LocalAI/pkg/model/initializers.go

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package model
import (
"context"
"errors"
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"fmt"
"os"
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"strings"
"time"
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grpc "github.com/mudler/LocalAI/pkg/grpc"
"github.com/mudler/xlog"
"github.com/phayes/freeport"
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)
feat: do not bundle llama-cpp anymore (#5790) * 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>
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const (
LLamaCPP = "llama-cpp"
IKLLamaCPP = "ik-llama-cpp"
feat: do not bundle llama-cpp anymore (#5790) * 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>
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)
var Aliases = map[string]string{
"go-llama": LLamaCPP,
"llama": LLamaCPP,
"ik_llama": IKLLamaCPP,
"ik-llama": IKLLamaCPP,
"embedded-store": LocalStoreBackend,
"huggingface-embeddings": TransformersBackend,
"transformers-musicgen": TransformersBackend,
"sentencetransformers": TransformersBackend,
"mamba": TransformersBackend,
"stablediffusion": StableDiffusionGGMLBackend,
}
var TypeAlias = map[string]string{
"sentencetransformers": "SentenceTransformer",
"huggingface-embeddings": "SentenceTransformer",
"mamba": "Mamba",
"transformers-musicgen": "MusicgenForConditionalGeneration",
}
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const (
WhisperBackend = "whisper"
StableDiffusionGGMLBackend = "stablediffusion-ggml"
TransformersBackend = "transformers"
LocalStoreBackend = "local-store"
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)
// starts the grpcModelProcess for the backend, and returns a grpc client
// It also loads the model
feat: do not bundle llama-cpp anymore (#5790) * 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>
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func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string, string, string) (*Model, error) {
return func(modelID, modelName, modelFile string) (*Model, error) {
xlog.Debug("Loading Model with gRPC", "modelID", modelID, "file", modelFile, "backend", backend, "options", *o)
feat: add distributed mode (#9124) * feat: add distributed mode (experimental) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix data races, mutexes, transactions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix events and tool stream in agent chat Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * use ginkgo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(cron): compute correctly time boundaries avoiding re-triggering Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not flood of healthy checks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not list obvious backends as text backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * tests fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop redundant healthcheck Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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// Distributed mode: delegate to the model router if set
ml.mu.Lock()
router := ml.modelRouter
ml.mu.Unlock()
if router != nil {
xlog.Info("Routing model to remote node via ModelRouter", "modelID", modelID, "backend", backend)
return router(o.context, backend, modelID, modelName, modelFile, o.gRPCOptions, o.parallelRequests)
}
var client *Model
getFreeAddress := func() (string, error) {
port, err := freeport.GetFreePort()
if err != nil {
return "", fmt.Errorf("failed allocating free ports: %s", err.Error())
}
return fmt.Sprintf("127.0.0.1:%d", port), nil
}
// If no specific model path is set for transformers/HF, set it to the model path
for _, env := range []string{"HF_HOME", "TRANSFORMERS_CACHE", "HUGGINGFACE_HUB_CACHE"} {
if os.Getenv(env) == "" {
err := os.Setenv(env, ml.ModelPath)
if err != nil {
xlog.Error("unable to set environment variable to modelPath", "error", err, "name", env, "modelPath", ml.ModelPath)
}
}
}
// Check if the backend is provided as external
feat: Add backend gallery (#5607) * feat: Add backend gallery This PR add support to manage backends as similar to models. There is now available a backend gallery which can be used to install and remove extra backends. The backend gallery can be configured similarly as a model gallery, and API calls allows to install and remove new backends in runtime, and as well during the startup phase of LocalAI. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add backends docs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * wip: Backend Dockerfile for python backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat: drop extras images, build python backends separately Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixup on all backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * test CI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Tweaks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop old backends leftovers Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixup CI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Move dockerfile upper Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fix proto Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Feature dropped for consistency - we prefer model galleries Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add missing packages in the build image Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * exllama is ponly available on cublas Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * pin torch on chatterbox Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixups to index Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * CI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Debug CI * Install accellerators deps Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add target arch * Add cuda minor version Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Use self-hosted runners Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ci: use quay for test images Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups for vllm and chatterbox Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Small fixups on CI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chatterbox is only available for nvidia Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Simplify CI builds Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Adapt test, use qwen3 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(model gallery): add jina-reranker-v1-tiny-en-gguf Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(gguf-parser): recover from potential panics that can happen while reading ggufs with gguf-parser Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Use reranker from llama.cpp in AIO images Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Limit concurrent jobs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
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if uri, ok := ml.GetAllExternalBackends(o)[backend]; ok {
xlog.Debug("Loading external backend", "uri", uri)
// check if uri is a file or an address
if fi, err := os.Stat(uri); err == nil {
xlog.Debug("external backend is file", "file", fi)
serverAddress, err := getFreeAddress()
if err != nil {
return nil, fmt.Errorf("failed allocating free ports: %s", err.Error())
}
// Make sure the process is executable
process, err := ml.startProcess(uri, modelID, serverAddress)
if err != nil {
xlog.Error("failed to launch", "error", err, "path", uri)
return nil, err
}
xlog.Debug("GRPC Service Started")
client = NewModel(modelID, serverAddress, process)
} else {
xlog.Debug("external backend is a uri")
// address
client = NewModel(modelID, uri, nil)
}
} else {
xlog.Error("Backend not found", "backend", backend)
return nil, fmt.Errorf("backend not found: %s", backend)
}
xlog.Debug("Wait for the service to start up")
xlog.Debug("Options", "options", o.gRPCOptions)
// Wait for the service to start up
ready := false
feat: add distributed mode (#9124) * feat: add distributed mode (experimental) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix data races, mutexes, transactions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix events and tool stream in agent chat Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * use ginkgo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(cron): compute correctly time boundaries avoiding re-triggering Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not flood of healthy checks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not list obvious backends as text backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * tests fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop redundant healthcheck Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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for i := range o.grpcAttempts {
alive, err := client.GRPC(o.parallelRequests, ml.wd).HealthCheck(context.Background())
if alive {
xlog.Debug("GRPC Service Ready")
ready = true
break
}
if err != nil && i == o.grpcAttempts-1 {
xlog.Error("failed starting/connecting to the gRPC service", "error", err)
}
time.Sleep(time.Duration(o.grpcAttemptsDelay) * time.Second)
}
if !ready {
xlog.Debug("GRPC Service NOT ready")
if process := client.Process(); process != nil {
process.Stop()
}
return nil, fmt.Errorf("grpc service not ready")
}
options := *o.gRPCOptions
options.Model = modelName
options.ModelFile = modelFile
options.ModelPath = ml.ModelPath
xlog.Debug("GRPC: Loading model with options", "options", options)
res, err := client.GRPC(o.parallelRequests, ml.wd).LoadModel(o.context, &options)
if err != nil {
if process := client.Process(); process != nil {
process.Stop()
}
return nil, fmt.Errorf("could not load model: %w", err)
}
if !res.Success {
if process := client.Process(); process != nil {
process.Stop()
}
return nil, fmt.Errorf("could not load model (no success): %s", res.Message)
}
return client, nil
}
}
func (ml *ModelLoader) backendLoader(opts ...Option) (client grpc.Backend, err error) {
o := NewOptions(opts...)
xlog.Info("BackendLoader starting", "modelID", o.modelID, "backend", o.backendString, "model", o.model)
backend := strings.ToLower(o.backendString)
if realBackend, exists := Aliases[backend]; exists {
typeAlias, exists := TypeAlias[backend]
if exists {
xlog.Debug("alias is a type alias", "alias", backend, "realBackend", realBackend, "type", typeAlias)
o.gRPCOptions.Type = typeAlias
} else {
xlog.Debug("alias", "alias", backend, "realBackend", realBackend)
}
backend = realBackend
}
model, err := ml.LoadModel(o.modelID, o.model, ml.grpcModel(backend, o))
if err != nil {
fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups (#9652) * fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups Two distinct bugs were causing tight retry loops in the distributed scheduler: 1. FindAndLockNodeWithModel ignored the model's NodeSelector. When a model was loaded on multiple nodes and only some matched the current selector, the function returned the lowest-in_flight node — even one the selector excluded. Route()'s post-check then fell through to scheduleNewModel, which targeted the matching node where the model was already at MaxReplicasPerModel capacity. Eviction couldn't help (the only loaded model on that node was the one being requested, and it was busy), so every request looped through "evicting LRU" → "all models busy". Fix: thread an optional candidateNodeIDs filter through FindAndLockNodeWithModel. Route() resolves the selector once via a new resolveSelectorCandidates helper and passes the matching IDs to both the cached-replica lookup and scheduleNewModel. The same helper replaces the inline selector block in scheduleNewModel. 2. ScheduleAndLoadModel (reconciler scale-up path) fell back to scheduleNewModel with backendType="" when no replica had ever been loaded for a model. The worker rejected the resulting backend.install ("backend name is empty") on every reconciler tick (~30s). Fix: remove the broken fallback. When GetModelLoadInfo has nothing stored, return a clear error instead of firing a doomed NATS install. The reconciler's existing scale-up failure log surfaces it once per tick; the model auto-replicates as soon as Route() serves it once and stores load info. Also downgrade the post-LoadModel-failure StopGRPC error to Debug — that cleanup attempt usually hits "model not found" because LoadModel failed before registering the process, and the outer "Failed to load model" error already carries the real reason. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash] * test(distributed): cover selector-aware FindAndLockNodeWithModel and reconciler scaleup guard Two regression tests for the bugs fixed in the previous commit: 1. FindAndLockNodeWithModel — registry-level integration tests verify the candidateNodeIDs filter: - Returns the included node even when an excluded node has lower in_flight (the original selector-mismatch loop scenario). - Returns not-found when the model is loaded only on excluded nodes, forcing Route() to fall through to a fresh schedule instead of reusing the excluded replica. 2. ScheduleAndLoadModel — mock-based test verifies the reconciler scale-up path returns an error and does NOT fire backend.install when no replica has been loaded yet. fakeUnloader gains an installCalls slice so this negative assertion is direct. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 07:42:14 +00:00
// Defensive cleanup: the model usually wasn't registered yet (LoadModel
// failed before that), so StopGRPC reporting "model not found" is the
// expected case, not an error. The outer Failed-to-load log below
// carries the real reason.
if stopErr := ml.StopGRPC(only(o.modelID)); stopErr != nil {
fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups (#9652) * fix(distributed): honor NodeSelector in cached-replica lookup, stop empty-backend reconciler scaleups Two distinct bugs were causing tight retry loops in the distributed scheduler: 1. FindAndLockNodeWithModel ignored the model's NodeSelector. When a model was loaded on multiple nodes and only some matched the current selector, the function returned the lowest-in_flight node — even one the selector excluded. Route()'s post-check then fell through to scheduleNewModel, which targeted the matching node where the model was already at MaxReplicasPerModel capacity. Eviction couldn't help (the only loaded model on that node was the one being requested, and it was busy), so every request looped through "evicting LRU" → "all models busy". Fix: thread an optional candidateNodeIDs filter through FindAndLockNodeWithModel. Route() resolves the selector once via a new resolveSelectorCandidates helper and passes the matching IDs to both the cached-replica lookup and scheduleNewModel. The same helper replaces the inline selector block in scheduleNewModel. 2. ScheduleAndLoadModel (reconciler scale-up path) fell back to scheduleNewModel with backendType="" when no replica had ever been loaded for a model. The worker rejected the resulting backend.install ("backend name is empty") on every reconciler tick (~30s). Fix: remove the broken fallback. When GetModelLoadInfo has nothing stored, return a clear error instead of firing a doomed NATS install. The reconciler's existing scale-up failure log surfaces it once per tick; the model auto-replicates as soon as Route() serves it once and stores load info. Also downgrade the post-LoadModel-failure StopGRPC error to Debug — that cleanup attempt usually hits "model not found" because LoadModel failed before registering the process, and the outer "Failed to load model" error already carries the real reason. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash] * test(distributed): cover selector-aware FindAndLockNodeWithModel and reconciler scaleup guard Two regression tests for the bugs fixed in the previous commit: 1. FindAndLockNodeWithModel — registry-level integration tests verify the candidateNodeIDs filter: - Returns the included node even when an excluded node has lower in_flight (the original selector-mismatch loop scenario). - Returns not-found when the model is loaded only on excluded nodes, forcing Route() to fall through to a fresh schedule instead of reusing the excluded replica. 2. ScheduleAndLoadModel — mock-based test verifies the reconciler scale-up path returns an error and does NOT fire backend.install when no replica has been loaded yet. fakeUnloader gains an installCalls slice so this negative assertion is direct. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash] --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-04 07:42:14 +00:00
xlog.Debug("cleanup stop after failed load", "error", stopErr, "model", o.modelID)
}
xlog.Error("Failed to load model", "modelID", o.modelID, "error", err, "backend", o.backendString)
feat: do not bundle llama-cpp anymore (#5790) * 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>
2025-07-18 11:24:12 +00:00
return nil, err
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}
return model.GRPC(o.parallelRequests, ml.wd), nil
2023-05-11 14:34:16 +00:00
}
feat(concurrency-groups): per-model exclusive groups for backend loading (#9662) * feat(concurrency-groups): per-model exclusive groups for backend loading Adds `concurrency_groups: [...]` to model YAML configs. Two models that share a group cannot be loaded concurrently on the same node — loading one evicts the others, reusing the existing pinned/busy/retry policy from LRU eviction. Layered design: - Watchdog (pkg/model): per-node correctness floor — on every Load(), evict any loaded model that shares a group with the requested one. Pinned skips surface NeedMore so the loader retries (and ultimately logs a clear warning), instead of silently allowing the rule to be violated. - Distributed scheduler (core/services/nodes): soft anti-affinity hint — scheduleNewModel prefers nodes that don't already host a same-group model, falling back to eviction only if every candidate has a conflict. Composes with NodeSelector at the same point in the candidate pipeline. Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy models running on different nodes is fine. The ConfigLoader is wired into SmartRouter via a small ConcurrencyConflictResolver interface so the nodes package keeps a narrow surface on core/config. Refactors the inner LRU eviction body into a shared collectEvictionsLocked helper and the loader retry loop into retryEnforce(fn, maxRetries, interval), so both LRU and group enforcement share busy/pinned/retry semantics. Closes #9659. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(watchdog): sync pinned + concurrency_groups at startup The startup-time watchdog setup lives in initializeWatchdog (startup.go), not in startWatchdog (watchdog.go). The latter is only invoked from the runtime-settings RestartWatchdog path. As a result, neither SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot, so `pinned: true` and `concurrency_groups: [...]` only became effective after a settings-driven watchdog restart. Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end: loading model A in group "heavy", then C with no group (coexists), then B in group "heavy" now correctly evicts A and leaves [B, C]. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec CI lint runs new-from-merge-base, so the existing pre-existing `defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the one introduced by the concurrency_groups YAML round-trip test is held to errcheck. Wrap the remove in a closure that discards the error. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 06:42:50 +00:00
// retryEnforce repeatedly invokes fn until it returns NeedMore=false or the
// retry budget is exhausted. It sleeps `retryInterval` between attempts and
// logs progress under `label`. Used by both LRU and group-exclusivity
// enforcement so the busy-model wait behaviour is identical.
func retryEnforce(fn func() EnforceLRULimitResult, maxRetries int, retryInterval time.Duration, label string) {
for attempt := range maxRetries {
result := fn()
if !result.NeedMore {
if result.EvictedCount > 0 {
xlog.Info("[ModelLoader] "+label+" enforcement complete", "evicted", result.EvictedCount)
}
return
}
if attempt < maxRetries-1 {
xlog.Info("[ModelLoader] Waiting for busy models to become idle before eviction",
"label", label,
"evicted", result.EvictedCount,
"attempt", attempt+1,
"maxRetries", maxRetries,
"retryIn", retryInterval)
time.Sleep(retryInterval)
} else {
xlog.Warn("[ModelLoader] "+label+" enforcement incomplete after max retries",
"evicted", result.EvictedCount,
"reason", "conflicts are still busy or pinned")
}
}
}
// enforceLRULimit enforces the LRU limit before loading a new model.
// This is called before loading a model to ensure we don't exceed the limit.
// It accounts for models that are currently being loaded by other goroutines.
// If models are busy and can't be evicted, it will wait and retry until space is available.
func (ml *ModelLoader) enforceLRULimit() {
if ml.wd == nil {
return
}
pendingLoads := ml.GetLoadingCount()
ml.mu.Lock()
maxRetries := ml.lruEvictionMaxRetries
retryInterval := ml.lruEvictionRetryInterval
ml.mu.Unlock()
feat(concurrency-groups): per-model exclusive groups for backend loading (#9662) * feat(concurrency-groups): per-model exclusive groups for backend loading Adds `concurrency_groups: [...]` to model YAML configs. Two models that share a group cannot be loaded concurrently on the same node — loading one evicts the others, reusing the existing pinned/busy/retry policy from LRU eviction. Layered design: - Watchdog (pkg/model): per-node correctness floor — on every Load(), evict any loaded model that shares a group with the requested one. Pinned skips surface NeedMore so the loader retries (and ultimately logs a clear warning), instead of silently allowing the rule to be violated. - Distributed scheduler (core/services/nodes): soft anti-affinity hint — scheduleNewModel prefers nodes that don't already host a same-group model, falling back to eviction only if every candidate has a conflict. Composes with NodeSelector at the same point in the candidate pipeline. Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy models running on different nodes is fine. The ConfigLoader is wired into SmartRouter via a small ConcurrencyConflictResolver interface so the nodes package keeps a narrow surface on core/config. Refactors the inner LRU eviction body into a shared collectEvictionsLocked helper and the loader retry loop into retryEnforce(fn, maxRetries, interval), so both LRU and group enforcement share busy/pinned/retry semantics. Closes #9659. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(watchdog): sync pinned + concurrency_groups at startup The startup-time watchdog setup lives in initializeWatchdog (startup.go), not in startWatchdog (watchdog.go). The latter is only invoked from the runtime-settings RestartWatchdog path. As a result, neither SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot, so `pinned: true` and `concurrency_groups: [...]` only became effective after a settings-driven watchdog restart. Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end: loading model A in group "heavy", then C with no group (coexists), then B in group "heavy" now correctly evicts A and leaves [B, C]. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec CI lint runs new-from-merge-base, so the existing pre-existing `defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the one introduced by the concurrency_groups YAML round-trip test is held to errcheck. Wrap the remove in a closure that discards the error. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 06:42:50 +00:00
retryEnforce(func() EnforceLRULimitResult {
return ml.wd.EnforceLRULimit(pendingLoads)
}, maxRetries, retryInterval, "LRU")
}
feat(concurrency-groups): per-model exclusive groups for backend loading (#9662) * feat(concurrency-groups): per-model exclusive groups for backend loading Adds `concurrency_groups: [...]` to model YAML configs. Two models that share a group cannot be loaded concurrently on the same node — loading one evicts the others, reusing the existing pinned/busy/retry policy from LRU eviction. Layered design: - Watchdog (pkg/model): per-node correctness floor — on every Load(), evict any loaded model that shares a group with the requested one. Pinned skips surface NeedMore so the loader retries (and ultimately logs a clear warning), instead of silently allowing the rule to be violated. - Distributed scheduler (core/services/nodes): soft anti-affinity hint — scheduleNewModel prefers nodes that don't already host a same-group model, falling back to eviction only if every candidate has a conflict. Composes with NodeSelector at the same point in the candidate pipeline. Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy models running on different nodes is fine. The ConfigLoader is wired into SmartRouter via a small ConcurrencyConflictResolver interface so the nodes package keeps a narrow surface on core/config. Refactors the inner LRU eviction body into a shared collectEvictionsLocked helper and the loader retry loop into retryEnforce(fn, maxRetries, interval), so both LRU and group enforcement share busy/pinned/retry semantics. Closes #9659. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(watchdog): sync pinned + concurrency_groups at startup The startup-time watchdog setup lives in initializeWatchdog (startup.go), not in startWatchdog (watchdog.go). The latter is only invoked from the runtime-settings RestartWatchdog path. As a result, neither SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot, so `pinned: true` and `concurrency_groups: [...]` only became effective after a settings-driven watchdog restart. Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end: loading model A in group "heavy", then C with no group (coexists), then B in group "heavy" now correctly evicts A and leaves [B, C]. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec CI lint runs new-from-merge-base, so the existing pre-existing `defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the one introduced by the concurrency_groups YAML round-trip test is held to errcheck. Wrap the remove in a closure that discards the error. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 06:42:50 +00:00
// enforceGroupExclusivity evicts every loaded model that shares a concurrency
// group with modelID before loading proceeds. Reuses the LRU retry settings so
// busy conflicts wait for the same window as a busy LRU eviction.
