mirror of
https://github.com/mudler/LocalAI.git
synced 2026-09-12 22:33:54 -04:00
* 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>
420 lines
20 KiB
Go
420 lines
20 KiB
Go
package config
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import (
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"slices"
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"strings"
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. "github.com/onsi/ginkgo/v2"
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. "github.com/onsi/gomega"
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)
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var _ = Describe("BackendCapabilities", func() {
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It("every backend declares possible/default usecases and gRPC methods", func() {
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for name, cap := range BackendCapabilities {
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Expect(cap.PossibleUsecases).NotTo(BeEmpty(), "backend %q has no possible usecases", name)
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Expect(cap.DefaultUsecases).NotTo(BeEmpty(), "backend %q has no default usecases", name)
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Expect(cap.GRPCMethods).NotTo(BeEmpty(), "backend %q has no gRPC methods", name)
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}
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})
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It("default usecases are a subset of possible usecases", func() {
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for name, cap := range BackendCapabilities {
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for _, d := range cap.DefaultUsecases {
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Expect(cap.PossibleUsecases).To(ContainElement(d), "backend %q: default %q not in possible %v", name, d, cap.PossibleUsecases)
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}
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}
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})
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It("every backend's possible usecases map to a known FLAG_*", func() {
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allFlags := GetAllModelConfigUsecases()
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for name, cap := range BackendCapabilities {
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for _, u := range cap.PossibleUsecases {
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info, ok := UsecaseInfoMap[u]
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Expect(ok).To(BeTrue(), "backend %q: usecase %q not in UsecaseInfoMap", name, u)
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flagName := "FLAG_" + strings.ToUpper(u)
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if _, ok := allFlags[flagName]; ok {
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continue
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}
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// Some usecase names don't transform exactly to FLAG_<UPPER>; fall back to flag value lookup.
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found := false
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for _, flag := range allFlags {
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if flag == info.Flag {
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found = true
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break
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}
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}
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Expect(found).To(BeTrue(), "backend %q: usecase %q flag %d not in GetAllModelConfigUsecases", name, u, info.Flag)
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}
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}
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})
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It("every UsecaseInfoMap entry has a non-zero flag and a gRPC method", func() {
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for name, info := range UsecaseInfoMap {
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Expect(info.Flag).NotTo(Equal(FLAG_ANY), "usecase %q has FLAG_ANY (zero) — should have a real flag", name)
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Expect(info.GRPCMethod).NotTo(BeEmpty(), "usecase %q has no gRPC method", name)
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}
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})
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})
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var _ = Describe("GetBackendCapability", func() {
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It("returns the capability for a known backend", func() {
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cap := GetBackendCapability("llama-cpp")
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Expect(cap).NotTo(BeNil())
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Expect(cap.PossibleUsecases).To(ContainElement("chat"))
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})
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It("normalizes hyphenated names so llama.cpp resolves to llama-cpp", func() {
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Expect(GetBackendCapability("llama.cpp")).NotTo(BeNil())
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})
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It("returns nil for unknown backends", func() {
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Expect(GetBackendCapability("nonexistent")).To(BeNil())
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})
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// The gallery ships one concrete image per hardware capability behind a
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// meta name, and an operator may pin any of them in a model's `backend:`.
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// An exact-match-only lookup silently treated every one of them as an
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// unknown backend, which cost vulkan-localvqe the 16 kHz mono fold its AEC
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// needs and would cost a pinned audio-cpp variant its voice-cloning
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// contract. Same class as #10945.
