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feat: Add Diffusers (#874)

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto 2023-08-09 08:38:51 +02:00 committed by GitHub
parent 93a4bec06b
commit 8c781a6a44
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GPG Key ID: 4AEE18F83AFDEB23
21 changed files with 741 additions and 217 deletions
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10
Dockerfile
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@ -11,7 +11,7 @@ ARG TARGETARCH
ARG TARGETVARIANT
ENV BUILD_TYPE=${BUILD_TYPE}
ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/extra/grpc/huggingface/huggingface.py,autogptq:/build/extra/grpc/autogptq/autogptq.py,bark:/build/extra/grpc/bark/ttsbark.py"
ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/extra/grpc/huggingface/huggingface.py,autogptq:/build/extra/grpc/autogptq/autogptq.py,bark:/build/extra/grpc/bark/ttsbark.py,diffusers:/build/extra/grpc/diffusers/backend_diffusers.py"
ARG GO_TAGS="stablediffusion tts"
RUN apt-get update && \
@ -35,10 +35,14 @@ ENV PATH /usr/local/cuda/bin:${PATH}
# Extras requirements
COPY extra/requirements.txt /build/extra/requirements.txt
ENV PATH="/root/.cargo/bin:${PATH}"
RUN pip install --upgrade pip
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
RUN if [ "${TARGETARCH}" = "amd64" ]; then \
pip install auto-gptq;\
pip install git+https://github.com/suno-ai/bark.git diffusers invisible_watermark transformers accelerate safetensors;\
fi
RUN if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "amd64" ]; then \
pip install torch && pip install auto-gptq;\
fi
RUN pip install -r /build/extra/requirements.txt && rm -rf /build/extra/requirements.txt

1
Makefile
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@ -338,6 +338,7 @@ protogen-python:
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/huggingface/ --grpc_python_out=extra/grpc/huggingface/ pkg/grpc/proto/backend.proto
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/autogptq/ --grpc_python_out=extra/grpc/autogptq/ pkg/grpc/proto/backend.proto
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/bark/ --grpc_python_out=extra/grpc/bark/ pkg/grpc/proto/backend.proto
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/diffusers/ --grpc_python_out=extra/grpc/diffusers/ pkg/grpc/proto/backend.proto
## GRPC

3
api/api_test.go
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@ -470,6 +470,9 @@ var _ = Describe("API test", func() {
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
ID: "model-gallery@stablediffusion",
Overrides: map[string]interface{}{
"parameters": map[string]interface{}{"model": "stablediffusion_assets"},
},
})
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))

2
api/backend/embeddings.go
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@ -23,7 +23,7 @@ func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.
var err error
opts := []model.Option{
model.WithLoadGRPCLLMModelOpts(grpcOpts),
model.WithLoadGRPCLoadModelOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)),
model.WithAssetDir(o.AssetsDestination),
model.WithModel(modelFile),

11
api/backend/image.go
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@ -1,7 +1,6 @@
package backend
import (
"fmt"
"sync"
config "github.com/go-skynet/LocalAI/api/config"
@ -11,16 +10,18 @@ import (
)
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
if c.Backend != model.StableDiffusionBackend {
return nil, fmt.Errorf("endpoint only working with stablediffusion models")
}
opts := []model.Option{
model.WithBackendString(c.Backend),
model.WithAssetDir(o.AssetsDestination),
model.WithThreads(uint32(c.Threads)),
model.WithContext(o.Context),
model.WithModel(c.ImageGenerationAssets),
model.WithModel(c.Model),
model.WithLoadGRPCLoadModelOpts(&proto.ModelOptions{
CUDA: c.Diffusers.CUDA,
SchedulerType: c.Diffusers.SchedulerType,
PipelineType: c.Diffusers.PipelineType,
}),
}
for k, v := range o.ExternalGRPCBackends {

2
api/backend/llm.go
View File

@ -24,7 +24,7 @@ func ModelInference(ctx context.Context, s string, loader *model.ModelLoader, c
var err error
opts := []model.Option{
model.WithLoadGRPCLLMModelOpts(grpcOpts),
model.WithLoadGRPCLoadModelOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
model.WithAssetDir(o.AssetsDestination),
model.WithModel(modelFile),

