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test/distributed-e2e-ci
12
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Ettore Di Giacinto
|
1e877e9f6c |
test(distributed): cover binary backend routes
Run one real frontend and worker against deterministic fixtures. The owner tunnel now covers every public backend route in this task. Store requests exposed a missing config revision. Forward the persisted revision so distributed routing accepts store models. The harness pins staging capacity because quota-backed CI filesystems can report misleading host totals. Assisted-by: Codex:GPT-5 [apply_patch] [exec_command] |
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Richard Palethorpe
|
d10374f849 |
feat(router): make KNN a first-class classifier with a persisted, curated corpus (#10652)
* feat(router): make KNN a first-class classifier with a persisted, curated corpus
Add `classifier: knn` — similarity-weighted voting over labelled
example prompts. Unlike score/colbert it needs no classifier model:
label knowledge lives in a corpus seeded and curated through the
admin API, so routing decisions are deterministic, auditable, and
grounded in graded experience rather than a model's opinion.
Epistemic gate: corpus entries below knn.similarity_threshold cannot
vote; when none clears it the classifier activates no labels and the
router uses the fallback — a prompt unlike all labelled experience is
treated as undecidable, not guessed. Decisions record
nearest_similarity (also on fallback rows) so admins can see how far
the nearest labelled experience was; the Routing tab explains
out-of-corpus fallbacks and shows per-label corpus counts.
Persistence: one JSONL file per router under
<data path>/router-corpus (text, labels, vector, embedder
fingerprint). The file is the source of truth; the local-store index
is rebuilt from it at classifier build time and stays a pure
in-memory index. Entries recorded under a different embedding model
re-embed on load. Also corrects the docs' false claim that
local-store collections persist — the embedding cache never survived
restarts (and still doesn't); the corpus does.
Corpus input is API-only by design (entries may contain example user
content): POST /api/router/{name}/corpus seeds (labels validated
against declared policies, embedded server-side, indexed
immediately), GET .../corpus/stats inspects — label counts only,
entry texts are never returned by any surface — DELETE .../corpus
wipes. Admin-gated like the sibling router endpoints, and exposed as
MCP tools (seed_router_corpus / get_router_corpus_stats /
clear_router_corpus) in both the httpapi and inproc clients with
coverage-test route mappings.
Plumbing: VectorStore gains SearchK (top-K was hardcoded to 1);
local-store gets InsertBatch/Delete as optional fast paths;
RouterConfig gains a knn block (embedding_model, k,
similarity_threshold, vote_threshold, store_name) with meta-registry
fields; the classifier dropdown now offers knn and the
previously-missing colbert; embedding_cache is ignored (with a
warning) for knn — it IS an embedding-KNN lookup; the stale
/api/instructions intelligent-routing entry is rewritten (it
described a classifier that no longer exists); swagger regenerated.
Tests: KNN vote/gate specs with hand-computed vote shares, corpus
manager suite (restart reload without re-embedding, fingerprint
re-embed, dedupe, hostile store names), middleware specs (corpus
routing, gate fallback, config validation, cache-wrap refusal),
corpus endpoint specs pinning the texts-never-returned contract, MCP
catalog + route-mapping gates, and a Playwright spec for corpus
stats and the out-of-corpus decision detail.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(router): name consulted corpus neighbours in knn decisions
Every knn decision (decision log rows and the /api/router/decide
response) now carries neighbors: the K retrieved corpus entries by
descending similarity - including ones below the epistemic gate, which
is what makes fallback decisions diagnosable - each as {id, similarity,
labels}. The id is the entry's content hash (first 8 bytes of the
SHA-256 of its text, hex): stable across reseeds and re-embeds, and
text-free, so an external platform that seeded the corpus can recompute
text->id on its own copy and bucket decisions by corpus region (per-
region reliability accounting) without corpus text ever leaving the
server. A corrupt index payload surfaces as an id-less neighbour at a
real similarity instead of disappearing.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* refactor(router): deduplicate knn plumbing and cut corpus hot-path waste
Post-review cleanup of the knn-first-class-router branch; no behaviour
changes on the API surface.