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It("resolves a pinned hardware variant to its meta backend", func() {
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for _, name := range []string{"cpu-localvqe", "vulkan-localvqe", "metal-localvqe"} {
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capability := GetBackendCapability(name)
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Expect(capability).NotTo(BeNil(), "pinned variant %q must resolve", name)
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Expect(capability.PossibleUsecases).To(ContainElement(UsecaseAudioTransform), name)
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}
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})
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It("resolves a pinned variant that also carries a release channel", func() {
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for _, name := range []string{
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"cuda12-audio-cpp", "cuda13-audio-cpp-development",
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"metal-audio-cpp", "cpu-audio-cpp-development",
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"cuda13-nvidia-l4t-arm64-llama-cpp", "intel-sycl-f16-llama-cpp",
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"metal-darwin-arm64-llama-cpp", "nvidia-l4t-arm64-llama-cpp",
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"rocm-llama-cpp-development", "intel-llama-cpp",
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} {
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Expect(GetBackendCapability(name)).NotTo(BeNil(), "pinned variant %q must resolve", name)
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}
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})
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It("does not invent a capability for a name that only looks like a variant", func() {
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Expect(GetBackendCapability("cpu-nonexistent")).To(BeNil())
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Expect(GetBackendCapability("vulkan-")).To(BeNil())
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})
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// Stripping is a fallback, never a rewrite: a backend registered under its
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// own name keeps its own entry even if that name starts with a prefix.
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It("prefers an exact match over the stripped one", func() {
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BackendCapabilities["cpu-exact-match-probe"] = BackendCapability{
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PossibleUsecases: []string{UsecaseChat},
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Description: "test fixture",
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}
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BackendCapabilities["exact-match-probe"] = BackendCapability{
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PossibleUsecases: []string{UsecaseTTS},
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Description: "test fixture",
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}
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DeferCleanup(func() {
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delete(BackendCapabilities, "cpu-exact-match-probe")
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delete(BackendCapabilities, "exact-match-probe")
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})
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capability := GetBackendCapability("cpu-exact-match-probe")
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Expect(capability).NotTo(BeNil())
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Expect(capability.PossibleUsecases).To(Equal([]string{UsecaseChat}))
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})
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})
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// nemo-speech-cpp fronts four model families from one server, and its
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// PossibleUsecases is their union. The entry has to stay in step with what
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// docs/content/features/nemo-speech-cpp.md tells operators to put in
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// known_usecases: nothing validates known_usecases against PossibleUsecases, so
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// a flag the docs recommend and the map omits fails silently, and the place it
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// surfaces is the gallery. GET /api/backends/usecases is derived from this list
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// and greys out the filters missing from it, so a recommended-but-unlisted flag
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// hides the very models it was recommended for.
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var _ = Describe("nemo-speech-cpp capabilities", func() {
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It("advertises every usecase its four families serve", func() {
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capability := GetBackendCapability("nemo-speech-cpp")
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Expect(capability).NotTo(BeNil())
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Expect(capability.PossibleUsecases).To(ContainElements(
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UsecaseTranscript, UsecaseDiarization, UsecaseTTS,
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UsecaseCompletion, UsecaseChat))
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})
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// Chat is the translation family's usecase, and it needs both Predict RPCs:
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// /v1/chat/completions streams through PredictStream and answers
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// non-streaming requests through Predict.
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It("backs the chat usecase with the RPCs chat actually drives", func() {
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capability := GetBackendCapability("nemo-speech-cpp")
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Expect(capability.GRPCMethods).To(ContainElements(MethodPredict, MethodPredictStream))
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})
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// Defaults stay conservative: a bare `backend: nemo-speech-cpp` with no
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// known_usecases is overwhelmingly an ASR model, and every other family is
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// expected to pin its own flags.
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It("still defaults to transcript alone", func() {
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Expect(DefaultUsecasesForBackendCap("nemo-speech-cpp")).To(Equal([]string{UsecaseTranscript}))
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})
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})
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var _ = Describe("MLX embedding capabilities", func() {
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It("does not advertise RPCs that the backends return as unimplemented", func() {
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for _, name := range []string{"mlx", "mlx-distributed", "mlx-vlm"} {
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capability := GetBackendCapability(name)
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Expect(capability).NotTo(BeNil())
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Expect(capability.GRPCMethods).ToNot(ContainElement(MethodEmbedding), name)
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Expect(capability.PossibleUsecases).ToNot(ContainElement(UsecaseEmbeddings), name)
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}
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})
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})
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// audio-cpp advertises voice cloning from the backend itself and ships
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// audio-cpp-chatterbox, whose family serves cloning and NOT plain TTS, so a
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// reference clip is the only way to use it. Without a capability entry
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// VoiceCloningForModel returns nil before it ever reads the model's own
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// tts.voice_cloning override, so `voice: "profile:<id>"` was refused with a 400
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// for every audio-cpp model and no model YAML could rescue it.
