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vllm.entrypoints.cli.run_batch

logger module-attribute 

logger = init_logger(__name__)

RunBatchSubcommand

Bases: CLISubcommand

The run-batch subcommand for vLLM CLI.

Source code in vllm/entrypoints/cli/run_batch.py 
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class RunBatchSubcommand(CLISubcommand):
    """The `run-batch` subcommand for vLLM CLI."""
    name = "run-batch"

    @staticmethod
    def cmd(args: argparse.Namespace) -> None:
        from vllm.entrypoints.openai.run_batch import main as run_batch_main

        logger.info("vLLM batch processing API version %s",
                    importlib.metadata.version("vllm"))
        logger.info("args: %s", args)

        # Start the Prometheus metrics server.
        # LLMEngine uses the Prometheus client
        # to publish metrics at the /metrics endpoint.
        if args.enable_metrics:
            from prometheus_client import start_http_server

            logger.info("Prometheus metrics enabled")
            start_http_server(port=args.port, addr=args.url)
        else:
            logger.info("Prometheus metrics disabled")

        asyncio.run(run_batch_main(args))

    def subparser_init(
            self,
            subparsers: argparse._SubParsersAction) -> FlexibleArgumentParser:
        from vllm.entrypoints.openai.run_batch import make_arg_parser

        run_batch_parser = subparsers.add_parser(
            "run-batch",
            help="Run batch prompts and write results to file.",
            description=(
                "Run batch prompts using vLLM's OpenAI-compatible API.\n"
                "Supports local or HTTP input/output files."),
            usage=
            "vllm run-batch -i INPUT.jsonl -o OUTPUT.jsonl --model <model>",
        )
        run_batch_parser = make_arg_parser(run_batch_parser)
        show_filtered_argument_or_group_from_help(run_batch_parser,
                                                  ["run-batch"])
        run_batch_parser.epilog = VLLM_SUBCMD_PARSER_EPILOG
        return run_batch_parser

name class-attribute instance-attribute 

name = 'run-batch'

cmd staticmethod 

cmd(args: Namespace) -> None
Source code in vllm/entrypoints/cli/run_batch.py 
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@staticmethod
def cmd(args: argparse.Namespace) -> None:
    from vllm.entrypoints.openai.run_batch import main as run_batch_main

    logger.info("vLLM batch processing API version %s",
                importlib.metadata.version("vllm"))
    logger.info("args: %s", args)

    # Start the Prometheus metrics server.
    # LLMEngine uses the Prometheus client
    # to publish metrics at the /metrics endpoint.
    if args.enable_metrics:
        from prometheus_client import start_http_server

        logger.info("Prometheus metrics enabled")
        start_http_server(port=args.port, addr=args.url)
    else:
        logger.info("Prometheus metrics disabled")

    asyncio.run(run_batch_main(args))

subparser_init 

subparser_init(
    subparsers: _SubParsersAction,
) -> FlexibleArgumentParser
Source code in vllm/entrypoints/cli/run_batch.py 
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def subparser_init(
        self,
        subparsers: argparse._SubParsersAction) -> FlexibleArgumentParser:
    from vllm.entrypoints.openai.run_batch import make_arg_parser

    run_batch_parser = subparsers.add_parser(
        "run-batch",
        help="Run batch prompts and write results to file.",
        description=(
            "Run batch prompts using vLLM's OpenAI-compatible API.\n"
            "Supports local or HTTP input/output files."),
        usage=
        "vllm run-batch -i INPUT.jsonl -o OUTPUT.jsonl --model <model>",
    )
    run_batch_parser = make_arg_parser(run_batch_parser)
    show_filtered_argument_or_group_from_help(run_batch_parser,
                                              ["run-batch"])
    run_batch_parser.epilog = VLLM_SUBCMD_PARSER_EPILOG
    return run_batch_parser

cmd_init 

cmd_init() -> list[CLISubcommand]
Source code in vllm/entrypoints/cli/run_batch.py 
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def cmd_init() -> list[CLISubcommand]:
    return [RunBatchSubcommand()]