# SPDX-License-Identifier: Apache-2.0

# The CLI entrypoint to vLLM.
import os
import signal
import sys

import vllm.entrypoints.cli.benchmark.main
import vllm.entrypoints.cli.openai
import vllm.entrypoints.cli.serve
import vllm.version
from vllm.logger import init_logger
from vllm.utils import FlexibleArgumentParser

logger = init_logger(__name__)

CMD_MODULES = [
    vllm.entrypoints.cli.openai,
    vllm.entrypoints.cli.serve,
    vllm.entrypoints.cli.benchmark.main,
]


def register_signal_handlers():

    def signal_handler(sig, frame):
        sys.exit(0)

    signal.signal(signal.SIGINT, signal_handler)
    signal.signal(signal.SIGTSTP, signal_handler)


def env_setup():
    # The safest multiprocessing method is `spawn`, as the default `fork` method
    # is not compatible with some accelerators. The default method will be
    # changing in future versions of Python, so we should use it explicitly when
    # possible.
    #
    # We only set it here in the CLI entrypoint, because changing to `spawn`
    # could break some existing code using vLLM as a library. `spawn` will cause
    # unexpected behavior if the code is not protected by
    # `if __name__ == "__main__":`.
    #
    # References:
    # - https://docs.python.org/3/library/multiprocessing.html#contexts-and-start-methods
    # - https://pytorch.org/docs/stable/notes/multiprocessing.html#cuda-in-multiprocessing
    # - https://pytorch.org/docs/stable/multiprocessing.html#sharing-cuda-tensors
    # - https://docs.habana.ai/en/latest/PyTorch/Getting_Started_with_PyTorch_and_Gaudi/Getting_Started_with_PyTorch.html?highlight=multiprocessing#torch-multiprocessing-for-dataloaders
    if "VLLM_WORKER_MULTIPROC_METHOD" not in os.environ:
        logger.debug("Setting VLLM_WORKER_MULTIPROC_METHOD to 'spawn'")
        os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"


def main():
    env_setup()

    parser = FlexibleArgumentParser(description="vLLM CLI")
    parser.add_argument('-v',
                        '--version',
                        action='version',
                        version=vllm.version.__version__)
    subparsers = parser.add_subparsers(required=False, dest="subparser")
    cmds = {}
    for cmd_module in CMD_MODULES:
        new_cmds = cmd_module.cmd_init()
        for cmd in new_cmds:
            cmd.subparser_init(subparsers).set_defaults(
                dispatch_function=cmd.cmd)
            cmds[cmd.name] = cmd
    args = parser.parse_args()
    if args.subparser in cmds:
        cmds[args.subparser].validate(args)

    if hasattr(args, "dispatch_function"):
        args.dispatch_function(args)
    else:
        parser.print_help()


if __name__ == "__main__":
    main()