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