Sample Java Client calling TF Serving gRPC endpoint

String host = "localhost";
    int port = 8501;
    // the model's name. 
    String modelName = "cool_model";
    // model's version
    long modelVersion = 123456789;
    // assume this model takes input of free text, and make some sentiment prediction.
    String modelInput = "some text input to make prediction with";
    
    // create a channel
    ManagedChannel channel = ManagedChannelBuilder.forAddress(host, port).usePlaintext().build();
    PredictionServiceGrpc.PredictionServiceBlockingStub stub = PredictionServiceGrpc.newBlockingStub(channel);
    
    // create a modelspec
    Model.ModelSpec.Builder modelSpecBuilder = Model.ModelSpec.newBuilder();
    modelSpecBuilder.setName(modelName);
    modelSpecBuilder.setVersion(Int64Value.of(modelVersion));
    modelSpecBuilder.setSignatureName("serving_default");

    Predict.PredictRequest.Builder builder = Predict.PredictRequest.newBuilder();
    builder.setModelSpec(modelSpecBuilder);
    
    // create the TensorProto and request
    TensorProto.Builder tensorProtoBuilder = TensorProto.newBuilder();
    tensorProtoBuilder.setDtype(DataType.DT_STRING);
    TensorShapeProto.Builder tensorShapeBuilder = TensorShapeProto.newBuilder();
    tensorShapeBuilder.addDim(TensorShapeProto.Dim.newBuilder().setSize(1));
    tensorProtoBuilder.setTensorShape(tensorShapeBuilder.build());
    tensorProtoBuilder.addStringVal(ByteString.copyFromUtf8(modelInput));
    TensorProto tp = tensorProtoBuilder.build();

    builder.putInputs("inputs", tp);
    
    Predict.PredictRequest request = builder.build();
    Predict.PredictResponse response = stub.predict(request);