def add_cli_args(parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
        """Shared CLI arguments for vLLM engine."""
        # Model arguments
        # TODO(shengguangming): delete the unused args
        parser.add_argument('--model',
                            type=str,
                            default='facebook/opt-125m',
                            help='name or path of the huggingface model to use')
        parser.add_argument('--tokenizer',
                            type=str,
                            default=EngineArgs.tokenizer,
                            help='name or path of the huggingface tokenizer to use')
        parser.add_argument('--revision',
                            type=str,
                            default=None,
                            help='the specific model version to use. It can be a branch '
                            'name, a tag name, or a commit id. If unspecified, will use '
                            'the default version.')
        parser.add_argument('--tokenizer-revision',
                            type=str,
                            default=None,
                            help='the specific tokenizer version to use. It can be a branch '
                            'name, a tag name, or a commit id. If unspecified, will use '
                            'the default version.')
        parser.add_argument('--tokenizer-mode',
                            type=str,
                            default=EngineArgs.tokenizer_mode,
                            choices=['auto', 'slow'],
                            help='tokenizer mode. "auto" will use the fast '
                            'tokenizer if available, and "slow" will '
                            'always use the slow tokenizer.')
        parser.add_argument('--trust-remote-code', action='store_true', help='trust remote code from huggingface')
        parser.add_argument('--download-dir',
                            type=str,
                            default=EngineArgs.download_dir,
                            help='directory to download and load the weights, '
                            'default to the default cache dir of '
                            'huggingface')
        parser.add_argument('--load-format',
                            type=str,
                            default=EngineArgs.load_format,
                            choices=['auto', 'pt', 'safetensors', 'npcache', 'dummy'],
                            help='The format of the model weights to load. '
                            '"auto" will try to load the weights in the safetensors format '
                            'and fall back to the pytorch bin format if safetensors format '
                            'is not available. '
                            '"pt" will load the weights in the pytorch bin format. '
                            '"safetensors" will load the weights in the safetensors format. '
                            '"npcache" will load the weights in pytorch format and store '
                            'a numpy cache to speed up the loading. '
                            '"dummy" will initialize the weights with random values, '
                            'which is mainly for profiling.')
        parser.add_argument('--dtype',
                            type=str,
                            default=EngineArgs.dtype,
                            choices=['auto', 'half', 'float16', 'bfloat16', 'float', 'float32'],
                            help='data type for model weights and activations. '
                            'The "auto" option will use FP16 precision '
                            'for FP32 and FP16 models, and BF16 precision '
                            'for BF16 models.')
        parser.add_argument('--max-model-len',
                            type=int,
                            default=None,
                            help='model context length. If unspecified, '
                            'will be automatically derived from the model.')
        # Parallel arguments
        parser.add_argument('--worker-use-ray',
                            action='store_true',
                            help='use Ray for distributed serving, will be '
                            'automatically set when using more than 1 GPU')
        parser.add_argument('--pipeline-parallel-size',
                            '-pp',
                            type=int,
                            default=EngineArgs.pipeline_parallel_size,
                            help='number of pipeline stages')
        parser.add_argument('--tensor-parallel-size',
                            '-tp',
                            type=int,
                            default=EngineArgs.tensor_parallel_size,
                            help='number of tensor parallel replicas')
        # KV cache arguments
        parser.add_argument('--block-size',
                            type=int,
                            default=EngineArgs.block_size,
                            choices=[8, 16, 32],
                            help='token block size')
        # TODO(woosuk): Support fine-grained seeds (e.g., seed per request).
        parser.add_argument('--seed', type=int, default=EngineArgs.seed, help='random seed')
        parser.add_argument('--swap-space',
                            type=int,
                            default=EngineArgs.swap_space,
                            help='CPU swap space size (GiB) per GPU')
        parser.add_argument('--gpu-memory-utilization',
                            type=float,
                            default=EngineArgs.gpu_memory_utilization,
                            help='the percentage of GPU memory to be used for'
                            'the model executor')
        parser.add_argument('--max-num-batched-tokens',
                            type=int,
                            default=EngineArgs.max_num_batched_tokens,
                            help='maximum number of batched tokens per '
                            'iteration')
        parser.add_argument('--max-num-seqs',
                            type=int,
                            default=EngineArgs.max_num_seqs,
                            help='maximum number of sequences per iteration')
        parser.add_argument('--disable-log-stats', action='store_true', help='disable logging statistics')
        # Quantization settings.
        parser.add_argument('--quantization',
                            '-q',
                            type=str,
                            choices=['awq', None],
                            default=None,
                            help='Method used to quantize the weights')
        return parser
Shared CLI arguments for vLLM engine.
verl/third_party/vllm/vllm_v_0_5_4/arg_utils.py