50
api/backend/options.go
View File

@ -15,27 +15,29 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
b = c.Batch
}
return &pb.ModelOptions{
ContextSize: int32(c.ContextSize),
Seed: int32(c.Seed),
NBatch: int32(b),
NGQA: c.NGQA,
ModelBaseName: c.ModelBaseName,
UseFastTokenizer: c.UseFastTokenizer,
Device: c.Device,
UseTriton: c.Triton,
RMSNormEps: c.RMSNormEps,
F16Memory: c.F16,
MLock: c.MMlock,
RopeFreqBase: c.RopeFreqBase,
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,
ContextSize: int32(c.ContextSize),
Seed: int32(c.Seed),
NBatch: int32(b),
NGQA: c.NGQA,
RMSNormEps: c.RMSNormEps,
F16Memory: c.F16,
MLock: c.MMlock,
RopeFreqBase: c.RopeFreqBase,
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,
}
}
@ -62,9 +64,9 @@ func gRPCPredictOpts(c config.Config, modelPath string) *pb.PredictOptions {
RopeFreqBase: c.RopeFreqBase,
RopeFreqScale: c.RopeFreqScale,
NegativePrompt: c.NegativePrompt,
Mirostat: int32(c.Mirostat),
MirostatETA: float32(c.MirostatETA),
MirostatTAU: float32(c.MirostatTAU),
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),

88
api/config/config.go
View File

@ -13,49 +13,65 @@ import (
type Config struct {
PredictionOptions `yaml:"parameters"`
Name string `yaml:"name"`
StopWords []string `yaml:"stopwords"`
Cutstrings []string `yaml:"cutstrings"`
TrimSpace []string `yaml:"trimspace"`
ContextSize int `yaml:"context_size"`
F16 bool `yaml:"f16"`
NUMA bool `yaml:"numa"`
Threads int `yaml:"threads"`
Debug bool `yaml:"debug"`
Roles map[string]string `yaml:"roles"`
Embeddings bool `yaml:"embeddings"`
Backend string `yaml:"backend"`
TemplateConfig TemplateConfig `yaml:"template"`
MirostatETA float64 `yaml:"mirostat_eta"`
MirostatTAU float64 `yaml:"mirostat_tau"`
Mirostat int `yaml:"mirostat"`
NGPULayers int `yaml:"gpu_layers"`
MMap bool `yaml:"mmap"`
MMlock bool `yaml:"mmlock"`
LowVRAM bool `yaml:"low_vram"`
Name string `yaml:"name"`
TensorSplit string `yaml:"tensor_split"`
MainGPU string `yaml:"main_gpu"`
ImageGenerationAssets string `yaml:"asset_dir"`
F16 bool `yaml:"f16"`
Threads int `yaml:"threads"`
Debug bool `yaml:"debug"`
Roles map[string]string `yaml:"roles"`
Embeddings bool `yaml:"embeddings"`
Backend string `yaml:"backend"`
TemplateConfig TemplateConfig `yaml:"template"`
PromptCachePath string `yaml:"prompt_cache_path"`
PromptCacheAll bool `yaml:"prompt_cache_all"`
PromptCacheRO bool `yaml:"prompt_cache_ro"`
Grammar string `yaml:"grammar"`
PromptStrings, InputStrings []string
InputToken [][]int
functionCallString, functionCallNameString string
PromptStrings, InputStrings []string `yaml:"-"`
InputToken [][]int `yaml:"-"`
functionCallString, functionCallNameString string `yaml:"-"`
FunctionsConfig Functions `yaml:"function"`
SystemPrompt string `yaml:"system_prompt"`
// LLM configs (GPT4ALL, Llama.cpp, ...)
LLMConfig `yaml:",inline"`
RMSNormEps float32 `yaml:"rms_norm_eps"`
NGQA int32 `yaml:"ngqa"`
// AutoGPTQ specifics
AutoGPTQ AutoGPTQ `yaml:"autogptq"`
// AutoGPTQ
// Diffusers
Diffusers Diffusers `yaml:"diffusers"`
Step int `yaml:"step"`
}
type Diffusers struct {
PipelineType string `yaml:"pipeline_type"`
SchedulerType string `yaml:"scheduler_type"`
CUDA bool `yaml:"cuda"`
}
type LLMConfig struct {
SystemPrompt string `yaml:"system_prompt"`
TensorSplit string `yaml:"tensor_split"`
MainGPU string `yaml:"main_gpu"`
RMSNormEps float32 `yaml:"rms_norm_eps"`
NGQA int32 `yaml:"ngqa"`
PromptCachePath string `yaml:"prompt_cache_path"`
PromptCacheAll bool `yaml:"prompt_cache_all"`
PromptCacheRO bool `yaml:"prompt_cache_ro"`
MirostatETA float64 `yaml:"mirostat_eta"`
MirostatTAU float64 `yaml:"mirostat_tau"`
Mirostat int `yaml:"mirostat"`
NGPULayers int `yaml:"gpu_layers"`
MMap bool `yaml:"mmap"`
MMlock bool `yaml:"mmlock"`
LowVRAM bool `yaml:"low_vram"`
Grammar string `yaml:"grammar"`
StopWords []string `yaml:"stopwords"`
Cutstrings []string `yaml:"cutstrings"`
TrimSpace []string `yaml:"trimspace"`
ContextSize int `yaml:"context_size"`
NUMA bool `yaml:"numa"`
}
type AutoGPTQ struct {
ModelBaseName string `yaml:"model_base_name"`
Device string `yaml:"device"`
Triton bool `yaml:"triton"`

