feat: add initial AutoGPTQ backend implementation

This commit is contained in:
Ettore Di Giacinto 2023-08-07 22:39:10 +02:00
parent 91d49cfe9f
commit a843e64fc2
37 changed files with 660 additions and 148 deletions

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@ -335,7 +335,8 @@ protogen-go:
pkg/grpc/proto/backend.proto pkg/grpc/proto/backend.proto
protogen-python: protogen-python:
python -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/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
## GRPC ## GRPC

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@ -26,7 +26,7 @@ func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.
model.WithLoadGRPCLLMModelOpts(grpcOpts), model.WithLoadGRPCLLMModelOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)), model.WithThreads(uint32(c.Threads)),
model.WithAssetDir(o.AssetsDestination), model.WithAssetDir(o.AssetsDestination),
model.WithModelFile(modelFile), model.WithModel(modelFile),
model.WithContext(o.Context), model.WithContext(o.Context),
} }

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@ -20,7 +20,7 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
model.WithAssetDir(o.AssetsDestination), model.WithAssetDir(o.AssetsDestination),
model.WithThreads(uint32(c.Threads)), model.WithThreads(uint32(c.Threads)),
model.WithContext(o.Context), model.WithContext(o.Context),
model.WithModelFile(c.ImageGenerationAssets), model.WithModel(c.ImageGenerationAssets),
} }
for k, v := range o.ExternalGRPCBackends { for k, v := range o.ExternalGRPCBackends {

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@ -27,7 +27,7 @@ func ModelInference(ctx context.Context, s string, loader *model.ModelLoader, c
model.WithLoadGRPCLLMModelOpts(grpcOpts), model.WithLoadGRPCLLMModelOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
model.WithAssetDir(o.AssetsDestination), model.WithAssetDir(o.AssetsDestination),
model.WithModelFile(modelFile), model.WithModel(modelFile),
model.WithContext(o.Context), model.WithContext(o.Context),
} }

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@ -19,6 +19,9 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
Seed: int32(c.Seed), Seed: int32(c.Seed),
NBatch: int32(b), NBatch: int32(b),
NGQA: c.NGQA, NGQA: c.NGQA,
ModelBaseName: c.ModelBaseName,
Device: c.Device,
UseTriton: c.Triton,
RMSNormEps: c.RMSNormEps, RMSNormEps: c.RMSNormEps,
F16Memory: c.F16, F16Memory: c.F16,
MLock: c.MMlock, MLock: c.MMlock,

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@ -15,7 +15,7 @@ import (
func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*api.Result, error) { func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*api.Result, error) {
opts := []model.Option{ opts := []model.Option{
model.WithBackendString(model.WhisperBackend), model.WithBackendString(model.WhisperBackend),
model.WithModelFile(c.Model), model.WithModel(c.Model),
model.WithContext(o.Context), model.WithContext(o.Context),
model.WithThreads(uint32(c.Threads)), model.WithThreads(uint32(c.Threads)),
model.WithAssetDir(o.AssetsDestination), model.WithAssetDir(o.AssetsDestination),

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@ -54,6 +54,11 @@ type Config struct {
RMSNormEps float32 `yaml:"rms_norm_eps"` RMSNormEps float32 `yaml:"rms_norm_eps"`
NGQA int32 `yaml:"ngqa"` NGQA int32 `yaml:"ngqa"`
// AutoGPTQ
ModelBaseName string `yaml:"model_base_name"`
Device string `yaml:"device"`
Triton bool `yaml:"triton"`
} }
type Functions struct { type Functions struct {

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@ -2,6 +2,7 @@ package openai
import ( import (
"context" "context"
config "github.com/go-skynet/LocalAI/api/config" config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/pkg/grammar" "github.com/go-skynet/LocalAI/pkg/grammar"
@ -106,4 +107,9 @@ type OpenAIRequest struct {
Grammar string `json:"grammar" yaml:"grammar"` Grammar string `json:"grammar" yaml:"grammar"`
JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"` JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
Backend string `json:"backend" yaml:"backend"`
// AutoGPTQ
ModelBaseName string `json:"model_base_name" yaml:"model_base_name"`
} }

