gRPC setup

Before developing and running client applications, you need to set up the gRPC environment for your programming language.

Basic steps

The basic steps in using the gRPC protocol for TTSaaS are:

  1. Install gRPC for the programming language of your choice, including C++, Java, Python, Go, Ruby, C#, Node.js, and others. See gRPC Documentation  for a complete list and instructions on using gRPC with each one. For example, for Python:

    python3 -m pip install --upgrade pip
python3 -m pip install grpcio
python3 -m pip install grpcio-tools
    python -m pip install --upgrade pip
python -m pip install grpcio
python -m pip install grpcio-tools

  2. Download proto files: nuance-tts-and-storage-protos.zip. These files contain a generic version of the functions or classes that perform speech synthesis and upload operations.

  1. Extract the file to the directory that contains or will contain your client apps, for example, /home/tts/clients on Linux or c:\TTS\clients on Windows. On Linux, use the unzip command:

    cd /home/tts/clients
unzip nuance_tts_and_storage_protos.zip

    The zip file extracts as a directory structure starting with nuance:

    ├── Your client apps here
├── nuance_tts_and_storage_protos.zip
└── nuance
    ├── rpc
    │   ├── error_details.proto
    │   ├── status_code.proto
    │   └── status.proto
    └── tts
        ├── storage
        │   └── v1beta1
        │       └── storage.proto
        └── v1
            └── synthesizer.proto

  1. If your programming language requires client stub files, generate the stubs from the proto files using gRPC protoc, following the Python example as guidance.

    These stubs contain the methods and fields from the proto files as implemented in your programming language. Some languages, such as Node.js, can use the proto files directly, meaning client stubs are not required. Consult the gRPC documentation for your programming language.

    # Generate Python stubs for synthesis and storage
python3 -m grpc_tools.protoc --proto_path=./ --python_out=./ --grpc_python_out=./ nuance/tts/v1/synthesizer.proto
python3 -m grpc_tools.protoc --proto_path=./ --python_out=./ --grpc_python_out=./ nuance/tts/storage/v1beta1/storage.proto

# Generate Python stubs for RPC messages, if not already present
python3 -m grpc_tools.protoc --proto_path=./ --python_out=./ nuance/rpc/status.proto
python3 -m grpc_tools.protoc --proto_path=./ --python_out=./ nuance/rpc/status_code.proto
python3 -m grpc_tools.protoc --proto_path=./ --python_out=./ nuance/rpc/error_details.proto
    # Generate Python stubs for synthesis and storage
python -m grpc_tools.protoc --proto_path=./ --python_out=./ --grpc_python_out=./ nuance/tts/v1/synthesizer.proto
python -m grpc_tools.protoc --proto_path=./ --python_out=./ --grpc_python_out=./ nuance/tts/storage/v1beta1/storage.proto

# Generate Python stubs for RPC messages, if not already present
python -m grpc_tools.protoc --proto_path=./ --python_out=./ nuance/rpc/status.proto
python -m grpc_tools.protoc --proto_path=./ --python_out=./ nuance/rpc/status_code.proto
python -m grpc_tools.protoc --proto_path=./ --python_out=./ nuance/rpc/error_details.proto

    If you already have client stubs for the RPC files in this location, you may use the existing files.

Final structure

The resulting files contain the information in the proto files in your programming language.

├── Your client apps here
└── nuance
    ├── rpc
    │   ├── error_details_pb2.py
    │   ├── error_details.proto
    │   ├── status_code_pb2.py
    │   ├── status_code.proto
    │   ├── status_pb2.py
    │   └── status.proto
    └── tts
        ├── storage
        │   └── v1beta1
        │       ├── storage_pb2.py
        │       ├── storage_pb2_grpc.py
        │       └── storage.proto
        └── v1
            ├── synthesizer_pb2.py
            ├── synthesizer_pb2_grpc.py
            └── synthesizer.proto

What’s next?

Once you have the proto files and optionally the client stubs, you are ready to develop and run client applications with the help of sample clients: