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https://github.com/mudler/LocalAI.git
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Add a routing middleware stack and a cloud-proxy backend. * cloud-proxy: a Go gRPC backend that forwards OpenAI- and Anthropic-shaped chat requests to upstream providers, with an optional translate mode (OpenAI request -> Anthropic /v1/messages -> OpenAI response) and full tool-calling support. * routing: admission control, content-aware model routing (embedding cache + classifier + rerank + Arch-Router score), PII detection/redaction (regex + NER) with streaming filter and OpenAI/Anthropic adapters, and a per-user/per-key billing recorder backed by GORM or in-memory storage. * middleware: UsageMiddleware records usage via the billing recorder, plus admission, route-model, usage-stamp and trace middlewares. * observability: BackendTrace ring buffer stores full request bodies (capped), MITM proxy emits structured trace events, and router classifier decisions surface at /api/router/decide. * gallery: Arch-Router-1.5B (Q4_K_M and Q8_0). * UI: cloud-proxy model-editor fields, classifier system-prompt and score-normalization config, and a Traces page rendering request bodies. Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash] Signed-off-by: Richard Palethorpe <io@richiejp.com>
336 lines
9.5 KiB
Go
336 lines
9.5 KiB
Go
package backend
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import (
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"encoding/json"
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"fmt"
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"math/rand/v2"
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"os"
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"path/filepath"
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"strings"
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"time"
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"github.com/mudler/LocalAI/core/config"
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"github.com/mudler/LocalAI/core/trace"
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pb "github.com/mudler/LocalAI/pkg/grpc/proto"
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"github.com/mudler/LocalAI/pkg/model"
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"github.com/mudler/xlog"
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)
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// recordModelLoadFailure records a backend trace when model loading fails.
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func recordModelLoadFailure(appConfig *config.ApplicationConfig, modelName, backend string, err error, data map[string]any) {
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if !appConfig.EnableTracing {
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return
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}
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trace.InitBackendTracingIfEnabled(appConfig.TracingMaxItems, appConfig.TracingMaxBodyBytes)
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trace.RecordBackendTrace(trace.BackendTrace{
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Timestamp: time.Now(),
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Type: trace.BackendTraceModelLoad,
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ModelName: modelName,
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Backend: backend,
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Summary: "Model load failed",
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Error: err.Error(),
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Data: data,
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})
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}
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func ModelOptions(c config.ModelConfig, so *config.ApplicationConfig, opts ...model.Option) []model.Option {
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name := c.Name
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if name == "" {
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name = c.Model
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}
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defOpts := []model.Option{
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model.WithBackendString(c.Backend),
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model.WithModel(c.Model),
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model.WithContext(so.Context),
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model.WithModelID(name),
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}
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threads := 1
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if c.Threads != nil {
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threads = *c.Threads
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}
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if so.Threads != 0 {
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threads = so.Threads
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}
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c.Threads = &threads
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grpcOpts := grpcModelOpts(c, so.SystemState.Model.ModelsPath)
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defOpts = append(defOpts, model.WithLoadGRPCLoadModelOpts(grpcOpts))
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defOpts = append(defOpts, model.EnableParallelRequests)
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if c.GRPC.Attempts != 0 {
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defOpts = append(defOpts, model.WithGRPCAttempts(c.GRPC.Attempts))
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}
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if c.GRPC.AttemptsSleepTime != 0 {
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defOpts = append(defOpts, model.WithGRPCAttemptsDelay(c.GRPC.AttemptsSleepTime))
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}
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for k, v := range so.ExternalGRPCBackends {
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defOpts = append(defOpts, model.WithExternalBackend(k, v))
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}
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return append(defOpts, opts...)
