233 lines
8.8 KiB
Python
233 lines
8.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import argparse
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import signal
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from typing import Optional
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import uvloop
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import vllm
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import vllm.envs as envs
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from vllm.entrypoints.cli.types import CLISubcommand
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from vllm.entrypoints.openai.api_server import (run_server, run_server_worker,
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setup_server)
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from vllm.entrypoints.openai.cli_args import (make_arg_parser,
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validate_parsed_serve_args)
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from vllm.entrypoints.utils import (VLLM_SUBCMD_PARSER_EPILOG,
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show_filtered_argument_or_group_from_help)
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from vllm.logger import init_logger
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from vllm.usage.usage_lib import UsageContext
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from vllm.utils import (FlexibleArgumentParser, decorate_logs, get_tcp_uri,
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set_process_title)
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from vllm.v1.engine.core import EngineCoreProc
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from vllm.v1.engine.utils import CoreEngineProcManager, launch_core_engines
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from vllm.v1.executor.abstract import Executor
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from vllm.v1.metrics.prometheus import setup_multiprocess_prometheus
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from vllm.v1.utils import (APIServerProcessManager,
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wait_for_completion_or_failure)
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logger = init_logger(__name__)
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class ServeSubcommand(CLISubcommand):
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"""The `serve` subcommand for the vLLM CLI. """
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name = "serve"
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@staticmethod
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def cmd(args: argparse.Namespace) -> None:
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# If model is specified in CLI (as positional arg), it takes precedence
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if hasattr(args, 'model_tag') and args.model_tag is not None:
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args.model = args.model_tag
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if args.headless or args.api_server_count < 1:
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run_headless(args)
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else:
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if args.api_server_count > 1:
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run_multi_api_server(args)
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else:
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# Single API server (this process).
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uvloop.run(run_server(args))
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def validate(self, args: argparse.Namespace) -> None:
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validate_parsed_serve_args(args)
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def subparser_init(
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self,
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subparsers: argparse._SubParsersAction) -> FlexibleArgumentParser:
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serve_parser = subparsers.add_parser(
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"serve",
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help="Start the vLLM OpenAI Compatible API server.",
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description="Start the vLLM OpenAI Compatible API server.",
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usage="vllm serve [model_tag] [options]")
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serve_parser = make_arg_parser(serve_parser)
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show_filtered_argument_or_group_from_help(serve_parser, ["serve"])
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serve_parser.epilog = VLLM_SUBCMD_PARSER_EPILOG
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return serve_parser
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def cmd_init() -> list[CLISubcommand]:
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return [ServeSubcommand()]
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def run_headless(args: argparse.Namespace):
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if args.api_server_count > 1:
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raise ValueError("api_server_count can't be set in headless mode")
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# Create the EngineConfig.
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engine_args = vllm.AsyncEngineArgs.from_cli_args(args)
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usage_context = UsageContext.OPENAI_API_SERVER
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vllm_config = engine_args.create_engine_config(usage_context=usage_context,
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headless=True)
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if not envs.VLLM_USE_V1:
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raise ValueError("Headless mode is only supported for V1")
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if engine_args.data_parallel_hybrid_lb:
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raise ValueError("data_parallel_hybrid_lb is not applicable in "
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"headless mode")
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parallel_config = vllm_config.parallel_config
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local_engine_count = parallel_config.data_parallel_size_local
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if local_engine_count <= 0:
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raise ValueError("data_parallel_size_local must be > 0 in "
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"headless mode")
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host = parallel_config.data_parallel_master_ip
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port = engine_args.data_parallel_rpc_port # add to config too
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handshake_address = get_tcp_uri(host, port)
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# Catch SIGTERM and SIGINT to allow graceful shutdown.
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def signal_handler(signum, frame):
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logger.debug("Received %d signal.", signum)
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raise SystemExit
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signal.signal(signal.SIGTERM, signal_handler)
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signal.signal(signal.SIGINT, signal_handler)
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logger.info(
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"Launching %d data parallel engine(s) in headless mode, "
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"with head node address %s.", local_engine_count, handshake_address)
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# Create the engines.
