  YAML when unset); forward them from the /v1/audio/speech handler.
- qwen-tts: prefer the per-request instruction over the YAML `instruct` option
  (used by both mode detection and generation) and merge per-request params.
- chatterbox: merge per-request params (coerced to float/int/bool) over YAML
  options into generate() kwargs.

Fully backward compatible: empty instructions fall back to the YAML option and
backends that don't support style/voice instructions ignore the field.

Closes #10164


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-04 11:45:02 +02:00
Richard Palethorpe
3a932a9803 feat(distributed): Add NATS JWT authentication and TLS/mTLS options (#10159)
* feat(distributed): NATS JWT auth, TLS/mTLS options, and e2e coverage

Mint per-node NATS user JWTs at registration when LOCALAI_NATS_ACCOUNT_SEED
is set, and connect workers with scoped credentials from the register response.
Add optional LOCALAI_NATS_TLS_CA/CERT/KEY for private CA and mTLS alongside
tls:// URLs, plus test-e2e-distributed and NatsJWT container e2e specs.

Document JWT setup (nats-auth-setup.sh) and TLS env vars in distributed-mode.

Assisted-by: Grok:grok grok-build
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* fix(distributed): correct NATS JWT scoping and harden client auth

The JWT-auth path added in 46467cc7 had several gaps that fail silently
under LOCALAI_NATS_REQUIRE_AUTH:

- Agent-worker minted JWTs did not allow the subjects the agent worker
  actually subscribes to (jobs.mcp-ci.new and nodes.<id>.backend.stop),
  so MCP-CI jobs and backend-stop session cleanup were silently dropped.
  Scope the agent permission set to those subjects.
- NATS subscription permission violations were swallowed (Subscribe
  returned a live-but-dead subscription). Confirm subscriptions with a
  server round-trip so a denial surfaces synchronously, and log async
  permission errors.
- The backend worker connected anonymously when given a JWT without its
  paired seed; reject the unpaired credential instead.
- The documented service-user permissions in nats-auth-setup.sh omitted
  prefixcache.>, which the frontend publishes and subscribes; add it.

Also: add a credential-provider hook to the messaging client (consumed by
the follow-up credential-lifecycle change), drop the always-nil error from
NatsMessagingOptions, run go mod tidy (jwt/v2 and nkeys are now direct),
and gofmt the feature's files.

Tests: an agent-JWT e2e spec that connects to the enforcing NATS server
and exercises every subscription the agent worker makes, plus permission
allow-list coverage unit tests.

Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

* feat(distributed): acquire and auto-refresh worker NATS credentials

Workers fetched NATS credentials once at startup, which broke two cases
under JWT auth: a worker that registered while still pending admin
approval never received a minted JWT (it connected unauthenticated and
gave up), and a long-running worker's 24h JWT expired with no way to renew
it.

Introduce workerregistry.NATSCredentialManager, built on idempotent
re-registration (the frontend preserves the node row and mints a fresh JWT
each call):

- Acquire re-registers through admin approval until the node is approved
  and credentials are minted (or returns the first success when auth is
  not required, preserving anonymous-NATS behavior).
- RefreshLoop re-registers before the JWT expires (~75% of its lifetime),
  updating the credentials served to the connection.
- Both are bounded (default 100 attempts / consecutive failures) and
  return an error on exhaustion, so an unapprovable or unrenewable worker
  exits non-zero and surfaces the problem instead of hanging or drifting
  toward an expired credential.

The messaging client gains WithUserJWTProvider, fetching credentials on
each (re)connect so the connection transparently adopts a refreshed JWT
when the server expires the old one. RegisterFull exposes the approval
status and full response; Register delegates to it.

Both the backend worker and the agent worker are wired to this: explicit
env credentials are used as-is, minted credentials are acquired-with-wait
and refreshed, and a permanent refresh failure shuts the worker down so it
restarts and re-acquires.

Tests cover Acquire (wait-through-pending, bounded give-up, context
cancel), RefreshLoop (refresh-before-expiry, bounded failure, no-expiry
exit) and jwtExpiry decoding. Docs updated in distributed-mode.md.

Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>

---------

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-06-03 19:43:56 +02:00
LocalAI [bot]
76fe0bb929 feat(crispasr): add CrispASR backend — multi-architecture ASR + TTS (#10099)
* feat(crispasr): backend source files (Go gRPC server, C-ABI shim, build files)

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

* polish(crispasr): brand error strings + fix stale shim comment

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

* build(crispasr): register backend in root Makefile

Mirror the whisper Go backend registration for the new crispasr
backend: NOTPARALLEL entry, prepare-test-extra/test-extra hooks,
BACKEND_CRISPASR definition, docker-build target generation, and the
docker-build-backends aggregate target.

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

* ci(crispasr): add backend build matrix entries

Mirror the 11 whisper golang Dockerfile matrix entries (CPU amd64/arm64,
CUDA 12/13, L4T CUDA 13, Intel SYCL f32/f16, Vulkan amd64/arm64, L4T
arm64, ROCm hipblas) with backend and tag-suffix substituted to crispasr.

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

* feat(gallery): add crispasr backend gallery entries

Add the crispasr meta anchor and its full set of image gallery entries
(cpu, metal, cuda12/13, rocm, intel-sycl f32/f16, vulkan, L4T arm64,
L4T cuda13 arm64, plus -development variants), mirroring the whisper
backend gallery block.

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

* ci(crispasr): bump CRISPASR_VERSION via bump_deps workflow

Track CrispStrobe/CrispASR main branch and bump CRISPASR_VERSION in
backend/go/crispasr/Makefile.

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

* build(crispasr): don't wire fixture-gated test into test-extra

Mirror the whisper Go backend: its AudioTranscription test is gated on
model/audio fixtures and skips in CI, so building crispasr (the heaviest
ggml compile in the tree) inside the unit-test lane adds a long compile
for zero coverage. The backend image build in backend-matrix.yml remains
the authoritative compile check.

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

* ci(crispasr): add darwin metal build entry (mirror whisper)

The metal-crispasr gallery entries and capabilities.metal mapping
reference -metal-darwin-arm64-crispasr, which is only produced by an
includeDarwin entry. Mirror whisper's darwin metal entry so the tag
actually gets built.

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

* ci(crispasr): place hipblas matrix entry next to whisper twin

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

* feat(crispasr): register crispasr as pref-only ASR backend + test

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

* test(crispasr): port whisper behavioral suite (cancellation + streaming)

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

* test(crispasr): fix skip message env var names to CRISPASR_*

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

* feat(crispasr): switch shim to crispasr_session_* multi-architecture API

The shim used whisper_full(), which in CrispASR is the whisper-only path:
libcrispasr only transcribes Whisper GGUFs through it. Multi-architecture
transcription (Parakeet, Voxtral, Qwen3-ASR, Canary, Granite, FunASR,
Paraformer, SenseVoice, ...) goes through the crispasr_session_* C-ABI,
which auto-detects the architecture from the GGUF and dispatches to the
matching backend.

Rewrite the C shim around crispasr_session_open / _transcribe_lang /
_result_* and add get_backend() so the selected backend is logged.
load_model now takes a threads param (session_open binds n_threads at
open). The session result is segment+word based with no token IDs and no
per-decode callback, so drop n_tokens / get_token_id /
get_segment_speaker_turn_next / set_new_segment_callback. set_abort is
kept for API parity but is best-effort: the session transcribe is blocking
with no abort hook.

Update the purego bindings and gocrispasr.go to match: tokens are left
empty, speaker-turn handling is removed, and AudioTranscriptionStream
emits one delta per non-empty segment after the blocking decode returns
(no progressive streaming via the session API), preserving the
concat(deltas) == final.Text invariant.

crispasr_session_set_translate is exported by libcrispasr but not declared
in crispasr.h, so it is forward-declared in the shim alongside the
open/transcribe/result functions.

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

* build(crispasr): link full CrispASR backend set for multi-arch support

The shim's crispasr_session_* dispatch calls into the per-architecture
backend libs (parakeet, voxtral, qwen3_asr, canary, funasr, paraformer,
sensevoice, ...), which CrispASR builds as static archives. Linking only
crispasr + ggml dead-stripped every backend object from the final module
(nm backend-symbol count: 0), leaving a whisper-only .so.

Link the same backend set as crispasr-cli so the static archives are
pulled in. After this the module carries the backend symbols (nm count
407, .so grows from ~2.1MB to ~6.7MB) and the session API can dispatch to
every compiled-in architecture.

Also rewrite ${CMAKE_SOURCE_DIR}/examples/talk-llama to
${PROJECT_SOURCE_DIR}/... in the vendored src/CMakeLists.txt: CrispASR
locates its vendored llama.cpp via ${CMAKE_SOURCE_DIR}, which is wrong when
CrispASR is add_subdirectory'd (CMAKE_SOURCE_DIR points at this backend
dir, not the CrispASR root). PROJECT_SOURCE_DIR is correct both standalone
and as a subproject; the sed is idempotent.

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

* test(crispasr): adapt suite to session API (blocking, no decode callback)

Register the new symbol set (drop the removed token/speaker/callback funcs,
add get_backend; load_model now takes 2 args). The session transcribe is
blocking with no abort hook, so a mid-decode cancel can't interrupt it:
change the cancellation spec to cancel the context before the call and
assert codes.Canceled from the pre-call ctx.Err() check, dropping the
<5s mid-decode timing assertion. The streaming spec still holds with
per-segment post-decode emission (>=2 deltas, concat(deltas) == final.Text).

