* fix(model): deterministic, file-type-filtered backend auto-detect (#9287)
When a model config declares no explicit `backend:`, Load() fell into a
trial loop built by ranging the external-backends Go map (random order)
with no filtering, returning the first backend whose gRPC LoadModel
succeeded. An unrelated installed backend - e.g. the "opus" audio codec -
could therefore win a GGUF/LLM model load, so a model that should run on
llama.cpp wrongly tried to use opus.
Extract the candidate selection into a pure, testable function
SelectAutoLoadBackends that:
- sorts the candidate list deterministically (no more map-order
nondeterminism), and
- for a `.gguf` model, filters to LLM-capable backends (via
core/config.BackendCapabilities) and puts llama-cpp first, so an
incompatible audio/codec/image backend can never win the trial loop.
If filtering would leave zero candidates, the full sorted set is returned
unchanged, so a previously-loadable model is never made unloadable.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(model): break core/config <-> pkg/model import cycle in backend auto-detect
The #9287 auto-detect change made pkg/model/autoload.go import core/config
for the backend capability table. core/config already imports pkg/model
(runtime_settings_registry.go uses model.DefaultWatchdogInterval), so this
closed a core/config -> pkg/model -> core/config import cycle and broke the
build and golangci-lint.
Invert the dependency so the lower-level pkg/model no longer imports the
higher-level core/config. pkg/model exposes RegisterLLMCapableBackendFunc and
uses the registered predicate; core/config (which owns the capability table)
registers it from an init(). The deterministic, GGUF-type-filtered selection
behaviour is unchanged. When the predicate is unwired the GGUF filter is
skipped, preserving the existing zero-candidate fallback.
The unit test now injects a fake capability predicate so SelectAutoLoadBackends
is exercised independently of the core/config table.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:opus-4.8 [Claude Code]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
* feat: add Valkey Search vector store backend
Add a new built-in Go gRPC store backend 'valkey-store' that implements the
four Stores RPCs (Set/Get/Delete/Find) against the Valkey Search module (FT.*)
using the pure-Go github.com/valkey-io/valkey-go client. It is selected via the
existing per-request 'backend' field on /stores, so there is no proto or HTTP
API change, and it mirrors the in-memory local-store while adding persistence
across restarts and opt-in HNSW.
Each vector is a Valkey HASH keyed by hex(little-endian float32); the index is
created lazily on first Set (FLAT+COSINE by default), cosine similarity is
derived as 1-distance, and namespaces get a collision-resistant token. Includes
unit tests (valkey-go mock) and env-gated integration tests against
valkey/valkey-bundle, plus build/matrix/gallery wiring and docs.
Assisted-by: Kiro:claude-opus-4.8 golangci-lint
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* Address review feedback: recover persisted index dimension, harden Find
- Load now recovers the persisted vector DIM from FT.INFO (not just index
existence), so a post-restart Set/Find validates against the real DIM
instead of silently re-learning a wrong one and dropping mismatched
vectors from the index. This also restores Find's dimension check after
a restart.
- StoresFind treats a dropped/missing index as an empty store (empty
result, no error) and clears the stale indexCreated flag, matching
local-store's empty-store behaviour.
- StoresSet reuses checkDims for its per-key length check so the four RPCs
share one dimension-guard implementation.
- Add unit tests for FT.INFO dimension recovery, loadIndexState, and the
dropped-index Find path.
Assisted-by: Kiro:claude-opus-4.8
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* Address review feedback: TLS ServerName/CA, Find nil-check, config fail-fast
Addresses external review comments on the valkey-store backend:
- StoresFind now rejects a nil/empty query Key before dereferencing it,
so a malformed gRPC request can no longer panic the backend.
- TLS: derive ServerName (SNI) from the VALKEY_ADDR host so certificate
verification works for IP-addressed endpoints, and add VALKEY_TLS_CA_CERT
(custom CA bundle) and VALKEY_TLS_SKIP_VERIFY (testing-only) knobs.
- Config integer parsing now fails fast on a malformed value (e.g.
VALKEY_HNSW_M=1x6) instead of silently defaulting, matching the
fail-fast behaviour of the index-algo/distance-metric validation.
- Add VALKEY_DB (SELECT n) support for logical-DB isolation.
- Cap the human-readable part of a namespace token at 64 chars so a very
long model name cannot produce an unbounded key prefix / index name
(the appended short hash keeps distinct namespaces collision-free).
- Document the KNN-query injection-safety invariant (fields are constants)
and why StoresGet uses a single aggregate DoMulti deadline for reads.
- Unit tests for the Find nil/empty-key guard, fail-fast HNSW parsing,
and VALKEY_DB parsing/validation; docs + .env updated for the new vars.
Assisted-by: Kiro:claude-opus-4.8 golangci-lint
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* Address review feedback: configure valkey-store via model config
richiejp asked that the valkey-store backend take its configuration from
a model config rather than process-wide VALKEY_* environment variables,
so multiple stores can each have their own Valkey config within one
LocalAI process. This removes every env access from the backend and
routes config through the model-config seam every other backend uses.
