Add the kev 0.8B decision model, converted for vllm.cpp and pinned to
revision c17e7366 of mudler/kev-0.8b-vllm-cpp. It is a redistribution of
jaredpalmer/kev-0.8b with the LoRA merged and the PointerHead stored as
head.safetensors, so only the vllm-cpp backend can load it.
The artifact sits under overrides, where the installer reads it. The
entry sets a 2048-token context and an explicit KV pool: with the
default 4096-token context the CPU KV pool holds only 4064 tokens and the
load fails.
List the entry in the decisions gallery table and drop kev from the
list of decision models that are not gallery entries yet.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-sonnet-5-5
* chore(vllm-cpp): bump vllm.cpp to 967883486 (ABI v30)
Moves the pin from c3bebc357 to 967883486. On top of the Nimble decision
adapter and the Qwen3.5 vision-loader fix, this brings Tev1 on
/v1/systemone and vllm_decide (opt-in through a "Tev1Model" architecture
in config.json), a tokenizer/ subdirectory fallback so the Laya HF
snapshot loads as downloaded, a stop-token fix, a logprobs fix under async
scheduling and a pinned parakeet.cpp fetch for the diarization build.
ABI v30 only adds the diarization and speaker-attributed ASR entry
points; no existing struct or signature changed, so the purego mirrors
keep their layout and only abiVersion moves to 30. Between 4479dc99f and
967883486 vllm.h changed only in a comment.
v30 turns VLLM_CPP_WITH_DIARIZATION on by default. The fetch is pinned
now, but ON still downloads parakeet.cpp at configure time and links a
second ggml into libvllm for calls this backend never makes, so build
with the option off: the symbols stay present as refusing stubs.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-sonnet-5-5
* feat(vllm-cpp): add the hf_overrides engine arg
vLLM parity: engine_args.hf_overrides is a JSON object of top-level
config.json keys merged over the model directory's own config.json. The
main use is opting a published checkpoint into an engine adapter its
config does not name, such as {"architectures": ["Tev1Model"]} on the
Tev1 snapshots, which declare Qwen3_5ForConditionalGeneration.
The C ABI has no override input and the engine reads config.json from
the directory it is given, so Load builds a private overlay directory:
the merged config.json plus a symlink to every other entry of the model
directory, and passes that to the engine. The download is never written.
Free, a failed load and the next Load remove the overlay.
validModelPath and the DFlash draft resolution still see the real
directory.
A value that is not a JSON object, a .gguf model or a directory without
config.json fails the load instead of being skipped like an unknown
engine_args key, because loading the unmodified config would serve a
different architecture than the one configured.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-sonnet-5-5
* fix(gallery): nest vllm-cpp artifacts under overrides
artifacts: is a model-config key, and the installer reads model-config
keys only from overrides:. Five vllm-cpp entries (laya, gliner25-decide,
qwen3-vl-4b, cua-s1-forms and gliner2.5) declared it at the entry top
level, where it is silently dropped: the install reports success, writes
a config whose model is the bare HF repo id and downloads nothing, and
vllm-cpp (which does not infer artifacts) then fails the first load with
"model path not found".
Move each block under overrides:, and add a guard test that refuses a
top-level artifacts: key in the index.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-sonnet-5-5
* feat(gallery): add Tev1 4B and 0.8B on vllm-cpp
Two decisions entries for Together AI's Tev1 checkpoints, pinned to the
current HF revisions. Tev1 is autoregressive: vllm.cpp answers
/v1/systemone by scoring the option letters, and the same engine still
serves chat completions. The published config.json names
Qwen3_5ForConditionalGeneration, so each entry sets
hf_overrides: {architectures: [Tev1Model]} to enable the decision route
without editing the download. known_usecases is [decisions] only, since
a declared decisions list is authoritative for reservation.
The descriptions state what was checked: agreement with transformers on
CPU over seven questions (4B 7/7, max probability difference 0.0004;
0.8B 6/7 with one near tie), CPU-only for the decision route, and a
fine-tune license the model card says is still being finalized, so no
license key is set.
The Decisions API page lists both entries, drops the note that Tev1
does not serve /v1/systemone and documents the 24-option limit (Ollama
allows 26).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-sonnet-5-5
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
The usecase describes what a model can do, and the category is the Decisions
API. SystemOne stays as the wire contract: the /v1/systemone routes, the
Score RPC question_type and the swagger tag are unchanged. The usecase,
flag, auth feature, UI label, gallery tags and docs page are now decisions.
