feat(tts): Add Kokoro backend (#4616)

* feat(kokoro): Add new TTS backend

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add kokoro to images

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Support combined voices

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Ignore pt and onnx

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add plbert and istfnet

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

backend/python/kokoro/backend.py

@@ -0,0 +1,131 @@
+#!/usr/bin/env python3
+"""
+Extra gRPC server for Kokoro models.
+"""
+from concurrent import futures
+
+import argparse
+import signal
+import sys
+import os
+import time
+import backend_pb2
+import backend_pb2_grpc
+import soundfile as sf
+import grpc
+
+from models import build_model
+from kokoro import generate
+import torch
+
+SAMPLE_RATE = 22050
+_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:
+            device = "cuda:0" if torch.cuda.is_available() else "cpu"
+            self.MODEL = build_model(request.ModelFile, device)
+            options = request.Options
+            # Find the voice from the options, options are a list of strings in this form optname:optvalue:
+            VOICE_NAME = None
+            for opt in options:
+                if opt.startswith("voice:"):
+                    VOICE_NAME = opt.split(":")[1]
+                    break
+            if VOICE_NAME is None:
+                return backend_pb2.Result(success=False, message=f"No voice specified in options")
+            MODELPATH = request.ModelPath
+            # If voice name contains a plus, split it and load the two models and combine them
+            if "+" in VOICE_NAME:
+                voice1, voice2 = VOICE_NAME.split("+")
+                voice1 = torch.load(f'{MODELPATH}/{voice1}.pt', weights_only=True).to(device)
+                voice2 = torch.load(f'{MODELPATH}/{voice2}.pt', weights_only=True).to(device)
+                self.VOICEPACK = torch.mean(torch.stack([voice1, voice2]), dim=0)
+            else:
+                self.VOICEPACK = torch.load(f'{MODELPATH}/{VOICE_NAME}.pt', weights_only=True).to(device)
+
+            self.VOICE_NAME = VOICE_NAME
+
+            print(f'Loaded voice: {VOICE_NAME}')
+        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:
+            audio, out_ps = generate(self.MODEL, request.text, self.VOICEPACK, lang=self.VOICE_NAME)
+            print(out_ps)
+            sf.write(request.dst, audio, SAMPLE_RATE)
+        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("[Kokoro] Server started. Listening on: " + address, file=sys.stderr)
+
+    # Define the signal handler function
+    def signal_handler(sig, frame):
+        print("[Kokoro] 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"[Kokoro] startup: {args}", file=sys.stderr)
+    serve(args.addr)