- config.go: loadConfig(opts *pb.ModelOptions) now parses the model
config `options:` list (key:value strings, split on the first ':')
instead of os.Getenv. Option keys mirror the old VALKEY_* names without
the prefix (addr, index_algo, distance_metric, ...). Defaults, fail-fast
validation and the mandatory client name are unchanged.
- store.go: Load threads opts into loadConfig; TLS comments/errors renamed
off the VALKEY_* names.
- core/backend/stores.go: StoreBackend and NewVectorStore take a
*config.ModelConfigLoader, resolve the per-store ModelConfig by store
name, and pass its Options (and Backend when unset) to the backend via
WithLoadGRPCLoadModelOpts. No config -> default backend + built-in
defaults, preserving the zero-config experience.
- Endpoints/routes/application: thread the config loader to StoreBackend.
- Unit + integration tests: configure via options; the integration test
passes addr through the model-config path (VALKEY_ADDR is now only the
test harness locating the server).
- docs + .env: document the model-config options, drop the env var table.
Assisted-by: Kiro:claude-opus-4.8
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* Remove valkey-store informational comment from .env The backend is configured via model config, not env vars — the comment was unnecessary noise in .env. The configuration is already documented in docs/content/features/stores.md.
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* feat(valkey-store): gate Load on NamespacePrefix to refuse autoload probing Mirror local-store's pattern: reject model names without store.NamespacePrefix so the model loader's greedy autoload probe cannot bind an arbitrary model name to the vector store backend (the #9287 failure mode). Also adds unit tests for the gate covering: prefixed namespace, prefix alone, unprefixed model name, empty model, and nil opts.
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* feat(valkey-store): add username_env/password_env credential indirection Add support for resolving Valkey credentials from environment variables named in the model config, mirroring cloud-proxy's api_key_env pattern. This keeps secrets out of model YAML files and lets distinct store configs each reference their own credentials. Options: username_env / password_env name the env var holding the value. The direct username / password options still work and take precedence when both are set (backward compatible). Includes 5 unit tests and updated stores.md documentation.
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
* fix: correct rebase artifacts in backend-matrix.yml and Makefile Fix two issues introduced by the conflict-resolution script during the rebase onto master: 1. .github/backend-matrix.yml: valkey-store entries were merged INTO the cloud-proxy entries (duplicate keys in same YAML map items) instead of being separate list items. This broke cloud-proxy Linux builds and the cloud-proxy darwin entry lost its build-type/lang. Fixed by making them standalone entries and restoring cloud-proxy exactly as on master. 2. Makefile: duplicated .NOTPARALLEL and docker-build-backends lines. Collapsed to single lines that are master's current content plus the valkey-store additions. Also adds the three optional pickups from #10801: - /valkey-store in .gitignore (the built binary) - valkey-store row in docs/content/reference/compatibility-table.md - valkey-store line in backend/README.md
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
---------
Signed-off-by: Daria Korenieva <daric2612@gmail.com>
Co-authored-by: Daria Korenieva <daric2612@gmail.com>
* feat(3d): add Generate3D RPC, FLAG_3D capability, and /v1/3d/generations endpoint
Adds the plumbing for image-conditioned 3D asset generation (binary
glTF / GLB output), modeled on the video generation path:
- backend.proto: Generate3D RPC + Generate3DRequest (staged image src,
glb dst, seed/step/cfg_scale/texture_steps, quality and background
enums, params map for backend-specific extras)
- pkg/grpc: thread Generate3D through client, server, embed, base and
the backend interfaces; connection-evicting and distributed-node
wrappers (in-flight tracking + file staging) included
- core/config: FLAG_3D usecase (guessed only for the trellis2cpp
backend), '3d' canonical usecase string mapped to the Generate3D
method, and a '3d' output modality
- REST: POST /v1/3d/generations (+ unversioned alias) returning
OpenAIResponse with a /generated-3d URL or b64_json; conditioning
image accepted as URL, base64, or data URI; quality/background
validated at the edge; .glb served as model/gltf-binary
- auth: '3d' route feature (default ON); /api/instructions entry
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(trellis2cpp): add the trellis2.cpp image-to-3D backend
Wraps localai-org/trellis2cpp (C++/GGML port of Microsoft TRELLIS.2,
pbr-textures branch) as a Go+purego backend, following the
stablediffusion-ggml pattern:
- backend/go/trellis2cpp: purego bindings to the flat C ABI (v9,
asserted at startup), eager pipeline load with model-set validation
(refuses non-trellis GGUFs; degrades coarse/geometry-only/textured
exactly like the upstream demo), Generate3D via t2_generate +
t2_bake_glb writing a binary glTF to dst. Weight-free unit tests
cover resolution/validation/param mapping — CI never downloads the
multi-GB GGUF set or runs inference.
- CPU SIMD variants build into per-variant directories (the shared
libggml sonames collide across variants, unlike sd-ggml's flat
renamed-.so scheme); run.sh picks one via /proc/cpuinfo.
- CI wiring: backend-matrix entries (cpu, cuda12/13, vulkan
amd64+arm64, l4t, l4t-cuda13, darwin metal), index.yaml meta +
latest/master image entries, bump_deps tracking of the pbr-textures
branch, changed-backends.js mapping, top-level Makefile targets.
