mirror of
https://github.com/mudler/LocalAI.git
synced 2024-12-19 04:37:53 +00:00
b99182c8d4
* update doc on COQUI_LANGUAGE env variable Signed-off-by: blob42 <contact@blob42.xyz> * return errors from tts gRPC backend Signed-off-by: blob42 <contact@blob42.xyz> * handle speaker_id and language in coqui TTS backend Signed-off-by: blob42 <contact@blob42.xyz> * TTS endpoint: add optional language paramter Signed-off-by: blob42 <contact@blob42.xyz> * tts fix: empty language string breaks non-multilingual models Signed-off-by: blob42 <contact@blob42.xyz> * allow tts param definition in config file - consolidate TTS options under `tts` config entry Signed-off-by: blob42 <contact@blob42.xyz> * tts: update doc Signed-off-by: blob42 <contact@blob42.xyz> --------- Signed-off-by: blob42 <contact@blob42.xyz> Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
119 lines
4.5 KiB
Python
119 lines
4.5 KiB
Python
#!/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)
|