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var _ = Describe("audio-cpp capabilities", func() {
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It("is registered", func() {
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Expect(GetBackendCapability("audio-cpp")).NotTo(BeNil())
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})
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It("advertises the RPCs its families actually serve", func() {
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capability := GetBackendCapability("audio-cpp")
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Expect(capability.GRPCMethods).To(ContainElements(
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MethodTTS, MethodTTSStream, MethodAudioTranscription,
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MethodVAD, MethodDiarize, MethodSoundGeneration, MethodAudioTransform))
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Expect(capability.PossibleUsecases).To(ContainElements(
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UsecaseTTS, UsecaseTranscript, UsecaseVAD, UsecaseDiarization,
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UsecaseSoundGeneration, UsecaseAudioTransform))
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})
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It("carries the reference-audio contract, for pinned variants too", func() {
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for _, name := range []string{"audio-cpp", "cuda12-audio-cpp", "metal-audio-cpp"} {
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cloning := VoiceCloningForModel(&ModelConfig{Backend: name})
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Expect(cloning).NotTo(BeNil(), "%q must reach the backend with a profile voice", name)
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Expect(cloning.AcceptedAudioFormats).To(ContainElement("audio/wav"))
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}
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})
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// The families audio-cpp reaches through AudioTransform are separation and
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// conversion, which refuse any rate but their checkpoint's own.
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It("does not ask for the 16 kHz mono fold", func() {
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Expect(AudioTransformRequiresMono16kInput("audio-cpp")).To(BeFalse())
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})
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})
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// The fold to 16 kHz mono in /audio/transform is opt-IN. It used to be
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// unconditional, which made source separation unreachable through the HTTP
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// API: htdemucs and mel_band_roformer refuse any rate but their checkpoint's
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// own and separate using the stereo image, so every such request died with an
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// INTERNAL raised inside the engine while the same call over gRPC worked.
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var _ = Describe("AudioTransformRequiresMono16kInput", func() {
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It("folds for localvqe, whose AEC is trained on 16 kHz mono", func() {
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Expect(AudioTransformRequiresMono16kInput("localvqe")).To(BeTrue())
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})
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// Pinned gallery variants are the same engine and must fold identically.
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// They did not: the lookup was exact-match only, so vulkan-localvqe was an
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// unknown backend, lost the fold that used to be unconditional, and started
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// failing inside LocalVQE. The usecase gate is no substitute, because
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// BuildFilteredFirstAvailableDefaultModel returns early once the client
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// names a model explicitly.
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It("folds for every pinned localvqe variant the gallery ships", func() {
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Expect(AudioTransformRequiresMono16kInput("cpu-localvqe")).To(BeTrue())
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Expect(AudioTransformRequiresMono16kInput("vulkan-localvqe")).To(BeTrue())
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Expect(AudioTransformRequiresMono16kInput("metal-localvqe")).To(BeTrue())
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})
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It("does not fold for a backend that has not asked for it", func() {
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// Registered, and deliberately NOT folding: its separation and
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// conversion families refuse any rate but their checkpoint's own.