5
api/openai/image.go
View File

@ -89,7 +89,10 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
}
mode := 0
step := 15
step := config.Step
if step == 0 {
step = 15
}
if input.Mode != 0 {
mode = input.Mode

8
api/openai/request.go
View File

@ -76,7 +76,7 @@ func updateConfig(config *config.Config, input *OpenAIRequest) {
}
if input.ModelBaseName != "" {
config.ModelBaseName = input.ModelBaseName
config.AutoGPTQ.ModelBaseName = input.ModelBaseName
}
if input.NegativePromptScale != 0 {
@ -149,15 +149,15 @@ func updateConfig(config *config.Config, input *OpenAIRequest) {
}
if input.Mirostat != 0 {
config.Mirostat = input.Mirostat
config.LLMConfig.Mirostat = input.Mirostat
}
if input.MirostatETA != 0 {
config.MirostatETA = input.MirostatETA
config.LLMConfig.MirostatETA = input.MirostatETA
}
if input.MirostatTAU != 0 {
config.MirostatTAU = input.MirostatTAU
config.LLMConfig.MirostatTAU = input.MirostatTAU
}
if input.TypicalP != 0 {

36
extra/grpc/autogptq/backend_pb2.py
View File

@ -13,7 +13,7 @@ _sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\xe2\x03\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\x12\x14\n\x0cRopeFreqBase\x18\x11 \x01(\x02\x12\x15\n\rRopeFreqScale\x18\x12 \x01(\x02\x12\x12\n\nRMSNormEps\x18\x13 \x01(\x02\x12\x0c\n\x04NGQA\x18\x14 \x01(\x05\x12\x11\n\tModelFile\x18\x15 \x01(\t\x12\x0e\n\x06\x44\x65vice\x18\x16 \x01(\t\x12\x11\n\tUseTriton\x18\x17 \x01(\x08\x12\x15\n\rModelBaseName\x18\x18 \x01(\t\x12\x18\n\x10UseFastTokenizer\x18\x19 \x01(\x08\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\x9d\x04\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\x12\x14\n\x0cRopeFreqBase\x18\x11 \x01(\x02\x12\x15\n\rRopeFreqScale\x18\x12 \x01(\x02\x12\x12\n\nRMSNormEps\x18\x13 \x01(\x02\x12\x0c\n\x04NGQA\x18\x14 \x01(\x05\x12\x11\n\tModelFile\x18\x15 \x01(\t\x12\x0e\n\x06\x44\x65vice\x18\x16 \x01(\t\x12\x11\n\tUseTriton\x18\x17 \x01(\x08\x12\x15\n\rModelBaseName\x18\x18 \x01(\t\x12\x18\n\x10UseFastTokenizer\x18\x19 \x01(\x08\x12\x14\n\x0cPipelineType\x18\x1a \x01(\t\x12\x15\n\rSchedulerType\x18\x1b \x01(\t\x12\x0c\n\x04\x43UDA\x18\x1c \x01(\x08\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
_globals = globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@ -29,21 +29,21 @@ if _descriptor._USE_C_DESCRIPTORS == False:
_globals['_REPLY']._serialized_start=820
_globals['_REPLY']._serialized_end=844
_globals['_MODELOPTIONS']._serialized_start=847
_globals['_MODELOPTIONS']._serialized_end=1329
_globals['_RESULT']._serialized_start=1331
_globals['_RESULT']._serialized_end=1373
_globals['_EMBEDDINGRESULT']._serialized_start=1375
_globals['_EMBEDDINGRESULT']._serialized_end=1412
_globals['_TRANSCRIPTREQUEST']._serialized_start=1414
_globals['_TRANSCRIPTREQUEST']._serialized_end=1481
_globals['_TRANSCRIPTRESULT']._serialized_start=1483
_globals['_TRANSCRIPTRESULT']._serialized_end=1561
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1563
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1652
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1655
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1813
_globals['_TTSREQUEST']._serialized_start=1815
_globals['_TTSREQUEST']._serialized_end=1869
_globals['_BACKEND']._serialized_start=1872
_globals['_BACKEND']._serialized_end=2363
_globals['_MODELOPTIONS']._serialized_end=1388
_globals['_RESULT']._serialized_start=1390
_globals['_RESULT']._serialized_end=1432
_globals['_EMBEDDINGRESULT']._serialized_start=1434
_globals['_EMBEDDINGRESULT']._serialized_end=1471
_globals['_TRANSCRIPTREQUEST']._serialized_start=1473
_globals['_TRANSCRIPTREQUEST']._serialized_end=1540
_globals['_TRANSCRIPTRESULT']._serialized_start=1542
_globals['_TRANSCRIPTRESULT']._serialized_end=1620
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1622
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1711
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1714
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1872
_globals['_TTSREQUEST']._serialized_start=1874
_globals['_TTSREQUEST']._serialized_end=1928
_globals['_BACKEND']._serialized_start=1931
_globals['_BACKEND']._serialized_end=2422
# @@protoc_insertion_point(module_scope)