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}
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func getSeed(c config.ModelConfig) int32 {
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var seed int32 = config.RAND_SEED
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if c.Seed != nil {
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seed = int32(*c.Seed)
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}
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if seed == config.RAND_SEED {
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seed = rand.Int32()
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}
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return seed
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}
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func grpcModelOpts(c config.ModelConfig, modelPath string) *pb.ModelOptions {
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b := 512
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if c.Batch != 0 {
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b = c.Batch
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}
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flashAttention := "auto"
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if c.FlashAttention != nil {
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flashAttention = *c.FlashAttention
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}
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f16 := false
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if c.F16 != nil {
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f16 = *c.F16
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}
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embeddings := false
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if c.Embeddings != nil {
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embeddings = *c.Embeddings
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}
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lowVRAM := false
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if c.LowVRAM != nil {
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lowVRAM = *c.LowVRAM
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}
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reranking := false
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if c.Reranking != nil {
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reranking = *c.Reranking
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}
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mmap := false
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if c.MMap != nil {
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mmap = *c.MMap
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}
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// Intel SYCL backend has issues with mmap enabled
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// See: https://github.com/mudler/LocalAI/issues/9012
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// Automatically disable mmap for Intel SYCL backends
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if c.Backend != "" {
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if strings.Contains(strings.ToLower(c.Backend), "intel") || strings.Contains(strings.ToLower(c.Backend), "sycl") {
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mmap = false
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xlog.Info("Auto-disabling mmap for Intel SYCL backend", "backend", c.Backend)
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}
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}
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ctxSize := 4096
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if c.ContextSize != nil {
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ctxSize = *c.ContextSize
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}
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mmlock := false
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if c.MMlock != nil {
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mmlock = *c.MMlock
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}
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nGPULayers := 9999999
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if c.NGPULayers != nil {
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nGPULayers = *c.NGPULayers
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}
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triggers := make([]*pb.GrammarTrigger, 0)
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for _, t := range c.FunctionsConfig.GrammarConfig.GrammarTriggers {
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triggers = append(triggers, &pb.GrammarTrigger{
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Word: t.Word,
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})
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}
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engineArgsJSON := ""
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if len(c.EngineArgs) > 0 {
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buf, err := json.Marshal(c.EngineArgs)
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if err != nil {
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// ModelConfig.Validate() rejects unmarshalable engine_args at
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// config load, so reaching here means the validator was bypassed.
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// Silently dropping user-set options would change runtime behaviour
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// without warning — fail loud instead.
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panic(fmt.Sprintf("engine_args marshal failed for model %q: %v (Validate() should have caught this)", c.Model, err))
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}
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engineArgsJSON = string(buf)
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}
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opts := &pb.ModelOptions{
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CUDA: c.CUDA || c.Diffusers.CUDA,
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SchedulerType: c.Diffusers.SchedulerType,
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GrammarTriggers: triggers,
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PipelineType: c.Diffusers.PipelineType,
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CFGScale: c.CFGScale,
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LoraAdapter: c.LoraAdapter,
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LoraScale: c.LoraScale,
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LoraAdapters: c.LoraAdapters,
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LoraScales: c.LoraScales,
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F16Memory: f16,
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LoraBase: c.LoraBase,
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IMG2IMG: c.Diffusers.IMG2IMG,
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CLIPModel: c.Diffusers.ClipModel,
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CLIPSubfolder: c.Diffusers.ClipSubFolder,
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Options: c.Options,
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Overrides: c.Overrides,
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EngineArgs: engineArgsJSON,
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CLIPSkip: int32(c.Diffusers.ClipSkip),
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ControlNet: c.Diffusers.ControlNet,
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ContextSize: int32(ctxSize),
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Seed: getSeed(c),
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NBatch: int32(b),
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NoMulMatQ: c.NoMulMatQ,
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DraftModel: c.DraftModel,
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AudioPath: c.AudioPath,
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Quantization: c.Quantization,
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LoadFormat: c.LoadFormat,
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GPUMemoryUtilization: c.GPUMemoryUtilization,
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TrustRemoteCode: c.TrustRemoteCode,
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EnforceEager: c.EnforceEager,
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SwapSpace: int32(c.SwapSpace),
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MaxModelLen: int32(c.MaxModelLen),
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TensorParallelSize: int32(c.TensorParallelSize),
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DisableLogStatus: c.DisableLogStatus,
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DType: c.DType,
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// LimitMMPerPrompt vLLM
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LimitImagePerPrompt: int32(c.LimitMMPerPrompt.LimitImagePerPrompt),
