mirror of
https://github.com/mudler/LocalAI.git
synced 2024-12-18 20:27:57 +00:00
feat: add initial AutoGPTQ backend implementation
This commit is contained in:
Ettore Di Giacinto
parent
91d49cfe9f
commit
a843e64fc2
3
Makefile
3
Makefile
@ -335,7 +335,8 @@ protogen-go:
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pkg/grpc/proto/backend.proto
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protogen-python:
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python -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/huggingface/ --grpc_python_out=extra/grpc/huggingface/ pkg/grpc/proto/backend.proto
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python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/huggingface/ --grpc_python_out=extra/grpc/huggingface/ pkg/grpc/proto/backend.proto
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python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/autogptq/ --grpc_python_out=extra/grpc/autogptq/ pkg/grpc/proto/backend.proto
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## GRPC
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@ -26,7 +26,7 @@ func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.
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model.WithLoadGRPCLLMModelOpts(grpcOpts),
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model.WithThreads(uint32(c.Threads)),
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model.WithAssetDir(o.AssetsDestination),
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model.WithModelFile(modelFile),
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model.WithModel(modelFile),
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model.WithContext(o.Context),
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}
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@ -20,7 +20,7 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
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model.WithAssetDir(o.AssetsDestination),
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model.WithThreads(uint32(c.Threads)),
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model.WithContext(o.Context),
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model.WithModelFile(c.ImageGenerationAssets),
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model.WithModel(c.ImageGenerationAssets),
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}
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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
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model.WithLoadGRPCLLMModelOpts(grpcOpts),
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model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
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model.WithAssetDir(o.AssetsDestination),
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model.WithModelFile(modelFile),
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model.WithModel(modelFile),
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model.WithContext(o.Context),
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}
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@ -19,6 +19,9 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
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Seed: int32(c.Seed),
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NBatch: int32(b),
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NGQA: c.NGQA,
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ModelBaseName: c.ModelBaseName,
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Device: c.Device,
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UseTriton: c.Triton,
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RMSNormEps: c.RMSNormEps,
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F16Memory: c.F16,
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MLock: c.MMlock,
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@ -15,7 +15,7 @@ import (
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func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*api.Result, error) {
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opts := []model.Option{
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model.WithBackendString(model.WhisperBackend),
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model.WithModelFile(c.Model),
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model.WithModel(c.Model),
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model.WithContext(o.Context),
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model.WithThreads(uint32(c.Threads)),
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model.WithAssetDir(o.AssetsDestination),
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@ -54,6 +54,11 @@ type Config struct {
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RMSNormEps float32 `yaml:"rms_norm_eps"`
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NGQA int32 `yaml:"ngqa"`
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// AutoGPTQ
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ModelBaseName string `yaml:"model_base_name"`
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Device string `yaml:"device"`
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Triton bool `yaml:"triton"`
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}
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type Functions struct {
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@ -2,6 +2,7 @@ package openai
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import (
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"context"
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config "github.com/go-skynet/LocalAI/api/config"
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"github.com/go-skynet/LocalAI/pkg/grammar"
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@ -106,4 +107,9 @@ type OpenAIRequest struct {
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Grammar string `json:"grammar" yaml:"grammar"`
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JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
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Backend string `json:"backend" yaml:"backend"`
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// AutoGPTQ
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ModelBaseName string `json:"model_base_name" yaml:"model_base_name"`
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}
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@ -71,6 +71,14 @@ func updateConfig(config *config.Config, input *OpenAIRequest) {
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config.TopP = input.TopP
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}
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if input.Backend != "" {
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config.Backend = input.Backend
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}
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if input.ModelBaseName != "" {
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config.ModelBaseName = input.ModelBaseName
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}
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if input.NegativePromptScale != 0 {
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config.NegativePromptScale = input.NegativePromptScale
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}
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94
extra/grpc/autogptq/autogptq.py
Executable file
94
extra/grpc/autogptq/autogptq.py
Executable file
@ -0,0 +1,94 @@
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#!/usr/bin/env python3
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import grpc
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from concurrent import futures
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import time
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import backend_pb2
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import backend_pb2_grpc
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import argparse
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import signal
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import sys
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import os
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from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
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from pathlib import Path
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from transformers import AutoTokenizer
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from transformers import TextGenerationPipeline
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_ONE_DAY_IN_SECONDS = 60 * 60 * 24
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# Implement the BackendServicer class with the service methods
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class BackendServicer(backend_pb2_grpc.BackendServicer):
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def Health(self, request, context):
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return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