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Expect(AudioTransformRequiresMono16kInput("audio-cpp")).To(BeFalse())
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Expect(AudioTransformRequiresMono16kInput("nonexistent")).To(BeFalse())
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Expect(AudioTransformRequiresMono16kInput("")).To(BeFalse())
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})
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It("is claimed by no other registered backend", func() {
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for name, capability := range BackendCapabilities {
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if name == "localvqe" {
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continue
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}
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Expect(capability.AudioTransformInputMono16k).To(BeFalse(),
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"backend %q asks for the 16 kHz mono fold; that has to be a deliberate, documented need", name)
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}
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})
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})
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var _ = Describe("VoiceCloningForModel", func() {
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voiceCloningSetting := func(enabled bool) *bool { return &enabled }
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DescribeTable("advertises only compatible model variants",
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func(cfg ModelConfig, expected bool) {
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Expect(VoiceCloningForModel(&cfg) != nil).To(Equal(expected))
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},
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Entry("Qwen C++ Base", ModelConfig{Name: "qwen3-tts-cpp-0.6b-base", Backend: "qwen3-tts-cpp"}, true),
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Entry("Qwen C++ CustomVoice", ModelConfig{Name: "qwen3-tts-cpp-customvoice", Backend: "qwen3-tts-cpp"}, false),
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Entry("VibeVoice realtime 0.5B", ModelConfig{Name: "vibevoice-cpp-0.5b", Backend: "vibevoice-cpp"}, false),
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Entry("VibeVoice 1.5B", ModelConfig{Name: "vibevoice-1.5b", Backend: "vibevoice-cpp"}, true),
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Entry("F5 through CrispASR", ModelConfig{Name: "f5-tts-crispasr", Backend: "crispasr"}, true),
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Entry("ASR through CrispASR", ModelConfig{Name: "parakeet-crispasr", Backend: "crispasr"}, false),
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Entry("VoxCPM", ModelConfig{Name: "voxcpm-1.5", Backend: "voxcpm"}, true),
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Entry("unsupported Piper", ModelConfig{Name: "piper", Backend: "piper"}, false),
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Entry("typed custom opt-in", ModelConfig{Name: "private-build", Backend: "qwen3-tts-cpp", TTSConfig: TTSConfig{VoiceCloning: voiceCloningSetting(true)}}, true),
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Entry("typed opt-out", ModelConfig{Name: "voxcpm-1.5", Backend: "voxcpm", TTSConfig: TTSConfig{VoiceCloning: voiceCloningSetting(false)}}, false),
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Entry("typed setting wins over compatibility option", ModelConfig{Name: "private-build", Backend: "qwen3-tts-cpp", TTSConfig: TTSConfig{VoiceCloning: voiceCloningSetting(true)}, Options: []string{"voice_cloning:false"}}, true),
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Entry("legacy option custom opt-in", ModelConfig{Name: "private-build", Backend: "qwen3-tts-cpp", Options: []string{"voice_cloning:true"}}, true),
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Entry("legacy option opt-out", ModelConfig{Name: "voxcpm-1.5", Backend: "voxcpm", Options: []string{"voice_cloning=false"}}, false),
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)
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// A pinned gallery variant must reach the SAME per-backend rule as the meta
|
|
// name, in both directions. Resolving the capability by stripping the prefix
|
|
// while still keying the model-variant switch on the pinned spelling made
|
|
// every variant fall through to the permissive default: cuda12-vibevoice-cpp
|
|
// advertised cloning for the realtime 0.5B model, which cannot do it, and
|
|
// /v1/audio/speech accepted a profile: voice it had to fail on in the backend
|
|
// instead of rejecting it with a 400.
|
|
DescribeTable("resolves the model-variant rule through pinned gallery variants",
|
|
func(cfg ModelConfig, expected bool) {
|
|
Expect(VoiceCloningForModel(&cfg) != nil).To(Equal(expected))
|
|
},
|
|
Entry("cuda12-vibevoice-cpp 0.5B stays unsupported", ModelConfig{Name: "vibevoice-cpp-0.5b", Backend: "cuda12-vibevoice-cpp"}, false),
|
|
Entry("cuda12-vibevoice-cpp 1.5B stays supported", ModelConfig{Name: "vibevoice-1.5b", Backend: "cuda12-vibevoice-cpp"}, true),
|
|
Entry("metal-coqui tacotron2 stays unsupported", ModelConfig{Name: "tacotron2-en", Backend: "metal-coqui"}, false),
|
|
Entry("metal-coqui xtts stays supported", ModelConfig{Name: "xtts-v2", Backend: "metal-coqui"}, true),
|
|
Entry("cuda12-crispasr ASR stays unsupported", ModelConfig{Name: "parakeet-asr", Backend: "cuda12-crispasr"}, false),
|
|
Entry("cuda12-crispasr F5 stays supported", ModelConfig{Name: "f5-tts-crispasr", Backend: "cuda12-crispasr"}, true),
|
|
Entry("cpu-qwen3-tts-cpp CustomVoice stays unsupported", ModelConfig{Name: "qwen3-tts-flash", Backend: "cpu-qwen3-tts-cpp"}, false),
|
|
Entry("cpu-qwen3-tts-cpp Base stays supported", ModelConfig{Name: "qwen3-tts-cpp-0.6b-base", Backend: "cpu-qwen3-tts-cpp"}, true),
|
|
Entry("release channel suffix too", ModelConfig{Name: "vibevoice-cpp-0.5b", Backend: "vibevoice-cpp-development"}, false),
|
|
Entry("pinned audio-cpp keeps its unconditional cloning", ModelConfig{Name: "audio-cpp-chatterbox", Backend: "cuda12-audio-cpp"}, true),
|
|
)
|
|
})
|
|
|
|
// llama.cpp serves Qwen3-TTS as well as the text LLMs it is known for, so the
|
|
// backend has to advertise TTS. That advertisement is what makes narrowing
|
|
// mandatory: the per-backend switch in VoiceCloningForModel ends in a
|
|
// permissive default, so an unnarrowed llama-cpp entry would offer
|
|
// reference-audio cloning on every GGUF chat model in the gallery.