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LimitVideoPerPrompt: int32(c.LimitMMPerPrompt.LimitVideoPerPrompt),
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LimitAudioPerPrompt: int32(c.LimitMMPerPrompt.LimitAudioPerPrompt),
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FlashAttention: flashAttention,
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CacheTypeKey: c.CacheTypeK,
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CacheTypeValue: c.CacheTypeV,
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NoKVOffload: c.NoKVOffloading,
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YarnExtFactor: c.YarnExtFactor,
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YarnAttnFactor: c.YarnAttnFactor,
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YarnBetaFast: c.YarnBetaFast,
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YarnBetaSlow: c.YarnBetaSlow,
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NGQA: c.NGQA,
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RMSNormEps: c.RMSNormEps,
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MLock: mmlock,
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RopeFreqBase: c.RopeFreqBase,
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RopeScaling: c.RopeScaling,
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Type: c.ModelType,
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RopeFreqScale: c.RopeFreqScale,
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NUMA: c.NUMA,
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Embeddings: embeddings,
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Reranking: reranking,
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LowVRAM: lowVRAM,
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NGPULayers: int32(nGPULayers),
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MMap: mmap,
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MainGPU: c.MainGPU,
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Threads: int32(*c.Threads),
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TensorSplit: c.TensorSplit,
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// RWKV
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Tokenizer: c.Tokenizer,
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}
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if c.Backend == "cloud-proxy" {
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opts.Proxy = &pb.ProxyOptions{
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UpstreamUrl: c.Proxy.UpstreamURL,
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Mode: c.Proxy.Mode,
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Provider: c.Proxy.Provider,
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ApiKeyEnv: c.Proxy.APIKeyEnv,
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ApiKeyFile: c.Proxy.APIKeyFile,
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UpstreamModel: c.Proxy.UpstreamModel,
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RequestTimeoutSeconds: int32(c.Proxy.RequestTimeoutSeconds),
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}
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}
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if c.MMProj != "" {
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opts.MMProj = filepath.Join(modelPath, c.MMProj)
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}
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// Resolve draft_model against the models directory, mirroring the
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// handling of parameters.model and mmproj. Always joining (without an
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// IsAbs shortcut) prevents user-supplied configs from pointing the
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// backend at arbitrary host files via an absolute path.
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if c.DraftModel != "" {
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opts.DraftModel = filepath.Join(modelPath, c.DraftModel)
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}
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return opts
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}
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func gRPCPredictOpts(c config.ModelConfig, modelPath string) *pb.PredictOptions {
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promptCachePath := ""
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if c.PromptCachePath != "" {
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p := filepath.Join(modelPath, c.PromptCachePath)
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err := os.MkdirAll(filepath.Dir(p), 0750)
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if err == nil {
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promptCachePath = p
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} else {
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xlog.Error("error creating prompt cache folder", "error", err, "promptCachePath", promptCachePath)
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}
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}
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pbOpts := &pb.PredictOptions{
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Temperature: float32(*c.Temperature),
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TopP: float32(*c.TopP),
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NDraft: c.NDraft,
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TopK: int32(*c.TopK),
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MinP: float32(*c.MinP),
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Tokens: int32(*c.Maxtokens),
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Threads: int32(*c.Threads),
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PromptCacheAll: *c.PromptCacheAll,
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PromptCacheRO: c.PromptCacheRO,
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PromptCachePath: promptCachePath,
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F16KV: *c.F16,
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DebugMode: *c.Debug,
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Grammar: c.Grammar,
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NegativePromptScale: c.NegativePromptScale,
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RopeFreqBase: c.RopeFreqBase,
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RopeFreqScale: c.RopeFreqScale,
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NegativePrompt: c.NegativePrompt,
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Mirostat: int32(*c.LLMConfig.Mirostat),
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MirostatETA: float32(*c.LLMConfig.MirostatETA),
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MirostatTAU: float32(*c.LLMConfig.MirostatTAU),
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Debug: *c.Debug,
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StopPrompts: c.StopWords,
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Repeat: int32(c.RepeatLastN),
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FrequencyPenalty: float32(c.FrequencyPenalty),
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PresencePenalty: float32(c.PresencePenalty),
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Penalty: float32(c.RepeatPenalty),
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NKeep: int32(c.Keep),
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Batch: int32(c.Batch),
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IgnoreEOS: c.IgnoreEOS,
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Seed: getSeed(c),
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MLock: *c.MMlock,
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MMap: *c.MMap,
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MainGPU: c.MainGPU,
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TensorSplit: c.TensorSplit,
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TailFreeSamplingZ: float32(*c.TFZ),
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TypicalP: float32(*c.TypicalP),
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}
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metadata := map[string]string{}
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if c.ReasoningConfig.DisableReasoning != nil {
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if *c.ReasoningConfig.DisableReasoning {
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metadata["enable_thinking"] = "false"
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} else {
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metadata["enable_thinking"] = "true"
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}
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}
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pbOpts.Metadata = metadata
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// Logprobs and TopLogprobs are set by the caller if provided
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return pbOpts
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}
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