import argparse
import os

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument('--port', '-p',
                        type=int,
                        default=9090,
                        help="Websocket port to run the server on.")
    parser.add_argument('--backend', '-b',
                        type=str,
                        default='faster_whisper',
                        help='Backends from ["tensorrt", "faster_whisper"]')
    parser.add_argument('--faster_whisper_custom_model_path', '-fw',
                        type=str, default=None,
                        help="Custom Faster Whisper Model")
    parser.add_argument('--trt_model_path', '-trt',
                        type=str,
                        default=None,
                        help='Whisper TensorRT model path')
    parser.add_argument('--trt_multilingual', '-m',
                        action="store_true",
                        help='Boolean only for TensorRT model. True if multilingual.')
    parser.add_argument('--omp_num_threads', '-omp',
                        type=int,
                        default=1,
                        help="Number of threads to use for OpenMP")
    parser.add_argument('--single_model', '-sm',
                        action="store_true",
                        help='Set to true if only one (custom) model instance should be served.')
    args = parser.parse_args()

    if args.backend == "tensorrt":
        if args.trt_model_path is None:
            raise ValueError("Please Provide a valid tensorrt model path")

    if "OMP_NUM_THREADS" not in os.environ:
        os.environ["OMP_NUM_THREADS"] = str(args.omp_num_threads)

    from whisper_live.server import TranscriptionServer
    server = TranscriptionServer()
    server.run(
        "0.0.0.0",
        port=args.port,
        backend=args.backend,
        faster_whisper_custom_model_path=args.faster_whisper_custom_model_path,
        whisper_tensorrt_path=args.trt_model_path,
        trt_multilingual=args.trt_multilingual,
        single_model=args.single_model,
    )