Reuse/altitude:
- RouterKNNConfig.ResolvedStoreName is now the single source of the
router-corpus-<name> default (was hand-derived in four files).
- corpus.ResolveKNNRouter + corpus.Seed carry the shared model
resolution and seed validation; the REST endpoints and the assistant
MCP client are thin transport adapters over them, with sentinel
errors mapped to HTTP statuses at the echo boundary.
- middleware.NewClassifierDeps assembles the classifier dependency set
once for all five entry points (OpenAI, Anthropic, realtime, decide,
corpus) instead of five hand-copied literals.
- router.AllClassifiers feeds both the status endpoint and the
unknown-classifier error, ending the classifier-list drift.
- Per-classifier requirements moved out of validateRouterPolicies into
their buildClassifier arms; the knn arm owns its embedding_cache
opt-out instead of a name-check in the shared wrap tail.
- adminOnly replaces four inline copies of the admin gate in the
middleware routes.
- localVectorStore.Search delegates to SearchK (identical traces).
Efficiency:
- Manager.Add embeds outside the manager mutex and appends to the
JSONL file (O(new) instead of O(corpus) rewrite); a torn tail from a
crash mid-append is tolerated on read and repaired on next write.
- Stats memoises per store keyed on the file's stat fingerprint and no
longer takes the manager mutex, so the 5s status poll stops parsing
vector-laden JSONL and stops blocking behind seeds.
- KNN Classify decodes each neighbour payload once (was twice) and
builds refs and votes in a single pass with one fallback return.
- Corpus file writes fsync before rename/close.
- The corpus manager is built eagerly in newApplication (sync.Once
dropped); test helper dead branch removed.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(router): bind knn corpus vectors to an embedder fingerprint and fail closed on mismatch
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(mcp): align corpus tool prompts and the mutating-tool safety list
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(proto,backend): report embedding shape from the llama-cpp backend
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(embeddings): Go-side pooling — mean/last/decayed_mean with half-life
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* feat(embeddings): accept chat messages[] and per-request pooling on /v1/embeddings
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(middleware): name the failing fields when post-merge validation 400s
An intermittent post-merge validation failure surfaced as an opaque 400
during integration (pooling scheme mismatch that no client had sent).
Log the model, the request's pooling override, and the merged config's
pooling fields at the failure point so the next occurrence identifies
whether the request or the stored config carried the bad value.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix(embeddings): scheme override must not inherit the config's half-life
A model config defaulting to decayed_mean pooling carries
pooling_half_life_tokens; a request overriding the scheme to mean/last
without its own half-life inherited that value, and post-merge
validation rejected the pair the server itself had assembled. Zero the
inherited half-life when the overridden scheme is not decayed_mean; a
request that explicitly pairs a half-life with a non-decayed scheme
still 400s.
Assisted-by: Claude:claude-fable-5 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* fix embedding pooling validation and router bounds
Declare backend embedding layouts and reject incompatible pooling modes. Reset local-store dimensions after a full clear, validate KNN thresholds, and add real backend and store integration coverage.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* ci: run local-store integration tests
Build and install the local-store backend in the Linux test job, then run the existing store integration suite so new specs are discovered automatically.