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def LoadModel(self, request, context):
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try:
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device = "cuda:0"
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if request.Device != "":
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device = request.Device
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tokenizer = AutoTokenizer.from_pretrained(request.Model, use_fast=True)
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model = AutoGPTQForCausalLM.from_quantized(request.Model,
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model_basename=request.ModelBaseName,
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use_safetensors=True,
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trust_remote_code=True,
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device=device,
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use_triton=request.UseTriton,
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quantize_config=None)
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self.model = model
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self.tokenizer = tokenizer
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except Exception as err:
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return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
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return backend_pb2.Result(message="Model loaded successfully", success=True)
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def Predict(self, request, context):
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# Implement Predict RPC
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pipeline = TextGenerationPipeline(
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model=self.model,
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tokenizer=self.tokenizer,
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max_new_tokens=request.Tokens,
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temperature=request.Temperature,
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top_p=request.TopP,
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repetition_penalty=request.Penalty,
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)
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return backend_pb2.Result(message=bytes(pipeline(request.Prompt)[0]["generated_text"]))
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def PredictStream(self, request, context):
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# Implement PredictStream RPC
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#for reply in some_data_generator():
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# yield reply
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# Not implemented yet
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return self.Predict(request, context)
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def serve(address):
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server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
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backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
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server.add_insecure_port(address)
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server.start()
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print("Server started. Listening on: " + address, file=sys.stderr)
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# Define the signal handler function
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def signal_handler(sig, frame):
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print("Received termination signal. Shutting down...")
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server.stop(0)
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sys.exit(0)
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# Set the signal handlers for SIGINT and SIGTERM
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signal.signal(signal.SIGINT, signal_handler)
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signal.signal(signal.SIGTERM, signal_handler)
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try:
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while True:
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time.sleep(_ONE_DAY_IN_SECONDS)
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except KeyboardInterrupt:
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server.stop(0)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Run the gRPC server.")
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parser.add_argument(
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"--addr", default="localhost:50051", help="The address to bind the server to."
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)
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args = parser.parse_args()
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serve(args.addr)
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49
extra/grpc/autogptq/backend_pb2.py
Normal file
49
extra/grpc/autogptq/backend_pb2.py
Normal file
@ -0,0 +1,49 @@
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# -*- coding: utf-8 -*-
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# Generated by the protocol buffer compiler. DO NOT EDIT!
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# source: backend.proto
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"""Generated protocol buffer code."""
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from google.protobuf import descriptor as _descriptor
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from google.protobuf import descriptor_pool as _descriptor_pool
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from google.protobuf import symbol_database as _symbol_database
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from google.protobuf.internal import builder as _builder
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# @@protoc_insertion_point(imports)
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_sym_db = _symbol_database.Default()
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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')
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_globals = globals()
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
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_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
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if _descriptor._USE_C_DESCRIPTORS == False:
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DESCRIPTOR._options = None
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DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
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_globals['_HEALTHMESSAGE']._serialized_start=26
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_globals['_HEALTHMESSAGE']._serialized_end=41
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_globals['_PREDICTOPTIONS']._serialized_start=44
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_globals['_PREDICTOPTIONS']._serialized_end=818
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_globals['_REPLY']._serialized_start=820
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_globals['_REPLY']._serialized_end=844
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_globals['_MODELOPTIONS']._serialized_start=847
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_globals['_MODELOPTIONS']._serialized_end=1303
|
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_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
|
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_globals['_TRANSCRIPTRESULT']._serialized_start=1457
|
||||
_globals['_TRANSCRIPTRESULT']._serialized_end=1535
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_globals['_TRANSCRIPTSEGMENT']._serialized_start=1537
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_globals['_TRANSCRIPTSEGMENT']._serialized_end=1626
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_globals['_GENERATEIMAGEREQUEST']._serialized_start=1629
|
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_globals['_GENERATEIMAGEREQUEST']._serialized_end=1787
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_globals['_TTSREQUEST']._serialized_start=1789
|
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_globals['_TTSREQUEST']._serialized_end=1843
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_globals['_BACKEND']._serialized_start=1846
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_globals['_BACKEND']._serialized_end=2337
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# @@protoc_insertion_point(module_scope)
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297
extra/grpc/autogptq/backend_pb2_grpc.py
Normal file
297
extra/grpc/autogptq/backend_pb2_grpc.py
Normal file
@ -0,0 +1,297 @@
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# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
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"""Client and server classes corresponding to protobuf-defined services."""