- Importer: auto-detects trellis GGUF repos/URIs (registered before
llama-cpp so the .gguf match isn't stolen) and expands any trellis
URI to the full 10-file component set spanning the three LocalAI-io
HF repos.
- Gallery: trellis2-4b (full PBR + 1024 cascade) and
trellis2-4b-geometry (512 untextured) with verified sha256s.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(ui): 3D generation page with native GLB viewer and IndexedDB history
Adds a Studio tab + /app/3d page for the new image-to-3D endpoint:
- GlbViewer ports the trellis2cpp demo's dependency-free WebGL2
renderer (quaternion trackball, metallic-roughness PBR, ACES,
hidden-line wireframe with a bounded index budget) and pairs it with
a minimal GLB parser for the two forms t2_bake_glb emits — dense
vertex-PBR (linear COLOR_0 + _METALLIC_ROUGHNESS, uploaded as
normalized integers) and the opt-in UV-atlas textured form. Parsing
happens before any GL so stats and errors render without WebGL2.
- use3DHistory stores past generations (params, input thumbnail, and
the GLB blob itself) in IndexedDB with keep-newest-20 eviction —
GLBs are multi-MB binaries localStorage can't hold — and the page
offers a download button for the active GLB.
- Wiring: CAP_3D capability constant (FLAG_3D — the exact string
/api/models/capabilities serves), threeDApi, router entries, Studio
tab, vite dev proxy, en locale keys.
- e2e: render-smoke entry plus a focused spec that feeds a real
one-triangle vertex-PBR GLB through the parser/viewer and exercises
IndexedDB persistence, selection, deletion, and API errors.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(3d): address API correctness and UX issues
Keep 3D generation on the LocalAI-specific /3d/generations route and ensure authentication and permissions cover it.
Propagate distributed transfer failures, publish a portable ARM64 backend image, honor importer overrides, and align discovery, upload validation, and touch controls.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(3d): add previewable print remeshing
Add a single-detail CGAL Alpha Wrap workflow for existing Trellis GLBs, including PBR reprojection, API documentation, tracing, and an in-browser preview before download.
Allow the remesh route to enforce its 512 MiB upload cap independently of the smaller global default so generated high-resolution meshes can be processed.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* build(trellis2cpp): centralize remesh dependency pins
Assisted-by: Codex:GPT-5 [apply_patch] [exec_command]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(kokoros): implement Generate3D stub for new proto RPC
The Generate3D RPC added to backend.proto for the trellis2cpp backend
made tonic's generated Backend trait require generate3_d, breaking the
kokoros-grpc build. Return unimplemented like the other unsupported
modalities.
Assisted-by: Claude Code:claude-fable-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
Co-authored-by: localai-org-maint-bot <bot-opensource@localaisrl.com>
backendLoader logged "BackendLoader starting" at INFO as its very first
statement, unconditionally. That reads as "a model is being loaded", but
backendLoader is not only a load path: in distributed mode Load()
deliberately bypasses the local cache and calls backendLoader on every
inference request so SmartRouter can re-pick a replica per request. The
model is already resident, no process is spawned, and nothing is loaded,
yet the banner fires at request rate.
On a live cluster this produced ~5 "BackendLoader starting" lines per
second for a single embedding model, sustained, starting 22 seconds
after the load had already completed. The model was state=loaded with
in_flight=0 and exactly one backend process on the worker. It looked
exactly like a retry storm and cost real debugging time during an
unrelated production investigation. The adjacent "effective runtime
tuning" banner, documented as "logged once per load", had the same
problem for the same reason.
Emit both banners at INFO only when the model is not already resident,
and keep the per-call trace at DEBUG for anyone following the routing
path. isResident is a plain store lookup with no health probe and no
eviction, so it is safe on the per-request hot path (unlike
checkIsLoaded, which probes and can evict).
Same class of defect as #10985: a log line that sends the reader after
the wrong thing.
Assisted-by: Claude Code:claude-opus-4-8[1m] [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(realtime): EOU-driven semantic_vad turn detection
Add a `semantic_vad` turn-detection mode to the realtime API that feeds
the transcription model live and decides "the user finished speaking"
from the `<EOU>` end-of-utterance token rather than from silence alone.
When EOU fires the turn commits immediately (~0.3s); otherwise it falls
back to an eagerness-scaled silence threshold (low/med/high = 8/4/2s).
Plumbing, bottom to top:
- proto: `AudioTranscriptionLive` bidirectional RPC (config-first oneof,
mono float PCM @16k, ready-ack / Unimplemented degrade signal) plus
`TranscriptResult.eou` for the unary retranscribe gate.
- pkg/grpc: client/server/base/embed scaffolding for the bidi stream,
modeled on AudioTransformStream; release stream conns on terminal Recv.
- parakeet-cpp: live transcription RPC with per-C-call engine locking
(one live stream per turn, finalize+free at commit); bump parakeet.cpp
to ABI v5 — incremental StreamingMel (no more quadratic per-feed mel
recompute that delayed EOU on long turns) and the <EOU>/<EOB> split;
strip the literal <EOU>/<EOB> from offline text and set Eou.
- core/backend: LiveTranscriptionSession wrapper + pipeline
`turn_detection:` config block (type/eagerness/retranscribe).