Assisted-by: Claude Code:claude-sonnet-5-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
laya declares the systemone usecase instead of chat. The gated Qwen3.6 27B
NVFP4 entries gain vision; the 35B-A3B entries gain it as experimental
because image input is not token-gated. Adds GLiNER2.5-Decide and
Qwen3-VL-4B. A guard test keeps capability tags and known_usecases in
agreement for every vllm-cpp entry.
Assisted-by: Claude Code:claude-sonnet-5-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet-cpp): load diarization and CED models and companions
Repin PARAKEET_VERSION to parakeet.cpp PR #75's head, which adds
parakeet_capi_model_kind (ABI v8). Bind the new diarization, sound
event and combined scene stream C symbols through the same
purego.Dlsym probe pattern already used for the batched JSON entry
point, so the backend still loads against an older libparakeet.so.
Load now classifies the loaded GGUF by role (ASR, diarization or
sound) via parakeet_capi_model_kind and can load up to two companion
models from Options[] (asr_model:, diarization_model:, sound_model:,
paths resolved against opts.ModelPath), verifying each companion's
kind and freeing every context opened so far on any failure. Free
releases the primary and every companion. AudioTranscription now
names the loaded role when it is not ASR instead of a generic model
not loaded error. The dynamic batcher starts only when an ASR context
ends up loaded, primary or companion.
This is groundwork only: the Diarize and SoundDetection RPCs and the
live scene stream that actually use these new roles land in later
commits.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(parakeet-cpp): reset role fields on a failed companion load
loadRoles' freeLoaded only released the C contexts it had opened; it
left ctxPtr/diarCtx/tagCtx and companions pointing at those now-freed
contexts, so a later Free() on the same instance would double-free.
Zero all four alongside the CppFree calls.
Also route AudioTranscriptionStream and AudioTranscriptionLive through
notASRError when ctxPtr is unset but a diarization or sound model is
loaded, matching AudioTranscription: both used to return the generic
model-not-loaded error instead of naming the loaded role.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet-cpp): add speaker diarization
Implement the Diarize RPC for the parakeet-cpp Go backend, wired to
Nemotron-3-Diarization through libparakeet.so's diarization C-API.
Plain diarization uses parakeet_capi_diarize_pcm; when include_text is
set and an ASR companion is loaded, parakeet_capi_transcribe_and_
diarize_json fills each segment's text instead. Speaker labels are the
decimal index, or "unknown" for -1 (no diarized speaker overlaps).
min_duration_off merges same-speaker segments across a short gap
before min_duration_on drops the segments still too short, then ids
are renumbered. num_speakers/min_speakers/max_speakers/clustering_
threshold have no Sortformer equivalent and are logged at debug
instead of rejected.
Verified against the real Nemotron-3-Diarization + parakeet-tdt_ctc-
110m checkpoints on the two_speakers.wav fixture: correct A-B-A-B
speaker segmentation and matching speaker-attributed transcripts.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet-cpp): add sound event detection
Wire the SoundDetection RPC to the CED tagger context (p.tagCtx)
loaded by Task 1's role classification. It runs the whole clip
through a one-shot parakeet_capi_sound_stream_* session (window
10s, hop 10s, top_k set to the tagger's class count so every
drained window carries a full score list), averages each class's
score across the drained windows, sorts descending, then applies
the request's threshold and top_k (0 keeps every class).
No tagCtx returns FailedPrecondition; a libparakeet.so missing the
sound_stream symbols returns Unimplemented. Every C call runs under
engineMu, and the stream is always freed, even when a feed or drain
call fails partway through.
Verified against a real ced-tiny-q8_0.gguf on the rooster.wav demo
clip: "Chicken, rooster" tops the list at score 0.91.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(parakeet-cpp): cancel sound detection mid-feed, shrink the lock
SoundDetection now checks ctx before each 10 s feed slice (mirroring
driver.go's feedSlices) and returns Canceled if the caller gave up,
so a long clip can be interrupted instead of feeding to completion
regardless. The stream is still freed on every path, cancellation
included.