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import grpc
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import backend_pb2 as backend__pb2
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class BackendStub(object):
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"""Missing associated documentation comment in .proto file."""
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def __init__(self, channel):
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"""Constructor.
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Args:
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channel: A grpc.Channel.
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"""
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self.Health = channel.unary_unary(
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'/backend.Backend/Health',
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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)
|
||||
@ -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()
|
||||
_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=1226
|
||||
_globals['_RESULT']._serialized_start=1228
|
||||
_globals['_RESULT']._serialized_end=1270
|
||||
_globals['_EMBEDDINGRESULT']._serialized_start=1272
|
||||
_globals['_EMBEDDINGRESULT']._serialized_end=1309
|
||||
_globals['_TRANSCRIPTREQUEST']._serialized_start=1311
|
||||
_globals['_TRANSCRIPTREQUEST']._serialized_end=1378
|
||||
_globals['_TRANSCRIPTRESULT']._serialized_start=1380
|
||||
_globals['_TRANSCRIPTRESULT']._serialized_end=1458
|
||||
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1460
|
||||
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1549
|
||||
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1552
|
||||
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1710
|
||||
_globals['_TTSREQUEST']._serialized_start=1712
|
||||
_globals['_TTSREQUEST']._serialized_end=1766
|
||||
_globals['_BACKEND']._serialized_start=1769
|
||||
_globals['_BACKEND']._serialized_end=2260
|
||||
_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)
|
||||
|
||||
@ -18,7 +18,6 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
|
||||
return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
|
||||
def LoadModel(self, request, context):
|
||||
model_name = request.Model
|
||||
model_name = os.path.basename(model_name)
|
||||
try:
|
||||
self.model = SentenceTransformer(model_name)
|
||||
except Exception as err:
|
||||
|
||||
@ -1,4 +1,6 @@
|
||||
sentence_transformers
|
||||
grpcio
|
||||
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"
|
||||
|
||||
@ -16,7 +16,7 @@ type StableDiffusion struct {
|
||||
func (sd *StableDiffusion) Load(opts *pb.ModelOptions) error {
|
||||
var err error
|
||||
// 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
|
||||
}
|
||||
|
||||
|
||||
@ -15,7 +15,7 @@ type Embeddings struct {
|
||||
}
|
||||
|
||||
func (llm *Embeddings) Load(opts *pb.ModelOptions) error {
|
||||
model, err := bert.New(opts.Model)
|
||||
model, err := bert.New(opts.ModelFile)
|
||||
llm.bert = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@ type LLM struct {
|
||||
}
|
||||
|
||||
func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
model, err := bloomz.New(opts.Model)
|
||||
model, err := bloomz.New(opts.ModelFile)
|
||||
llm.bloomz = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -40,7 +40,7 @@ func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
ggllmOpts = append(ggllmOpts, ggllm.SetNBatch(512))
|
||||
}
|
||||
|
||||
model, err := ggllm.New(opts.Model, ggllmOpts...)
|
||||
model, err := ggllm.New(opts.ModelFile, ggllmOpts...)
|
||||
llm.falcon = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -17,7 +17,7 @@ type LLM struct {
|
||||
}
|
||||
|
||||
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.SetLibrarySearchPath(opts.LibrarySearchPath))
|
||||
llm.gpt4all = model
|
||||
|
||||
@ -71,7 +71,7 @@ func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
llamaOpts = append(llamaOpts, llama.EnabelLowVRAM)
|
||||
}
|
||||
|
||||
model, err := llama.New(opts.Model, llamaOpts...)
|
||||
model, err := llama.New(opts.ModelFile, llamaOpts...)