- realtime: semantic_vad integration — live input captions streamed as
transcription deltas while the user speaks, EOU-immediate commit with
eagerness fallback, optional retranscribe gate (batch re-decode must
also end in <EOU> to confirm), clause synthesis off the LLM token
callback, and per-turn live-transcription / model_load telemetry.
- UI: show the realtime pipeline components as a vertical list.
Docs and tests included; opt-in via the pipeline YAML or per-session
`session.update`. Non-streaming STT backends degrade to silence-only.
Assisted-by: Claude Code:claude-opus-4-8 [Read] [Edit] [Write] [Bash]
Assisted-by: Claude Code:claude-fable-5 [Read] [Edit] [Bash]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(realtime): explicit formally-verified state machines + parakeet streaming driver
The realtime API had several implicit state machines whose state was inferred
from scattered booleans, channels, and five separate mutexes, leaving
illegal/inconsistent states reachable. Make them explicit and keep the
implementation in step with a formal design; rework the parakeet streaming
backend along the same lines.
Realtime state machines (M1-M5). Each is a sealed sum-type State/Event/Effect
with a total, pure Next(state,event)->(state,[]effect) behind a single-writer
Coordinator:
M1 conncoord connection lifecycle: VAD toggle + once-only teardown
(replaces vadServerStarted + a `done` channel closed from
two sites).
M2 turncoord turn detection: collapses speechStarted and the live-stream
"turn open" flag into one state, so discardTurn can no longer
desync them and suppress the next onset.
M3 respcoord response coordination: serializes the dual-writer
start/cancel so at most one response is live; one
response.done per response.create.
M4 compactcoord conversation compaction: single-flight (replaces the
`compacting atomic.Bool` CAS).
M5 ttscoord TTS pipeline: open->closing->closed, idempotent wait(),
rejects enqueue-after-close (was a silent drop).
The Coordinator/Sink/Next plumbing — only the sealed types and Next differed
per machine — is extracted once into core/http/endpoints/openai/coordinator as
a generic Coordinator[S,E,F]; each machine keeps its public API via type
aliases, so no sink, call-site, or test moved.
Hierarchy. session_lifecycle.fizz models M1 as the parent region with its
children (M2/M3/M4) as one statechart and asserts ChildrenDieWithParent (conn
torn => all children terminal, none start after teardown). respcoord and
compactcoord gain an absorbing Terminated state + Shutdown event; conncoord's
teardown drives the children terminal. This closes a compaction teardown gap: a
fire-and-forget compaction could outlive a torn session — compactionSink now
takes a session-scoped cancellable context + WaitGroup and joins the in-flight
summarize+evict on shutdown.
Formal verification. formal-verification/ holds one authoritative FizzBee spec
per machine plus the composition spec, each with an always-assertion and a
documented one-line edit that makes the checker fail (verified non-vacuous).
scripts/realtime-conformance.sh is fail-closed: all Go conformance suites under
-race AND a model-check of every .fizz spec; a missing FizzBee is a hard error
(only the loud REALTIME_CONFORMANCE_SKIP_FIZZBEE=1 bypasses it, never in CI).
FizzBee is pinned by sha256 and installed via scripts/install-fizzbee.sh into
.tools/ (gitignored). Wired as make test-realtime-conformance, a CI workflow,
and a pre-commit path filter. Go conformance tests are Ginkgo/Gomega (per the
repo's forbidigo lint): transition tables + fixed-seed property walks +
concurrent/-race specs, no rapid dependency. Design map:
docs/design/realtime-state-machines.md.
Parakeet streaming backend. The same treatment applied to the parakeet-cpp
streaming paths:
- AudioTranscriptionStream returns codes.Unimplemented for non-streaming models
instead of decoding offline and emitting it as one delta + final. A client
that asked for streaming learns the model cannot stream rather than receiving
a batch result shaped like a stream. New grpcerrors.StreamTranscriptionUnsupported
carries that signal; the HTTP /v1/audio/transcriptions stream path surfaces it
as an SSE error event. Mirrors AudioTranscriptionLive, which already did this.
- utteranceBoundary (boundary.go): a single definition of the end-of-utterance
latch, replacing three open-coded finalEou toggles. Modelled as a two-valued
type so illegal states are unrepresentable.
- Shared decode driver (driver.go): streamFeedResult (one per-feed event) +
feedChunk (hides the ABI v4 JSON vs text-only split) + feedSlices + flushTail.
The feed loop is written once.
- AudioTranscriptionLive becomes a bidi adapter: it streams the per-feed
{delta,eou,eob,words} the realtime turn detector consumes and a terminal
FinalResult carrying only Text. Segments/duration/eou are offline-only and no
longer produced (nor read) on the live path; liveTraceState drops the terminal
eou and keeps the per-feed eou_events count.
- AudioTranscriptionStream + streamJSON merge into one driver-based function;
streamSegmenter is generalized to the unified event with a text-only fallback
that preserves the legacy (no-words) library's per-utterance segmentation.
Verified: build/vet/gofumpt clean, golangci-lint 0 issues, all coordinator and
parakeet packages under -race, the fail-closed conformance gate green, and
make test-realtime (12 e2e WS+WebRTC).