Also narrow engineMu to the C calls: the drained JSON document is
now decoded after the lock is released, splitting soundStreamScores
into a locked soundStreamDrain (opts, begin, feed, drain, free) and
an unlocked json.Unmarshal.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet-cpp): stream speaker and sound events during live transcription
Add two additive proto fields, LiveSpeakerSegment and LiveSoundEvent,
repeated on TranscriptLiveResponse. When a diarization or sound
companion model is loaded, AudioTranscriptionLive now runs a no-ASR
scene stream (parakeet_capi_scene_stream_begin) beside the ASR
streaming session, feeding it the same PCM slices and forwarding any
closed speaker or sound events alongside the matching ASR delta, or
on their own when a slice has no ASR output.
The scene stream is freed and reopened on a mid-stream Config reset,
flushed with is_last before the closing FinalResult, and degrades
gracefully (a warning, not an error) when begin or a later feed call
fails, so live transcription keeps working ASR-only. Existing live
behavior is unchanged when no companion is configured, and no scene
C call is made in that case.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(parakeet-cpp): keep scene events off the ASR critical path in live
Emit each slice's ASR result right after the ASR feed, before the
scene feed for that slice runs, so a companion diarization/sound
model never adds scene compute latency in front of the delta or
<EOU> that drives realtime turn detection. Closed speakers/sounds go
out afterward as their own response, so a slice with both now
produces two responses, ASR first. The live feed log line now
reports ASR and scene wall time separately.
Re-check the diarization/sound contexts a scene stream was begun
with against the live contexts before every feed, under the same
lock: Free() can race between an ASR feed and the matching scene
feed and free the model the stream borrows. A mismatch now returns
without touching the C side. Freeing the stream itself stays
unconditional; the scene stream's destructor only releases its own
buffers and never touches the borrowed contexts.
Also recover a panicking stub inside the live test goroutine instead
of crashing the test binary, and reset the live decode-lag tracker on
a mid-stream config reset, matching what its own comment already
promised.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(realtime): surface live speaker and sound events
Carry the backend's closed speaker segments and sound events
(TranscriptLiveResponse fields 7/8) through LiveTranscriptionEvent
as LiveSpeakerSegment/LiveSoundEvent (nanoseconds mapped to
seconds), and forward them from the semantic_vad live path.
Each speaker segment emits
conversation.item.input_audio_transcription.segment with speaker,
start, end and empty text under the turn's item id. Each sound
event emits conversation.item.sound_detection with one tag
(label, score = peak, index) and the event's new optional
start/end seconds fields, omitted when unset so the existing
unary/windowed sound-detection path is unaffected.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(realtime): keep start/end on a zero-second transcription segment
ConversationItemInputAudioTranscriptionSegmentEvent.Start/End used
omitempty, so a speaker segment starting at 0.0s dropped its
"start" key. Nothing emitted this event before the live scene-event
path, so drop omitempty: the segment always carries real times.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(gallery): add parakeet-cpp diarization, CED and realtime scene models
Add gallery entries for the new parakeet-cpp capabilities: standalone
Nemotron-3-Diarization, the same paired with the Parakeet TDT+CTC
110M ASR model for speaker-attributed text, CED-Tiny and CED-Base
sound classifiers, and a realtime scene bundle combining the
streaming EOU ASR model with diarization and sound companions.
SHA256 taken from the Hub API; licenses from each model card
(openmdw-1.1 for Nemotron-3-Diarization, apache-2.0 for CED,
cc-by-4.0 for the Parakeet ASR models).
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: document parakeet-cpp diarization, sound detection and live scene events
Cover the new parakeet-cpp capabilities across the feature pages:
Nemotron-3-Diarization as a diarization backend (with and without
speaker text, the ignored speaker-count hints, the Sortformer
voice-like-sound quirk), CED as a sound classification backend, the
asr_model/diarization_model/sound_model/diarization_latency companion
options, and the realtime live speaker/sound events (event shapes,
the speech-turn-only limitation, and using this or
pipeline.sound_detection but not both).
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gallery): correct the realtime-scene license and wording nits
parakeet-cpp-realtime-scene mistakenly copied cc-by-4.0 from the
existing realtime_eou_120m-v1 entry; the model card lists the NVIDIA
open model license instead. Switch to the gallery's usual spelling
for that license and keep the diarization/CED licenses called out in
the description.