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

* feat(gallery): add CrispASR ASR model entries (-crispasr)

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

* fix(gallery): keep only session-auto-detectable CrispASR ASR models

The crispasr backend loads models via crispasr_session_open, which
auto-detects the backend from the GGUF general.architecture using
crispasr_detect_backend_from_gguf. Architectures not in that detect
map cannot be opened, so those gallery entries fail to load.

Removed entries whose architecture is not wired into CrispASR
v0.6.11's session auto-detect router (they can be re-added when
upstream maps them):

- Not in the detect map: data2vec, firered-asr, funasr,
  fun-asr-mlt-nano, glm-asr, hubert, kyutai-stt, mega-asr, mimo-asr,
  moonshine{,-de,-streaming,-tiny-de}, omniasr{,-llm,-llm-1b},
  paraformer, sensevoice.
- Pending verification (filename-heuristic routed, not arch-detected):
  parakeet-ctc-0.6b, parakeet-ctc-1.1b. Their GGUFs are routed to the
  fastconformer-ctc backend by a filename heuristic in the model
  registry, which implies general.architecture is not a mapped string.

Kept the parakeet rnnt/tdt_ctc variants: convert-parakeet-to-gguf.py
writes general.architecture="parakeet" unconditionally and encodes the
rnnt/ctc distinction in metadata fields, so they session-auto-detect.

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

* feat(crispasr): TTS synthesis via crispasr_session_synthesize (24kHz)

Add tts_synthesize/tts_free/tts_set_voice to the C-ABI shim. They reuse
the already-open g_session (crispasr_session_open auto-detects a TTS
model) and dispatch to the upstream synthesis call, which returns
malloc'd 24 kHz mono float PCM. Orpheus needs a SNAC codec path that we
do not set, so it returns NULL here and surfaces as an error Go-side.

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

* feat(crispasr): implement TTS/TTSStream gRPC methods

Bind the new shim functions via purego and implement TTS, TTSStream and
a writeWAV24k helper. synthesize copies the C-owned PCM out before
freeing it; TTS writes a 24 kHz mono 16-bit WAV to req.Dst via
go-audio/wav. CrispASR has no progressive synth, so TTSStream
synthesizes fully, encodes to WAV, and emits the bytes as a single
chunk; it owns the results-channel close (the gRPC server wrapper ranges
until close), mirroring vibevoice-cpp's TTSStream.

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

* feat(crispasr): log when a TTS voice override is not honored

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

* feat(gallery): add CrispASR vibevoice-tts model entry

Only vibevoice-tts works through the current shim: qwen3-tts, chatterbox,
and orpheus require companion codec/s3gen/SNAC paths (set_codec_path /
set_s3gen_path) that the shim doesn't wire yet, and kokoro/indextts/voxcpm2
aren't in the session auto-detect map. Those are follow-ups.

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

* test(crispasr): gated TTS synthesis spec

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

* fix(crispasr): satisfy golangci-lint (errcheck defers + unsafeptr nolint)

The crispasr Go file is entirely new, so new-from-merge-base lints every
line (unlike the grandfathered whisper backend it was forked from):
- handle os.RemoveAll / fh.Close return values in AudioTranscription
- annotate the two intentional C-pointer unsafe.Slice sites with //nolint:govet

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

* feat(crispasr): backend: and codec: model options (explicit arch + companion files)

Add two model-config options to the CrispASR backend via opts.Options:

- backend:<name> selects an explicit CrispASR backend (bypassing
  auto-detect) by routing load_model through
  crispasr_session_open_explicit, unlocking architectures the
  detector won't pick on its own (qwen3, cohere, granite, voxtral,
  moonshine, mimo-asr, orpheus, kokoro, chatterbox, etc.).
- codec:<path> loads a companion file (qwen3-tts codec, orpheus SNAC,
  chatterbox s3gen, or mimo-asr tokenizer) via the universal
  crispasr_session_set_codec_path setter after the session opens. A
  relative path resolves against the model directory. rc==0 means
  success or not-applicable; only a negative rc is fatal.

The C shim load_model gains a backend_name argument and a new
set_codec_path entry point; the Go bridge parses the prefix:value
options and registers the new symbol. The vad_only path is unchanged.

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

* feat(gallery): expand CrispASR models via backend:/codec: options (explicit arch + companions)

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

* refactor(gallery): use virtual.yaml base for crispasr models

The crispasr entries are just backend + model + a couple options, fully
expressed inline via overrides:/files: in gallery/index.yaml. Point each
url: at the shared gallery/virtual.yaml (the established 'virtual' model
trick) and drop the 36 redundant per-model gallery/*-crispasr.yaml files.

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

* fix(gallery): drop voice-requiring TTS entries (keep vibevoice-tts)

Real e2e showed qwen3-tts/orpheus/chatterbox don't synthesize through the
current shim: the codec: companion loads fine, but these engines additionally
need a voice pack / voice prompt / reference clip (qwen3-tts base errors
'no voice'; chatterbox is zero-shot cloning; orpheus uses named voices) that
the backend doesn't wire. (qwen3-tts also can't auto-detect: its GGUF arch is
'qwen3tts', unmapped by the detector — would need backend:qwen3-tts.) Removed
to avoid shipping non-working gallery entries; vibevoice-tts (built-in voice,
e2e-verified) remains the working TTS. Voice-pack wiring is a follow-up.

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

* feat(crispasr): speaker: and voice: TTS options (baked speakers + voice packs/prompts)

speaker:<name> -> crispasr_session_set_speaker_name (baked speakers: qwen3-tts
CustomVoice, orpheus). voice:<path>(+voice_text:<ref>) -> crispasr_session_set_voice
(voice-pack GGUF, or WAV zero-shot clone with ref text). Applied at Load as the
default voice; req.Voice still overrides the speaker per request.

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

* feat(gallery): re-add e2e-verified TTS engines (chatterbox, qwen3-tts-customvoice, orpheus)

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>
2026-05-31 12:11:03 +02:00
LocalAI [bot]
a44bdb29d4 feat: prefix-cache-aware routing for distributed mode (#10071)
* feat(radixtree): generic prefix tree skeleton with longest-match

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

* feat(radixtree): Insert with path recency refresh and entry cap

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

* feat(radixtree): TTL idle-expiry and Evict sweep with branch pruning

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

* feat(radixtree): recency-weighted per-value Weight

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

* feat(radixtree): Remove all entries for a value

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

* test(radixtree): race-free concurrency smoke test

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

* fix(radixtree): reclaim empty branches, RWMutex reads, TTL boundary, empty-key guard

Address review findings on the generic prefix tree:

- Extract a shared pruneWalk helper parameterized by a shouldClear
  predicate and use it from Evict, Remove, and the MaxEntries path.
  Previously evictOldestLocked cleared a victim's value but never
  removed the now value-less node or its childless ancestors, so
  internal nodes accumulated under sustained churn at the cap. The
  MaxEntries path now prunes the victim and its empty ancestors.
- DRY: pruneWalk replaces the duplicated logic in the former
  pruneLocked and Remove's inner closure.
- Switch Tree.mu to sync.RWMutex; LongestMatch, Weight and Len take
  the read lock (RLock) while Insert, Evict and Remove keep the write
  lock. Confirmed race-clean under go test -race.
- Document the strict greater-than TTL boundary on Options.TTL and
  expired: age exactly equal to TTL is still live.
- Guard Insert against an empty key (no-op): the root never holds a
  value.

Adds Ginkgo specs covering MaxEntries eviction, ancestor reclamation,
the no-growth-past-cap invariant, the TTL boundary, and empty-key
behavior for both Insert and LongestMatch.

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

* feat(prefixcache): RoutePolicy enum with parse/resolve

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

* feat(prefixcache): Config with defaults and validation

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

* feat(prefixcache): deterministic xxhash prefix-chain extractor

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

* feat(prefixcache): pure filter-then-score replica selection

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

* feat(prefixcache): Provider interface and radix-tree-backed Index

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

* style(prefixcache): gofmt policy enum comment alignment

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

* fix(prefixcache): head-first prefix chunking and hoist Weight out of sort

Address code-quality review findings in the prefixcache package.

Correctness: ExtractChain now chunks from absolute offset 0 with fixed
[0,W),[W,2W),... boundaries and caps the chain to the FIRST MaxDepth
head blocks. The previous tail-keeping logic shifted the byte offset by a
non-window amount once a conversation grew past MaxDepth*WindowBytes,
changing every hash each turn and silently breaking cross-turn
longest-prefix matching. The reusable KV/prefix cache lives at the head
of the prompt, so anchoring at offset 0 makes the chain a true
prefix-chain: P and P+suffix share their full leading overlap. Add a
regression spec proving cross-turn stability past the cap.

Performance: Index.Decide precomputes each candidate's Weight once
(decorate-sort-undecorate) instead of calling the O(tree size) Weight
inside the O(n log n) sort comparator. Behavior is unchanged.

Lint: encode prev with binary.LittleEndian.PutUint64 instead of a manual
byte loop, clearing the modernize rangeint finding.

Also add a concurrent Decide/Observe/Invalidate spec to exercise Index's
documented concurrency safety under go test -race.