Assisted-by: Codex:gpt-5
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
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Richard Palethorpe
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799cc9f211 |
feat: bound global admission and expose running backend traces (#11560)
feat: bound backend admission and expose running traces Add process-wide backend execution admission without blocking UI or administrative HTTP work. Represent backend operations while they are in flight, surface running traces with immediate log links, and tie streaming admission leases to the gRPC receive lifecycle. Assisted-by: OpenAI Codex: GPT-5 Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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localai-org-maint-botandDaria Korenieva
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9bfd71387b |
feat(stores): add Valkey Search vector store backend (#11196)
* 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> |
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Richard Palethorpe
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1f9fda7138 |
fix(backends): refuse foreign model loads in opus and local-store (#10769)
When a model config has no explicit backend, the model loader greedily probes every installed backend and binds to the first Load that succeeds. opus and local-store were the only in-tree backends with no model artefact to validate, so they accepted anything — an LLM installed after them could silently bind to the audio codec or the vector store and then fail at inference with "unimplemented" (see #9287). opus now accepts only its own name (what the realtime WebRTC path sends) or none. local-store namespaces are arbitrary (router caches, biometrics, user-named stores), so core's StoreBackend now marks genuine store loads with a store:// prefix on the gRPC model name and the backend refuses names without it; core and backend ship from the same release, so the convention upgrades in lockstep. Also repair the bit-rotted 'make test-stores' bootstrap (the suite never registered external backends, so BACKENDS_PATH was dead weight) and add the Load-validation rule to the adding-backends checklist. Related: #9287 Assisted-by: Claude:claude-fable-5 golangci-lint Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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Richard Palethorpe
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085fc53bbc |
fix(router): production-ready request router + auto-size batch for embedding/rerank (#10104)
* fix(router): score classifier production-readiness Conversation trimming runs through the classifier model's chat template and trims by exact token count, sized to the model's n_batch which is now scaled to context so long probes can't crash the backend. Missing chat_message templates are a hard error at router build time. Router- facing factories (Embedder/Scorer/Reranker/TokenCounter) re-resolve ModelConfig per call so a model installed post-startup doesn't bind a stub Backend="" config and silently fall into the loader's auto- iterate path. New 'vector_store' backend trace recorded inside localVectorStore on every Search/Insert — including the backend-load-failure path that previously vanished into an xlog.Warn — with outcome tagging (hit/miss/empty_store/backend_load_error/find_error/insert_error/ok). Companion cleanup drops misleading similarity:0 and input_tokens_count:0 from non-hit and text-mode traces. Gallery local-store-development aliases to 'local-store' so the master image satisfies pkg/model.LocalStoreBackend lookups from the embedding cache. Misc: llama-cpp TokenizeString reads the correct 'prompt' JSON key (the original bug); ModelTokenize nil-guard; non-fatal mitm proxy startup; PII 'route_local' renamed to 'allow' with docs/UI in sync; model-editor footer no longer eats the edit area on small screens; several config-editor template/dropdown/section fixes. Tests: e2e router specs (casual/code-hint + long-conversation trim), vector_store trace specs, lazy-factory specs, gallery dev-alias resolution, Playwright trace badge + scroll regression. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(backend): auto-size batch to context for embedding and rerank models Embedding and rerank models pool over the whole input in a single physical batch (n_ubatch). With batch left at the 512 default, the backend rejects longer inputs with "input is too large to process", silently capping a large-context embedder (e.g. 8k/32k) at 512 tokens. Size n_batch to the context for these single-pass usecases, mirroring the existing FLAG_SCORE behaviour; an explicit batch: still wins. Extracts EffectiveContextSize/EffectiveBatchSize from grpcModelOpts so the effective decode window has one home for other callers to reuse. Adds an e2e-aio regression test that embeds a >512-token input. The AIO embedding model is switched to nomic-embed-text-v1.5 (2048 context) because the previous granite model was capped at 512 tokens and could not exercise the larger batch. Assisted-by: claude-code:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(gallery): raise arch-router scoring output cap via parallel:64 Scoring decodes the whole prompt+candidate in a single llama_decode and reads one logit row per candidate token. The vendored llama.cpp server caps causal output rows at n_parallel, so the default of 1 aborts with GGML_ASSERT(n_outputs_max <= cparams.n_outputs_max) on multi-token route labels. Set options: [parallel:64] on both arch-router quant entries to lift the cap; kv_unified (the grpc-server default) keeps the full context per sequence, so this does not split the KV cache. Assisted-by: claude-code:claude-opus-4-8 [Claude Code] Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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Richard Palethorpe
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6a80e23733 |
feat(middleware): Model routing, PII filtering, Cloud model proxies (#9802)
Add a routing middleware stack and a cloud-proxy backend. * cloud-proxy: a Go gRPC backend that forwards OpenAI- and Anthropic-shaped chat requests to upstream providers, with an optional translate mode (OpenAI request -> Anthropic /v1/messages -> OpenAI response) and full tool-calling support. * routing: admission control, content-aware model routing (embedding cache + classifier + rerank + Arch-Router score), PII detection/redaction (regex + NER) with streaming filter and OpenAI/Anthropic adapters, and a per-user/per-key billing recorder backed by GORM or in-memory storage. * middleware: UsageMiddleware records usage via the billing recorder, plus admission, route-model, usage-stamp and trace middlewares. * observability: BackendTrace ring buffer stores full request bodies (capped), MITM proxy emits structured trace events, and router classifier decisions surface at /api/router/decide. * gallery: Arch-Router-1.5B (Q4_K_M and Q8_0). * UI: cloud-proxy model-editor fields, classifier system-prompt and score-normalization config, and a Traces page rendering request bodies. Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash] Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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Ettore Di Giacinto
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4906cbad04 |
feat: add biometrics UI (#9524)
* feat(react-ui): add Face & Voice Recognition pages
Expose the face and voice biometrics endpoints
(/v1/face/*, /v1/voice/*) through the React UI. Each page has four
tabs driving the six endpoints per modality: Analyze (demographics
with bounding boxes / waveform segments), Compare (verify with a
match gauge and live threshold slider), Enrollment (register /
identify / forget with a top-K matches view), Embedding (raw
vector inspector with sparkline + copy).
MediaInput supports file upload plus live capture: webcam
snap-to-canvas for face, MediaRecorder -> AudioContext ->
16-bit PCM mono WAV transcode for voice (libsndfile on the
backend only handles WAV/FLAC/OGG natively).
Sidebar gets a new Biometrics section feature-gated on
face_recognition / voice_recognition; routes are wrapped in
<RequireFeature>. No new dependencies -- Font Awesome icons
picked from the Free set.
Assisted-by: Claude:Opus 4.7
* fix(localai): accept data URI prefixes with codec/charset params
Browser MediaRecorder produces data URIs like
data:audio/webm;codecs=opus;base64,...
so the pre-';base64,' section can carry multiple parameter
segments. The `^data:([^;]+);base64,` regex in pkg/utils/base64.go
and core/http/endpoints/localai/audio.go only matched exactly one
segment, so recordings straight from the React UI's live-capture
tab failed the strip and then tripped the base64 decoder on the
leading 'data:' literal, surfacing as
"invalid audio base64: illegal base64 data at input byte 4"
Widened both regexes to `^data:[^,]+?;base64,` so any number of
';param=value' segments between the mime type and ';base64,' are
tolerated. Added a regression test covering the MediaRecorder
shape.
Assisted-by: Claude:Opus 4.7
* fix(insightface): scope pack ONNX loading to known manifests
LocalAI's gallery extracts buffalo_* zips flat into the models
directory, which inevitably mixes with ONNX files from other
backends (opencv face engine, MiniFASNet antispoof, WeSpeaker
voice embedding) and older buffalo pack installs. Feeding those
foreign files into insightface's model_zoo.get_model() blows up
inside the router -- it assumes a 4-D NCHW input and indexes
`input_shape[2]` on tensors that aren't shaped like a face model,
raising IndexError mid-load and leaving the backend unusable.