func (ml *ModelLoader) enforceGroupExclusivity(modelID string) {
if ml.wd == nil {
return
}
feat(concurrency-groups): per-model exclusive groups for backend loading (#9662) * feat(concurrency-groups): per-model exclusive groups for backend loading Adds `concurrency_groups: [...]` to model YAML configs. Two models that share a group cannot be loaded concurrently on the same node — loading one evicts the others, reusing the existing pinned/busy/retry policy from LRU eviction. Layered design: - Watchdog (pkg/model): per-node correctness floor — on every Load(), evict any loaded model that shares a group with the requested one. Pinned skips surface NeedMore so the loader retries (and ultimately logs a clear warning), instead of silently allowing the rule to be violated. - Distributed scheduler (core/services/nodes): soft anti-affinity hint — scheduleNewModel prefers nodes that don't already host a same-group model, falling back to eviction only if every candidate has a conflict. Composes with NodeSelector at the same point in the candidate pipeline. Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy models running on different nodes is fine. The ConfigLoader is wired into SmartRouter via a small ConcurrencyConflictResolver interface so the nodes package keeps a narrow surface on core/config. Refactors the inner LRU eviction body into a shared collectEvictionsLocked helper and the loader retry loop into retryEnforce(fn, maxRetries, interval), so both LRU and group enforcement share busy/pinned/retry semantics. Closes #9659. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(watchdog): sync pinned + concurrency_groups at startup The startup-time watchdog setup lives in initializeWatchdog (startup.go), not in startWatchdog (watchdog.go). The latter is only invoked from the runtime-settings RestartWatchdog path. As a result, neither SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot, so `pinned: true` and `concurrency_groups: [...]` only became effective after a settings-driven watchdog restart. Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end: loading model A in group "heavy", then C with no group (coexists), then B in group "heavy" now correctly evicts A and leaves [B, C]. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec CI lint runs new-from-merge-base, so the existing pre-existing `defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the one introduced by the concurrency_groups YAML round-trip test is held to errcheck. Wrap the remove in a closure that discards the error. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 06:42:50 +00:00
ml.mu.Lock()
maxRetries := ml.lruEvictionMaxRetries
retryInterval := ml.lruEvictionRetryInterval
ml.mu.Unlock()
retryEnforce(func() EnforceLRULimitResult {
return ml.wd.EnforceGroupExclusivity(modelID)
}, maxRetries, retryInterval, "group-exclusivity")
}
// updateModelLastUsed updates the last used time for a model (for LRU tracking)
func (ml *ModelLoader) updateModelLastUsed(m *Model) {
if ml.wd == nil || m == nil {
return
}
ml.wd.UpdateLastUsed(m.address)
}
func (ml *ModelLoader) Load(opts ...Option) (grpc.Backend, error) {
o := NewOptions(opts...)
// Return earlier if we have a model already loaded
// (avoid looping through all the backends)
if m := ml.CheckIsLoaded(o.modelID); m != nil {
xlog.Debug("Model already loaded", "model", o.modelID)
// Update last used time for LRU tracking
ml.updateModelLastUsed(m)
client := m.GRPC(o.parallelRequests, ml.wd)
// Wrap remote models so connection errors during inference trigger eviction
if m.Process() == nil {
client = newConnectionEvictingClient(client, o.modelID, func() {
ml.ShutdownModel(o.modelID)
})
}
return client, nil
2023-05-11 14:34:16 +00:00
}
feat(concurrency-groups): per-model exclusive groups for backend loading (#9662) * feat(concurrency-groups): per-model exclusive groups for backend loading Adds `concurrency_groups: [...]` to model YAML configs. Two models that share a group cannot be loaded concurrently on the same node — loading one evicts the others, reusing the existing pinned/busy/retry policy from LRU eviction. Layered design: - Watchdog (pkg/model): per-node correctness floor — on every Load(), evict any loaded model that shares a group with the requested one. Pinned skips surface NeedMore so the loader retries (and ultimately logs a clear warning), instead of silently allowing the rule to be violated. - Distributed scheduler (core/services/nodes): soft anti-affinity hint — scheduleNewModel prefers nodes that don't already host a same-group model, falling back to eviction only if every candidate has a conflict. Composes with NodeSelector at the same point in the candidate pipeline. Per-node, not cluster-wide: VRAM is a node-local resource, and two heavy models running on different nodes is fine. The ConfigLoader is wired into SmartRouter via a small ConcurrencyConflictResolver interface so the nodes package keeps a narrow surface on core/config. Refactors the inner LRU eviction body into a shared collectEvictionsLocked helper and the loader retry loop into retryEnforce(fn, maxRetries, interval), so both LRU and group enforcement share busy/pinned/retry semantics. Closes #9659. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(watchdog): sync pinned + concurrency_groups at startup The startup-time watchdog setup lives in initializeWatchdog (startup.go), not in startWatchdog (watchdog.go). The latter is only invoked from the runtime-settings RestartWatchdog path. As a result, neither SyncPinnedModelsToWatchdog nor SyncModelGroupsToWatchdog ran at boot, so `pinned: true` and `concurrency_groups: [...]` only became effective after a settings-driven watchdog restart. Fix by adding both sync calls to initializeWatchdog. Confirmed end-to-end: loading model A in group "heavy", then C with no group (coexists), then B in group "heavy" now correctly evicts A and leaves [B, C]. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(test): satisfy errcheck on new os.Remove in concurrency_groups spec CI lint runs new-from-merge-base, so the existing pre-existing `defer os.Remove(tmp.Name())` lines are baseline-grandfathered but the one introduced by the concurrency_groups YAML round-trip test is held to errcheck. Wrap the remove in a closure that discards the error. Assisted-by: Claude:claude-opus-4-7 [Claude Code] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 06:42:50 +00:00
// Evict any loaded model that shares a concurrency group with the
// requested one before applying the global LRU cap — group eviction may
// already make room, and otherwise LRU might evict an unrelated model
// only for the group check to immediately evict another.
ml.enforceGroupExclusivity(o.modelID)
// Enforce LRU limit before loading a new model
ml.enforceLRULimit()
// if a backend is defined, return the loader directly
if o.backendString != "" {
client, err := ml.backendLoader(opts...)
if err != nil {
return nil, err
}
// Wrap remote models so connection errors during inference trigger eviction
if m := ml.CheckIsLoaded(o.modelID); m != nil && m.Process() == nil {
client = newConnectionEvictingClient(client, o.modelID, func() {
ml.ShutdownModel(o.modelID)
})
}
return client, nil
}
// Otherwise scan for backends in the asset directory
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var err error
// get backends embedded in the binary
autoLoadBackends := []string{}
// append externalBackends supplied by the user via the CLI
feat: do not bundle llama-cpp anymore (#5790) * 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>
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for b := range ml.GetAllExternalBackends(o) {
autoLoadBackends = append(autoLoadBackends, b)
}
if len(autoLoadBackends) == 0 {
xlog.Error("No backends found")
return nil, fmt.Errorf("no backends found")
}
xlog.Debug("Loading from the following backends (in order)", "backends", autoLoadBackends)
xlog.Info("Trying to load the model", "modelID", o.modelID, "backends", autoLoadBackends)
for _, key := range autoLoadBackends {
xlog.Info("Attempting to load", "backend", key)
options := append(opts, []Option{
WithBackendString(key),
}...)
model, modelerr := ml.backendLoader(options...)
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if modelerr == nil && model != nil {
xlog.Info("Loads OK", "backend", key)
// Wrap remote models so connection errors during inference trigger eviction
if m := ml.CheckIsLoaded(o.modelID); m != nil && m.Process() == nil {
model = newConnectionEvictingClient(model, o.modelID, func() {
ml.ShutdownModel(o.modelID)
})
}
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return model, nil
} else if modelerr != nil {
err = errors.Join(err, fmt.Errorf("[%s]: %w", key, modelerr))
xlog.Info("Fails", "backend", key, "error", modelerr.Error())
} else if model == nil {
err = errors.Join(err, fmt.Errorf("backend %s returned no usable model", key))
xlog.Info("Fails", "backend", key, "error", "backend returned no usable model")
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}
}
return nil, fmt.Errorf("could not load model - all backends returned error: %s", err.Error())
}