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

* feat(messaging): prefixcache observe/invalidate subjects and payloads

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

* feat(prefixcache): NATS sync publish/apply for observe and invalidate

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

* feat(distributedhdr): ctx carrier for prefix-hash chain

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

* feat(distributedhdr): PrefixChainHook indirection for backend-side chain build

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

* feat(backend): stash prompt prefix chain on ctx before distributed routing

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

* fix(backend): mirror modelID fallback for prefix-chain salt parity

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

* feat(nodes): scheduling config columns for prefix-cache routing

Add RoutePolicy and per-model balance/prefix-match override columns to
ModelSchedulingConfig and include them in the SetModelScheduling upsert
DoUpdates list so updates are not dropped on conflict.

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

* feat(nodes): optional route preference in FindAndLockNodeWithModel

Add a RoutePreference type and a new pref parameter so the atomic
pick+lock+increment can be biased toward a preferred node without
weakening atomicity. A nil preference reproduces the previous ORDER BY
behavior exactly. Update the ModelRouter interface, both router.go call
sites (pass nil for now; Phase 5 builds the real preference), the test
doubles, and the distributed e2e caller.

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

* feat(prefixcache): make Sync satisfy Provider with Evict

Sync.Observe now returns whether the local index treated the assignment as
new or extended, and Sync gains an Evict method that delegates to the wrapped
index. Together these let SmartRouter hold a single prefixcache.Provider that
broadcasts via NATS. Adds a compile-time Provider assertion and an
Evict-delegates behavioral test.

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

* feat(nodes): prefix-cache-aware preference and observe in SmartRouter.Route

Add a PrefixProvider + PrefixConfig to SmartRouterOptions/SmartRouter (nil
keeps routing byte-for-byte the round-robin floor). On each request Route now
calls buildPreference: it reads the prompt prefix chain from ctx
(distributedhdr.PrefixChain), resolves the per-model policy/thresholds over
the global config, loads candidate replica in-flight via a new registry read
LoadedReplicaStats (deduped to one entry per node using the MIN in-flight
across that node's replicas), asks the provider to Decide, and runs
prefixcache.Select. The chosen node is passed as the RoutePreference to
FindAndLockNodeWithModel on all three pick paths (cache hit, locked re-pick,
cold scheduleAndLoad), and the served node is recorded via Observe only when
the resolved policy is prefix_cache so round-robin models never pollute the
tree.

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

* feat(nodes): invalidate prefix-cache entries on unload and stale removal

UnloadModel and both staleness fall-through paths in Route (after a failed
gRPC probe and RemoveNodeModel) now call prefixProvider.Invalidate(model,
nodeID), guarded by a nil-provider check so the round-robin floor is
unchanged. At runtime the provider is the *prefixcache.Sync, so invalidations
also broadcast to peer frontends. Adds a test that a previously hot prefix no
longer Decides to a node after UnloadModel.

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

* feat(prefixcache): rolling forced-disturb pressure counter

Add a concurrency-safe per-model rolling counter that tracks how many
times a request had a usable hot prefix match but the load guard forced
it off the warm node. Entries outside the window are dropped lazily on
Count so the backing slice stays bounded.

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

* feat(nodes): autoscale on prefix-cache forced-disturb pressure

Wire the rolling forced-disturb counter into the SmartRouter and the
ReplicaReconciler.

Router: in buildPreference, after Decide + Select, record a forced-disturb
when a usable hot prefix match existed (d.HotNodeID != "" and
d.MatchRatio >= cfg.MinPrefixMatch) but Select chose a different node (or
nothing) because the load guard ruled the warm node out. This is the
scale-worthy signal: the cache-warm replica is saturated. It deliberately
does not fire for all-unique workloads (no hot match), avoiding
false-positive scale-ups. Pressure is optional on SmartRouterOptions; nil
keeps the path a no-op.

Reconciler: read the same Pressure instance in reconcileModel as an extra
scale-up reason, reusing the existing MaxReplicas + ClusterCapacityForModel
guards and the UnsatisfiableUntil cooldown that gates the whole method.
Pressure never overrides MaxReplicas and never force-evicts; a no-capacity
model does not spin. Window and threshold come from prefixcache.Config
(PressureWindow default 1m, PressureScaleThreshold default 1) and are
configurable via ReplicaReconcilerOptions.

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

* fix(prefixcache): bound Pressure slice in Record; drop dead reconciler pressureWindow

Record now prunes entries older than the rolling window (the same prune
Count does), via a shared pruneLocked helper, so a model that takes
forced-disturb records but is never Counted (e.g. one with zero loaded
replicas the reconciler skips) no longer grows its backing slice
unbounded.

Also removes the dead pressureWindow struct field and the
ReplicaReconcilerOptions.PressureWindow option from the reconciler: they
were stored but never read (the window lives inside the *prefixcache.Pressure
instance). The scale block now reads pressure.Count once into a local.

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

* feat(api): prefix-cache fields in scheduling endpoint DTO with validation

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

* feat(ui): prefix-cache routing controls in node scheduling form

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

* feat(distributed): wire prefix-cache index, NATS sync, and config

Activates prefix-cache-aware routing in distributed mode. Builds the
prefixcache Index + NATS-backed Sync + Pressure counter, installs the
distributedhdr.PrefixChainHook so core/backend/llm.go attaches a prefix
chain per request, subscribes to prefixcache.observe/prefixcache.invalidate
to apply peers' events to the local index (no re-broadcast), threads
PrefixProvider/PrefixConfig/Pressure into the SmartRouter and
Pressure/PressureThreshold into the ReplicaReconciler, and runs a
background eviction ticker (every TTL/2) bound to the app context.

Enabled by default; --distributed-prefix-cache=false (LOCALAI_DISTRIBUTED_PREFIX_CACHE)
opts out and leaves the provider/pressure nil so routing stays round-robin.
--distributed-prefix-cache-ttl (LOCALAI_DISTRIBUTED_PREFIX_CACHE_TTL, default 5m)
controls entry idle-timeout and eviction cadence.

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

* test(nodes): round-robin-floor invariant for prefix-cache routing

Drives Select directly: a saturated hot node (in_flight 50 vs 0) is never
picked even with a perfect prefix match (round-robin floor holds), while a
balanced hot node within the load slack is reused.

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

* chore(prefixcache): clear branch lint findings and em dashes

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

* feat(distributed): validate prefix-cache config at startup wiring

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

* perf(radixtree): single-walk WeightsFor for batch value weights

Add Tree.WeightsFor(values, now) which computes the recency-weighted
weight for many values in a single O(N + len(values)) tree traversal,
versus calling Weight once per value (O(len(values) * N)). Consumers
that score K candidates against the tree under the read lock no longer
pay K full walks.

Extract the per-entry contribution math into an unexported helper shared
by both Weight and WeightsFor so the metric stays identical (DRY).
Weight's public behavior is unchanged.

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

* refactor(config): add ModelConfig.ModelID() single source of truth

The c.Name fallback to c.Model was duplicated in core/backend/options.go
(feeding model.WithModelID) and hand-copied into core/backend/llm.go (the
prefix-chain salt). These MUST agree or the prefix-cache salt diverges
silently from the id the model loader tracks. Consolidate both into a new
config.ModelConfig.ModelID() helper and call it from both sites. Behavior
is identical.

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

* perf(prefixcache): reuse one xxhash.Digest in ExtractChain

ExtractChain allocated a fresh xxhash.New() Digest per block (up to MaxDepth
per call) and grew the chain slice without preallocation. Reuse a single
Digest via Reset() before each block and preallocate the chain to
min(nBlocks, MaxDepth).

xxhash seed 0 is stateless, so Reset()+Write produces the byte-identical
value to a fresh New()+Write. Output hashes are unchanged, preserving the
cross-process determinism that peers rely on over NATS. Verified by capturing
ExtractChain output for the existing test inputs before and after the
refactor: identical. Existing extractor tests pass unchanged.

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

* fix(prefixcache): drop hot match when matched node is not a candidate; weigh cold candidates in one walk

Index.Decide called radixtree.LongestMatch over the whole tree, so the
deepest match could be a node that is offline, unloaded, or simply not in
the passed candidate set. Honoring that as HotNodeID produced a false
forced-disturb signal upstream (buildPreference records pressure when
chosen != HotNodeID), making it look like a warm replica was load
saturated when it was actually absent.

Build the candidate set once and only set HotNodeID/MatchRatio when the
matched node is an actual candidate; otherwise fall back to cold
placement. A future refinement could ask the tree for the longest match
restricted to the candidate nodes (shallower-but-valid) instead of
dropping it.

Also replace the per-candidate tree.Weight call in the cold-order sort
with a single tree.WeightsFor walk, turning O(K*N) under the read lock
into O(N + K).

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

* refactor(prefixcache): remove Select's unreachable deterministic fallback

buildPreference always passes ColdOrder as a permutation of the full
candidate set, so the cold-order loop hits every eligible candidate. The
trailing best/bestIF scan was dead. Replace it with a plain "return """
and document that ColdOrder is guaranteed to cover all candidates, so ""
means none were eligible.

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

* refactor(nodes): fetch model scheduling config once per Route

GetModelScheduling was read three times per request - in
resolveSelectorCandidates, buildPreference, and nodeMatchesScheduling -
three DB round-trips for one row that is immutable for the life of the
request, and not a consistent snapshot. Fetch it once near the top of
Route and thread the *ModelSchedulingConfig (may be nil) into all three
helpers. scheduleNewModel keeps its own fetch since it runs outside the
Route snapshot. Behavior is identical for nil sched.

