266 lines
10 KiB
Python
266 lines
10 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
|
|
import argparse
|
|
import os
|
|
import signal
|
|
import sys
|
|
from typing import Optional
|
|
|
|
import uvloop
|
|
|
|
import vllm
|
|
import vllm.envs as envs
|
|
from vllm.entrypoints.cli.types import CLISubcommand
|
|
from vllm.entrypoints.openai.api_server import (run_server, run_server_worker,
|
|
setup_server)
|
|
from vllm.entrypoints.openai.cli_args import (make_arg_parser,
|
|
validate_parsed_serve_args)
|
|
from vllm.entrypoints.utils import (VLLM_SUBCMD_PARSER_EPILOG,
|
|
show_filtered_argument_or_group_from_help)
|
|
from vllm.executor.multiproc_worker_utils import _add_prefix
|
|
from vllm.logger import init_logger
|
|
from vllm.usage.usage_lib import UsageContext
|
|
from vllm.utils import FlexibleArgumentParser, get_tcp_uri
|
|
from vllm.v1.engine.core import EngineCoreProc
|
|
from vllm.v1.engine.utils import CoreEngineProcManager, launch_core_engines
|
|
from vllm.v1.executor.abstract import Executor
|
|
from vllm.v1.metrics.prometheus import setup_multiprocess_prometheus
|
|
from vllm.v1.utils import (APIServerProcessManager,
|
|
wait_for_completion_or_failure)
|
|
|
|
logger = init_logger(__name__)
|
|
|
|
|
|
class ServeSubcommand(CLISubcommand):
|
|
"""The `serve` subcommand for the vLLM CLI. """
|
|
name = "serve"
|
|
|
|
@staticmethod
|
|
def cmd(args: argparse.Namespace) -> None:
|
|
# If model is specified in CLI (as positional arg), it takes precedence
|
|
if hasattr(args, 'model_tag') and args.model_tag is not None:
|
|
args.model = args.model_tag
|
|
|
|
if args.headless or args.api_server_count < 1:
|
|
run_headless(args)
|
|
else:
|
|
if args.data_parallel_start_rank:
|
|
raise ValueError("data_parallel_start_rank is only "
|
|
"applicable in headless mode")
|
|
if args.api_server_count > 1:
|
|
run_multi_api_server(args)
|
|
else:
|
|
# Single API server (this process).
|
|
uvloop.run(run_server(args))
|
|
|
|
def validate(self, args: argparse.Namespace) -> None:
|
|
validate_parsed_serve_args(args)
|
|
|
|
def subparser_init(
|
|
self,
|
|
subparsers: argparse._SubParsersAction) -> FlexibleArgumentParser:
|
|
serve_parser = subparsers.add_parser(
|
|
"serve",
|
|
help="Start the vLLM OpenAI Compatible API server.",
|
|
description="Start the vLLM OpenAI Compatible API server.",
|
|
usage="vllm serve [model_tag] [options]")
|
|
serve_parser.add_argument("model_tag",
|
|
type=str,
|
|
nargs='?',
|
|
help="The model tag to serve "
|
|
"(optional if specified in config)")
|
|
serve_parser.add_argument(
|
|
"--headless",
|
|
action='store_true',
|
|
default=False,
|
|
help="Run in headless mode. See multi-node data parallel "
|
|
"documentation for more details.")
|
|
serve_parser.add_argument(
|
|
'--data-parallel-start-rank',
|
|
'-dpr',
|
|
type=int,
|
|
default=0,
|
|
help='Starting data parallel rank for secondary nodes.')
|
|
serve_parser.add_argument('--api-server-count',
|
|
'-asc',
|
|
type=int,
|
|
default=1,
|
|
help='How many API server processes to run.')
|
|
serve_parser.add_argument(
|
|
"--config",
|
|
type=str,
|
|
default='',
|
|
required=False,
|
|
help="Read CLI options from a config file. "
|
|
"Must be a YAML with the following options: "
|
|
"https://docs.vllm.ai/en/latest/configuration/serve_args.html")
|
|
|
|
serve_parser = make_arg_parser(serve_parser)
|
|
show_filtered_argument_or_group_from_help(serve_parser, ["serve"])
|
|
serve_parser.epilog = VLLM_SUBCMD_PARSER_EPILOG
|
|
return serve_parser
|
|
|
|
|
|
def cmd_init() -> list[CLISubcommand]:
|
|
return [ServeSubcommand()]
|
|
|
|
|
|
def run_headless(args: argparse.Namespace):
|
|
|
|
if args.api_server_count > 1:
|
|
raise ValueError("api_server_count can't be set in headless mode")
|
|
|
|
# Create the EngineConfig.
|
|
engine_args = vllm.AsyncEngineArgs.from_cli_args(args)
|
|
usage_context = UsageContext.OPENAI_API_SERVER
|
|
vllm_config = engine_args.create_engine_config(usage_context=usage_context)
|
|
|
|
if not envs.VLLM_USE_V1:
|
|
raise ValueError("Headless mode is only supported for V1")
|
|
|
|
if engine_args.data_parallel_rank is not None:
|
|
raise ValueError("data_parallel_rank is not applicable in "
|
|
"headless mode")
|
|
|
|
parallel_config = vllm_config.parallel_config
|
|
local_engine_count = parallel_config.data_parallel_size_local
|
|
|
|
if local_engine_count <= 0:
|
|
raise ValueError("data_parallel_size_local must be > 0 in "
|
|
"headless mode")
|
|
|
|
host = parallel_config.data_parallel_master_ip
|
|
port = engine_args.data_parallel_rpc_port # add to config too
|
|
handshake_address = get_tcp_uri(host, port)
