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#!/usr/bin/env python3 | |
""" | |
This is an extra gRPC server of LocalAI for Bark TTS | |
""" | |
from concurrent import futures | |
import time | |
import argparse | |
import signal | |
import sys | |
import os | |
import backend_pb2 | |
import backend_pb2_grpc | |
import torch | |
from TTS.api import TTS | |
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')) | |
COQUI_LANGUAGE = os.environ.get('COQUI_LANGUAGE', None) | |
# Implement the BackendServicer class with the service methods | |
class BackendServicer(backend_pb2_grpc.BackendServicer): | |
""" | |
BackendServicer is the class that implements the gRPC service | |
""" | |
def Health(self, request, context): | |
return backend_pb2.Reply(message=bytes("OK", 'utf-8')) | |
def LoadModel(self, request, context): | |
# Get device | |
# device = "cuda" if request.CUDA else "cpu" | |
if torch.cuda.is_available(): | |
print("CUDA is available", file=sys.stderr) | |
device = "cuda" | |
else: | |
print("CUDA is not available", file=sys.stderr) | |
device = "cpu" | |
if not torch.cuda.is_available() and request.CUDA: | |
return backend_pb2.Result(success=False, message="CUDA is not available") | |
self.AudioPath = None | |
# List available 🐸TTS models | |
print(TTS().list_models()) | |
if os.path.isabs(request.AudioPath): | |
self.AudioPath = request.AudioPath | |
elif request.AudioPath and request.ModelFile != "" and not os.path.isabs(request.AudioPath): | |
# get base path of modelFile | |
modelFileBase = os.path.dirname(request.ModelFile) | |
# modify LoraAdapter to be relative to modelFileBase | |
self.AudioPath = os.path.join(modelFileBase, request.AudioPath) | |
try: | |
print("Preparing models, please wait", file=sys.stderr) | |
self.tts = TTS(request.Model).to(device) | |
except Exception as err: | |
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}") | |
# Implement your logic here for the LoadModel service | |
# Replace this with your desired response | |
return backend_pb2.Result(message="Model loaded successfully", success=True) | |
def TTS(self, request, context): | |
try: | |
# if model is multilangual add language from request or env as fallback | |
lang = request.language or COQUI_LANGUAGE | |
if lang == "": | |
lang = None | |
if self.tts.is_multi_lingual and lang is None: | |
return backend_pb2.Result(success=False, message=f"Model is multi-lingual, but no language was provided") | |
# if model is multi-speaker, use speaker_wav or the speaker_id from request.voice | |
if self.tts.is_multi_speaker and self.AudioPath is None and request.voice is None: | |
return backend_pb2.Result(success=False, message=f"Model is multi-speaker, but no speaker was provided") | |
if self.tts.is_multi_speaker and request.voice is not None: | |
self.tts.tts_to_file(text=request.text, speaker=request.voice, language=lang, file_path=request.dst) | |
else: | |
self.tts.tts_to_file(text=request.text, speaker_wav=self.AudioPath, language=lang, file_path=request.dst) | |
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("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) | |