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

* fix(autoscale): add Pressure.Reset to consume forced-disturb signal

Pressure.Count is non-draining (it prunes only by age), so a single burst
of forced-disturbs stays within the rolling window for the whole window and
keeps Count >= threshold on every reconciler tick. The reconciler will use
Reset to clear a model's events after acting on the signal so a fresh
scale-up requires fresh forced-disturbs to accumulate, rather than one burst
driving the model toward MaxReplicas.

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

* fix(autoscale): at most one scale-up per reconcile tick, consume pressure

Two autoscale bugs:

1. Over-scaling: the pressure scale-up block read Pressure.Count but never
   consumed it. With a non-draining counter a single forced-disturb burst
   kept Count >= threshold across the whole window, firing scaleUp on every
   tick and pushing the model toward MaxReplicas off one transient burst.
   After a successful pressure-triggered scale-up the reconciler now calls
   Pressure.Reset to consume the signal.

2. Double scale-up in one tick: the all-replicas-busy block and the pressure
   block could both fire in the same reconcileModel pass, each calling
   scaleUp(+1) against the same `current` read once at the top, so a model
   that was both busy and over threshold scaled +2 and could overshoot
   MaxReplicas by one. A scaledUp flag now enforces at most one scaleUp(+1)
   per tick: the pressure block is skipped if the busy block already scaled,
   and scale-down is skipped in any tick that scaled up.

MinReplicas enforcement, UnsatisfiableUntil backoff, and capacity guards are
unchanged.

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

* feat(nodes): replica-removed chokepoint hook for prefix-cache invalidation

Add SetReplicaRemovedHook to NodeRegistry and fire it from both
RemoveNodeModel and RemoveAllNodeModelReplicas after a successful
delete. This is the single chokepoint every replica-removal path funnels
through (router eviction, reconciler scale-down, probe reaper,
health-monitor node-down reap, RemoteUnloaderAdapter), so the
prefix-cache index can be invalidated by construction rather than wiring
each call site individually.

The hook is stored in an atomic.Pointer so the startup wiring (setter)
and the request/reconcile-time fire are race-free; it is nil-safe when
unset. GORM Delete reports no error for a no-op delete, so the hook also
fires when nothing was removed; the consumer's Invalidate(model, node)
is idempotent so this is harmless.

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

* feat(distributed): invalidate prefix-cache on any replica removal via registry hook

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

* refactor(prefixcache): single source of truth for threshold bounds

Extract ValidateThresholds into prefixcache/config.go so the per-model
override validation (nodes.go endpoint) and Config.Validate share one
implementation of the numeric bounds (min_prefix_match in [0,1],
balance_abs_threshold >= 0, balance_rel_threshold == 0-or->= 1) instead
of hard-coding them in two places. The route_policy allow-list stays
explicit (not ParsePolicy, which maps typos to Default).

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

* fix(nodes): preserve prefix-cache settings on partial scheduling update

A scheduling POST that omitted route_policy/thresholds (e.g. a
min_replicas-only update) full-replaced every column and silently reset
the model's previously-configured prefix-cache settings to empty/zero.

Make the four prefix-cache request fields pointers so omitted is
distinguishable from explicit zero, and merge PATCH-style in
SetSchedulingEndpoint: a provided pointer wins, an omitted one preserves
the existing config value (zero default when none). Non-prefix fields
keep their full-replace PUT semantics. Validation now runs on the
resolved values via prefixcache.ValidateThresholds.

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

* fix(prefixcache): make Invalidate a no-op for uncached models and skip empty broadcasts

A registry chokepoint fires Sync.Invalidate(model, nodeID) for every replica
removal of every model, including round-robin models that never used the
prefix cache. Index.Invalidate previously called tree(model), which lazily
created and permanently retained an empty radix tree for any model that ever
lost a replica, growing the trees map without bound. Sync.Invalidate also
published a NATS PrefixCacheInvalidateEvent on every call, amplifying no-op
removals across the cluster.

Index.Invalidate now looks the tree up read-only via existingTree and returns
without allocating when none exists. The Provider interface is unchanged;
Sync gates the broadcast through an optional invalidateExisting(bool) capability
type-asserted from the wrapped Index, falling back to the prior always-broadcast
behavior for other Provider implementations.

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

* perf(prefixcache): derive Decide candidacy from WeightsFor and skip trivial sort

WeightsFor already returns a map keyed by every requested candidate, so the
separate candidates set built to validate the hot match was redundant: a node
is a candidate iff it is a key in the weights map. Drop the extra map and gate
the hot-match check on weights membership. Also skip the sort when there is at
most one candidate, since the input order is already the cold order. Behavior
is unchanged.

Deferred follow-up: skipping the WeightsFor walk entirely when a hot match wins
would need lazy cross-file changes and is out of scope here.

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

* fix(nodes): fire replica-removed hook on bulk node_models deletes; trim LoadedReplicaStats columns

Bulk node-scoped node_models deletes (Register re-register cleanup,
MarkOffline, MarkDraining, Deregister) removed rows directly without
firing the replica-removed hook, so the prefix-cache index kept
pointing at nodes whose models were gone. Capture the DISTINCT model
names before each bulk delete and fire fireReplicaRemoved once per
model after a successful delete, restoring the single-chokepoint
invariant for all removal paths. The pre-query is skipped when no hook
is set so the no-hook path stays cheap.

Also narrow LoadedReplicaStats to SELECT only node_id and in_flight
(the only fields the router consumer reads), dropping the JOIN-side
available_vram fetch and unused columns while keeping the
[]ReplicaCandidate return type unchanged.

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

* fix(reconciler): consume autoscale signals only on a real scale-up

scaleUp was fire-and-forget (void) yet its callers unconditionally
consumed the pressure signal (Pressure.Reset) and the MinReplicas
hysteresis (ClearUnsatisfiable) right after calling it. If scaleUp
added nothing (ScheduleAndLoadModel errored, or no node could be
loaded) the saturated warm replica got no new replica AND its
accumulated forced-disturb history was wiped, forcing the signal to
re-accumulate over a full PressureWindow before the next attempt.

Make scaleUp return whether at least one replica was actually
scheduled, and gate the side effects on it:

- pressure block (2b): set scaledUp and call Pressure.Reset only on
  success; on failure preserve the signal so the next tick retries off
  the same accumulated pressure.
- busy-burst block (2): set scaledUp from the return value so a failed
  attempt does not suppress the pressure path or scale-down.
- MinReplicas block: call ClearUnsatisfiable only on success so a
  failed attempt does not reset the unsatisfiable counter.

All existing invariants (MaxReplicas, capacity gating,
UnsatisfiableUntil cooldown, at-most-one-scale-up-per-tick) are
preserved.

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

* refactor(nodes): drop router's redundant prefix-cache Invalidate calls

The NodeRegistry removal chokepoint (RemoveNodeModel /
RemoveAllNodeModelReplicas) now fires SetReplicaRemovedHook, which
invalidates the prefix-cache index. The router was also calling
prefixProvider.Invalidate explicitly right after each registry removal
on the two stale-replica health-probe fall-throughs in Route and in
UnloadModel, so every router-side eviction invalidated twice (double
tree-prune + double NATS broadcast).

Remove the three redundant explicit Invalidate calls and their empty
nil-guards. Each removed call sat immediately after a registry removal
that fires the hook, so invalidation is preserved via the chokepoint.
Decide/Observe usage is untouched.

Re-point the unit test (fake registry fires no hook) to assert the
removal chokepoint is exercised on unload instead of the router's
direct invalidation.

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

* fix(prefixcache): broadcast invalidations unconditionally for cross-frontend coherence

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

* fix(prefixcache): reject TTL<=0 in Config.Validate (eviction ticker would panic)

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

* fix(nodes): make capture+delete atomic in bulk node_models removal paths

MarkOffline, MarkDraining, and the Register re-register cleanup ran the
nodeModelNames SELECT and the bulk node_models DELETE as two separate
statements on r.db with no transaction. A SetNodeModel landing between
the two was deleted but its replica-removed hook never fired, leaving
the prefix-cache index pointing at a removed replica until TTL or
candidacy self-heal.

Wrap the capture and the delete in a single db.Transaction in each path
(mirroring how Deregister already does it). The captured model names are
collected into a slice declared outside the closure; the
replica-removed hook fires for each only after the transaction commits,
so a rollback never invalidates the index for a removal that did not
persist. The set of fired hooks now equals exactly the set of
node_models rows actually deleted, with no interleaving gap.

The status flip in MarkOffline/MarkDraining (setStatus) is a separate,
pre-existing operation and routing already filters non-healthy nodes, so
it stays outside the transaction; return contracts are unchanged.
Deregister was already correct and is untouched. The cheap-path skip
(no hook -> skip the SELECT) is preserved.

Adds a spec asserting MarkOffline fires hooks for exactly the rows it
deletes and leaves no node_models row behind (consistent snapshot).

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

* chore(nodes): debug logging for prefix-cache routing decisions and observations

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

* fix(radixtree): match shared prefixes by valuing every node on insert

Insert recorded the value (node id) only on the final node of the key
chain, leaving every intermediate prefix node valueless. LongestMatch
returns the deepest node that hasValue, so two chains that share a
leading block but diverge in the tail never matched: only exact-repeat
queries hit. That broke the prefix-cache routing core use cases (shared
system prompt, multi-turn extension, volatile tail), all of which rely
on prefix matching rather than exact-repeat.

