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https://github.com/mudler/LocalAI.git
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* feat(grpc): add a Forecast RPC for time-series models Add Forecast to the backend service with columnar request and response messages: flat row-major arrays, NaN for missing values, and one message per series so a caller can send series of different shapes in one call. The response keeps the request order. Wire the RPC through the server, client, embedded client, connection evicting client, in-flight tracking client and the base backend, which answers unimplemented. core/backend gains a Forecast helper that stamps the model identity and records a trace, like the other single-purpose RPCs. Assisted-by: Claude:claude-sonnet-5-5 go-vet * feat(config): add the forecast usecase FLAG_FORECAST marks a model as a time-series forecaster. The timestral-cpp backend declares it as its default usecase, so a config with that backend needs no extra lines. The backend is also listed as a non-text backend, so a forecast model is never offered as a chat model. It shows up in the gallery filter and in the capability list. Assisted-by: Claude:claude-sonnet-5-5 go-vet * feat(api): add POST /v1/forecast Take one or more numeric series and return quantile trajectories for the next prediction_length steps. Targets are [variates][steps] or a flat array for one variate; JSON null marks a missing value. Past and known covariates and categorical codes are checked for length before the backend sees them. Quantiles default to 0.1, 0.5 and 0.9 in the backend. The route is gated by a new default-on forecast API feature. The endpoint is listed in the swagger spec, the /api/instructions index, the UI model filter and the capability symbols. Assisted-by: Claude:claude-sonnet-5-5 go-vet * feat(backends): add the timestral-cpp forecast backend Wrap the timestral.cpp C ABI with purego, the way the other ggml backends do: libtimestral is built from a pinned commit with ggml embedded, and the Go binary loads it at start. Forecast validates the counts against the array lengths, groups the series by shape, makes one library call per group and puts the results back in the order the caller sent them. Quantiles default to 0.1, 0.5 and 0.9, and a level the model does not have is refused with the list of valid ones. A mutex guards the handle because the library is not reentrant. Request size is bounded by two model options. The unit specs use a fake library. The integration specs and a gRPC spec run against the 5M F32 model that test.sh downloads and checks against a fixed SHA-256. Assisted-by: Claude:claude-sonnet-5-5 go-vet * build(backends): register timestral-cpp in the build and the library Add the CPU image to the backend matrix for amd64 and arm64, plus an Apple silicon entry that is not built or tested yet. The image has no GPU keys because the engine runs on the CPU only. Wire the make targets, the path filter and the dependency bump bot. The library entries were generated with backendcatalog. The images are not published yet, so the release entries are unpinned until a maintainer runs --repin. The gallery reader test now counts the names in the library instead of a fixed number, so adding a backend does not break it. Assisted-by: Claude:claude-sonnet-5-5 go-vet * feat(gallery): add the Timestral forecast models Add Timestral 5M, 28M, 123M and 209M as F32 entries, each with its F16 build as a variant. Q8_0 and the K-quants are left out until the quality question is settled. Each entry runs on the timestral-cpp backend, on the CPU only. The weights use Mistral's Modified MIT licence, which bars use by companies above a monthly revenue threshold. The first paragraph after the summary says so, the licence file is installed next to the weights, and the revenue-restricted-license tag makes the entries filterable. The memory each build needs has not been measured, so no size is set. Assisted-by: Claude:claude-sonnet-5-5 * docs(forecast): document /v1/forecast and the Timestral models Add a feature page with the request and response shapes, the error cases, the model options and the licence note. List the engine in the README, the compatibility table and the backend categories. Assisted-by: Claude:claude-sonnet-5-5 --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
505 lines
24 KiB
Go
505 lines
24 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("advertises diffusers sound generation", func() {
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capability := GetBackendCapability("diffusers")
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Expect(capability.GRPCMethods).To(ContainElement(MethodSoundGeneration))
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Expect(capability.PossibleUsecases).To(ContainElement(UsecaseSoundGeneration))
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})
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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
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// name, in both directions. Resolving the capability by stripping the prefix
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// while still keying the model-variant switch on the pinned spelling made
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// every variant fall through to the permissive default: cuda12-vibevoice-cpp
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// advertised cloning for the realtime 0.5B model, which cannot do it, and
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// /v1/audio/speech accepted a profile: voice it had to fail on in the backend
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// instead of rejecting it with a 400.
