add openvoice backend (#2334)

Wip openvoice

backend/python/openvoice/backend.py

@@ -0,0 +1,158 @@
+#!/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)