|
|
var _ = Describe("llama-cpp TTS capabilities", func() {
|
|
It("advertises the TTS RPCs and usecase", func() {
|
|
capability := GetBackendCapability("llama-cpp")
|
|
Expect(capability).NotTo(BeNil())
|
|
Expect(capability.GRPCMethods).To(ContainElements(MethodTTS, MethodTTSStream))
|
|
Expect(capability.PossibleUsecases).To(ContainElement(UsecaseTTS))
|
|
})
|
|
|
|
// The gallery filter and the model importer both read DefaultUsecases, and a
|
|
// bare GGUF served by llama.cpp is a chat model, not a TTS model.
|
|
It("keeps chat as its only default usecase", func() {
|
|
Expect(GetBackendCapability("llama-cpp").DefaultUsecases).To(Equal([]string{UsecaseChat}))
|
|
})
|
|
|
|
ttsModel := func(backend string) ModelConfig {
|
|
cfg := ModelConfig{Name: "qwen3-tts-llamacpp", Backend: backend}
|
|
cfg.KnownUsecaseStrings = []string{"tts"}
|
|
cfg.syncKnownUsecasesFromString()
|
|
return cfg
|
|
}
|
|
|
|
It("resolves voice cloning for a model that declares the TTS usecase", func() {
|
|
cfg := ttsModel("llama-cpp")
|
|
cloning := VoiceCloningForModel(&cfg)
|
|
Expect(cloning).NotTo(BeNil())
|
|
Expect(cloning.AcceptedAudioFormats).To(ContainElement("audio/wav"))
|
|
})
|
|
|
|
// The spec that constrains the fix. Every one of these is an ordinary
|
|
// llama.cpp text model, and none of them may be offered in the Voice
|
|
// Library or accept a localai://voice-profiles/... reference.
|
|
DescribeTable("never resolves voice cloning for an ordinary llama.cpp model",
|
|
func(cfg ModelConfig) {
|
|
Expect(VoiceCloningForModel(&cfg)).To(BeNil())
|
|
},
|
|
Entry("plain chat model", ModelConfig{Name: "qwen3-8b", Backend: "llama-cpp"}),
|
|
Entry("auto-detected GGUF with no backend pinned", ModelConfig{Name: "mistral-7b"}),
|
|
Entry("a vision model with an mmproj", ModelConfig{Name: "gemma-3-12b", Backend: "llama-cpp", LLMConfig: LLMConfig{MMProj: "mmproj-gemma-3-12b.gguf"}}),
|
|
Entry("a chat model whose name happens to say base", ModelConfig{Name: "llama-3.1-8b-base", Backend: "llama-cpp"}),
|
|
Entry("a pinned hardware variant", ModelConfig{Name: "qwen3-8b", Backend: "cuda12-llama-cpp"}),
|
|
)
|
|
|
|
// A declared-TTS model must keep its contract through the pinned gallery
|
|
// variants an operator can put in `backend:`, the same way vibevoice-cpp
|
|
// and crispasr do.