36
extra/grpc/bark/backend_pb2.py
View File

@ -13,7 +13,7 @@ _sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\xe2\x03\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\x12\x14\n\x0cRopeFreqBase\x18\x11 \x01(\x02\x12\x15\n\rRopeFreqScale\x18\x12 \x01(\x02\x12\x12\n\nRMSNormEps\x18\x13 \x01(\x02\x12\x0c\n\x04NGQA\x18\x14 \x01(\x05\x12\x11\n\tModelFile\x18\x15 \x01(\t\x12\x0e\n\x06\x44\x65vice\x18\x16 \x01(\t\x12\x11\n\tUseTriton\x18\x17 \x01(\x08\x12\x15\n\rModelBaseName\x18\x18 \x01(\t\x12\x18\n\x10UseFastTokenizer\x18\x19 \x01(\x08\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\x9d\x04\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\x12\x14\n\x0cRopeFreqBase\x18\x11 \x01(\x02\x12\x15\n\rRopeFreqScale\x18\x12 \x01(\x02\x12\x12\n\nRMSNormEps\x18\x13 \x01(\x02\x12\x0c\n\x04NGQA\x18\x14 \x01(\x05\x12\x11\n\tModelFile\x18\x15 \x01(\t\x12\x0e\n\x06\x44\x65vice\x18\x16 \x01(\t\x12\x11\n\tUseTriton\x18\x17 \x01(\x08\x12\x15\n\rModelBaseName\x18\x18 \x01(\t\x12\x18\n\x10UseFastTokenizer\x18\x19 \x01(\x08\x12\x14\n\x0cPipelineType\x18\x1a \x01(\t\x12\x15\n\rSchedulerType\x18\x1b \x01(\t\x12\x0c\n\x04\x43UDA\x18\x1c \x01(\x08\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
_globals = globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@ -29,21 +29,21 @@ if _descriptor._USE_C_DESCRIPTORS == False:
_globals['_REPLY']._serialized_start=820
_globals['_REPLY']._serialized_end=844
_globals['_MODELOPTIONS']._serialized_start=847
_globals['_MODELOPTIONS']._serialized_end=1329
_globals['_RESULT']._serialized_start=1331
_globals['_RESULT']._serialized_end=1373
_globals['_EMBEDDINGRESULT']._serialized_start=1375
_globals['_EMBEDDINGRESULT']._serialized_end=1412
_globals['_TRANSCRIPTREQUEST']._serialized_start=1414
_globals['_TRANSCRIPTREQUEST']._serialized_end=1481
_globals['_TRANSCRIPTRESULT']._serialized_start=1483
_globals['_TRANSCRIPTRESULT']._serialized_end=1561
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1563
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1652
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1655
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1813
_globals['_TTSREQUEST']._serialized_start=1815
_globals['_TTSREQUEST']._serialized_end=1869
_globals['_BACKEND']._serialized_start=1872
_globals['_BACKEND']._serialized_end=2363
_globals['_MODELOPTIONS']._serialized_end=1388
_globals['_RESULT']._serialized_start=1390
_globals['_RESULT']._serialized_end=1432
_globals['_EMBEDDINGRESULT']._serialized_start=1434
_globals['_EMBEDDINGRESULT']._serialized_end=1471
_globals['_TRANSCRIPTREQUEST']._serialized_start=1473
_globals['_TRANSCRIPTREQUEST']._serialized_end=1540
_globals['_TRANSCRIPTRESULT']._serialized_start=1542
_globals['_TRANSCRIPTRESULT']._serialized_end=1620
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1622
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1711
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1714
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1872
_globals['_TTSREQUEST']._serialized_start=1874
_globals['_TTSREQUEST']._serialized_end=1928
_globals['_BACKEND']._serialized_start=1931
_globals['_BACKEND']._serialized_end=2422
# @@protoc_insertion_point(module_scope)