The router's dispatch isn't amenable to per-file try/except alone
(first-file-wins picks det_10g.onnx from buffalo_l even when the
user asked for buffalo_sc -- alphabetical order happens to favour
the wrong pack). Instead, ship an explicit manifest of the
upstream v0.7 pack contents and scope the glob to that when the
requested pack is known. The manifest is small and stable; future
packs can be added alongside or fall through to the tolerance
loop, which also swallows any remaining IndexError / ValueError
from foreign files with a clear `[insightface] skipped` stderr
line for diagnostics.
Assisted-by: Claude:Opus 4.7
* fix(speaker-recognition): extract FBank features for rank-3 ONNX encoders
Pre-exported speaker-encoder ONNX graphs come in two shapes:
rank-2 [batch, samples] -- some 3D-Speaker exports,
take raw waveform directly.
rank-3 [batch, frames, n_mels] -- WeSpeaker and most Kaldi-
lineage encoders, expect
pre-computed Kaldi FBank.
OnnxDirectEngine unconditionally fed `audio.reshape(1, -1)` --
correct for rank-2, IndexError-on-input_shape[3] on rank-3, which
surfaced to the UI as
"Invalid rank for input: feats Got: 2 Expected: 3"
Detect the input rank at session init and run Kaldi FBank
(80-dim, 25ms/10ms frames, dither=0.0, per-utterance CMN) before
the forward pass when rank>=3. All knobs are configurable via
backend options for encoders that deviate from defaults.
torchaudio.compliance.kaldi is already in the backend's
requirements (SpeechBrain pulls torchaudio in), so no new
dependency.
Assisted-by: Claude:Opus 4.7
* fix(biometrics): isolate face and voice vector stores
Face (ArcFace, 512-D) and voice (ECAPA-TDNN 192-D / WeSpeaker
256-D) biometric embeddings were colliding inside a single
in-memory local-store instance. Enrolling one after the other
failed with
"Try to add key with length N when existing length is M"
because local-store correctly refuses to mix dimensions in one
keyspace.
The registries were constructed with `storeName=""`, which in
StoreBackend() is just a WithModel() call. But ModelLoader's
cache is keyed on `modelID`, not `model` -- so both registries
collapsed to the same `modelID=""` slot and reused the same
backend process despite looking isolated on paper.
Three complementary fixes:
1. application.go -- give each registry a distinct default
namespace ("localai-face-biometrics" /
"localai-voice-biometrics"). The comment claimed
isolation, now it's actually enforced.
2. stores.go -- pass the storeName as both WithModelID and
WithModel so the ModelLoader cache key separates
namespaces and the loader spawns distinct processes.
3. local-store/store.go -- drop the Load() `opts.Model != ""`
guard. It was there to prevent generic model-loading loops
from picking up local-store by accident, but that auto-load
path is being retired; the guard now just blocks legitimate
namespace isolation. opts.Model is treated as a tag; the
per-tuple process isolation upstream handles discrimination.
Assisted-by: Claude:Opus 4.7
* fix(gallery): stale-file cleanup and upgrade-tmp directory safety
Two related robustness fixes for backend install/upgrade:
pkg/downloader/uri.go
OCI downloads passed through
if filepath.Ext(filePath) != "" ...
filePath = filepath.Dir(filePath)
which was intended to redirect file-shaped download targets
into their parent directory for OCI extraction. The heuristic
misfires on directory-shaped paths with a dot-suffix --
gallery.UpgradeBackend uses
tmpPath = "<backendsPath>/<name>.upgrade-tmp"
and Go's filepath.Ext treats ".upgrade-tmp" as an extension.