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@ -71,6 +71,14 @@ func updateConfig(config *config.Config, input *OpenAIRequest) {
config.TopP = input.TopP config.TopP = input.TopP
} }
if input.Backend != "" {
config.Backend = input.Backend
}
if input.ModelBaseName != "" {
config.ModelBaseName = input.ModelBaseName
}
if input.NegativePromptScale != 0 { if input.NegativePromptScale != 0 {
config.NegativePromptScale = input.NegativePromptScale config.NegativePromptScale = input.NegativePromptScale
} }

94
extra/grpc/autogptq/autogptq.py Executable file
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@ -0,0 +1,94 @@
#!/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
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
from pathlib import Path
from transformers import AutoTokenizer
from transformers import TextGenerationPipeline
_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:
device = "cuda:0"
if request.Device != "":
device = request.Device
tokenizer = AutoTokenizer.from_pretrained(request.Model, use_fast=True)
model = AutoGPTQForCausalLM.from_quantized(request.Model,
model_basename=request.ModelBaseName,
use_safetensors=True,
trust_remote_code=True,
device=device,
use_triton=request.UseTriton,
quantize_config=None)
self.model = model
self.tokenizer = tokenizer
except Exception as err:
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
return backend_pb2.Result(message="Model loaded successfully", success=True)
def Predict(self, request, context):
# Implement Predict RPC
pipeline = TextGenerationPipeline(
model=self.model,
tokenizer=self.tokenizer,
max_new_tokens=request.Tokens,
temperature=request.Temperature,
top_p=request.TopP,
repetition_penalty=request.Penalty,
)
return backend_pb2.Result(message=bytes(pipeline(request.Prompt)[0]["generated_text"]))
def PredictStream(self, request, context):
# Implement PredictStream RPC
#for reply in some_data_generator():
# yield reply
# Not implemented yet
return self.Predict(request, context)
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)

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@ -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\"\xc8\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\"*\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=1303
_globals['_RESULT']._serialized_start=1305
_globals['_RESULT']._serialized_end=1347
_globals['_EMBEDDINGRESULT']._serialized_start=1349
_globals['_EMBEDDINGRESULT']._serialized_end=1386
_globals['_TRANSCRIPTREQUEST']._serialized_start=1388
_globals['_TRANSCRIPTREQUEST']._serialized_end=1455
_globals['_TRANSCRIPTRESULT']._serialized_start=1457
_globals['_TRANSCRIPTRESULT']._serialized_end=1535
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1537
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1626
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1629
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1787
_globals['_TTSREQUEST']._serialized_start=1789
_globals['_TTSREQUEST']._serialized_end=1843
_globals['_BACKEND']._serialized_start=1846
_globals['_BACKEND']._serialized_end=2337
# @@protoc_insertion_point(module_scope)

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@ -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)

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\"\xfb\x02\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\"*\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\"\xc8\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\"*\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() _globals = globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals) _builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@ -29,21 +29,21 @@ if _descriptor._USE_C_DESCRIPTORS == False:
_globals['_REPLY']._serialized_start=820 _globals['_REPLY']._serialized_start=820
_globals['_REPLY']._serialized_end=844 _globals['_REPLY']._serialized_end=844
_globals['_MODELOPTIONS']._serialized_start=847 _globals['_MODELOPTIONS']._serialized_start=847
_globals['_MODELOPTIONS']._serialized_end=1226 _globals['_MODELOPTIONS']._serialized_end=1303
_globals['_RESULT']._serialized_start=1228 _globals['_RESULT']._serialized_start=1305
_globals['_RESULT']._serialized_end=1270 _globals['_RESULT']._serialized_end=1347
_globals['_EMBEDDINGRESULT']._serialized_start=1272 _globals['_EMBEDDINGRESULT']._serialized_start=1349
_globals['_EMBEDDINGRESULT']._serialized_end=1309 _globals['_EMBEDDINGRESULT']._serialized_end=1386
_globals['_TRANSCRIPTREQUEST']._serialized_start=1311 _globals['_TRANSCRIPTREQUEST']._serialized_start=1388
_globals['_TRANSCRIPTREQUEST']._serialized_end=1378 _globals['_TRANSCRIPTREQUEST']._serialized_end=1455
_globals['_TRANSCRIPTRESULT']._serialized_start=1380 _globals['_TRANSCRIPTRESULT']._serialized_start=1457
_globals['_TRANSCRIPTRESULT']._serialized_end=1458 _globals['_TRANSCRIPTRESULT']._serialized_end=1535
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1460 _globals['_TRANSCRIPTSEGMENT']._serialized_start=1537
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1549 _globals['_TRANSCRIPTSEGMENT']._serialized_end=1626
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1552 _globals['_GENERATEIMAGEREQUEST']._serialized_start=1629
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1710 _globals['_GENERATEIMAGEREQUEST']._serialized_end=1787
_globals['_TTSREQUEST']._serialized_start=1712 _globals['_TTSREQUEST']._serialized_start=1789
_globals['_TTSREQUEST']._serialized_end=1766 _globals['_TTSREQUEST']._serialized_end=1843
_globals['_BACKEND']._serialized_start=1769 _globals['_BACKEND']._serialized_start=1846
_globals['_BACKEND']._serialized_end=2260 _globals['_BACKEND']._serialized_end=2337
# @@protoc_insertion_point(module_scope) # @@protoc_insertion_point(module_scope)