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>
The first #10485 fix (#10494) made the Blackwell physical-batch boost
per-device/context-aware, which neutralized the big compute-buffer OOM, but
the reporter's 2x16 GiB consumer Blackwell still OOM'd. Tracing the post-fix
log: the model now loads its weights, builds the main context and warms up
fine, and dies only on the *last* allocation — the MTP draft context's 800 MiB
KV cache on the tighter device.
#10411 changed only two defaults: the physical batch (now gated) and a
VRAM-scaled parallel-slot count. The KV cache is unified (n_ctx_seq == full
context proves slots share the budget, so parallel doesn't multiply KV), but
n_seq_max=4 still adds per-slot compute-graph / context-checkpoint / output
scratch. On a device packed ~99% by a 27B model spanning both cards, that
overhead is the few-hundred-MiB straw — which is why reverting #10411 (and only
#10411) restores a working load.
Gate the parallel-slot default on the same per-device headroom predicate as the
batch boost: when a large context already fills a single card
(largeContextForDevice), keep n_parallel=1. A user running one big-context model
that barely fits across two consumer GPUs is not serving four concurrent
tenants. Small contexts and large unified-memory devices (GB10) keep full
concurrency. Applied on both the single-host path and the distributed router.
Also make the auto-tuning visible and reversible (the debugging here needed
DEBUG logs and a git bisect):
- Log the effective performance-relevant runtime options at INFO once per
model load ("effective runtime tuning …": context, n_batch, n_gpu_layers,
parallel, flash_attention, f16) so an admin can see what will run and pin or
override any value in the model YAML.
- LOCALAI_DISABLE_HARDWARE_DEFAULTS=true skips the hardware auto-tuning
entirely (mirrors LOCALAI_DISABLE_GUESSING) for stock llama.cpp behavior.
Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(watchdog): add size-aware LRU eviction mode
When the model count hits the LRU limit or the memory reclaimer fires,
evict the largest model by on-disk file size first rather than the
least-recently-used one. For GGUF models the file size is a reliable
proxy for GPU/RAM footprint, so evicting the largest candidate maximises
freed memory per eviction round while keeping small utility models
(embeddings, classifiers, rerankers) resident.
Changes:
- `pkg/model/watchdog.go`: add `sizeAwareEviction` flag and
`modelSizes map[string]int64` to `WatchDog`; sort candidates by
`sizeBytes` desc (LRU time as tiebreaker) when the flag is set;
add `RegisterModelSize`, `SetSizeAwareEviction`, `GetSizeAwareEviction`
- `pkg/model/watchdog_options.go`: add `WithSizeAwareEviction` option
- `pkg/model/initializers.go`: stat model file after load and call
`RegisterModelSize` so size data is available before the first eviction
- `core/config/application_config.go`, `runtime_settings.go`: add
`SizeAwareEviction` field and `WithSizeAwareEviction` app option;
expose via `ToRuntimeSettings` / `ApplyRuntimeSettings` for the
`POST /api/settings` live-reload path
- `core/cli/run.go`: add `--size-aware-eviction` flag /
`LOCALAI_SIZE_AWARE_EVICTION` env var
- `core/application/startup.go`, `watchdog.go`: wire the new option
through to `NewWatchDog`
- `pkg/model/watchdog_test.go`: 5 new specs — option enable, dynamic
toggle, largest-first ordering, equal-size LRU tiebreaker, no-size
fallback to LRU, and size-map cleanup on eviction
Closes#9375
Signed-off-by: supermario_leo <leo.stack@outlook.com>
* refactor(watchdog): use vram estimation scaffolding for model size
Replace the brittle os.Stat(modelFile) approach with a proper call to
pkg/vram, which handles multi-file models (DownloadFiles, MMProj) and
all weight file types, not just single GGUF files.
- Add estimateModelSizeBytes() in core/backend/options.go that collects
all weight file URIs from the model config, resolves them to file://
URIs, and calls vram.Estimate() with the shared DefaultCachedSizeResolver
(15-min TTL cache avoids redundant stat calls on repeated loads)
- Thread the result through via a new WithModelSizeBytes() loader option
- In initializers.go, consume the pre-computed size instead of calling
os.Stat; if no size was supplied (e.g. for external/router-dispatched
models) the registration is simply skipped
Signed-off-by: supermario_leo <leo.stack@outlook.com>
* refactor(watchdog): use EstimateModel with HF fallback for size estimation
Switch estimateModelSizeBytes from calling vram.Estimate directly to the
unified vram.EstimateModel entry point, which adds automatic fallbacks:
file-based GGUF metadata → HF API → size string.
Also extract the HuggingFace repo ID from model URIs (huggingface://,
hf://, https://huggingface.co/ and org/model short-form) and pass it
as ModelEstimateInput.HFRepo, so models not yet downloaded locally can
still get a size estimate via the HF API.
Addresses @mudler's review feedback: "better to rely on EstimateModel
and pass by the HF URL of the model extracted from the URI".
Signed-off-by: supermario_leo <leo.stack@outlook.com>
* feat(webui): add Size-Aware Eviction toggle to settings page
The size-aware eviction setting was wired through the CLI flag and the
RuntimeSettings live-reload path (POST /api/settings) but had no handle
on the React settings page, so it could not be toggled from the UI.