|
||||
llm.llama = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -20,9 +20,9 @@ type LLM struct {
|
||||
}
|
||||
|
||||
func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
modelPath := filepath.Dir(opts.Model)
|
||||
modelFile := filepath.Base(opts.Model)
|
||||
model := rwkv.LoadFiles(opts.Model, filepath.Join(modelPath, modelFile+tokenizerSuffix), uint32(opts.GetThreads()))
|
||||
modelPath := filepath.Dir(opts.ModelFile)
|
||||
modelFile := filepath.Base(opts.ModelFile)
|
||||
model := rwkv.LoadFiles(opts.ModelFile, filepath.Join(modelPath, modelFile+tokenizerSuffix), uint32(opts.GetThreads()))
|
||||
|
||||
if model == nil {
|
||||
return fmt.Errorf("could not load model")
|
||||
|
||||
@ -18,7 +18,7 @@ type Dolly struct {
|
||||
}
|
||||
|
||||
func (llm *Dolly) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewDolly(opts.Model)
|
||||
model, err := transformers.NewDolly(opts.ModelFile)
|
||||
llm.dolly = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@ type Falcon struct {
|
||||
}
|
||||
|
||||
func (llm *Falcon) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewFalcon(opts.Model)
|
||||
model, err := transformers.NewFalcon(opts.ModelFile)
|
||||
llm.falcon = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@ type GPT2 struct {
|
||||
}
|
||||
|
||||
func (llm *GPT2) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.New(opts.Model)
|
||||
model, err := transformers.New(opts.ModelFile)
|
||||
llm.gpt2 = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@ type GPTJ struct {
|
||||
}
|
||||
|
||||
func (llm *GPTJ) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewGPTJ(opts.Model)
|
||||
model, err := transformers.NewGPTJ(opts.ModelFile)
|
||||
llm.gptj = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@ type GPTNeoX struct {
|
||||
}
|
||||
|
||||
func (llm *GPTNeoX) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewGPTNeoX(opts.Model)
|
||||
model, err := transformers.NewGPTNeoX(opts.ModelFile)
|
||||
llm.gptneox = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@ type MPT struct {
|
||||
}
|
||||
|
||||
func (llm *MPT) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewMPT(opts.Model)
|
||||
model, err := transformers.NewMPT(opts.ModelFile)
|
||||
llm.mpt = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@ type Replit struct {
|
||||
}
|
||||
|
||||
func (llm *Replit) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewReplit(opts.Model)
|
||||
model, err := transformers.NewReplit(opts.ModelFile)
|
||||
llm.replit = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,7 +18,7 @@ type Starcoder struct {
|
||||
}
|
||||
|
||||
func (llm *Starcoder) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewStarcoder(opts.Model)
|
||||
model, err := transformers.NewStarcoder(opts.ModelFile)
|
||||
llm.starcoder = model
|
||||
return err
|
||||
}
|
||||
|
||||
@ -483,6 +483,11 @@ type ModelOptions struct {
|
||||
RopeFreqScale float32 `protobuf:"fixed32,18,opt,name=RopeFreqScale,proto3" json:"RopeFreqScale,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"`
|
||||
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() {
|
||||
@ -657,6 +662,34 @@ func (x *ModelOptions) GetNGQA() int32 {
|
||||
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 {
|
||||
state protoimpl.MessageState
|
||||
sizeCache protoimpl.SizeCache
|
||||
@ -1207,7 +1240,7 @@ 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,
|
||||
0x21, 0x0a, 0x05, 0x52, 0x65, 0x70, 0x6c, 0x79, 0x12, 0x18, 0x0a, 0x07, 0x6d, 0x65, 0x73, 0x73,
|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
0x65, 0x74, 0x2f, 0x4c, 0x6f, 0x63, 0x61, 0x6c, 0x41, 0x49, 0x2f, 0x70, 0x6b, 0x67, 0x2f, 0x67,
|
||||
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|
||||
0x33,
|
||||
}
|
||||
|
||||
var (
|
||||
|
||||
@ -89,6 +89,12 @@ message ModelOptions {
|
||||
float RopeFreqScale = 18;
|
||||
float RMSNormEps = 19;
|
||||
int32 NGQA = 20;
|
||||
string ModelFile = 21;
|
||||
|
||||
// AutoGPTQ
|
||||
string Device = 22;
|
||||
bool UseTriton = 23;
|
||||
string ModelBaseName = 24;
|
||||
}
|
||||
|
||||
message Result {
|
||||
|
||||
@ -17,7 +17,7 @@ type Whisper struct {
|
||||
|
||||
func (sd *Whisper) Load(opts *pb.ModelOptions) error {
|
||||
// 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