Set value/hasValue/lastSeen at every node along the chain so each
prefix-block node remembers the node id that served that prefix
(SGLang/vLLM-style). The deepest match wins, and the last writer owns a
shared prefix node (a recency heuristic: the most recent chain through a
block is the one most likely still warm). size now counts valued nodes,
which is the intended meaning.

Updated radixtree tests to the new semantics: deepest-prefix test uses
non-overlapping chains, a new test asserts last-writer-owns-shared-node,
Evict/Remove/MaxEntries expectations recomputed for per-prefix-node
counting, and a shared-prefix LongestMatch red test added. Added a
prefixcache Decide test proving a prefix-only query routes to the warm
node. No prefixcache .go logic changed.

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

* test(distributed): lock in prefix-cache routing behavior end to end

Add a DB-backed e2e spec that drives SmartRouter against a real
NodeRegistry (Postgres testcontainer) and the real prefixcache.Index
radix-tree provider, using a fake gRPC backend factory so no real
inference runs. Covers the five behaviors validated by hand:

1. Cold miss + observe: an unseen prefix chain cold-places and is recorded.
2. Hot-match affinity: the same chain returns to its warm node X.
3. Shared-prefix match: a divergent chain sharing X's leading prefix
   still routes to X (the radix-tree regression we fixed).
4. Negative control: an unrelated chain is a cold miss, not a false
   hot match on X.
5. Failover + invalidation: removing X's replica fires the registry
   chokepoint hook to invalidate the prefix entry, and the chain fails
   over to surviving node Y and re-homes there.

Replaces the need for manual docker-compose re-runs.

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

* refactor(prefixcache): make prefix-cache affinity replica-granular

Track prefix-cache affinity per loaded replica (a backend process with its
own KV cache) instead of per node, so multiple replicas of the same model on
one node each keep distinct affinity and a hot prefix routes back to the exact
replica that served it.

- radixtree: add RemoveFunc(pred) and reimplement Remove on top of it.
- prefixcache: introduce ReplicaKey{NodeID, Replica}; Index/Candidate/
  PrefixDecision/Select/Provider now key on ReplicaKey. Add InvalidateNode to
  drop every replica of a node; Invalidate drops one replica. Select returns
  (ReplicaKey, bool) and gains a deterministic least-in-flight eligible
  fallback (tiebreak NodeID then Replica).
- messaging: carry Replica on PrefixCacheObserveEvent and
  PrefixCacheInvalidateEvent (Replica < 0 means all replicas of the node).
- Sync delegates + broadcasts with replica; InvalidateNode broadcasts
  Replica=-1; ApplyInvalidate routes negative replica to InvalidateNode.

This is part 1 of 2; the registry/router/wiring consumers are updated
separately.

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

* feat(distributed): make prefix-cache routing replica-granular

Wire the SmartRouter, NodeRegistry, and distributed startup to the
replica-keyed prefixcache API. Affinity is now tracked per replica
(each replica is a separate process with its own KV cache), so a prefix
served by (node,0) no longer leaks onto the same-node sibling (node,1).

- RoutePreference gains PreferredReplica; FindAndLockNodeWithModel locks
  the EXACT (node_id, replica_index) row, falling through to the default
  ORDER BY when that replica is not loaded.
- SetReplicaRemovedHook now carries replicaIndex; RemoveNodeModel fires
  the specific replica, RemoveAllNodeModelReplicas and the four bulk
  node-scoped deletes fire replica<0 (all replicas of the node).
- buildPreference builds one Candidate per loaded replica and locks the
  exact replica the policy chose; observePrefix records the served
  ReplicaKey at every call site.
- distributed.go routes the hook to InvalidateNode (replica<0) or
  Invalidate(key).
- Tests updated to the replica-keyed API plus new coverage: a hot prefix
  on (node,0) prefers replica 0 over the same-node sibling (router unit +
  e2e), and FindAndLock locks the exact preferred replica.

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

* fix(distributed): derive prefix chain from messages for tokenizer-template models

Prefix-cache-aware routing built its prompt-prefix chain from the rendered
prompt string `s` in ModelInference. For models with
TemplateConfig.UseTokenizerTemplate the frontend never renders a prompt - the
backend tokenizes the structured messages itself - so `s` is empty, the chain
is empty, and routing silently falls back to round-robin. That covers the bulk
of modern chat models (qwen3, llama3, ...), so the feature effectively never
engaged for them.

Fall back to messagesPrefixSource(messages): a deterministic, prefix-stable
head-first serialization of the conversation (role + content per turn). Two
requests sharing a leading system prompt and early turns share a leading byte
prefix, which ExtractChain maps to a shared chain prefix - landing both on the
same cache-warm replica. The rendered `s` is still preferred when present
(higher fidelity for non-template models).

Found via the multi-replica-per-node e2e: zero "prefix-cache routing decision"
logs despite per-request Route calls, traced to the empty-chain guard.

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

* docs(distributed): document prefix-cache routing roadmap

Add a routing-and-caching roadmap section to the distributed-mode guide,
linking the epic (#10063) and the follow-up issues (#10064-#10070) surfaced
from a survey of SGLang, vLLM production-stack, Ray Serve, llm-d, AIBrix, and
NVIDIA Dynamo.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-30 23:24:22 +02:00
Richard Palethorpe
12d1f3a697 security(http): refuse redirects on outbound clients via hardened pkg/httpclient (#10087)
LocalAI's outbound HTTP clients used Go's default redirect policy, which
follows up to 10 redirects. On a cross-host redirect Go forwards custom
request headers — including credential headers such as Anthropic's
x-api-key — to the redirect target (Go strips Authorization, Cookie and
WWW-Authenticate cross-host, but NOT arbitrary custom headers). An
attacker able to elicit a redirect from an upstream (a hijacked or
spoofed upstream, DNS trickery, or a malicious upstream_url) then
harvests the operator's provider API key.

This was first reported against the cloud-proxy / MITM PII path
(GHSA-3mj3-57v2-4636); the same class affects every other outbound
client. Rather than patch each call site, add pkg/httpclient as the one
sanctioned constructor for outbound HTTP and route everything through it.

pkg/httpclient:
  - New(...)             refuses redirects, TLS 1.2 floor, no body
                         deadline (streaming/SSE safe)
  - NewWithTimeout(d)    simple request/response calls
  - WithFollowRedirects  opt-in following that still strips credential
                         headers on any cross-host hop; different
                         scheme/host/port == different origin, guarding
                         the curl CVE-2022-27774 port-confusion class
  - WithTransport(rt)    keep a custom transport (IP-pin, HTTP/2, a
                         credential-injecting RoundTripper)
  - HardenedTransport()  base transport with the TLS floor + bounded setup
  - Harden(c)            apply the policy to a library-supplied *http.Client
  - NoRedirect           the CheckRedirect policy; wraps ErrRedirectBlocked

Lint: a forbidigo rule flags http.DefaultClient and http.Get/Post/
PostForm/Head, pointing at pkg/httpclient (.golangci.yml,
.agents/coding-style.md). forbidigo cannot match the &http.Client{}
composite literal without also flagging legitimate *http.Client type
references, so that form is enforced by review.

Migrates every non-test outbound call site across core/, pkg/, cmd/, and
the Go backend (backend/go/cloud-proxy). Credential-bearing and
internal-RPC clients refuse redirects; download / CDN / registry clients
use WithFollowRedirects so they keep working while stripping secrets
cross-host. The only credential-bearing client that follows redirects is
the gated-download path (pkg/downloader/uri.go), which strips the token
on the cross-host hop to the CDN. Hardening this closes, in passing:
  - MCP remote-server bearer token leaking via a redirect (the
    RoundTripper re-injected Authorization on every hop)
  - agent multimedia/webhook clients leaking user-supplied auth headers
  - cors_proxy following redirects, bypassing its SSRF IP-pin
  - downloader's authorized read path leaking the token cross-host

Fixes: GHSA-3mj3-57v2-4636 (cloud-proxy leaks operator provider API key
(x-api-key) to attacker host on cross-host redirect)
Reported-by: tonghuaroot
Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-30 12:04:10 +02:00
泊舟
e1a782b70f fix(openai): stop streaming tool-call double-emission when autoparser is active (#10055)
Streaming /v1/chat/completions could emit the same logical tool call at
multiple `index` values. In processStreamWithTools the Go-side iterative
parser (ParseXMLIterative / ParseJSONIterative) runs on every token and
emits tool-call deltas, while the C++ chat-template autoparser delivers
its own tool calls via ChatDeltas that are flushed at end-of-stream by
ToolCallsFromChatDeltas -> buildDeferredToolCallChunks. With both paths
active the same call is emitted twice at different indices, so OpenAI
clients that accumulate tool calls by `index` dispatch the tool N times.

Skip the Go-side iterative parser once the autoparser is producing tool
calls (hasChatDeltaToolCalls). The deferred flush stays guarded by
lastEmittedCount, so the race where the Go parser emitted before the flag
flipped also remains single-emission. Backends without an autoparser
(e.g. vLLM) keep hasChatDeltaToolCalls=false and are unaffected.

Refs #9722

Signed-off-by: bozhouDev <259759010+bozhouDev@users.noreply.github.com>
Co-authored-by: bozhouDev <259759010+bozhouDev@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-29 11:39:09 +02:00
Tai An
0fd666ee6e fix(openresponses): populate Content and accept bare {role,content} items (#10039) (#10040)
* fix(openresponses): populate Content and accept bare {role,content} items (#10039)

Fixes mudler/LocalAI#10039 — `/v1/responses` silently returned empty
output on any model whose YAML doesn't include a Go-side
`template.chat_message` block.