114
extra/grpc/diffusers/backend_diffusers.py Executable file
View File

@ -0,0 +1,114 @@
#!/usr/bin/env python3
import grpc
from concurrent import futures
import time
import backend_pb2
import backend_pb2_grpc
import argparse
import signal
import sys
import os
# import diffusers
import torch
from torch import autocast
from diffusers import StableDiffusionXLPipeline, DPMSolverMultistepScheduler, StableDiffusionPipeline, DiffusionPipeline, EulerAncestralDiscreteScheduler
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
# Implement the BackendServicer class with the service methods
class BackendServicer(backend_pb2_grpc.BackendServicer):
def Health(self, request, context):
return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
def LoadModel(self, request, context):
try:
print(f"Loading model {request.Model}...", file=sys.stderr)
print(f"Request {request}", file=sys.stderr)
torchType = torch.float32
if request.F16Memory:
torchType = torch.float16
if request.PipelineType == "":
request.PipelineType == "StableDiffusionPipeline"
if request.PipelineType == "StableDiffusionPipeline":
self.pipe = StableDiffusionPipeline.from_pretrained(request.Model,
torch_dtype=torchType)
if request.PipelineType == "DiffusionPipeline":
self.pipe = DiffusionPipeline.from_pretrained(request.Model,
torch_dtype=torchType)
if request.PipelineType == "StableDiffusionXLPipeline":
self.pipe = StableDiffusionXLPipeline.from_pretrained(
request.Model,
torch_dtype=torchType,
use_safetensors=True,
# variant="fp16"
)
# torch_dtype needs to be customized. float16 for GPU, float32 for CPU
# TODO: this needs to be customized
if request.SchedulerType == "EulerAncestralDiscreteScheduler":
self.pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(self.pipe.scheduler.config)
if request.SchedulerType == "DPMSolverMultistepScheduler":
self.pipe.scheduler = DPMSolverMultistepScheduler.from_config(self.pipe.scheduler.config)
if request.CUDA:
self.pipe.to('cuda')
except Exception as err:
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
# Implement your logic here for the LoadModel service
# Replace this with your desired response
return backend_pb2.Result(message="Model loaded successfully", success=True)
def GenerateImage(self, request, context):
prompt = request.positive_prompt
negative_prompt = request.negative_prompt
image = self.pipe(
prompt,
negative_prompt=negative_prompt,
width=request.width,
height=request.height,
# guidance_scale=12,
target_size=(request.width,request.height),
original_size=(4096,4096),
num_inference_steps=request.step
).images[0]
image.save(request.dst)
return backend_pb2.Result(message="Model loaded successfully", success=True)
def serve(address):
server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
server.add_insecure_port(address)
server.start()
print("Server started. Listening on: " + address, file=sys.stderr)
# Define the signal handler function
def signal_handler(sig, frame):
print("Received termination signal. Shutting down...")
server.stop(0)
sys.exit(0)
# Set the signal handlers for SIGINT and SIGTERM
signal.signal(signal.SIGINT, signal_handler)
signal.signal(signal.SIGTERM, signal_handler)
try:
while True:
time.sleep(_ONE_DAY_IN_SECONDS)
except KeyboardInterrupt:
server.stop(0)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run the gRPC server.")
parser.add_argument(
"--addr", default="localhost:50051", help="The address to bind the server to."
)
args = parser.parse_args()
serve(args.addr)

49
extra/grpc/diffusers/backend_pb2.py Normal file
View File

@ -0,0 +1,49 @@
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: backend.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\x9d\x04\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\x12\x14\n\x0cRopeFreqBase\x18\x11 \x01(\x02\x12\x15\n\rRopeFreqScale\x18\x12 \x01(\x02\x12\x12\n\nRMSNormEps\x18\x13 \x01(\x02\x12\x0c\n\x04NGQA\x18\x14 \x01(\x05\x12\x11\n\tModelFile\x18\x15 \x01(\t\x12\x0e\n\x06\x44\x65vice\x18\x16 \x01(\t\x12\x11\n\tUseTriton\x18\x17 \x01(\x08\x12\x15\n\rModelBaseName\x18\x18 \x01(\t\x12\x18\n\x10UseFastTokenizer\x18\x19 \x01(\x08\x12\x14\n\x0cPipelineType\x18\x1a \x01(\t\x12\x15\n\rSchedulerType\x18\x1b \x01(\t\x12\x0c\n\x04\x43UDA\x18\x1c \x01(\x08\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
_globals = globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
if _descriptor._USE_C_DESCRIPTORS == False:
DESCRIPTOR._options = None
DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
_globals['_HEALTHMESSAGE']._serialized_start=26
_globals['_HEALTHMESSAGE']._serialized_end=41
_globals['_PREDICTOPTIONS']._serialized_start=44
_globals['_PREDICTOPTIONS']._serialized_end=818
_globals['_REPLY']._serialized_start=820
_globals['_REPLY']._serialized_end=844
_globals['_MODELOPTIONS']._serialized_start=847
_globals['_MODELOPTIONS']._serialized_end=1388
_globals['_RESULT']._serialized_start=1390
_globals['_RESULT']._serialized_end=1432
_globals['_EMBEDDINGRESULT']._serialized_start=1434
_globals['_EMBEDDINGRESULT']._serialized_end=1471
_globals['_TRANSCRIPTREQUEST']._serialized_start=1473
_globals['_TRANSCRIPTREQUEST']._serialized_end=1540
_globals['_TRANSCRIPTRESULT']._serialized_start=1542
_globals['_TRANSCRIPTRESULT']._serialized_end=1620
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1622
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1711
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1714
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1872
_globals['_TTSREQUEST']._serialized_start=1874
_globals['_TTSREQUEST']._serialized_end=1928
_globals['_BACKEND']._serialized_start=1931
_globals['_BACKEND']._serialized_end=2422
# @@protoc_insertion_point(module_scope)