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engine_manager = CoreEngineProcManager(
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target_fn=EngineCoreProc.run_engine_core,
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local_engine_count=local_engine_count,
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start_index=vllm_config.parallel_config.data_parallel_rank,
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local_start_index=0,
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vllm_config=vllm_config,
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local_client=False,
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handshake_address=handshake_address,
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executor_class=Executor.get_class(vllm_config),
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log_stats=not engine_args.disable_log_stats,
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)
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try:
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engine_manager.join_first()
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finally:
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logger.info("Shutting down.")
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engine_manager.close()
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def run_multi_api_server(args: argparse.Namespace):
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assert not args.headless
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num_api_servers = args.api_server_count
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assert num_api_servers > 0
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orig_mm_processor_cache_gb = args.mm_processor_cache_gb
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if num_api_servers > 1:
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setup_multiprocess_prometheus()
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# Not compatible with API server scale-out
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args.mm_processor_cache_gb = 0
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listen_address, sock = setup_server(args)
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engine_args = vllm.AsyncEngineArgs.from_cli_args(args)
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usage_context = UsageContext.OPENAI_API_SERVER
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vllm_config = engine_args.create_engine_config(usage_context=usage_context)
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model_config = vllm_config.model_config
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if num_api_servers > 1:
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if not envs.VLLM_USE_V1:
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raise ValueError("api_server_count > 1 is only supported for V1")
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if envs.VLLM_ALLOW_RUNTIME_LORA_UPDATING:
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raise ValueError("VLLM_ALLOW_RUNTIME_LORA_UPDATING cannot be used "
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"with api_server_count > 1")
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if model_config.is_multimodal_model and orig_mm_processor_cache_gb > 0:
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logger.warning("Multi-modal processor cache is disabled because "
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"it is not compatible with `api_server_count > 1`.")
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executor_class = Executor.get_class(vllm_config)
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log_stats = not engine_args.disable_log_stats
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parallel_config = vllm_config.parallel_config
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dp_rank = parallel_config.data_parallel_rank
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external_dp_lb = parallel_config.data_parallel_external_lb
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hybrid_dp_lb = parallel_config.data_parallel_hybrid_lb
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assert external_dp_lb or hybrid_dp_lb or dp_rank == 0
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api_server_manager: Optional[APIServerProcessManager] = None
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with launch_core_engines(vllm_config, executor_class, log_stats,
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num_api_servers) as (local_engine_manager,
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coordinator, addresses):
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# Construct common args for the APIServerProcessManager up-front.
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api_server_manager_kwargs = dict(
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target_server_fn=run_api_server_worker_proc,
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listen_address=listen_address,
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sock=sock,
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args=args,
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num_servers=num_api_servers,
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input_addresses=addresses.inputs,
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output_addresses=addresses.outputs,
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stats_update_address=coordinator.get_stats_publish_address()
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if coordinator else None)
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# For dp ranks > 0 in external/hybrid DP LB modes, we must delay the
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# start of the API servers until the local engine is started
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# (after the launcher context manager exits),
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# since we get the front-end stats update address from the coordinator
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# via the handshake with the local engine.
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if dp_rank == 0 or not (external_dp_lb or hybrid_dp_lb):
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# Start API servers using the manager.
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api_server_manager = APIServerProcessManager(
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**api_server_manager_kwargs)
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# Start API servers now if they weren't already started.
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if api_server_manager is None:
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api_server_manager_kwargs["stats_update_address"] = (
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addresses.frontend_stats_publish_address)
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api_server_manager = APIServerProcessManager(
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**api_server_manager_kwargs)
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# Wait for API servers
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wait_for_completion_or_failure(api_server_manager=api_server_manager,
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engine_manager=local_engine_manager,
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coordinator=coordinator)
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def run_api_server_worker_proc(listen_address,
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sock,
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args,
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client_config=None,
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**uvicorn_kwargs) -> None:
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"""Entrypoint for individual API server worker processes."""
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# Set process title and add process-specific prefix to stdout and stderr.
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server_index = client_config.get("client_index", 0) if client_config else 0
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set_process_title("APIServer", str(server_index))
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decorate_logs()
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uvloop.run(
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run_server_worker(listen_address, sock, args, client_config,
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**uvicorn_kwargs))
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