Also: audio-diarization.md now says getting per-segment text needs
both an asr_model companion and include_text=true on the request, and
audio-to-text.md's option table reads "Use on" (a pairing the loader
does not enforce) instead of "Allowed on".
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(parakeet-cpp): reject a companion role that duplicates the primary's
loadRoles let a companion option (asr_model:/diarization_model:/
sound_model:) assign into a role field the primary already occupied,
for example asr_model: on an already-ASR primary. The companion's
context silently overwrote ctxPtr/diarCtx/tagCtx, and Free() only
walks those three fields, so the original primary context was never
freed again.
Reject a companion whose role the primary already holds before its
GGUF is even loaded, freeing everything loadRoles opened so far, the
same way a wrong-kind companion is already rejected.
Also warn, rather than silently fall through, when
parakeet_capi_model_kind reports PARAKEET_MODEL_KIND_NONE for a
successfully loaded primary; the primary is still treated as ASR,
matching today's behavior.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(parakeet-cpp): cap live scene sound score retention
sceneBegin started the live diarization/sound companion stream with
the C API's default sound options, whose top_k keeps 5 scores per
window forever until drained. The live scene path never drains sound
scores (only the offline SoundDetection RPC does, with its own fresh
stream), so this window queue on the C side grew for the whole
session's lifetime.
Set opts.Sound.TopK = 0 before starting the scene stream: this
disables score retention while leaving sound event detection (onset/
offset), which the live path actually consumes, unaffected.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(parakeet-cpp): merge diarization segments per speaker, harden Diarize
mergeCloseSegments only compared neighbors in the single start-sorted
segment list, so two same-speaker segments never merged once another
speaker's turn fell between them (A, B, A): the short B segment broke
the adjacency the merge relied on. Group segments by speaker first,
merge within each speaker's own start-ordered run, then re-sort the
result by start so interleaved speakers come back out in timeline
order.
Also harden Diarize's entry points the same way streamFeedDoc/
sceneFeed already are: diarizeCall re-checks p.diarCtx (and, on the
include_text path, p.ctxPtr) under engineMu right before the C call,
so a Free() racing between Diarize's own checks and the lock can no
longer reach the C side with a freed context. When the include_text
call returns NULL, last_error is now read from both contexts and
whichever came back non-empty is reported, since either side of the
pairing can be the one that failed. A WAV decode failure is reported
as InvalidArgument instead of an unwrapped/untyped error.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(parakeet-cpp): harden SoundDetection's engine checks
soundStreamDrain ran every C call under engineMu but never re-checked
p.tagCtx there, so a Free() racing between SoundDetection's own
tagCtx==0 check and this lock could still reach the C side with a
freed context. Re-check p.tagCtx under the lock and return
ModelNotLoaded when it was cleared, mirroring diarizeCall's own
re-check. A WAV decode failure is now reported as InvalidArgument
instead of an unwrapped/untyped error.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(parakeet-cpp): cover a mid-session scene feed failure
feedSlicesScene already degrades gracefully when a scene feed call
fails mid-session: it frees the broken stream and carries the ASR-only
session forward. Add a spec covering that path end to end: the scene
stream is freed exactly once, later audio slices still produce ASR
responses, and no speaker/sound events appear before or after the
failure.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: fix the parakeet-cpp companion role table and realtime scene docs
audio-to-text.md's companion option table read "Use on" with a note
that the loader did not enforce the pairing; it now rejects a
companion whose role duplicates the primary's, so restore the
"Allowed on" wording and describe the real enforcement.
openai-realtime.md's live speaker/sound section claimed a mid-stream
session.update resets the companion stream and that it flushes on
session close; neither happens, since the realtime core opens one
live stream (and so one scene stream) per speech turn and closes it
at that turn's commit, with no mid-stream Config in between. Document
that lifecycle instead, state precisely that start/end are seconds
from the start of the turn's own audio, and note that the diarization
model starts a fresh session every turn, so a speaker index is only
meaningful within one turn. The example sound tag ("Rooster", index
17) did not match any real CED label; index 17 in ced-tiny-q8_0.gguf
is "Baby laughter". Replaced with "Chicken, rooster" at its real
index, 99.
Assisted-by: Claude:claude-sonnet-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(parakeet-cpp): use CED's real index for Chicken, rooster
The scene feed comment and the live test's canned document gave
"Chicken, rooster" index 365. In CED's AudioSet label list it is 99,
which is also what the realtime docs show.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(realtime): call the test event accessor
The scene-event tests range over a method instead of its returned slice.