297
extra/grpc/diffusers/backend_pb2_grpc.py Normal file
View File

@ -0,0 +1,297 @@
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import backend_pb2 as backend__pb2
class BackendStub(object):
"""Missing associated documentation comment in .proto file."""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
self.Health = channel.unary_unary(
'/backend.Backend/Health',
request_serializer=backend__pb2.HealthMessage.SerializeToString,
response_deserializer=backend__pb2.Reply.FromString,
)
self.Predict = channel.unary_unary(
'/backend.Backend/Predict',
request_serializer=backend__pb2.PredictOptions.SerializeToString,
response_deserializer=backend__pb2.Reply.FromString,
)
self.LoadModel = channel.unary_unary(
'/backend.Backend/LoadModel',
request_serializer=backend__pb2.ModelOptions.SerializeToString,
response_deserializer=backend__pb2.Result.FromString,
)
self.PredictStream = channel.unary_stream(
'/backend.Backend/PredictStream',
request_serializer=backend__pb2.PredictOptions.SerializeToString,
response_deserializer=backend__pb2.Reply.FromString,
)
self.Embedding = channel.unary_unary(
'/backend.Backend/Embedding',
request_serializer=backend__pb2.PredictOptions.SerializeToString,
response_deserializer=backend__pb2.EmbeddingResult.FromString,
)
self.GenerateImage = channel.unary_unary(
'/backend.Backend/GenerateImage',
request_serializer=backend__pb2.GenerateImageRequest.SerializeToString,
response_deserializer=backend__pb2.Result.FromString,
)
self.AudioTranscription = channel.unary_unary(
'/backend.Backend/AudioTranscription',
request_serializer=backend__pb2.TranscriptRequest.SerializeToString,
response_deserializer=backend__pb2.TranscriptResult.FromString,
)
self.TTS = channel.unary_unary(
'/backend.Backend/TTS',
request_serializer=backend__pb2.TTSRequest.SerializeToString,
response_deserializer=backend__pb2.Result.FromString,
)
class BackendServicer(object):
"""Missing associated documentation comment in .proto file."""
def Health(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def Predict(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def LoadModel(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def PredictStream(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def Embedding(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def GenerateImage(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def AudioTranscription(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def TTS(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def add_BackendServicer_to_server(servicer, server):
rpc_method_handlers = {
'Health': grpc.unary_unary_rpc_method_handler(
servicer.Health,
request_deserializer=backend__pb2.HealthMessage.FromString,
response_serializer=backend__pb2.Reply.SerializeToString,
),
'Predict': grpc.unary_unary_rpc_method_handler(
servicer.Predict,
request_deserializer=backend__pb2.PredictOptions.FromString,
response_serializer=backend__pb2.Reply.SerializeToString,
),
'LoadModel': grpc.unary_unary_rpc_method_handler(
servicer.LoadModel,
request_deserializer=backend__pb2.ModelOptions.FromString,
response_serializer=backend__pb2.Result.SerializeToString,
),
'PredictStream': grpc.unary_stream_rpc_method_handler(
servicer.PredictStream,
request_deserializer=backend__pb2.PredictOptions.FromString,
response_serializer=backend__pb2.Reply.SerializeToString,
),
'Embedding': grpc.unary_unary_rpc_method_handler(
servicer.Embedding,
request_deserializer=backend__pb2.PredictOptions.FromString,
response_serializer=backend__pb2.EmbeddingResult.SerializeToString,
),
'GenerateImage': grpc.unary_unary_rpc_method_handler(
servicer.GenerateImage,
request_deserializer=backend__pb2.GenerateImageRequest.FromString,
response_serializer=backend__pb2.Result.SerializeToString,
),
'AudioTranscription': grpc.unary_unary_rpc_method_handler(
servicer.AudioTranscription,
request_deserializer=backend__pb2.TranscriptRequest.FromString,
response_serializer=backend__pb2.TranscriptResult.SerializeToString,
),
'TTS': grpc.unary_unary_rpc_method_handler(
servicer.TTS,
request_deserializer=backend__pb2.TTSRequest.FromString,
response_serializer=backend__pb2.Result.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
'backend.Backend', rpc_method_handlers)
server.add_generic_rpc_handlers((generic_handler,))
# This class is part of an EXPERIMENTAL API.
class Backend(object):
"""Missing associated documentation comment in .proto file."""
@staticmethod
def Health(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/backend.Backend/Health',
backend__pb2.HealthMessage.SerializeToString,
backend__pb2.Reply.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def Predict(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/backend.Backend/Predict',
backend__pb2.PredictOptions.SerializeToString,
backend__pb2.Reply.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def LoadModel(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/backend.Backend/LoadModel',
backend__pb2.ModelOptions.SerializeToString,
backend__pb2.Result.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def PredictStream(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_stream(request, target, '/backend.Backend/PredictStream',
backend__pb2.PredictOptions.SerializeToString,
backend__pb2.Reply.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def Embedding(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/backend.Backend/Embedding',
backend__pb2.PredictOptions.SerializeToString,
backend__pb2.EmbeddingResult.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def GenerateImage(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/backend.Backend/GenerateImage',
backend__pb2.GenerateImageRequest.SerializeToString,
backend__pb2.Result.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def AudioTranscription(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/backend.Backend/AudioTranscription',
backend__pb2.TranscriptRequest.SerializeToString,
backend__pb2.TranscriptResult.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def TTS(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/backend.Backend/TTS',
backend__pb2.TTSRequest.SerializeToString,
backend__pb2.Result.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)