|
|
|
|
# Catch SIGTERM and SIGINT to allow graceful shutdown.
|
|
def signal_handler(signum, frame):
|
|
logger.debug("Received %d signal.", signum)
|
|
raise SystemExit
|
|
|
|
signal.signal(signal.SIGTERM, signal_handler)
|
|
signal.signal(signal.SIGINT, signal_handler)
|
|
|
|
logger.info(
|
|
"Launching %d data parallel engine(s) in headless mode, "
|
|
"with head node address %s.", local_engine_count, handshake_address)
|
|
|
|
# Create the engines.
|
|
engine_manager = CoreEngineProcManager(
|
|
target_fn=EngineCoreProc.run_engine_core,
|
|
local_engine_count=local_engine_count,
|
|
start_index=args.data_parallel_start_rank,
|
|
local_start_index=0,
|
|
vllm_config=vllm_config,
|
|
local_client=False,
|
|
handshake_address=handshake_address,
|
|
executor_class=Executor.get_class(vllm_config),
|
|
log_stats=not engine_args.disable_log_stats,
|
|
)
|
|
|
|
try:
|
|
engine_manager.join_first()
|
|
finally:
|
|
logger.info("Shutting down.")
|
|
engine_manager.close()
|
|
|
|
|
|
def run_multi_api_server(args: argparse.Namespace):
|
|
|
|
assert not args.headless
|
|
num_api_servers = args.api_server_count
|
|
assert num_api_servers > 0
|
|
|
|
if num_api_servers > 1:
|
|
setup_multiprocess_prometheus()
|
|
|
|
listen_address, sock = setup_server(args)
|
|
|
|
engine_args = vllm.AsyncEngineArgs.from_cli_args(args)
|
|
usage_context = UsageContext.OPENAI_API_SERVER
|
|
vllm_config = engine_args.create_engine_config(usage_context=usage_context)
|
|
model_config = vllm_config.model_config
|
|
|
|
if num_api_servers > 1:
|
|
if not envs.VLLM_USE_V1:
|
|
raise ValueError("api_server_count > 1 is only supported for V1")
|
|
|
|
if envs.VLLM_ALLOW_RUNTIME_LORA_UPDATING:
|
|
raise ValueError("VLLM_ALLOW_RUNTIME_LORA_UPDATING cannot be used "
|
|
"with api_server_count > 1")
|
|
|
|
if model_config.is_multimodal_model and not (
|
|
model_config.disable_mm_preprocessor_cache):
|
|
logger.warning(
|
|
"Multi-model preprocessor cache will be disabled for"
|
|
" api_server_count > 1")
|
|
model_config.disable_mm_preprocessor_cache = True
|
|
|
|
executor_class = Executor.get_class(vllm_config)
|
|
log_stats = not engine_args.disable_log_stats
|
|
|
|
parallel_config = vllm_config.parallel_config
|
|
dp_rank = parallel_config.data_parallel_rank
|
|
external_dp_lb = parallel_config.data_parallel_external_lb
|
|
assert external_dp_lb or dp_rank == 0
|
|
|
|
api_server_manager: Optional[APIServerProcessManager] = None
|
|
|
|
with launch_core_engines(vllm_config, executor_class, log_stats,
|
|
num_api_servers) as (local_engine_manager,
|
|
coordinator, addresses):
|
|
|
|
# Construct common args for the APIServerProcessManager up-front.
|
|
api_server_manager_kwargs = dict(
|
|
target_server_fn=run_api_server_worker_proc,
|
|
listen_address=listen_address,
|
|
sock=sock,
|
|
args=args,
|
|
num_servers=num_api_servers,
|
|
input_addresses=addresses.inputs,
|
|
output_addresses=addresses.outputs,
|
|
stats_update_address=coordinator.get_stats_publish_address()
|
|
if coordinator else None)
|
|
|
|
# For dp ranks > 0 in external DP LB mode, we must delay the
|
|
# start of the API servers until the local engine is started
|
|
# (after the launcher context manager exits),
|
|
# since we get the front-end stats update address from the coordinator
|
|
# via the handshake with the local engine.
|
|
if dp_rank == 0 or not external_dp_lb:
|
|
# Start API servers using the manager.
|
|
api_server_manager = APIServerProcessManager(
|
|
**api_server_manager_kwargs)
|
|
|
|
# Start API servers now if they weren't already started.
|
|
if api_server_manager is None:
|
|
api_server_manager_kwargs["stats_update_address"] = (
|
|
addresses.frontend_stats_publish_address)
|
|
api_server_manager = APIServerProcessManager(
|
|
**api_server_manager_kwargs)
|
|
|
|
# Wait for API servers
|
|
wait_for_completion_or_failure(api_server_manager=api_server_manager,
|
|
engine_manager=local_engine_manager,
|
|
coordinator=coordinator)
|
|
|
|
|
|
def run_api_server_worker_proc(listen_address,
|
|
sock,
|
|
args,
|
|
client_config=None,
|
|
**uvicorn_kwargs) -> None:
|
|
"""Entrypoint for individual API server worker processes."""
|
|
|
|
# Add process-specific prefix to stdout and stderr.
|
|
from multiprocessing import current_process
|
|
process_name = current_process().name
|
|
pid = os.getpid()
|
|
_add_prefix(sys.stdout, process_name, pid)
|
|
_add_prefix(sys.stderr, process_name, pid)
|
|
|
|
uvloop.run(
|
|
run_server_worker(listen_address, sock, args, client_config,
|
|
**uvicorn_kwargs))
|