|
|
DescribeTable("resolves through pinned gallery variants",
|
|
func(backend string) {
|
|
cfg := ttsModel(backend)
|
|
Expect(VoiceCloningForModel(&cfg)).NotTo(BeNil())
|
|
},
|
|
Entry("cuda12", "cuda12-llama-cpp"),
|
|
Entry("vulkan", "vulkan-llama-cpp"),
|
|
Entry("metal darwin arm64", "metal-darwin-arm64-llama-cpp"),
|
|
Entry("development channel", "llama-cpp-development"),
|
|
)
|
|
|
|
// tts.voice_cloning is the documented escape hatch for a custom build. It
|
|
// only ever reaches the operator once the backend carries the contract at
|
|
// all, which is precisely what the unregistered entry prevented.
|
|
It("still honours an explicit opt-out on a declared-TTS model", func() {
|
|
cfg := ttsModel("llama-cpp")
|
|
disabled := false
|
|
cfg.TTSConfig.VoiceCloning = &disabled
|
|
Expect(VoiceCloningForModel(&cfg)).To(BeNil())
|
|
})
|
|
})
|
|
|
|
var _ = Describe("IsValidUsecaseForBackend", func() {
|
|
It("accepts a backend's declared usecases", func() {
|
|
Expect(IsValidUsecaseForBackend("piper", "tts")).To(BeTrue())
|
|
})
|
|
|
|
It("rejects usecases outside a backend's possible set", func() {
|
|
Expect(IsValidUsecaseForBackend("piper", "chat")).To(BeFalse())
|
|
})
|
|
|
|
It("is permissive for unknown backends", func() {
|
|
Expect(IsValidUsecaseForBackend("unknown", "anything")).To(BeTrue())
|
|
})
|
|
})
|
|
|
|
var _ = Describe("IsLlamaCppBackend", func() {
|
|
DescribeTable("classifies a backend name",
|
|
func(backend string, expected bool) {
|
|
Expect(IsLlamaCppBackend(backend)).To(Equal(expected))
|
|
},
|
|
Entry("meta name", "llama-cpp", true),
|
|
Entry("dotted spelling", "llama.cpp", true),
|
|
Entry("auto-detect (empty)", "", true),
|
|
Entry("development channel", "llama-cpp-development", true),
|
|
Entry("quantization channel", "llama-cpp-quantization", true),
|
|
Entry("vulkan variant", "vulkan-llama-cpp", true),
|
|
Entry("cuda 12 variant", "cuda12-llama-cpp", true),
|
|
Entry("cuda 13 variant", "cuda13-llama-cpp", true),
|
|
Entry("jetson variant", "cuda13-nvidia-l4t-arm64-llama-cpp", true),
|
|
Entry("rocm variant", "rocm-llama-cpp", true),
|
|
Entry("metal variant", "metal-llama-cpp", true),
|
|
Entry("intel sycl f16 variant", "intel-sycl-f16-llama-cpp", true),
|
|
Entry("intel sycl f32 variant", "intel-sycl-f32-llama-cpp", true),
|
|
Entry("cpu variant", "cpu-llama-cpp", true),
|
|
Entry("variant on the development channel", "rocm-llama-cpp-development", true),
|
|
Entry("darwin quantization variant", "metal-darwin-arm64-llama-cpp-quantization", true),
|
|
// ik-llama.cpp is a distinct engine that merely shares the suffix.
|
|
Entry("ik-llama-cpp", "ik-llama-cpp", false),
|
|
Entry("ik-llama-cpp development", "ik-llama-cpp-development", false),
|
|
Entry("cpu ik-llama-cpp", "cpu-ik-llama-cpp", false),
|
|
Entry("cpu ik-llama-cpp development", "cpu-ik-llama-cpp-development", false),
|
|
Entry("vllm", "vllm", false),
|
|
Entry("mlx", "mlx", false),
|
|
Entry("whisper", "whisper", false),
|
|
Entry("bark-cpp", "bark-cpp", false),
|
|
)
|
|
})
|
|
|
|
var _ = Describe("AllBackendNames", func() {
|
|
It("returns 30+ backends in sorted order", func() {
|
|
names := AllBackendNames()
|
|
Expect(len(names)).To(BeNumerically(">=", 30))
|
|
Expect(slices.IsSorted(names)).To(BeTrue())
|
|
})
|
|
})
|