Call the synchronized accessor so the OpenAI test package compiles.
Assisted-by: Codex:gpt-6
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(parakeet-cpp): pin parakeet.cpp master with sound events
mudler/parakeet.cpp#75 (sound events, scene stream, model kinds) and
#74 (the missing <algorithm> include that broke the image builds) are
on master now. Pin 6dea76a instead of the #75 PR head, and update the
header comment the bump bot reads.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(parakeet-cpp): pin parakeet.cpp with ced.cpp on main
parakeet.cpp #76 moved its ced.cpp submodule from the head of
localai-org/ced.cpp#3 (a branch-only commit) to ced.cpp main, where
#3 landed with an identical tree. Pin 623a968 so the image builds no
longer depend on that branch.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(transcription): carry speaker labels on words and streamed segments
A diarizing backend could label transcript segments, but two paths
dropped the label: TranscriptWord had no speaker field, so live
transcription words and word-level timestamps could not carry one, and
the stream=true transcript.text.done event left the speaker out of
its segments.
TranscriptWord gains an optional speaker (proto field 4, additive).
It flows through the live event and result mapping, the JSON word
output of the endpoint and the CLI, and transcript.text.done now
includes a segment's speaker when there is one. Empty labels are
omitted, so responses without diarization are unchanged.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
(cherry picked from commit 2f0049f979)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(importers): detect the parakeet.cpp diarization GGUF
The Nemotron-3-Diarization GGUFs are published in
mudler/parakeet-cpp-gguf as nemotron-3-diarization-<quant>.gguf. The
parakeet-cpp importer did not recognise that name, so a direct
`local-ai models import` of the file fell through to another importer.
A direct URL to the file now imports with the diarization usecase. A
repo import still picks ASR weights when the repo also ships the
diarization model, and falls back to the diarization weights only
when there are no others.
Ported from #12323.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(config): advertise diarization and sound detection for parakeet-cpp
The capability table listed parakeet-cpp as transcription only, though
the backend now answers Diarize (Nemotron-3-Diarization) and
SoundDetection (CED) depending on the model kind it loads.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet-cpp): label transcript segments with the diarization companion
A diarization_model companion only fed live speaker events and
Diarize; /v1/audio/transcriptions ignored it.
With the companion attached and diarize=true (the OpenAI endpoint's
default), unary transcription now labels each segment with its
speaker and splits segments at speaker turns; with word timestamps
each word carries its speaker. The stream=true final result labels
each utterance with the speaker who said most of it. Both use the
checkpoint's own diarization over the whole clip, as NeMo's diarize()
does. Words take the speaker whose segments overlap them most, or the
nearest segment within 0.5 s, the same rule as parakeet.cpp's
speaker-attributed ASR.
Docs: the diarization_model row and a paragraph on transcript
speakers; Nemotron-3-Diarization handles up to 8 speakers.
Ported from #12323.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(realtime): speaker segments from committed-turn transcription
Speaker events reached a realtime session only from the live
semantic_vad path, which needs a cache-aware streaming transcription
model. Committed-turn transcription (server_vad, or any offline
model) always asked the backend for diarize=false and dropped the
segments' speakers.
pipeline.diarization (off by default) asks the transcription model for
speaker labels on each committed turn and emits every labelled segment
as a conversation.item.input_audio_transcription.segment event, with
its text, before the turn's completed event. It is opt-in because some
backends fail a diarization request they cannot serve.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): add parakeet-cpp-realtime-scene-tdt
parakeet-cpp-realtime-scene pairs the streaming EOU model with the
diarization and CED companions; its speaker and sound events need a
cache-aware streaming model. This entry does the same with Parakeet
TDT 0.6B v3 (multilingual, offline) for realtime under server_vad:
set it as both transcription and sound_detection and turn on
pipeline.diarization, and each committed turn gets speaker segments
and sound tags from one parakeet-cpp backend.
Files and sha256 match the Hub and are shared with the existing TDT v3,
diarization and CED-Tiny entries. A real-model spec checks the
combination on a clip with two speakers and a rooster: A-B-A-B speaker
turns, and "Chicken, rooster" among the sound tags. The test loader
now binds the sound entry points like main.go.