Add a Size-Aware Eviction toggle to the Watchdog section, next to the
existing Force Eviction When Busy / LRU eviction handles. The settings
page loads and saves the whole RuntimeSettings object, so the new
size_aware_eviction key is picked up with no extra plumbing.
Addresses @mudler's review feedback: the application config setting
should land on the same UI settings page as the other handles.
Signed-off-by: supermario_leo <leo.stack@outlook.com>
---------
Signed-off-by: supermario_leo <leo.stack@outlook.com>
* refactor(distributed): extract PickBestReplica from FindAndLockNodeWithModel
Lifts the replica-selection policy (in_flight ASC, last_used ASC,
available_vram DESC) out of the SQL ORDER BY into a pure Go function in
the new replicapicker.go. The SQL clause keeps its FOR UPDATE atomicity
and remains the production path used by SmartRouter; PickBestReplica is
the canonical implementation that the future per-frontend rotating
replica cache (TODO referenced from pkg/model) will call against an
in-memory snapshot without paying a DB round-trip per inference.
A new registry_test mirror spec seeds a multi-tier scenario and asserts
both layers pick the same replica, so any future tweak to either side
fails the test until the other side is updated.
No behavior change.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
* fix(distributed): route per inference request and cache probeHealth
Two related fixes that together restore load balancing across loaded
replicas of the same model.
1. ModelLoader.Load and LoadModel bypass the local *Model cache when
modelRouter is set. The cached *Model wraps an InFlightTrackingClient
bound to a single (nodeID, replicaIndex) — reusing it pinned every
subsequent request to whichever node won the very first pick, so
FindAndLockNodeWithModel's round-robin never got a chance to run
even after the reconciler scaled the model out to a second node. In
distributed mode SmartRouter.Route now runs per request, and
PickBestReplica picks the least-loaded replica each time.
SmartRouter has its own coalescing (advisory DB lock for first-time
loads + singleflight on backend.install RPC) so concurrent first
requests for a not-yet-loaded model still produce a single worker
side install.
2. SmartRouter.probeHealth memoizes successful gRPC HealthCheck results
in a new probeCache (probe_cache.go) with a 30s TTL. With per-request
routing every inference call hits probeHealth, and llama.cpp-style
backends serialize HealthCheck behind active Predict — so a burst of
incoming requests stalled on the probe to a node already mid-stream,
tripping the 2s timeout and falling through to the install path.
singleflight collapses N concurrent first-time probes for the same
(node, addr) into one round-trip, failed probes invalidate the entry
so the staleness-recovery path still triggers, and the TTL matches
pkg/model/model.go's healthCheckTTL so the single-process and
distributed paths share a staleness budget. The background
HealthMonitor still reaps actually-dead backends within ~45s.
The bypass introduces one short FindAndLockNodeWithModel transaction per
inference. A TODO in pkg/model/loader.go documents the future per modelID
rotating-replica cache that would reuse PickBestReplica against an
in-memory snapshot and skip the DB round-trip for hot paths.
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>
* feat(concurrency-groups): per-model exclusive groups for backend loading
Adds `concurrency_groups: [...]` to model YAML configs. Two models that share
a group cannot be loaded concurrently on the same node — loading one evicts
the others, reusing the existing pinned/busy/retry policy from LRU eviction.
Layered design:
- Watchdog (pkg/model): per-node correctness floor — on every Load(), evict
any loaded model that shares a group with the requested one. Pinned skips
surface NeedMore so the loader retries (and ultimately logs a clear
warning), instead of silently allowing the rule to be violated.
- Distributed scheduler (core/services/nodes): soft anti-affinity hint —
scheduleNewModel prefers nodes that don't already host a same-group
model, falling back to eviction only if every candidate has a conflict.
Composes with NodeSelector at the same point in the candidate pipeline.
Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy
models running on different nodes is fine. The ConfigLoader is wired into
SmartRouter via a small ConcurrencyConflictResolver interface so the nodes
package keeps a narrow surface on core/config.
Refactors the inner LRU eviction body into a shared collectEvictionsLocked
helper and the loader retry loop into retryEnforce(fn, maxRetries, interval),
so both LRU and group enforcement share busy/pinned/retry semantics.
Closes#9659.
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(watchdog): sync pinned + concurrency_groups at startup
The startup-time watchdog setup lives in initializeWatchdog (startup.go),
not in startWatchdog (watchdog.go). The latter is only invoked from the
runtime-settings RestartWatchdog path. As a result, neither
SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot,
so `pinned: true` and `concurrency_groups: [...]` only became effective
after a settings-driven watchdog restart.
Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end:
loading model A in group "heavy", then C with no group (coexists),
then B in group "heavy" now correctly evicts A and leaves [B, C].
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec
CI lint runs new-from-merge-base, so the existing pre-existing
`defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the
one introduced by the concurrency_groups YAML round-trip test is held
to errcheck. Wrap the remove in a closure that discards the error.