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DescribeTable("resolves the model-variant rule through pinned gallery 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("cuda12-vibevoice-cpp 0.5B stays unsupported", ModelConfig{Name: "vibevoice-cpp-0.5b", Backend: "cuda12-vibevoice-cpp"}, false),
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Entry("cuda12-vibevoice-cpp 1.5B stays supported", ModelConfig{Name: "vibevoice-1.5b", Backend: "cuda12-vibevoice-cpp"}, true),
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Entry("metal-coqui tacotron2 stays unsupported", ModelConfig{Name: "tacotron2-en", Backend: "metal-coqui"}, false),
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Entry("metal-coqui xtts stays supported", ModelConfig{Name: "xtts-v2", Backend: "metal-coqui"}, true),
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Entry("cuda12-crispasr ASR stays unsupported", ModelConfig{Name: "parakeet-asr", Backend: "cuda12-crispasr"}, false),
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Entry("cuda12-crispasr F5 stays supported", ModelConfig{Name: "f5-tts-crispasr", Backend: "cuda12-crispasr"}, true),
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Entry("cpu-qwen3-tts-cpp CustomVoice stays unsupported", ModelConfig{Name: "qwen3-tts-flash", Backend: "cpu-qwen3-tts-cpp"}, false),
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Entry("cpu-qwen3-tts-cpp Base stays supported", ModelConfig{Name: "qwen3-tts-cpp-0.6b-base", Backend: "cpu-qwen3-tts-cpp"}, true),
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Entry("release channel suffix too", ModelConfig{Name: "vibevoice-cpp-0.5b", Backend: "vibevoice-cpp-development"}, false),
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Entry("pinned audio-cpp keeps its unconditional cloning", ModelConfig{Name: "audio-cpp-chatterbox", Backend: "cuda12-audio-cpp"}, true),
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)
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})
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var _ = Describe("TTSVoicesForModel", func() {
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It("returns the built-in Pocket TTS voice catalog", func() {
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voices := TTSVoicesForModel(&ModelConfig{Name: "pocket", Backend: "pocket-tts"})
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Expect(voices).To(ContainElement(TTSVoice{Name: "alba", Language: "en_US", Gender: "female"}))
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Expect(voices).To(ContainElement(TTSVoice{Name: "giovanni", Language: "it_IT", Gender: "male"}))
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})
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It("resolves the catalog for pinned backend variants", func() {
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voices := TTSVoicesForModel(&ModelConfig{Name: "pocket", Backend: "cuda12-pocket-tts"})
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Expect(voices).To(ContainElement(TTSVoice{Name: "alba", Language: "en_US", Gender: "female"}))
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})
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It("prefers model-specific voice metadata", func() {
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configured := []TTSVoice{{Name: "custom", Language: "en_GB"}}
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voices := TTSVoicesForModel(&ModelConfig{
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Backend: "pocket-tts",
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TTSConfig: TTSConfig{Voices: configured},
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})
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Expect(voices).To(Equal(configured))
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})
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})
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// 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())
|
|
})
|
|
})
|
|
|
|
var _ = Describe("Upscale backend declaration", func() {
|
|
It("maps upscale to its dedicated RPC and advertises SD GGML support", func() {
|
|
info := UsecaseInfoMap[UsecaseUpscale]
|
|
Expect(info.Flag).To(Equal(FLAG_UPSCALE))
|
|
Expect(info.GRPCMethod).To(Equal(MethodUpscaleImage))
|
|
cap := GetBackendCapability("stablediffusion-ggml")
|
|
Expect(cap.GRPCMethods).To(ContainElement(MethodUpscaleImage))
|
|
Expect(cap.PossibleUsecases).To(ContainElement(UsecaseUpscale))
|
|
Expect(cap.DefaultUsecases).NotTo(ContainElement(UsecaseUpscale))
|
|
})
|
|
})
|
|
|
|
var _ = Describe("GEM-X motion capability", func() {
|
|
It("discovers motion without advertising animation generation", func() {
|
|
Expect(DefaultUsecasesForBackendCap("gemxcpp")).To(Equal([]string{UsecaseMotion}))
|
|
cfg := &ModelConfig{Backend: "gemxcpp"}
|
|
Expect(cfg.HasUsecases(FLAG_MOTION)).To(BeTrue())
|
|
Expect(cfg.HasUsecases(FLAG_3D_ANIMATION)).To(BeFalse())
|
|
Expect(cfg.HasUsecases(FLAG_DECISIONS)).To(BeFalse())
|
|
decisions := FLAG_DECISIONS
|
|
Expect((&ModelConfig{Backend: "vllm-cpp", KnownUsecases: &decisions}).HasUsecases(FLAG_MOTION)).To(BeFalse())
|
|
Expect(FLAG_MOTION & FLAG_DECISIONS).To(BeZero())
|
|
Expect((&ModelConfig{Backend: "llama-cpp"}).HasUsecases(FLAG_MOTION)).To(BeFalse())
|
|
})
|
|
})
|
|
|
|
var _ = Describe("timestral forecast capability", func() {
|
|
It("discovers forecast on the backend and keeps the model out of chat", func() {
|
|
Expect(DefaultUsecasesForBackendCap("timestral-cpp")).To(Equal([]string{UsecaseForecast}))
|
|
cfg := &ModelConfig{Backend: "timestral-cpp"}
|
|
Expect(cfg.HasUsecases(FLAG_FORECAST)).To(BeTrue())
|
|
Expect(cfg.HasUsecases(FLAG_CHAT)).To(BeFalse())
|
|
Expect(cfg.HasUsecases(FLAG_COMPLETION)).To(BeFalse())
|
|
Expect(cfg.HasUsecases(FLAG_EMBEDDINGS)).To(BeFalse())
|
|
Expect(cfg.HasUsecases(FLAG_DEPTH)).To(BeFalse())
|
|
Expect(cfg.Capabilities()).To(ContainElement(UsecaseForecast))
|
|
Expect(cfg.Capabilities()).NotTo(ContainElement(UsecaseChat))
|
|
})
|
|
|
|
It("keeps chat models and other backends out of forecast", func() {
|
|
Expect((&ModelConfig{Backend: "llama-cpp"}).HasUsecases(FLAG_FORECAST)).To(BeFalse())
|
|
chat := &ModelConfig{Backend: "timestral-cpp"}
|
|
chat.TemplateConfig.UseTokenizerTemplate = true
|
|
Expect(chat.HasUsecases(FLAG_CHAT)).To(BeFalse(), "a timestral model never serves text")
|
|
})
|
|
|
|
It("maps the usecase to its flag, RPC and string form", func() {
|
|
info := UsecaseInfoMap[UsecaseForecast]
|
|
Expect(info.Flag).To(Equal(FLAG_FORECAST))
|
|
Expect(info.GRPCMethod).To(Equal(MethodForecast))
|
|
Expect(GetAllModelConfigUsecases()).To(HaveKeyWithValue("FLAG_FORECAST", FLAG_FORECAST))
|
|
flags := GetUsecasesFromYAML([]string{"forecast"})
|
|
Expect(flags).NotTo(BeNil())
|
|
Expect(*flags).To(Equal(FLAG_FORECAST))
|
|
})
|
|
})
|