View file

@ -18,7 +18,6 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
return backend_pb2.Reply(message=bytes("OK", 'utf-8')) return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
def LoadModel(self, request, context): def LoadModel(self, request, context):
model_name = request.Model model_name = request.Model
model_name = os.path.basename(model_name)
try: try:
self.model = SentenceTransformer(model_name) self.model = SentenceTransformer(model_name)
except Exception as err: except Exception as err:

View file

@ -1,4 +1,6 @@
sentence_transformers sentence_transformers
grpcio grpcio
google google
protobuf protobuf
https://github.com/PanQiWei/AutoGPTQ/releases/download/v0.3.0/auto_gptq-0.3.0+cu117-cp310-cp310-win_amd64.whl; platform_system == "Windows"
https://github.com/PanQiWei/AutoGPTQ/releases/download/v0.3.0/auto_gptq-0.3.0+cu117-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64"

View file

@ -16,7 +16,7 @@ type StableDiffusion struct {
func (sd *StableDiffusion) Load(opts *pb.ModelOptions) error { func (sd *StableDiffusion) Load(opts *pb.ModelOptions) error {
var err error var err error
// Note: the Model here is a path to a directory containing the model files // Note: the Model here is a path to a directory containing the model files
sd.stablediffusion, err = stablediffusion.New(opts.Model) sd.stablediffusion, err = stablediffusion.New(opts.ModelFile)
return err return err
} }

View file

@ -15,7 +15,7 @@ type Embeddings struct {
} }
func (llm *Embeddings) Load(opts *pb.ModelOptions) error { func (llm *Embeddings) Load(opts *pb.ModelOptions) error {
model, err := bert.New(opts.Model) model, err := bert.New(opts.ModelFile)
llm.bert = model llm.bert = model
return err return err
} }

View file

@ -18,7 +18,7 @@ type LLM struct {
} }
func (llm *LLM) Load(opts *pb.ModelOptions) error { func (llm *LLM) Load(opts *pb.ModelOptions) error {
model, err := bloomz.New(opts.Model) model, err := bloomz.New(opts.ModelFile)
llm.bloomz = model llm.bloomz = model
return err return err
} }

View file

@ -40,7 +40,7 @@ func (llm *LLM) Load(opts *pb.ModelOptions) error {
ggllmOpts = append(ggllmOpts, ggllm.SetNBatch(512)) ggllmOpts = append(ggllmOpts, ggllm.SetNBatch(512))
} }
model, err := ggllm.New(opts.Model, ggllmOpts...) model, err := ggllm.New(opts.ModelFile, ggllmOpts...)
llm.falcon = model llm.falcon = model
return err return err
} }

View file

@ -17,7 +17,7 @@ type LLM struct {
} }
func (llm *LLM) Load(opts *pb.ModelOptions) error { func (llm *LLM) Load(opts *pb.ModelOptions) error {
model, err := gpt4all.New(opts.Model, model, err := gpt4all.New(opts.ModelFile,
gpt4all.SetThreads(int(opts.Threads)), gpt4all.SetThreads(int(opts.Threads)),
gpt4all.SetLibrarySearchPath(opts.LibrarySearchPath)) gpt4all.SetLibrarySearchPath(opts.LibrarySearchPath))
llm.gpt4all = model llm.gpt4all = model