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups
Two distinct bugs were causing tight retry loops in the distributed scheduler:
1. FindAndLockNodeWithModel ignored the model's NodeSelector. When a model
was loaded on multiple nodes and only some matched the current selector,
the function returned the lowest-in_flight node — even one the selector
excluded. Route()'s post-check then fell through to scheduleNewModel,
which targeted the matching node where the model was already at
MaxReplicasPerModel capacity. Eviction couldn't help (the only loaded
model on that node was the one being requested, and it was busy), so
every request looped through "evicting LRU" → "all models busy".
Fix: thread an optional candidateNodeIDs filter through
FindAndLockNodeWithModel. Route() resolves the selector once via a new
resolveSelectorCandidates helper and passes the matching IDs to both
the cached-replica lookup and scheduleNewModel. The same helper
replaces the inline selector block in scheduleNewModel.
2. ScheduleAndLoadModel (reconciler scale-up path) fell back to
scheduleNewModel with backendType="" when no replica had ever been
loaded for a model. The worker rejected the resulting backend.install
("backend name is empty") on every reconciler tick (~30s).
Fix: remove the broken fallback. When GetModelLoadInfo has nothing
stored, return a clear error instead of firing a doomed NATS install.
The reconciler's existing scale-up failure log surfaces it once per
tick; the model auto-replicates as soon as Route() serves it once and
stores load info.
Also downgrade the post-LoadModel-failure StopGRPC error to Debug — that
cleanup attempt usually hits "model not found" because LoadModel failed
before registering the process, and the outer "Failed to load model"
error already carries the real reason.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]
* test(distributed): cover selector-aware FindAndLockNodeWithModel and reconciler scaleup guard
Two regression tests for the bugs fixed in the previous commit:
1. FindAndLockNodeWithModel — registry-level integration tests verify the
candidateNodeIDs filter:
- Returns the included node even when an excluded node has lower
in_flight (the original selector-mismatch loop scenario).
- Returns not-found when the model is loaded only on excluded nodes,
forcing Route() to fall through to a fresh schedule instead of
reusing the excluded replica.
2. ScheduleAndLoadModel — mock-based test verifies the reconciler scale-up
path returns an error and does NOT fire backend.install when no replica
has been loaded yet. fakeUnloader gains an installCalls slice so this
negative assertion is direct.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat: add distributed mode (experimental)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix data races, mutexes, transactions
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix events and tool stream in agent chat
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* use ginkgo
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(cron): compute correctly time boundaries avoiding re-triggering
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* enhancements, refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* do not flood of healthy checks
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* do not list obvious backends as text backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* tests fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactoring and consolidation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Drop redundant healthcheck
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* enhancements, refactorings
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Remove HuggingFace backend support, restore other backends
- Removed backend/go/huggingface directory and all related files
- Removed pkg/langchain/huggingface.go
- Removed LCHuggingFaceBackend from pkg/model/initializers.go
- Removed huggingface backend entries from backend/index.yaml
- Updated backend/README.md to remove HuggingFace backend reference
- Restored kitten-tts, local-store, silero-vad, piper backends that were incorrectly removed
This change removes only HuggingFace backend support from LocalAI
as per the P0 priority request in issue #8963, while preserving
other backends (kitten-tts, local-store, silero-vad, piper).
Signed-off-by: team-coding-agent-1 <team-coding-agent-1@localai.dev>
* Remove huggingface backend from test.yml build command
The tests-linux CI job was failing because it was trying to build the
huggingface backend which no longer exists after the backend removal.
This removes huggingface from the build command in test.yml.
* Apply suggestion from @mudler
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
---------
Signed-off-by: team-coding-agent-1 <team-coding-agent-1@localai.dev>
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: team-coding-agent-1 <team-coding-agent-1@localai.dev>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* WIP response format implementation for audio transcriptions
(cherry picked from commit e271dd764bbc13846accf3beb8b6522153aa276f)
Signed-off-by: Andres Smith <andressmithdev@pm.me>
* Rework transcript response_format and add more formats
(cherry picked from commit 6a93a8f63e2ee5726bca2980b0c9cf4ef8b7aeb8)
Signed-off-by: Andres Smith <andressmithdev@pm.me>
* Add test and replace go-openai package with official openai go client
(cherry picked from commit f25d1a04e46526429c89db4c739e1e65942ca893)
Signed-off-by: Andres Smith <andressmithdev@pm.me>
* Fix faster-whisper backend and refactor transcription formatting to also work on CLI
Signed-off-by: Andres Smith <andressmithdev@pm.me>
(cherry picked from commit 69a93977d5e113eb7172bd85a0f918592d3d2168)
Signed-off-by: Andres Smith <andressmithdev@pm.me>
---------
Signed-off-by: Andres Smith <andressmithdev@pm.me>
Co-authored-by: nanoandrew4 <nanoandrew4@gmail.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* feat: allow to set forcing backends eviction while requests are in flight
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: try to make the request sit and retry if eviction couldn't be done
Otherwise calls that in order to pass would need to shutdown other
backends would just fail.