The rewrite landed the extraction at "<backendsPath>/", which
then **overwrote the real install** (backends/<name>/) with a
flat-layout file and left a stray run.sh at the top level. The
tmp dir itself stayed empty, so the validation step that
checked "<tmpPath>/run.sh" predictably failed with
"upgrade validation failed: run.sh not found in new backend"
Every manual upgrade silently corrupted the backends tree this
way. Guard the rewrite behind "target isn't already an existing
directory" -- InstallBackend / UpgradeBackend both pre-create
the target as a directory, so they get the correct behaviour;
existing file-path callers with a genuine dot-extension still
get the parent redirect.
core/gallery/backends.go
InstallBackend's MkdirAll returned ENOTDIR when something at
the target path was already a file (legacy dev builds dropped
golang backend binaries directly at `<backendsPath>/<name>`
instead of nesting them under their own subdir). That
permanently blocked reinstall and upgrade for anyone carrying
that state, since every retry hit the same error. Detect a
pre-existing non-directory, warn, and remove it before the
MkdirAll so the fresh install can write the correct nested
layout with metadata.json + run.sh.
Assisted-by: Claude:Opus 4.7
* fix(galleryop): refresh upgrade cache after backend ops
UpgradeChecker caches the last upgrade-check result and only
refreshes on the 6-hour tick or after an auto-upgrade cycle.
Manual upgrades (POST /api/backends/upgrade/:name) go through
the async galleryop worker, which completes the upgrade
correctly but never tells UpgradeChecker to re-check -- so
/api/backends/upgrades continued to list a just-upgraded backend
as upgradeable, indistinguishable from a failed upgrade, for up
to six hours.
Add an optional `OnBackendOpCompleted func()` hook on
GalleryService that fires after every successful install /
upgrade / delete on the backend channel (async, so a slow
callback doesn't stall the queue). startup.go wires it to
UpgradeChecker.TriggerCheck after both services exist. Result:
the upgrade banner clears within milliseconds of the worker
finishing.
Assisted-by: Claude:Opus 4.7
* build: prepend GOPATH/bin to PATH for protogen-go
install-go-tools runs `go install` for protoc-gen-go and
protoc-gen-go-grpc, which writes them into `go env GOPATH`/bin.
That directory isn't on every dev's PATH, and protoc resolves
its code-gen plugins via PATH, so the immediately-following
protoc invocation fails with
"protoc-gen-go: program not found"
which in turn blocks `make build` and any
`make backends/%` target that depends on build.
Prepend `go env GOPATH`/bin to PATH for the protoc invocation
so the freshly-installed plugins are found without requiring a
shell-profile change.
Assisted-by: Claude:Opus 4.7
* refactor(ui-api): non-blocking backend upgrade handler with opcache
POST /api/backends/upgrade/:name used to send the ManagementOp
directly onto the unbuffered BackendGalleryChannel, which blocked
the HTTP request whenever the galleryop worker was busy with a
prior operation. The op also didn't show up in /api/operations,
so the Backends UI couldn't reflect upgrade progress on the
affected row.
Register the op in opcache immediately, wrap it in a cancellable
context, store the cancellation function on the GalleryService,
and push onto the channel from a goroutine so the handler
returns right away. Response gains a `jobID` field and a
`message` string so clients have a consistent handle regardless
of whether the op is queued or running.
Pairs with the OnBackendOpCompleted hook added in the galleryop
commit — together the UI sees the upgrade start, watches
progress via /api/operations, and drops the "upgradeable" flag
the moment the worker finishes.
Assisted-by: Claude:Opus 4.7
|
||
|
Ettore Di Giacinto
|
98e5291afc |
feat: refactor build process, drop embedded backends (#5875)
* 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> |
||
|
Ettore Di Giacinto
|
6daef00d30 |
chore(refactor): drop unnecessary code in loader (#4096)
* chore: simplify passing options to ModelOptions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(refactor): do not expose internal backend Loader Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
||
|
Sertaç Özercan
|
5866fc8ded |
chore: fix go.mod module (#2635)
Signed-off-by: Sertac Ozercan <sozercan@gmail.com> |
||
|
Richard Palethorpe
|
643d85d2cc |
feat(stores): Vector store backend (#1795)
Add simple vector store backend Signed-off-by: Richard Palethorpe <io@richiejp.com> |