36
extra/grpc/huggingface/backend_pb2.py
View File

@ -13,7 +13,7 @@ _sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\xe2\x03\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\x12\x14\n\x0cRopeFreqBase\x18\x11 \x01(\x02\x12\x15\n\rRopeFreqScale\x18\x12 \x01(\x02\x12\x12\n\nRMSNormEps\x18\x13 \x01(\x02\x12\x0c\n\x04NGQA\x18\x14 \x01(\x05\x12\x11\n\tModelFile\x18\x15 \x01(\t\x12\x0e\n\x06\x44\x65vice\x18\x16 \x01(\t\x12\x11\n\tUseTriton\x18\x17 \x01(\x08\x12\x15\n\rModelBaseName\x18\x18 \x01(\t\x12\x18\n\x10UseFastTokenizer\x18\x19 \x01(\x08\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\x9d\x04\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\x12\x14\n\x0cRopeFreqBase\x18\x11 \x01(\x02\x12\x15\n\rRopeFreqScale\x18\x12 \x01(\x02\x12\x12\n\nRMSNormEps\x18\x13 \x01(\x02\x12\x0c\n\x04NGQA\x18\x14 \x01(\x05\x12\x11\n\tModelFile\x18\x15 \x01(\t\x12\x0e\n\x06\x44\x65vice\x18\x16 \x01(\t\x12\x11\n\tUseTriton\x18\x17 \x01(\x08\x12\x15\n\rModelBaseName\x18\x18 \x01(\t\x12\x18\n\x10UseFastTokenizer\x18\x19 \x01(\x08\x12\x14\n\x0cPipelineType\x18\x1a \x01(\t\x12\x15\n\rSchedulerType\x18\x1b \x01(\t\x12\x0c\n\x04\x43UDA\x18\x1c \x01(\x08\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
_globals = globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@ -29,21 +29,21 @@ if _descriptor._USE_C_DESCRIPTORS == False:
_globals['_REPLY']._serialized_start=820
_globals['_REPLY']._serialized_end=844
_globals['_MODELOPTIONS']._serialized_start=847
_globals['_MODELOPTIONS']._serialized_end=1329
_globals['_RESULT']._serialized_start=1331
_globals['_RESULT']._serialized_end=1373
_globals['_EMBEDDINGRESULT']._serialized_start=1375
_globals['_EMBEDDINGRESULT']._serialized_end=1412
_globals['_TRANSCRIPTREQUEST']._serialized_start=1414
_globals['_TRANSCRIPTREQUEST']._serialized_end=1481
_globals['_TRANSCRIPTRESULT']._serialized_start=1483
_globals['_TRANSCRIPTRESULT']._serialized_end=1561
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1563
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1652
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1655
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1813
_globals['_TTSREQUEST']._serialized_start=1815
_globals['_TTSREQUEST']._serialized_end=1869
_globals['_BACKEND']._serialized_start=1872
_globals['_BACKEND']._serialized_end=2363
_globals['_MODELOPTIONS']._serialized_end=1388
_globals['_RESULT']._serialized_start=1390
_globals['_RESULT']._serialized_end=1432
_globals['_EMBEDDINGRESULT']._serialized_start=1434
_globals['_EMBEDDINGRESULT']._serialized_end=1471
_globals['_TRANSCRIPTREQUEST']._serialized_start=1473
_globals['_TRANSCRIPTREQUEST']._serialized_end=1540
_globals['_TRANSCRIPTRESULT']._serialized_start=1542
_globals['_TRANSCRIPTRESULT']._serialized_end=1620
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1622
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1711
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1714
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1872
_globals['_TTSREQUEST']._serialized_start=1874
_globals['_TTSREQUEST']._serialized_end=1928
_globals['_BACKEND']._serialized_start=1931
_globals['_BACKEND']._serialized_end=2422
# @@protoc_insertion_point(module_scope)