View file

@ -71,7 +71,7 @@ func (llm *LLM) Load(opts *pb.ModelOptions) error {
llamaOpts = append(llamaOpts, llama.EnabelLowVRAM) llamaOpts = append(llamaOpts, llama.EnabelLowVRAM)
} }
model, err := llama.New(opts.Model, llamaOpts...) model, err := llama.New(opts.ModelFile, llamaOpts...)
llm.llama = model llm.llama = model
return err return err
} }

View file

@ -20,9 +20,9 @@ type LLM struct {
} }
func (llm *LLM) Load(opts *pb.ModelOptions) error { func (llm *LLM) Load(opts *pb.ModelOptions) error {
modelPath := filepath.Dir(opts.Model) modelPath := filepath.Dir(opts.ModelFile)
modelFile := filepath.Base(opts.Model) modelFile := filepath.Base(opts.ModelFile)
model := rwkv.LoadFiles(opts.Model, filepath.Join(modelPath, modelFile+tokenizerSuffix), uint32(opts.GetThreads())) model := rwkv.LoadFiles(opts.ModelFile, filepath.Join(modelPath, modelFile+tokenizerSuffix), uint32(opts.GetThreads()))
if model == nil { if model == nil {
return fmt.Errorf("could not load model") return fmt.Errorf("could not load model")

View file

@ -18,7 +18,7 @@ type Dolly struct {
} }
func (llm *Dolly) Load(opts *pb.ModelOptions) error { func (llm *Dolly) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewDolly(opts.Model) model, err := transformers.NewDolly(opts.ModelFile)
llm.dolly = model llm.dolly = model
return err return err
} }

View file

@ -18,7 +18,7 @@ type Falcon struct {
} }
func (llm *Falcon) Load(opts *pb.ModelOptions) error { func (llm *Falcon) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewFalcon(opts.Model) model, err := transformers.NewFalcon(opts.ModelFile)
llm.falcon = model llm.falcon = model
return err return err
} }

View file

@ -18,7 +18,7 @@ type GPT2 struct {
} }
func (llm *GPT2) Load(opts *pb.ModelOptions) error { func (llm *GPT2) Load(opts *pb.ModelOptions) error {
model, err := transformers.New(opts.Model) model, err := transformers.New(opts.ModelFile)
llm.gpt2 = model llm.gpt2 = model
return err return err
} }

View file

@ -18,7 +18,7 @@ type GPTJ struct {
} }
func (llm *GPTJ) Load(opts *pb.ModelOptions) error { func (llm *GPTJ) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewGPTJ(opts.Model) model, err := transformers.NewGPTJ(opts.ModelFile)
llm.gptj = model llm.gptj = model
return err return err
} }

View file

@ -18,7 +18,7 @@ type GPTNeoX struct {
} }
func (llm *GPTNeoX) Load(opts *pb.ModelOptions) error { func (llm *GPTNeoX) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewGPTNeoX(opts.Model) model, err := transformers.NewGPTNeoX(opts.ModelFile)
llm.gptneox = model llm.gptneox = model
return err return err
} }

View file

@ -18,7 +18,7 @@ type MPT struct {
} }
func (llm *MPT) Load(opts *pb.ModelOptions) error { func (llm *MPT) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewMPT(opts.Model) model, err := transformers.NewMPT(opts.ModelFile)
llm.mpt = model llm.mpt = model
return err return err
} }

View file

@ -18,7 +18,7 @@ type Replit struct {
} }
func (llm *Replit) Load(opts *pb.ModelOptions) error { func (llm *Replit) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewReplit(opts.Model) model, err := transformers.NewReplit(opts.ModelFile)
llm.replit = model llm.replit = model
return err return err
} }

View file

@ -18,7 +18,7 @@ type Starcoder struct {
} }
func (llm *Starcoder) Load(opts *pb.ModelOptions) error { func (llm *Starcoder) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewStarcoder(opts.Model) model, err := transformers.NewStarcoder(opts.ModelFile)
llm.starcoder = model llm.starcoder = model
return err return err
} }