Three cooperating bugs:

* `convertORInputToMessages` populated only `StringContent` for string
  input and for the `input.Instructions` system message, leaving the
  `Content` (any) field nil.
* `TemplateMessages` gated all fallback content-rendering branches on
  `Content != nil && StringContent != ""` — but every branch in that
  function consumes `StringContent`, not `Content`. The `&&` silently
  dropped messages that had StringContent set and Content nil, producing
  an empty prompt that the 5× empty-retry guard then turned into a
  200 OK with `output: []`.
* The array-input branch of `convertORInputToMessages` dispatched on
  `itemMap["type"]` with no default, dropping bare `{role, content}`
  items emitted by the OpenAI Python SDK helper
  `client.responses.create(input=[{...}])`.

Fix:

* Set both `Content` and `StringContent` in the two openresponses
  message-construction sites that only set one.
* Treat a bare `{role, content}` item (no `type`) as
  `type: "message"` for OpenAI-SDK compatibility.
* Gate `TemplateMessages` fallback rendering on `StringContent != ""`,
  which is what every downstream branch in that function actually
  reads.

Regression test added to `evaluator_test.go` covering the fallback
path (no `ChatMessage` template) with a StringContent-only message,
both with and without a role mapping.

* test(openresponses): guard Content population and ToProto path (#10039)

Add regression tests for the two seams the original fix touched but
left uncovered:

* convertORInputToMessages must populate both Content and StringContent
  for plain string input and for bare {role, content} array items (the
  OpenAI SDK shape that omits the type discriminator). Both are
  functional reds against the pre-fix code.
* Messages.ToProto reads Content, not StringContent — this is the path
  UseTokenizerTemplate backends (imported GGUFs) take. The cases pin
  that contract so a future regression on the producer side is caught.

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>
2026-05-28 07:21:48 +00:00
Richard Palethorpe
8d70855ea6 test: add Go + React UI coverage gates and fill test gaps (#9989)
- Strict monotonic Go coverage gate (make test-coverage-check, 45% baseline)
  run in CI; fixes ginkgo dropping all-but-one coverprofile across multiple
  recursive roots, builds with -tags auth, and folds in the in-process
  tests/e2e suite via --coverpkg.
- React UI e2e coverage (make test-ui-coverage: vite-plugin-istanbul + nyc,
  nix-provided Chromium) plus e2e specs for 6 previously-untested pages, and a
  UI coverage gate (make test-ui-coverage-check) with a small tolerance since
  e2e line coverage jitters ~0.5pp run-to-run.
- pre-commit hook: lint + coverage on Go changes, Playwright e2e + UI coverage
  gate on react-ui changes; install with make install-hooks.
- New Go handler tests (settings, branding), hermetic base64 download test.
- fix(ui): model editor reads vram_display (snake_case), so the VRAM estimate
  renders again; covered by a regression test.

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

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-26 22:06:10 +02:00
LocalAI [bot]
e4c70fca7a fix(streaming/tools): don't leak prefill-misclassified content as trailing reasoning chunk (#10000)
When the C++ autoparser is in pure-content fallback mode (qwen3-4b after
model emits a tool-call JSON in non-thinking mode, the streaming worker
ended the SSE stream with a spurious

    data: {...,"delta":{"reasoning":"{\"name\":\"exec\",\"arguments\":...}"}}

chunk carrying the same JSON that was already in delta.tool_calls.

The Go-side ReasoningExtractor is configured from
DetectThinkingStartToken, which scans the model's jinja chat template
verbatim and finds <think> inside an {% if enable_thinking %} block
without evaluating the conditional. Every output chunk then runs through
PrependThinkingTokenIfNeeded, which synthesizes a <think> in front and
makes ExtractReasoning treat everything after as reasoning. The autoparser
correctly classifies zero reasoning (qwen3's tool format isn't on
llama.cpp's recognized-tool list, so all tokens land in
ChatDelta.Content), but processStreamWithTools then preferred
extractor.Reasoning() over functions.ReasoningFromChatDeltas at the
end-of-stream flush — handing the polluted Go-side state to
buildDeferredToolCallChunks, which emitted it as a trailing reasoning
chunk.

Two changes:

* Add a sticky preferAutoparser flag to processStreamWithTools, mirroring
  the analogous flag in processStream from #9985. Once any ChatDelta
  carries content or reasoning, the flag stays on for the rest of the
  stream and the worker stops falling back to the Go-side extractor for
  per-token deltas. This avoids the per-chunk leak path and the cumulative
  pollution.

* Extract chooseDeferredReasoning, a small helper that selects the
  end-of-stream reasoning source. When preferAutoparser is set, return
  functions.ReasoningFromChatDeltas(chatDeltas); otherwise fall back to
  extractor.Reasoning() (the correct source for vLLM and other backends
  with no autoparser).

The helper has a focused test suite covering both sides of the contract:
autoparser-active with empty reasoning (the qwen3 case — the fix's
purpose), autoparser-active with real reasoning_content
(jinja-with-recognized-format models), and autoparser-not-active with
genuine Go-side reasoning (vLLM-style backends).

E2E with combined #9988 and this fix on qwen3-4b post-#9985 gallery
shape: 18 content chunks of the tool-call JSON, 1 tool_call chunk with
name='exec' and the right arguments, finish_reason=tool_calls, and zero
reasoning chunks — down from one polluted reasoning chunk before this
fix.

Depends on #9999 (the streaming JSON tool-call gating bug for qwen3) to
make the trailing chunk observable end-to-end; the helper unit tests are
independent.

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

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-26 08:34:26 +02:00
LocalAI [bot]
f17d99f6e5 fix(streaming/tools): stop healing-marker stubs from gating off content (#9999)
* fix(streaming/tools): stop healing-marker stubs from gating off content

When the C++ autoparser is in pure-content fallback mode (e.g. qwen3
without --jinja) and the model emits a tool call as JSON, the streaming
worker calls ParseJSONIterative on each new chunk. parseJSONWithStack
heals partial input like `{` into `{"<marker>":1}` where <marker> is a
random integer. removeHealingMarkerFromJSON only stripped the marker
from values, so the synthetic key survived and downstream callers saw
a stub object with a random-looking key.

chat_stream_workers.go's JSON tool-call detector then bumped
lastEmittedCount past the stub even though no real tool call was
emitted, gating off ALL subsequent content chunks. The qwen3 + tools +
streaming case ended up dribbling only the first `{"` to clients and
then nothing, even when the model went on to call the noAction
`answer({"message": "…"})` pseudo-tool.

Three changes, each with its own regression test:

* removeHealingMarkerFromJSON now strips the marker suffix from keys
  too, dropping the entry when the truncated key is empty. Inputs like
  `{` no longer leak `{"<marker>":1}` to callers; partial keys like
  `{ "code` still preserve the model-typed prefix `code`.

* ParseJSONIterative skips empty-after-healing maps so a healed `{`
  doesn't surface as a stub result.

* The streaming JSON detector now breaks (not continues) on entries
  without a usable `name`, and only bumps lastEmittedCount past
  successfully-emitted entries. Defense-in-depth against any future
  partial-parse shape.

The parser tests cover eight partial-JSON-prefix shapes and verify no
marker characters leak into keys, plus the two early shapes (`{`,
`{"`) that should not surface a stub at all.

Fixes #9988

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

* test(streaming/tools): cover the autoparser-correctly-working path

Extract the JSON tool-call streaming emit loop into emitJSONToolCallDeltas
and unit-test it against every shape that can hit the streaming worker:

* the bug case — a healing-marker stub at index 0 must NOT bump
  lastEmittedCount, so subsequent content chunks keep flowing;
* the autoparser-correctly-working case — empty jsonResults (because
  the C++ autoparser cleared the raw text and delivers tool calls via
  TokenUsage.ChatDeltas) is a no-op, leaving the deferred end-of-stream
  emitter to ship the autoparser's tool calls;
* a single complete tool call — emit one chunk, advance to 1;
* arguments arriving as a JSON-string vs as a nested object — both
  serialize to the wire as JSON-string arguments;
* multiple parallel tool calls — one chunk each;
* a real tool call followed by a partial stub — emit the real one,
  stop at the stub, resume on a later chunk once the stub completes.

Locks down the no-regression guarantee the user asked for: this PR's
fix is scoped to the pure-content fallback path; when the autoparser
actually classifies tool calls (jinja-recognized chat format with tool
support), the helper is a no-op and nothing changes.

Assisted-by: Claude:opus-4-7 [Read] [Edit] [Bash] [Write]
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>
2026-05-25 23:55:35 +02:00
LocalAI [bot]
1c6c3adad6 fix(reasoning): stop <think> leaking into content when autoparser is in pure-content mode (#9991)
When LocalAI templates a thinking model outside of jinja (the default for
the qwen3 gallery family), llama.cpp's chat parser falls back to a
"pure content" PEG parser that dumps the entire raw response into
ChatDelta.Content with an empty ReasoningContent. The Go side then
trusted that content verbatim and overrode tokenCallback's
correctly-split reasoning, so <think>...</think> blocks ended up in the
OpenAI `content` field. Regression from v4.0.0 introduced when the
autoparser ChatDeltas path was added (#9224).

