Squashed feat/pii-ner-tier-engine rebased onto master (was 45 commits; see
backup/pii-ner-tier-engine-prerebase). Net change:
- privacy-filter.cpp: standalone GGML engine for the openai-privacy-filter
PII/NER token classifier, wired as a LocalAI gRPC backend (CPU/CUDA/Vulkan).
TokenClassify moves off the patched llama.cpp path onto this backend.
- PII filter reworked to be NER-centric (encoder/NER detection tier scanning
whole conversations as one document), with a recreated bounded restricted-
regex secret-matching pattern detector tier alongside it (per-model
pii_detection.builtins / .patterns + core/services/routing/piipattern).
- Detection labelled by source (ner vs pattern); backend trace / confidence /
debug observability; analyze/redact exposed as a synchronous API.
- Instance-wide default detector policy + per-usecase default-on; request
filtering extended to completions, embeddings, edits & Ollama.
- React UI: NER-centric PII editor, detector-models table, pattern/builtins
editor, middleware default-policy UI.
- Gallery: privacy-filter-multilingual token-classify model + NER install
filter; token_classify known_usecase; batch sized to context for NER models.
privacy-filter backend registered in the backend gallery (cpu/vulkan/cuda-13
meta + image entries with a capabilities map) matching its CI matrix jobs,
and an /import-model auto-detect importer (PrivacyFilterImporter, narrow
privacy-filter GGUF detection) replacing the prior pref-only registration.
Reconciled against master's independent evolution:
- Dropped master's PIIPatternOverrides feature (global-pattern runtime
overrides + /api/pii/patterns API + runtime_settings.json persistence). The
per-model NER + pattern-detector design supersedes it; it was built on the
global redactor pattern set this branch replaced.
- Reverted the llama.cpp Score carry-patch (0006-server-task-type-score):
removed the patch and restored master's grpc-server.cpp Score RPC (direct
llama_decode, slot-loop bypass) and LLAMA_VERSION pin, plus master's
model_config validation forbidding score + chat/completion/embeddings on
llama-cpp. token_classify is unaffected (it runs on the privacy-filter
backend, not llama-cpp).
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
The build context shipped to the daemon included several large
untracked directories the image never needs: saved image tarballs
(backend-images), locally-installed backends (local-backends), the
host-built binary (local-ai), the rust target/ build output, and
host node_modules/protoc/tests. This bloated the context to ~23GB.
Exclude them so only the sources the Dockerfile actually copies are
transferred. backend/rust sources stay tracked; only target/ is ignored.
Assisted-by: Claude:claude-opus-4-7 [Claude Code]
Signed-off-by: Richard Palethorpe <io@richiejp.com>
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>
* fix(ci): Avoid matching wrong backend with the same prefix
Signed-off-by: Richard Palethorpe <io@richiejp.com>
* chore(whisper): Use Purego and enable VAD
This replaces the Whisper CGO bindings with our own Purego based module
to make compilation easier.
In addition this allows VAD models to be loaded by Whisper. There is not
much benefit now except that the same backend can be used for VAD and
transcription. Depending on upstream we may also be able to use GPU for
VAD in the future, but presently it is disabled.
Signed-off-by: Richard Palethorpe <io@richiejp.com>
---------
Signed-off-by: Richard Palethorpe <io@richiejp.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* 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>
* fix: clean up Makefile dependencies to allow for parallel builds
* refactor: remove old unused backend from Makefile
* fix: finish removing legacy backend, update piper
* fix: I broke llama... I fixed llama
* feat: give the tests and builds a few threads
* fix: ensure libraries are replaced before build, add dropreplace target
* Fix image build workflows