View file

@ -483,6 +483,11 @@ type ModelOptions struct {
RopeFreqScale float32 `protobuf:"fixed32,18,opt,name=RopeFreqScale,proto3" json:"RopeFreqScale,omitempty"` RopeFreqScale float32 `protobuf:"fixed32,18,opt,name=RopeFreqScale,proto3" json:"RopeFreqScale,omitempty"`
RMSNormEps float32 `protobuf:"fixed32,19,opt,name=RMSNormEps,proto3" json:"RMSNormEps,omitempty"` RMSNormEps float32 `protobuf:"fixed32,19,opt,name=RMSNormEps,proto3" json:"RMSNormEps,omitempty"`
NGQA int32 `protobuf:"varint,20,opt,name=NGQA,proto3" json:"NGQA,omitempty"` NGQA int32 `protobuf:"varint,20,opt,name=NGQA,proto3" json:"NGQA,omitempty"`
ModelFile string `protobuf:"bytes,21,opt,name=ModelFile,proto3" json:"ModelFile,omitempty"`
// AutoGPTQ
Device string `protobuf:"bytes,22,opt,name=Device,proto3" json:"Device,omitempty"`
UseTriton bool `protobuf:"varint,23,opt,name=UseTriton,proto3" json:"UseTriton,omitempty"`
ModelBaseName string `protobuf:"bytes,24,opt,name=ModelBaseName,proto3" json:"ModelBaseName,omitempty"`
} }
func (x *ModelOptions) Reset() { func (x *ModelOptions) Reset() {
@ -657,6 +662,34 @@ func (x *ModelOptions) GetNGQA() int32 {
return 0 return 0
} }
func (x *ModelOptions) GetModelFile() string {
if x != nil {
return x.ModelFile
}
return ""
}
func (x *ModelOptions) GetDevice() string {
if x != nil {
return x.Device
}
return ""
}
func (x *ModelOptions) GetUseTriton() bool {
if x != nil {
return x.UseTriton
}
return false
}
func (x *ModelOptions) GetModelBaseName() string {
if x != nil {
return x.ModelBaseName
}
return ""
}
type Result struct { type Result struct {
state protoimpl.MessageState state protoimpl.MessageState
sizeCache protoimpl.SizeCache sizeCache protoimpl.SizeCache
@ -1207,7 +1240,7 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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@ -1243,90 +1276,98 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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0x33,
} }
var ( var (

View file

@ -89,6 +89,12 @@ message ModelOptions {
float RopeFreqScale = 18; float RopeFreqScale = 18;
float RMSNormEps = 19; float RMSNormEps = 19;
int32 NGQA = 20; int32 NGQA = 20;
string ModelFile = 21;
// AutoGPTQ
string Device = 22;
bool UseTriton = 23;
string ModelBaseName = 24;
} }
message Result { message Result {

View file

@ -17,7 +17,7 @@ type Whisper struct {
func (sd *Whisper) Load(opts *pb.ModelOptions) error { func (sd *Whisper) Load(opts *pb.ModelOptions) error {
// Note: the Model here is a path to a directory containing the model files // Note: the Model here is a path to a directory containing the model files
w, err := whisper.New(opts.Model) w, err := whisper.New(opts.ModelFile)
sd.whisper = w sd.whisper = w
return err return err
} }

View file

@ -18,8 +18,8 @@ type Piper struct {
} }
func (sd *Piper) Load(opts *pb.ModelOptions) error { func (sd *Piper) Load(opts *pb.ModelOptions) error {
if filepath.Ext(opts.Model) != ".onnx" { if filepath.Ext(opts.ModelFile) != ".onnx" {
return fmt.Errorf("unsupported model type %s (should end with .onnx)", opts.Model) return fmt.Errorf("unsupported model type %s (should end with .onnx)", opts.ModelFile)
} }
var err error var err error
// Note: the Model here is a path to a directory containing the model files // Note: the Model here is a path to a directory containing the model files