The override now runs Go-side reasoning extraction defensively when the
autoparser delivered content but no reasoning. The streaming worker
gains a sticky preferAutoparser flag that flips on the first chunk
where the autoparser classified reasoning_content; until then we use
the streaming Go-side extractor. Realtime mirrors the non-streaming
fallback. When the autoparser already populated ReasoningContent we
trust it untouched, so jinja-enabled installs are not regressed.

gallery/qwen3.yaml now enables use_jinja, letting the autoparser
classify <think> natively for all 20+ qwen3 family entries that share
this template.

Fixes #9985

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

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-25 22:39:50 +02:00
LocalAI [bot]
06e777b75e feat(distributed): gated X-LocalAI-Node response header (middleware + wrapper) (#9976)
* feat(distributed): add per-request node ID context holder

Introduce pkg/distributedhdr, a leaf package carrying a per-request
*atomic.Value holder for the picked worker node ID from the
SmartRouter (core/services/nodes) up to the HTTP response writer
wrapper (core/http/middleware). Avoids the import cycle that a shared
key in either consumer would create.

Exposes NewHolder, WithHolder, Holder, Stamp, Load, Inherit. The
holder is atomic.Value so cross-goroutine publish from the router to
the response writer wrapper is race-clean.

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

* feat(distributed): add ExposeNodeHeader middleware + response writer wrapper

New ApplicationConfig.ExposeNodeHeader bool + --expose-node-header CLI
flag / LOCALAI_EXPOSE_NODE_HEADER env var (default off; the node ID
reveals internal topology and is opt-in).

The middleware creates a per-request *atomic.Value holder, attaches it
to c.Request().Context() via distributedhdr.WithHolder, and wraps
c.Response().Writer with a custom http.ResponseWriter that sets the
X-LocalAI-Node header on first Write / WriteHeader / Flush by reading
the holder. Implements http.Flusher, http.Hijacker, Unwrap so it
composes cleanly with Echo and http.NewResponseController.

request.go propagates the holder onto derived contexts via
distributedhdr.Inherit so the holder survives the correlation-ID
context replacement.

Unit + race-clean concurrency + integration specs.

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

* feat(distributed): stamp node ID in router and wire middleware to inference routes

ModelRouterAdapter.Route stamps the picked node ID into the
per-request holder via distributedhdr.Stamp(ctx, result.Node.ID) right
after replica selection.

Wire ExposeNodeHeader middleware to:
- OpenAI chat/completion/embeddings + audio transcriptions/speech + image generations/inpainting
- Anthropic /v1/messages
- Ollama /api/chat, /api/generate, /api/embed, /api/embeddings
- Jina /v1/rerank
- LocalAI /v1/vad

The middleware's wrapper reads the holder on first byte and sets the
X-LocalAI-Node response header before delegating to the underlying
writer. Per-request scope means no race under concurrent multi-replica
routing.

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

* fix(distributed): thread request context through backend Load + cover ctx propagation

Five non-OpenAI backend helpers were silently using app.Context instead
of the request context for the gRPC backend call: transcription, TTS,
image generation, rerank, VAD. Effect: distributedhdr.Stamp in the
router callback was a silent no-op for these paths, AND client
cancellation didn't propagate to in-flight inference.

Thread c.Request().Context() (or the equivalent input.Context after
the request middleware has installed the correlation-ID derived
context) through each helper and into ModelOptions via
model.WithContext(ctx). ImageGeneration's signature gains a leading
ctx parameter; in-tree callers (openai image, openai inpainting,
openai inpainting_test) are updated to match.

ModelEmbedding gains a leading ctx parameter for the same reason; the
openai and ollama embedding handlers pass the request context through.

chat_stream_workers.go defers the initial role=assistant chunk
emission until the first token callback so the wrapper's lazy
X-LocalAI-Node lookup against the loader runs AFTER ml.Load has
stamped the per-modelID node ID; semantically identical for clients
(role still arrives before any text).

Regression test core/backend/ctx_propagation_test.go pins ctx
propagation for all five helpers.

Docs updated to enumerate the full endpoint coverage of the
--expose-node-header flag.

Assisted-by: Claude:claude-opus-4-7[1m]
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>
2026-05-25 10:51:48 +02:00
Richard Palethorpe
6a80e23733 feat(middleware): Model routing, PII filtering, Cloud model proxies (#9802)
Add a routing middleware stack and a cloud-proxy backend.

* cloud-proxy: a Go gRPC backend that forwards OpenAI- and
  Anthropic-shaped chat requests to upstream providers, with an
  optional translate mode (OpenAI request -> Anthropic /v1/messages
  -> OpenAI response) and full tool-calling support.

* routing: admission control, content-aware model routing
  (embedding cache + classifier + rerank + Arch-Router score),
  PII detection/redaction (regex + NER) with streaming filter and
  OpenAI/Anthropic adapters, and a per-user/per-key billing recorder
  backed by GORM or in-memory storage.

* middleware: UsageMiddleware records usage via the billing recorder,
  plus admission, route-model, usage-stamp and trace middlewares.

* observability: BackendTrace ring buffer stores full request bodies
  (capped), MITM proxy emits structured trace events, and router
  classifier decisions surface at /api/router/decide.

* gallery: Arch-Router-1.5B (Q4_K_M and Q8_0).

* UI: cloud-proxy model-editor fields, classifier system-prompt and
  score-normalization config, and a Traces page rendering request
  bodies.

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

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-25 09:28:27 +02:00
LocalAI [bot]
0b2ae3c6ca fix(openai): stream usage non-zero when tools are enabled (#9941)
* chore: ignore local .worktrees directory

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

* fix(openai): stream usage non-zero when tools are enabled

The streaming chat-completions worker for tool-bearing requests
(processTools in core/http/endpoints/openai/chat.go) never forwarded the
cumulative TokenUsage from ComputeChoices to the chunks it placed on the
responses channel. The outer streaming loop's running usage tracker
therefore stayed at the zero value, and the include_usage trailer
reported {prompt_tokens:0, completion_tokens:0, total_tokens:0} whenever
the request carried a `tools` array. Without tools, the alternative
`process` path stamps Usage on every chunk, so that path was unaffected.

Forward the final TokenUsage via a usage-only sentinel chunk (empty
Choices, populated Usage) emitted right before close(responses). The
outer loop's per-chunk Usage capture moves above the empty-Choices skip
so the sentinel updates the tracker without ever reaching the wire,
keeping the existing OpenAI spec contract (intermediate chunks carry no
`usage` field, and the deferred-final-chunk helpers remain Usage-free
per the regression test for issue #8546).

Adds streamUsageFromTokenUsage, usageSentinelChunk, and
applyChunkToUsage helpers with focused Ginkgo coverage plus a flow-level
test that mirrors the outer-loop sequence.

Fixes #9927

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

* refactor(openai): return final TokenUsage from stream workers

Replace the usage-only sentinel SSE chunk introduced in the previous
commit with a plain return value. The streaming workers process and
processTools (now extracted as package-level processStream and
processStreamWithTools) return (backend.TokenUsage, error); the outer
ChatEndpoint loop reads the cumulative counts off the existing `ended`
channel (now carrying streamWorkerResult{usage, err}) and builds the
include_usage trailer from a normal Go value after the LOOP exits.

This drops the empty-Choices "skip but capture Usage" rule from the
outer loop and removes the usageSentinelChunk / applyChunkToUsage
helpers entirely. The SSE responses channel is back to a single
purpose: wire chunks only.

processStream and processStreamWithTools move into chat_stream_workers.go
so they can be exercised directly from tests. The chat_stream_usage_test.go
suite now drives the workers with a mocked backend.ModelInferenceFunc
and asserts on the returned TokenUsage. The regression coverage for
issue #9927 is therefore behavioral: reverting the fix (discarding
ComputeChoices' usage return) makes the assertions fail with concrete
count mismatches.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-22 10:13:41 +02:00
LocalAI [bot]
a39e025d64 fix(nodes): make per-node backend install async via gallery job queue (#9928)
* feat(galleryop): add TargetNodeID to ManagementOp for single-node installs

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

* feat(galleryop): add NodeScopedKey helpers for per-node opcache rows

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

* refactor(galleryop): use strings.Cut for NodeScopedKey parsing, reject empty nodeID

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

* feat(nodes): scope DistributedBackendManager.InstallBackend to single node via TargetNodeID

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

* feat(http): make /api/nodes/:id/backends/install async via gallery service job queue

The handler previously called unloader.InstallBackend synchronously and
blocked the browser for up to 3 minutes waiting on the NATS reply. It now
enqueues a TargetNodeID-scoped ManagementOp on BackendGalleryChannel and
returns HTTP 202 + jobID immediately, matching /api/backends/install/:id.

The opcache key is built via NodeScopedKey(nodeID, backend) so concurrent
installs of the same backend across different nodes do not stomp each
other. galleryService/opcache/appConfig are threaded through
RegisterNodeAdminRoutes for this.

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

* refactor(http): log malformed backend_galleries override and stop test drain goroutine

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

* feat(api): expose nodeID for node-scoped backend ops in /api/operations

Node-scoped backend installs land in opcache under "node:<nodeID>:<backend>"
keys. Without splitting that prefix back out, the operations panel renders
the full key as the display name and has no structured way to label which
worker an install is targeting. Detect the prefix, surface nodeID as its own
response field, and reduce the display name back to the bare backend slug.
Bare (non-scoped) ops are left untouched so legacy installs do not gain a
misleading empty nodeID.