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): add CED-Base variants of the parakeet-cpp scene models
parakeet-cpp-realtime-scene and parakeet-cpp-realtime-scene-tdt ship
with CED-Tiny. The -base variants use CED-Base (86M), which tags sounds
more confidently (on the rooster clip "Crowing" 0.65 against 0.49 for
Tiny).
Measured on CPU over a 37 s clip: the live diarization + sound stream
runs at 0.125 of real time with CED-Base against 0.103 with CED-Tiny,
because diarization dominates; sound detection per committed turn costs
0.031 against 0.005. The realtime docs list both and note that any CED
size works as sound_model.
Files and sha256 match the Hub and are shared with the existing
parakeet-cpp-ced-base entry. The TDT variant passes the real-model
scene spec with CED-Base (A-B-A-B speakers, "Chicken, rooster" found).
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(config): register pipeline.diarization in the config metadata
TestAllFieldsHaveRegistryEntries fails on the branch because the new
pipeline.diarization field has no registry entry. Add one so the model
editor shows it as a toggle next to the sound detection options.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
PTQ1_0 is a Prism-private GGUF type (GGML_TYPE_PTQ1_0 = 143 in the
PrismML llama.cpp fork), so stock llama-cpp cannot load it. Switch to
the bonsai backend like the existing ternary-bonsai-27b entries, and
replace the scraped Qwen3.8 description and icon.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
The entry enables spec_type:draft-mtp, so variant ranking needs the mtp
tag. Replace the scraped model-card description, set the Swift Open
License v1.0 and link the base model repo.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-5-5 [Claude Code]
Add IQ4_XS and Q4_K_M GGUF builds with a BF16 vision projector.
Pin verified artifacts and document installation and variant selection.
Assisted-by: Codex:gpt-6
Add Q4_K_M and Q8_0 builds with the F16 vision projector and install docs.
Pin artifact revisions and verify SHA256 against HF LFS metadata and HTTP
headers.
Assisted-by: Codex:gpt-6
Add four text-only llama.cpp builds with pinned download URLs and
verified checksums. Document variant selection and the model license.
Assisted-by: Codex:gpt-6
Add Q4_K_M and Q8_0 builds with the F16 vision projector and pinned
artifact URLs. Document installation and explicit variant selection.
Assisted-by: Codex:GPT-6
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(gallery): remove invalid Qwen-Image chat entry
The entry sends diffusion weights to llama.cpp as a chat model.
Remove it and document the existing image-generation alternatives.
Assisted-by: Codex:gpt-6
* feat(gallery): add Hemmingway-1 GGUF variants
Add Q4_K_M and Q8_0 builds for llama.cpp with embedded chat templates.
Record the upstream CC BY-NC 4.0 license and installation instructions.
Verify both SHA256 values against Hugging Face LFS metadata and headers.
Assisted-by: Codex:gpt-6
---------
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
Add five nemo-speech-cpp gallery entries for the diarization
capability introduced by the NeMo-Speech.cpp bump in #12257:
- nemo-speech-cpp-sortformer-diarization-v2: standalone streaming
Sortformer 4-speaker diarization (nvidia/diar_streaming_sortformer_4spk-v2).
Serves /v1/audio/diarization with known_usecases: [diarization].
- nemo-speech-cpp-nemotron-3.5-asr-streaming: standalone multilingual
streaming ASR (nvidia/nemotron-3.5-asr-streaming-0.6b).
- nemo-speech-cpp-nemotron-3.5-asr-streaming-diarized: Nemotron ASR
with the sortformer attached via the diar_model option, giving
per-word speaker tags on /v1/audio/transcriptions.
- nemo-speech-cpp-parakeet-tdt-0.6b-v3: standalone multilingual ASR,
25 languages (nvidia/parakeet-tdt-0.6b-v3).
- nemo-speech-cpp-parakeet-tdt-0.6b-v3-diarized: Parakeet v3 ASR
with the sortformer attached via the diar_model option, giving
per-word speaker tags on /v1/audio/transcriptions.
No backend code changes: the sortformer to familyDiarization mapping,
the diar_model option, and the MethodDiarize gRPC method already exist.
All five entries verified end-to-end against a running LocalAI instance.