View file

@ -124,8 +124,8 @@ func (ml *ModelLoader) startProcess(grpcProcess, id string, serverAddress string
// starts the grpcModelProcess for the backend, and returns a grpc client // starts the grpcModelProcess for the backend, and returns a grpc client
// It also loads the model // It also loads the model
func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc.Client, error) { func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string, string) (*grpc.Client, error) {
return func(s string) (*grpc.Client, error) { return func(modelName, modelFile string) (*grpc.Client, error) {
log.Debug().Msgf("Loading GRPC Model %s: %+v", backend, *o) log.Debug().Msgf("Loading GRPC Model %s: %+v", backend, *o)
var client *grpc.Client var client *grpc.Client
@ -148,7 +148,7 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
return nil, fmt.Errorf("failed allocating free ports: %s", err.Error()) return nil, fmt.Errorf("failed allocating free ports: %s", err.Error())
} }
// Make sure the process is executable // Make sure the process is executable
if err := ml.startProcess(uri, o.modelFile, serverAddress); err != nil { if err := ml.startProcess(uri, o.model, serverAddress); err != nil {
return nil, err return nil, err
} }
@ -172,7 +172,7 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
} }
// Make sure the process is executable // Make sure the process is executable
if err := ml.startProcess(grpcProcess, o.modelFile, serverAddress); err != nil { if err := ml.startProcess(grpcProcess, o.model, serverAddress); err != nil {
return nil, err return nil, err
} }
@ -198,7 +198,8 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
} }
options := *o.gRPCOptions options := *o.gRPCOptions
options.Model = s options.Model = modelName
options.ModelFile = modelFile
log.Debug().Msgf("GRPC: Loading model with options: %+v", options) log.Debug().Msgf("GRPC: Loading model with options: %+v", options)
@ -217,14 +218,14 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
func (ml *ModelLoader) BackendLoader(opts ...Option) (model *grpc.Client, err error) { func (ml *ModelLoader) BackendLoader(opts ...Option) (model *grpc.Client, err error) {
o := NewOptions(opts...) o := NewOptions(opts...)
log.Debug().Msgf("Loading model %s from %s", o.backendString, o.modelFile) log.Debug().Msgf("Loading model %s from %s", o.backendString, o.model)
backend := strings.ToLower(o.backendString) backend := strings.ToLower(o.backendString)
// if an external backend is provided, use it // if an external backend is provided, use it
_, externalBackendExists := o.externalBackends[backend] _, externalBackendExists := o.externalBackends[backend]
if externalBackendExists { if externalBackendExists {
return ml.LoadModel(o.modelFile, ml.grpcModel(backend, o)) return ml.LoadModel(o.model, ml.grpcModel(backend, o))
} }
switch backend { switch backend {
@ -232,13 +233,13 @@ func (ml *ModelLoader) BackendLoader(opts ...Option) (model *grpc.Client, err er
MPTBackend, Gpt2Backend, FalconBackend, MPTBackend, Gpt2Backend, FalconBackend,
GPTNeoXBackend, ReplitBackend, StarcoderBackend, BloomzBackend, GPTNeoXBackend, ReplitBackend, StarcoderBackend, BloomzBackend,
RwkvBackend, LCHuggingFaceBackend, BertEmbeddingsBackend, FalconGGMLBackend, StableDiffusionBackend, WhisperBackend: RwkvBackend, LCHuggingFaceBackend, BertEmbeddingsBackend, FalconGGMLBackend, StableDiffusionBackend, WhisperBackend:
return ml.LoadModel(o.modelFile, ml.grpcModel(backend, o)) return ml.LoadModel(o.model, ml.grpcModel(backend, o))
case Gpt4AllLlamaBackend, Gpt4AllMptBackend, Gpt4AllJBackend, Gpt4All: case Gpt4AllLlamaBackend, Gpt4AllMptBackend, Gpt4AllJBackend, Gpt4All:
o.gRPCOptions.LibrarySearchPath = filepath.Join(o.assetDir, "backend-assets", "gpt4all") o.gRPCOptions.LibrarySearchPath = filepath.Join(o.assetDir, "backend-assets", "gpt4all")
return ml.LoadModel(o.modelFile, ml.grpcModel(Gpt4All, o)) return ml.LoadModel(o.model, ml.grpcModel(Gpt4All, o))
case PiperBackend: case PiperBackend:
o.gRPCOptions.LibrarySearchPath = filepath.Join(o.assetDir, "backend-assets", "espeak-ng-data") o.gRPCOptions.LibrarySearchPath = filepath.Join(o.assetDir, "backend-assets", "espeak-ng-data")
return ml.LoadModel(o.modelFile, ml.grpcModel(PiperBackend, o)) return ml.LoadModel(o.model, ml.grpcModel(PiperBackend, o))
default: default:
return nil, fmt.Errorf("backend unsupported: %s", o.backendString) return nil, fmt.Errorf("backend unsupported: %s", o.backendString)
} }
@ -249,8 +250,8 @@ func (ml *ModelLoader) GreedyLoader(opts ...Option) (*grpc.Client, error) {
// Is this really needed? BackendLoader already does this // Is this really needed? BackendLoader already does this
ml.mu.Lock() ml.mu.Lock()
if m := ml.checkIsLoaded(o.modelFile); m != nil { if m := ml.checkIsLoaded(o.model); m != nil {
log.Debug().Msgf("Model '%s' already loaded", o.modelFile) log.Debug().Msgf("Model '%s' already loaded", o.model)
ml.mu.Unlock() ml.mu.Unlock()
return m, nil return m, nil
} }
@ -263,13 +264,13 @@ func (ml *ModelLoader) GreedyLoader(opts ...Option) (*grpc.Client, error) {
for _, b := range o.externalBackends { for _, b := range o.externalBackends {
allBackendsToAutoLoad = append(allBackendsToAutoLoad, b) allBackendsToAutoLoad = append(allBackendsToAutoLoad, b)
} }
log.Debug().Msgf("Loading model '%s' greedly from all the available backends: %s", o.modelFile, strings.Join(allBackendsToAutoLoad, ", ")) log.Debug().Msgf("Loading model '%s' greedly from all the available backends: %s", o.model, strings.Join(allBackendsToAutoLoad, ", "))
for _, b := range allBackendsToAutoLoad { for _, b := range allBackendsToAutoLoad {
log.Debug().Msgf("[%s] Attempting to load", b) log.Debug().Msgf("[%s] Attempting to load", b)
options := []Option{ options := []Option{
WithBackendString(b), WithBackendString(b),
WithModelFile(o.modelFile), WithModel(o.model),
WithLoadGRPCLLMModelOpts(o.gRPCOptions), WithLoadGRPCLLMModelOpts(o.gRPCOptions),
WithThreads(o.threads), WithThreads(o.threads),
WithAssetDir(o.assetDir), WithAssetDir(o.assetDir),

