package backend import ( "os" "path/filepath" "github.com/go-skynet/LocalAI/core/config" pb "github.com/go-skynet/LocalAI/pkg/grpc/proto" model "github.com/go-skynet/LocalAI/pkg/model" ) func modelOpts(c config.BackendConfig, so *config.ApplicationConfig, opts []model.Option) []model.Option { if so.SingleBackend { opts = append(opts, model.WithSingleActiveBackend()) } if so.ParallelBackendRequests { opts = append(opts, model.EnableParallelRequests) } if c.GRPC.Attempts != 0 { opts = append(opts, model.WithGRPCAttempts(c.GRPC.Attempts)) } if c.GRPC.AttemptsSleepTime != 0 { opts = append(opts, model.WithGRPCAttemptsDelay(c.GRPC.AttemptsSleepTime)) } for k, v := range so.ExternalGRPCBackends { opts = append(opts, model.WithExternalBackend(k, v)) } return opts } func gRPCModelOpts(c config.BackendConfig) *pb.ModelOptions { b := 512 if c.Batch != 0 { b = c.Batch } return &pb.ModelOptions{ CUDA: c.CUDA || c.Diffusers.CUDA, SchedulerType: c.Diffusers.SchedulerType, PipelineType: c.Diffusers.PipelineType, CFGScale: c.Diffusers.CFGScale, LoraAdapter: c.LoraAdapter, LoraScale: c.LoraScale, F16Memory: *c.F16, LoraBase: c.LoraBase, IMG2IMG: c.Diffusers.IMG2IMG, CLIPModel: c.Diffusers.ClipModel, CLIPSubfolder: c.Diffusers.ClipSubFolder, CLIPSkip: int32(c.Diffusers.ClipSkip), ControlNet: c.Diffusers.ControlNet, ContextSize: int32(*c.ContextSize), Seed: int32(*c.Seed), NBatch: int32(b), NoMulMatQ: c.NoMulMatQ, DraftModel: c.DraftModel, AudioPath: c.VallE.AudioPath, Quantization: c.Quantization, GPUMemoryUtilization: c.GPUMemoryUtilization, TrustRemoteCode: c.TrustRemoteCode, EnforceEager: c.EnforceEager, SwapSpace: int32(c.SwapSpace), MaxModelLen: int32(c.MaxModelLen), MMProj: c.MMProj, YarnExtFactor: c.YarnExtFactor, YarnAttnFactor: c.YarnAttnFactor, YarnBetaFast: c.YarnBetaFast, YarnBetaSlow: c.YarnBetaSlow, NGQA: c.NGQA, RMSNormEps: c.RMSNormEps, MLock: *c.MMlock, RopeFreqBase: c.RopeFreqBase, RopeScaling: c.RopeScaling, Type: c.ModelType, RopeFreqScale: c.RopeFreqScale, NUMA: c.NUMA, Embeddings: c.Embeddings, LowVRAM: *c.LowVRAM, NGPULayers: int32(*c.NGPULayers), MMap: *c.MMap, MainGPU: c.MainGPU, Threads: int32(*c.Threads), TensorSplit: c.TensorSplit, // AutoGPTQ ModelBaseName: c.AutoGPTQ.ModelBaseName, Device: c.AutoGPTQ.Device, UseTriton: c.AutoGPTQ.Triton, UseFastTokenizer: c.AutoGPTQ.UseFastTokenizer, // RWKV Tokenizer: c.Tokenizer, } } func gRPCPredictOpts(c config.BackendConfig, modelPath string) *pb.PredictOptions { promptCachePath := "" if c.PromptCachePath != "" { p := filepath.Join(modelPath, c.PromptCachePath) os.MkdirAll(filepath.Dir(p), 0755) promptCachePath = p } return &pb.PredictOptions{ Temperature: float32(*c.Temperature), TopP: float32(*c.TopP), NDraft: c.NDraft, TopK: int32(*c.TopK), Tokens: int32(*c.Maxtokens), Threads: int32(*c.Threads), PromptCacheAll: c.PromptCacheAll, PromptCacheRO: c.PromptCacheRO, PromptCachePath: promptCachePath, F16KV: *c.F16, DebugMode: *c.Debug, Grammar: c.Grammar, NegativePromptScale: c.NegativePromptScale, RopeFreqBase: c.RopeFreqBase, RopeFreqScale: c.RopeFreqScale, NegativePrompt: c.NegativePrompt, Mirostat: int32(*c.LLMConfig.Mirostat), MirostatETA: float32(*c.LLMConfig.MirostatETA), MirostatTAU: float32(*c.LLMConfig.MirostatTAU), Debug: *c.Debug, StopPrompts: c.StopWords, Repeat: int32(c.RepeatPenalty), NKeep: int32(c.Keep), Batch: int32(c.Batch), IgnoreEOS: c.IgnoreEOS, Seed: int32(*c.Seed), FrequencyPenalty: float32(c.FrequencyPenalty), MLock: *c.MMlock, MMap: *c.MMap, MainGPU: c.MainGPU, TensorSplit: c.TensorSplit, TailFreeSamplingZ: float32(c.TFZ), TypicalP: float32(c.TypicalP), } }