|
||||
return err
|
||||
}
|
||||
|
||||
@ -18,8 +18,8 @@ type Piper struct {
|
||||
}
|
||||
|
||||
func (sd *Piper) Load(opts *pb.ModelOptions) error {
|
||||
if filepath.Ext(opts.Model) != ".onnx" {
|
||||
return fmt.Errorf("unsupported model type %s (should end with .onnx)", opts.Model)
|
||||
if filepath.Ext(opts.ModelFile) != ".onnx" {
|
||||
return fmt.Errorf("unsupported model type %s (should end with .onnx)", opts.ModelFile)
|
||||
}
|
||||
var err error
|
||||
// Note: the Model here is a path to a directory containing the model files
|
||||
|
||||
@ -124,8 +124,8 @@ func (ml *ModelLoader) startProcess(grpcProcess, id string, serverAddress string
|
||||
|
||||
// starts the grpcModelProcess for the backend, and returns a grpc client
|
||||
// It also loads the model
|
||||
func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc.Client, error) {
|
||||
return func(s string) (*grpc.Client, error) {
|
||||
func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string, string) (*grpc.Client, error) {
|
||||
return func(modelName, modelFile string) (*grpc.Client, error) {
|
||||
log.Debug().Msgf("Loading GRPC Model %s: %+v", backend, *o)
|
||||
|
||||
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())
|
||||
}
|
||||
// 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
|
||||
}
|
||||
|
||||
@ -172,7 +172,7 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
|
||||
}
|
||||
|
||||
// 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
|
||||
}
|
||||
|
||||
@ -198,7 +198,8 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
|
||||
}
|
||||
|
||||
options := *o.gRPCOptions
|
||||
options.Model = s
|
||||
options.Model = modelName
|
||||
options.ModelFile = modelFile
|
||||
|
||||
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) {
|
||||
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)
|
||||
|
||||
// if an external backend is provided, use it
|
||||
_, externalBackendExists := o.externalBackends[backend]
|
||||
if externalBackendExists {
|
||||
return ml.LoadModel(o.modelFile, ml.grpcModel(backend, o))
|
||||
return ml.LoadModel(o.model, ml.grpcModel(backend, o))
|
||||
}
|
||||
|
||||
switch backend {
|
||||
@ -232,13 +233,13 @@ func (ml *ModelLoader) BackendLoader(opts ...Option) (model *grpc.Client, err er
|
||||
MPTBackend, Gpt2Backend, FalconBackend,
|
||||
GPTNeoXBackend, ReplitBackend, StarcoderBackend, BloomzBackend,
|
||||
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:
|
||||
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:
|
||||
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:
|
||||
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
|
||||
ml.mu.Lock()
|
||||
if m := ml.checkIsLoaded(o.modelFile); m != nil {
|
||||
log.Debug().Msgf("Model '%s' already loaded", o.modelFile)
|
||||
if m := ml.checkIsLoaded(o.model); m != nil {
|
||||
log.Debug().Msgf("Model '%s' already loaded", o.model)
|
||||
ml.mu.Unlock()
|
||||
return m, nil
|
||||
}
|
||||
@ -263,13 +264,13 @@ func (ml *ModelLoader) GreedyLoader(opts ...Option) (*grpc.Client, error) {
|
||||
for _, b := range o.externalBackends {
|
||||
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 {
|
||||
log.Debug().Msgf("[%s] Attempting to load", b)
|
||||
options := []Option{
|
||||
WithBackendString(b),
|
||||
WithModelFile(o.modelFile),
|
||||
WithModel(o.model),
|
||||
WithLoadGRPCLLMModelOpts(o.gRPCOptions),
|
||||
WithThreads(o.threads),
|
||||
WithAssetDir(o.assetDir),
|
||||
|
||||
@ -98,7 +98,7 @@ func (ml *ModelLoader) ListModels() ([]string, error) {
|
||||
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()
|
||||
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)
|
||||
log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
|
||||
|
||||
model, err := loader(modelFile)
|
||||
model, err := loader(modelName, modelFile)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
@ -8,7 +8,7 @@ import (
|
||||
|
||||
type Options struct {
|
||||
backendString string
|
||||
modelFile string
|
||||
model string
|
||||
threads uint32
|
||||
assetDir string
|
||||
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) {
|
||||
o.modelFile = modelFile
|
||||
o.model = modelFile
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user