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Add gallery entries for three vllm.cpp-backed models:
- laya-vllm-cpp: multilingual non-autoregressive System 1 decision
model (ModernBERT-large, 421M params). Served via POST /v1/systemone.
Weights from convaiinnovations/laya (Apache-2.0).
- cua-s1-forms-vllm-cpp: one-pass option scorer for GUI form filling.
Served via POST /api/score. Weights from cua-ai/cua-s1-forms (MIT).
- gliner2.5-vllm-cpp: zero-shot named entity recognition and structured
extraction (GLiNER2.5, mDeBERTa-v3-base, 287M params). Served via the
token classification endpoint. Weights from fastino/gliner2.5-multi-v1
(Apache-2.0).
All entries set backend: vllm-cpp and declare CPU+GPU tags.
Assisted-by: Maki:regolo/glm5.2 [maki]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* chore(model gallery): 🤖 add new models via gallery agent
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* feat(gallery): add NeoHorse-1-9B GGUF variants
Add the official Q4_K_M, Q5_K_M, and Q8_0 builds with revision-pinned
weights and verified SHA256 values.
Assisted-by: Codex:gpt-6
* chore(model gallery): 🤖 add new models via gallery agent
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* feat(gallery): add Qwen3.8 35B Distill variants
Add Q4_K_M, Q5_K_M, and Q8_0 builds with the vision projector.
Pin publisher revisions and document installation and variant selection.
Assisted-by: Codex:gpt-6
* feat(gallery): add ByteShape Qwen3.8 variants
Offer five ShapeLearn GGUF builds with a vision projector and MTP.
Pin downloads to a verified HF revision and document variant selection.
Assisted-by: Codex:gpt-6
* feat(gallery): add Flash Next GSQ-RCO variants
Offer Q2_0, IQ2_XS, and IQ3_XXS builds with both model shards and the
vision projector. Pin and verify download hashes and document how to
select each variant.
Assisted-by: Codex:GPT-6
* feat(gallery): add Occamy-1.0 GGUF variants
Add the publisher's Q4_K_M and Q8_0 builds with the F16 vision projector.
Link the builds as variants and pin downloads to a verified revision.
Document installation and the source tokenizer's NFC requirement.
Assisted-by: Codex:gpt-6
* fix(gallery): set MiniCPM5 context at the top level
The Q4 and Q8 overrides place context_size inside parameters, where
PredictionOptions ignores it. Move it beside parameters so both
builds use the intended 8,192-token context, matching F16.
Assisted-by: Codex:GPT-6
* feat(gallery): add Hy-MT2 7B GGUF variants
Offer the official Q4_K_M, Q6_K, and Q8_0 builds for translation.
Pin the downloads and document installation and translation prompts.
Assisted-by: Codex:gpt-6
* feat(gallery): add Maple-Preview GGUF variants
Offer four ternary builds through the existing llama.cpp backend.
Use the publisher's CPU settings and embedded chat template.
Pin downloads and verify SHA256 values against two HF metadata sources.
Document installation and explicit variant selection.
Assisted-by: Codex:gpt-6
* feat(gallery): add Qwen3.8 Cyber GGUF variants
Offer IQ4_XS and Q8_0 builds with the matching BF16 vision projector.
Pin download revisions and document automatic and explicit selection.
Assisted-by: Codex:GPT-6
* feat(gallery): add official NeoHorse 4B variants
Offer the official Q5_K_M and BF16 GGUF builds alongside the existing
community quantizations. Pin both downloads and document variant selection.
Assisted-by: Codex:gpt-6
* chore(model gallery): 🤖 add new models via gallery agent
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* chore(model gallery): 🤖 add new models via gallery agent
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* fix(stablediffusion-ggml): bump sd.cpp for Qwen-Image 2.1, fix RPC build
Bump stable-diffusion.cpp to c678dfe70, which adds Qwen-Image 2.1
support (leejet/stable-diffusion.cpp#1994).
The same range pulls a ggml update that adds GGML_OP_SAGE_ATTN but
does not update the GGML_OP_COUNT static_assert in ggml-rpc.h. We build
with SD_RPC=ON and upstream CI does not, so every backend image failed
to compile (see #12170).