In this way instead we make the request sit and retry eviction until it
succeeds. The thresholds can be configured by the user.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* add tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* expose settings to CLI
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Update docs
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(loader): refactor single active backend support to LRU
This changeset introduces LRU management of loaded backends. Users can
set now a maximum number of models to be loaded concurrently, and, when
setting LocalAI in single active backend mode we set LRU to 1 for
backward compatibility.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: add tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Update docs
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: split remaining backends and drop embedded backends
- Drop silero-vad, huggingface, and stores backend from embedded
binaries
- Refactor Makefile and Dockerfile to avoid building grpc backends
- Drop golang code that was used to embed backends
- Simplify building by using goreleaser
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(gallery): be specific with llama-cpp backend templates
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(docs): update
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(ci): minor fixes
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: drop all ffmpeg references
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: run protogen-go
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Always enable p2p mode
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Update gorelease file
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(stores): do not always load
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fix linting issues
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Simplify
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Mac OS fixup
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Build llama.cpp separately
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* WIP
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* WIP
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* WIP
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Start to try to attach some tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add git and small fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: correctly autoload external backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Try to run AIO tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Slightly update the Makefile helps
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt auto-bumper
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Try to run linux test
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add llama-cpp into build pipelines
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add default capability (for cpu)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Drop llama-cpp specific logic from the backend loader
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* drop grpc install in ci for tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Pass by backends path for tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Build protogen at start
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(tests): set backends path consistently
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Correctly configure the backends path
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Try to build for darwin
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* WIP
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Compile for metal on arm64/darwin
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Try to run build off from cross-arch
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add to the backend index nvidia-l4t and cpu's llama-cpp backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Build also darwin-x86 for llama-cpp
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Disable arm64 builds temporary
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Test backend build on PR
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixup build backend reusable workflow
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* pass by skip drivers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Use crane
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Skip drivers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* x86 darwin
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add packaging step for llama.cpp
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fix leftover from bark-cpp extraction
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Try to fix hipblas build
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: Add backend gallery
This PR add support to manage backends as similar to models. There is
now available a backend gallery which can be used to install and remove
extra backends.
The backend gallery can be configured similarly as a model gallery, and
API calls allows to install and remove new backends in runtime, and as
well during the startup phase of LocalAI.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add backends docs
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* wip: Backend Dockerfile for python backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: drop extras images, build python backends separately
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixup on all backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test CI
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Tweaks
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Drop old backends leftovers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixup CI
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Move dockerfile upper
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fix proto
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Feature dropped for consistency - we prefer model galleries
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add missing packages in the build image
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* exllama is ponly available on cublas
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* pin torch on chatterbox
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixups to index
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* CI
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Debug CI
* Install accellerators deps
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add target arch
* Add cuda minor version
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Use self-hosted runners
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci: use quay for test images
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fixups for vllm and chatterbox
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Small fixups on CI
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chatterbox is only available for nvidia
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Simplify CI builds
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt test, use qwen3
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(model gallery): add jina-reranker-v1-tiny-en-gguf
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(gguf-parser): recover from potential panics that can happen while reading ggufs with gguf-parser
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Use reranker from llama.cpp in AIO images
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Limit concurrent jobs
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* chore: drop double call to stop all backends, refactors
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: do lock when cycling to models to delete
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
The GGML format is now dead, since in the next version of LocalAI we
already bring many breaking compatibility changes, taking the occasion
also to drop ggml support (pre-gguf).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(stablediffusion-ncn): drop in favor of ggml implementation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(ci): drop stablediffusion build
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): add
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): try to fixup current tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Try to fix tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Tests improvements
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): use quality to specify step
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): switch to sd-1.5
also increase prep time for downloading models
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* merge sentencetransformers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add alias to silently redirect sentencetransformers to transformers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add alias also for transformers-musicgen
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Drop from makefile
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Move tests from sentencetransformers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Remove sentencetransformers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Remove tests from CI (part of transformers)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Do not always try to load the tokenizer
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fix typo
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Tiny adjustments
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(backends): Drop bert.cpp
use llama.cpp 3.2 as a drop-in replacement for bert.cpp
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): make test more robust
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Instead of trying to derive it from the model file. In backends that
specify HF url this results in a fragile logic.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This is in order to identify also builds which are not using
alternatives based on capabilities.
For instance, there are cases when we build the backend only natively in
the host.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(llama-cpp): consistently select fallback
We didn't took in consideration the case where the host has the CPU
flagset, but the binaries were not actually present in the asset dir.
This made possible for instance for models that specified the llama-cpp
backend directly in the config to not eventually pick-up the fallback
binary in case the optimized binaries were not present.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: adjust and simplify selection
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: move failure recovery to BackendLoader()
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* comments
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* minor fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(refactor): track internally started models by ID
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Just extend options, no need to copy
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Improve debugging for rerankers failures
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Simplify model loading with rerankers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Be more consistent when generating model options
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Uncommitted code
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Make deleteProcess more idiomatic
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt CLI for sound generation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixup threads definition
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Handle corner case where c.Seed is nil
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Consistently use ModelOptions
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt new code to refactoring
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Dave <dave@gray101.com>
* chore(refactor): track grpcProcess in the model structure
This avoids to have to handle in two parts the data relative to the same
model. It makes it easier to track and use mutex with.
This also fixes races conditions while accessing to the model.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): run protogen-go before starting aio tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): install protoc in aio tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