View file

@ -98,7 +98,7 @@ func (ml *ModelLoader) ListModels() ([]string, error) {
return models, nil return models, nil
} }
func (ml *ModelLoader) LoadModel(modelName string, loader func(string) (*grpc.Client, error)) (*grpc.Client, error) { func (ml *ModelLoader) LoadModel(modelName string, loader func(string, string) (*grpc.Client, error)) (*grpc.Client, error) {
ml.mu.Lock() ml.mu.Lock()
defer ml.mu.Unlock() defer ml.mu.Unlock()
@ -111,7 +111,7 @@ func (ml *ModelLoader) LoadModel(modelName string, loader func(string) (*grpc.Cl
modelFile := filepath.Join(ml.ModelPath, modelName) modelFile := filepath.Join(ml.ModelPath, modelName)
log.Debug().Msgf("Loading model in memory from file: %s", modelFile) log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
model, err := loader(modelFile) model, err := loader(modelName, modelFile)
if err != nil { if err != nil {
return nil, err return nil, err
} }

View file

@ -8,7 +8,7 @@ import (
type Options struct { type Options struct {
backendString string backendString string
modelFile string model string
threads uint32 threads uint32
assetDir string assetDir string
context context.Context context context.Context
@ -35,9 +35,9 @@ func WithBackendString(backend string) Option {
} }
} }
func WithModelFile(modelFile string) Option { func WithModel(modelFile string) Option {
return func(o *Options) { return func(o *Options) {
o.modelFile = modelFile o.model = modelFile
} }
} }