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

* feat(react-ui): poll job status for node-targeted backend installs

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

* fix(react-ui): make NodeInstallPicker state updates pure and surface cancellations as errors

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

* refactor(react-ui): clarify async semantics in handleInstallOnTarget

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

* refactor(http): use statusUrl casing for node install response to match codebase precedent

Assisted-by: Claude:opus-4-7 [Edit] [Bash]
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>
2026-05-21 22:25:53 +02:00
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
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
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]
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
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
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
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
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
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
Ettore Di Giacinto
b1a99436c7 feat(branding): admin-configurable instance name, tagline, and assets (#9635)
Adds a whitelabeling feature so an operator can replace the LocalAI
instance name, tagline, square logo, horizontal logo, and favicon from
the admin Settings page. Defaults fall back to the bundled assets so
existing installs are unaffected.

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

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

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

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

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

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

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


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

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-02 15:51:36 +02:00
Ettore Di Giacinto
bcef72b9c1 feat: localai assistant chat modality (#9602)
* fix(tests): inline model_test fixtures after tests/models_fixtures removal

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

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

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

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

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

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

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

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

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

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

Same Go package powers two modes:

  pkg/mcp/localaitools/

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

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

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

Wiring:

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

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

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

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

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

UI:

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

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

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

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

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

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

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

This pulls them into typed constants:

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

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

No behaviour change. All tests pass with -race.

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

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

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

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

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

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

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

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

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

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

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

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

Two related leaks:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Three small cleanups landing together:

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

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

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

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

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

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

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

Convert every test file in the assistant scope to Ginkgo:

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

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

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

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

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

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

* test+docs(assistant): drift detector for Tool ↔ REST route mapping

Honest gap from the audit: the parity_test.go suite only checks four
methods, and uses the same httpapi.Client for both sides — it asserts
stability of the DTO shapes, not equivalence between in-process and
HTTP. If a contributor adds an admin REST endpoint without an MCP tool,
or a tool without a matching httpapi route, both surfaces silently
diverge.

Add a coverage test plus stronger docs:

- pkg/mcp/localaitools/coverage_test.go introduces a hand-maintained
  toolToHTTPRoute map: every Tool* constant must list the REST endpoint
  the httpapi.Client hits (or "(none)" with a documented reason). Two
  Ginkgo specs assert the map and the published catalog stay in sync —
  one fails when a Tool is added without a route entry, the other fails
  when a route entry references a tool that no longer exists. Verified
  by removing the ToolDeleteModel entry locally; the test fired with a
  clear message pointing the contributor at the file.

  Deliberate non-test: we don't enumerate live admin REST routes from
  here. Walking the route registry requires booting Application;
  parsing core/http/routes/localai.go is brittle. The "new admin REST
  endpoint → MCP tool" direction stays a PR checklist item — see below.

- AGENTS.md gets a new Quick Reference bullet that calls out the rule
  and points at the test by name.

- .agents/api-endpoints-and-auth.md tightens the existing "Companion:
  MCP admin tool surface" subsection from "if useful, consider..." to
  "MUST be considered, with three concrete outcomes (tool added,
  deliberately skipped with documented reason, or forgot — which
  breaks the contract)". Adds a checklist item at the bottom of the
  file's authoritative checklist.

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

* refactor(assistant): drop duplicate DTOs, surface canonical types

Audit feedback: localaitools/dto.go reinvented several types that already
existed in the codebase. Replace the duplicates with the canonical types
so the LLM-visible wire format stays aligned with the rest of LocalAI by
construction (no parallel structs to keep in sync).

Removed (and the canonical type now used by the LocalAIClient interface):

  localaitools.Gallery          → config.Gallery
  localaitools.GalleryModelHit  → gallery.Metadata
  localaitools.VRAMEstimate     → vram.EstimateResult

Tightened scope:

  localaitools.Backend          → kept, but reduced to {Name, Installed}.
                                  ListKnownBackends now returns
                                  []schema.KnownBackend (the canonical
                                  type already used by REST /backends/known).

Kept with documented rationale:

  localaitools.JobStatus       — galleryop.OpStatus has Error error which
                                 marshals to "{}". JobStatus is the
                                 JSON-friendly mirror.
  localaitools.Node            — nodes.BackendNode carries gorm internals
                                 + token hash; we expose only the
                                 LLM-relevant fields.
  ImportModelURIRequest/Response — schema.ImportModelRequest and
                                   GalleryResponse are wire-shaped, mine
                                   are LLM-shaped (BackendPreference flat,
                                   AmbiguousBackend exposed).

Side wins:

  - Drop bytesPerMiB; vram.EstimateResult already carries human-readable
    display strings (size_display, vram_display) the LLM uses directly.
  - Drop the handler-private vramEstimateRequest in
    core/http/endpoints/localai/vram.go and bind directly into
    modeladmin.VRAMRequest (now JSON-tagged).

Both clients pass through these types now where possible (e.g.
ListGalleries in inproc.Client is a one-liner returning
AppConfig.Galleries; httpapi.Client.GallerySearch decodes straight into
[]gallery.Metadata).

All tests green with -race.

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

* refactor(assistant): extract REST route paths into named constants

httpapi.Client had 18 bare-string path sites scattered across methods.
Pull them into pkg/mcp/localaitools/httpapi/routes.go: static paths as
package-private constants, dynamic paths as small builders that handle
url.PathEscape on segment values.

No behaviour change. Drops the now-unused net/url import from client.go
since path escaping moved into routes.go alongside the path it applies to.

Local-only by design: the server-side registrations in
core/http/routes/localai.go remain bare strings. Sharing constants across
the pkg/ ↔ core/ boundary would invert the layering today; the existing
Tool↔REST drift-detector in coverage_test.go is the safety net for that
direction.

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

* docs(assistant): align with shipped UI and dropped bootstrap env vars

The LocalAI Assistant doc still described the older iteration:

- The in-chat toggle was renamed from "Admin" to "Manage" (the badge is
  now "Manage mode" and the home page exposes a "Manage by chat" CTA).
- LOCALAI_ASSISTANT_BOOTSTRAP_MODEL / --localai-assistant-bootstrap-model
  and the bootstrap_default_model tool were removed — admins pick a model
  from the existing selector instead, no env-var configuration required.
- The shipped tool catalog includes import_model_uri but didn't appear in
  the doc; bootstrap_default_model appeared but no longer exists.
- The Settings → LocalAI Assistant runtime toggle wasn't mentioned as the
  preferred way to disable without restart.

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

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-28 19:29:27 +02:00
Ettore Di Giacinto
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
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
2da1a4d230 feat(distributed): per-node backend installation from the gallery
In distributed mode the Backends gallery used to fan every install out to
every worker — fine for auto-resolving (meta) backends like llama-cpp where
each node picks its own variant, but wrong for hardware-specific builds
like cpu-llama-cpp that would silently land on every GPU node.

Adds a node-targeted install path through the existing
POST /api/nodes/:id/backends/install plumbing, with two entry points:

- Backends gallery row gets a split-button in distributed mode. Auto-
  resolving keeps "Install on all nodes" as the primary; chevron menu
  opens the picker. Hardware-specific routes the primary directly to the
  picker — no fan-out path on the row.
- Nodes-page drawer gets a "+ Add backend" button that navigates to
  /app/backends?target=<node-id>; the gallery scopes itself to that node
  (banner, single per-row install button, Reinstall/Remove for already-
  installed). One gallery, two scopes — no second UI to maintain.

The picker (new NodeInstallPicker) shows a 3-state suitability column
(Compatible / Override / Installed), an auto-expanding variant override
disclosure that fires when selected nodes have no working GPU, parallel
per-node installs with inline status and Retry-failed-nodes, and a
mismatch confirm that names the consequence on the button itself.

A 409 fan-out guard on /api/backends/apply protects CLI/Terraform/script
users from the same footgun: hardware-specific installs in distributed
mode now return code "concrete_backend_requires_target" with a human-
readable error and a meta_alternative pointer.

The gallery list payload now surfaces capabilities, metaBackendFor and
per-row nodes (NodeBackendRef) so the picker and the new Nodes column
have everything they need without re-walking the gallery client-side.

GODEBUG=netdns=go is set on the compose services because the cgo DNS
resolver follows the container's nsswitch.conf to host systemd-resolved
(127.0.0.53), unreachable from inside the container; the pure-Go
resolver reads /etc/resolv.conf directly and uses Docker's embedded DNS.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-7[1m] [Edit] [Bash] [Read] [Write]
2026-04-26 22:05:18 +00:00
Richard Palethorpe
3db60b57e6 fix(realtime): consume ChatDeltas when C++ autoparser clears Response (#9538)
The llama.cpp C++-side chat autoparser clears Reply.Message and delivers
parsed content/reasoning/tool-calls via Reply.chat_deltas. chat.go handles
this (non-SSE path uses ToolCallsFromChatDeltas/ContentFromChatDeltas/
ReasoningFromChatDeltas), but realtime.go only read pred.Response, so any
model routed through the autoparser (Qwen2.5/3 and friends) produced a
silent reply: backend emitted N tokens, the session surface saw zero.

Mirror the non-SSE chat path in realtime's triggerResponse: when deltas
carry tool calls or content, use them directly; otherwise fall back to
the existing raw-text parsing.

Assisted-by: claude-opus-4-7-1M [Claude Code]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-04-24 14:41:38 +02:00