Add a sync-rpc-op-count step after checkout. It sets the ggml-rpc.h
assert to the count that ggml.c asserts. The new op is appended before
GGML_OP_COUNT, so existing op ids on the wire do not change, and the
RPC handshake compares only major and minor versions. When upstream
fixes the header, the step does nothing, so future automated bumps
stay green.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(gallery): add Qwen-Image 2.1 GGUF for stablediffusion-ggml
Add qwen-image-2.1-q4_k-ggml, with qwen-image-2.1-q8_0-ggml as a
variant, from leejet/Qwen-Image-2.1-GGUF. The config follows the
upstream stable-diffusion.cpp recipe: Qwen3-VL-8B-Instruct text
encoder, the Qwen-Image 2.1 VAE, cfg scale 6, euler sampler.
The bundle also pulls the Qwen3-VL mmproj as llm_vision_path, so that
image editing with reference images works. The text encoder and mmproj
use the same filenames and checksums as the qwen3-vl-8b-instruct
entry, so both entries share the files on disk.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Consolidates all 25 pending gallery bot PRs into a single merge to resolve
the conflict cascade — every PR branched from a different point in master
and they all touch gallery/index.yaml, so merging them individually was
blocked by constant conflicts.
Changes:
- gallery/index.yaml: +739 lines (new model entries and fixes)
- docs/content/features/model-gallery.md: +116 lines (new model docs)
- docs/content/features/audio-cpp.md: +12 lines (Sortformer checksum fix)
Entry count: 1597 -> 1890 (293 new entries, no duplicates, YAML validated).
Supersedes: #11986#11992#11994#11996#11999#12002#12017#12019#12021#12025#12027#12029#12032#12036#12037#12038#12041#12042#12043#12047#12050#12064#12065#12066#12118
Assisted-by: MAKI:regolo/glm5.2
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
chore(model gallery): add four Italian community Piper voices
Add the Ugo voice from Einrich99/PiperTTS-UGO-Italian and the Aurora,
Giorgio and Leonardo voices from kirys79/piper_italiano. All four use
the piper backend and are CC BY 4.0.
The kirys79 Giorgio and Leonardo files carry checkpoint names and a
bare .json config. The entries save them as it_IT-<voice>-high.onnx
and .onnx.json, because the piper backend looks for the config at
<model>.onnx.json.
Assisted-by: Claude:claude-opus-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* fix(vulkan): preserve host ICD discovery for packaged backends
Add bundled Mesa manifests through VK_ADD_DRIVER_FILES instead of replacing the system driver list. Merge inherited and model-specific additive paths while preserving explicit operator overrides, with regression coverage.
Assisted-by: Codex:gpt-5 golangci-lint
Assisted-by: Codex:gpt-5.6-sol
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(3d): add Kimodo CPU and Vulkan animation backend
Introduce a distinct animation capability and model-described 3D operations, with a typed /3d/animate API, RPC transport, distributed media staging, permissions, and tracing.
Add a persistent kimodo.cpp adapter, skeleton GLB export, CPU/Vulkan packages, model and backend galleries, importer support, CI builds, and documentation. Adapt Studio inputs to each model and provide real-time skeleton playback, seeking, and history.
Cover backend validation, packaging, API behavior, importer inventories, distributed staging, and Studio workflows. Validate real-model CPU/Vulkan generation and deploy the integration to the local QA instance.
Assisted-by: Codex:gpt-5 golangci-lint
Assisted-by: Codex:gpt-5.6-sol
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(kimodocpp): adopt monolithic encoders and resident inference
Update upstream for resident weights, packed execution paths, and cached motion graphs. Default to all 32 text layers while retaining configurable streaming and legacy bundle support.
Use monolithic Q8_0 encoders by default and offer all six published quantizations through the gallery and importer. Refresh pinned hashes, tests, and documentation; remove the obsolete thread patch and ensure cached source checkouts follow the upstream pin.
Validated CPU and Vulkan generation, lower-bit streaming, gallery/importer suites, packaging, lint, and cold/warm Studio generation on localai-dev.
Assisted-by: Codex:gpt-5 golangci-lint
Assisted-by: Codex:gpt-5.6-sol
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
The Ministral 3 14B Reasoning entry inherits a Mistral 0.3 prompt and
JSON parser. Its name-first tool calls can therefore reach clients as
plain text.
Use the embedded template and llama.cpp's native tool parser. Document
migration for installed configurations, which gallery updates do not
rewrite.
Assisted-by: Codex:gpt-6
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