4
extra/requirements.txt
View File

@ -1,6 +1,4 @@
sentence_transformers
grpcio
google
protobuf
torch
git+https://github.com/suno-ai/bark.git
protobuf

197
pkg/grpc/proto/backend.pb.go
View File

@ -489,6 +489,10 @@ type ModelOptions struct {
UseTriton bool `protobuf:"varint,23,opt,name=UseTriton,proto3" json:"UseTriton,omitempty"`
ModelBaseName string `protobuf:"bytes,24,opt,name=ModelBaseName,proto3" json:"ModelBaseName,omitempty"`
UseFastTokenizer bool `protobuf:"varint,25,opt,name=UseFastTokenizer,proto3" json:"UseFastTokenizer,omitempty"`
// Diffusers
PipelineType string `protobuf:"bytes,26,opt,name=PipelineType,proto3" json:"PipelineType,omitempty"`
SchedulerType string `protobuf:"bytes,27,opt,name=SchedulerType,proto3" json:"SchedulerType,omitempty"`
CUDA bool `protobuf:"varint,28,opt,name=CUDA,proto3" json:"CUDA,omitempty"`
}
func (x *ModelOptions) Reset() {
@ -698,6 +702,27 @@ func (x *ModelOptions) GetUseFastTokenizer() bool {
return false
}
func (x *ModelOptions) GetPipelineType() string {
if x != nil {
return x.PipelineType
}
return ""
}
func (x *ModelOptions) GetSchedulerType() string {
if x != nil {
return x.SchedulerType
}
return ""
}
func (x *ModelOptions) GetCUDA() bool {
if x != nil {
return x.CUDA
}
return false
}
type Result struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
@ -1248,7 +1273,7 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
0x0e, 0x4e, 0x65, 0x67, 0x61, 0x74, 0x69, 0x76, 0x65, 0x50, 0x72, 0x6f, 0x6d, 0x70, 0x74, 0x22,
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0x74, 0x65, 0x78, 0x74, 0x53, 0x69, 0x7a, 0x65, 0x18, 0x02, 0x20, 0x01, 0x28, 0x05, 0x52, 0x0b,
@ -1295,89 +1320,95 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
0x61, 0x73, 0x65, 0x4e, 0x61, 0x6d, 0x65, 0x12, 0x2a, 0x0a, 0x10, 0x55, 0x73, 0x65, 0x46, 0x61,
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}
var (

5
pkg/grpc/proto/backend.proto
View File

@ -96,6 +96,11 @@ message ModelOptions {
bool UseTriton = 23;
string ModelBaseName = 24;
bool UseFastTokenizer = 25;
// Diffusers
string PipelineType = 26;
string SchedulerType = 27;
bool CUDA = 28;
}
message Result {

2
pkg/model/initializers.go
View File

@ -273,7 +273,7 @@ func (ml *ModelLoader) GreedyLoader(opts ...Option) (*grpc.Client, error) {
options := []Option{
WithBackendString(b),
WithModel(o.model),
WithLoadGRPCLLMModelOpts(o.gRPCOptions),
WithLoadGRPCLoadModelOpts(o.gRPCOptions),
WithThreads(o.threads),
WithAssetDir(o.assetDir),
}

2
pkg/model/options.go
View File

@ -41,7 +41,7 @@ func WithModel(modelFile string) Option {
}
}
func WithLoadGRPCLLMModelOpts(opts *pb.ModelOptions) Option {
func WithLoadGRPCLoadModelOpts(opts *pb.ModelOptions) Option {
return func(o *Options) {
o.gRPCOptions = opts
}