mirror of
https://github.com/mudler/LocalAI.git
synced 2024-12-19 04:37:53 +00:00
8ad669339e
Wip openvoice
159 lines
6.0 KiB
Python
Executable File
159 lines
6.0 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
"""
|
|
Extra gRPC server for OpenVoice models.
|
|
"""
|
|
from concurrent import futures
|
|
|
|
import argparse
|
|
import signal
|
|
import sys
|
|
import os
|
|
import torch
|
|
from openvoice import se_extractor
|
|
from openvoice.api import ToneColorConverter
|
|
from melo.api import TTS
|
|
|
|
import time
|
|
import backend_pb2
|
|
import backend_pb2_grpc
|
|
|
|
import grpc
|
|
|
|
|
|
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
|
|
|
|
# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
|
|
MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
|
|
|
|
# Implement the BackendServicer class with the service methods
|
|
class BackendServicer(backend_pb2_grpc.BackendServicer):
|
|
"""
|
|
A gRPC servicer for the backend service.
|
|
|
|
This class implements the gRPC methods for the backend service, including Health, LoadModel, and Embedding.
|
|
"""
|
|
def Health(self, request, context):
|
|
"""
|
|
A gRPC method that returns the health status of the backend service.
|
|
|
|
Args:
|
|
request: A HealthRequest object that contains the request parameters.
|
|
context: A grpc.ServicerContext object that provides information about the RPC.
|
|
|
|
Returns:
|
|
A Reply object that contains the health status of the backend service.
|
|
"""
|
|
return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
|
|
|
|
def LoadModel(self, request, context):
|
|
"""
|
|
A gRPC method that loads a model into memory.
|
|
|
|
Args:
|
|
request: A LoadModelRequest object that contains the request parameters.
|
|
context: A grpc.ServicerContext object that provides information about the RPC.
|
|
|
|
Returns:
|
|
A Result object that contains the result of the LoadModel operation.
|
|
"""
|
|
model_name = request.Model
|
|
try:
|
|
|
|
self.clonedVoice = False
|
|
# Assume directory from request.ModelFile.
|
|
# Only if request.LoraAdapter it's not an absolute path
|
|
if request.AudioPath and request.ModelFile != "" and not os.path.isabs(request.AudioPath):
|
|
# get base path of modelFile
|
|
modelFileBase = os.path.dirname(request.ModelFile)
|
|
request.AudioPath = os.path.join(modelFileBase, request.AudioPath)
|
|
if request.AudioPath != "":
|
|
self.clonedVoice = True
|
|
|
|
self.modelpath = request.ModelFile
|
|
self.speaker = request.Type
|
|
self.ClonedVoicePath = request.AudioPath
|
|
|
|
ckpt_converter = request.Model+'/converter'
|
|
device = "cuda:0" if torch.cuda.is_available() else "cpu"
|
|
self.device = device
|
|
self.tone_color_converter = None
|
|
if self.clonedVoice:
|
|
self.tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device)
|
|
self.tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')
|
|
|
|
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 TTS(self, request, context):
|
|
model_name = request.model
|
|
if model_name == "":
|
|
return backend_pb2.Result(success=False, message="request.model is required")
|
|
try:
|
|
# Speed is adjustable
|
|
speed = 1.0
|
|
voice = "EN"
|
|
if request.voice:
|
|
voice = request.voice
|
|
model = TTS(language=voice, device=self.device)
|
|
speaker_ids = model.hps.data.spk2id
|
|
speaker_key = self.speaker
|
|
modelpath = self.modelpath
|
|
for s in speaker_ids.keys():
|
|
print(f"Speaker: {s} - ID: {speaker_ids[s]}")
|
|
speaker_id = speaker_ids[speaker_key]
|
|
speaker_key = speaker_key.lower().replace('_', '-')
|
|
source_se = torch.load(f'{modelpath}/base_speakers/ses/{speaker_key}.pth', map_location=self.device)
|
|
model.tts_to_file(request.text, speaker_id, request.dst, speed=speed)
|
|
if self.clonedVoice:
|
|
reference_speaker = self.ClonedVoicePath
|
|
target_se, audio_name = se_extractor.get_se(reference_speaker, self.tone_color_converter, vad=False)
|
|
# Run the tone color converter
|
|
encode_message = "@MyShell"
|
|
self.tone_color_converter.convert(
|
|
audio_src_path=request.dst,
|
|
src_se=source_se,
|
|
tgt_se=target_se,
|
|
output_path=request.dst,
|
|
message=encode_message)
|
|
|
|
print("[OpenVoice] TTS generated!", file=sys.stderr)
|
|
print("[OpenVoice] TTS saved to", request.dst, file=sys.stderr)
|
|
print(request, file=sys.stderr)
|
|
except Exception as err:
|
|
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
|
|
return backend_pb2.Result(success=True)
|
|
|
|
def serve(address):
|
|
server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))
|
|
backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
|
|
server.add_insecure_port(address)
|
|
server.start()
|
|
print("[OpenVoice] Server started. Listening on: " + address, file=sys.stderr)
|
|
|
|
# Define the signal handler function
|
|
def signal_handler(sig, frame):
|
|
print("[OpenVoice] 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()
|
|
print(f"[OpenVoice] startup: {args}", file=sys.stderr)
|
|
serve(args.addr)
|