217 lines
8.1 KiB
Python
217 lines
8.1 KiB
Python
#!/usr/bin/env python3
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"""在宿主机启动独立的 Qwen3-ASR VLLM 服务。"""
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from __future__ import annotations
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import argparse
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import os
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import shutil
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import signal
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import subprocess
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import sys
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import time
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from pathlib import Path
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from urllib.error import URLError
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from urllib.request import urlopen
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from dotenv import load_dotenv
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# 启动器自动读取 demo/.env；系统环境变量仍然优先，便于部署平台临时覆盖配置。
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PROJECT_ROOT = Path(__file__).resolve().parents[1]
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load_dotenv(PROJECT_ROOT / ".env")
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# 将服务端口集中在代码变量中维护，启动时不需要额外传入端口参数；健康检查、
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# VLLM 子进程命令和就绪提示都使用同一个端口，避免配置不一致导致误判。
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SERVER_PORT = int(os.getenv("VLLM_PORT", "9950"))
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try:
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from .model_manifest import load_manifest, model_directory, resolve_model_id
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except ImportError:
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from model_manifest import load_manifest, model_directory, resolve_model_id
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def has_model_weights(model_path: Path) -> bool:
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"""检查 VLLM 加载模型前必须存在的最小本地文件集合。"""
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if not model_path.is_dir() or not (model_path / "config.json").is_file():
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return False
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return any(model_path.rglob("*.safetensors")) or any(model_path.rglob("*.bin"))
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def positive_int(value: str) -> int:
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"""解析启动轮询使用的正整数参数，并拒绝零和负数。"""
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parsed = int(value)
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if parsed < 1:
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raise argparse.ArgumentTypeError("value must be at least 1")
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return parsed
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def non_negative_float(value: str) -> float:
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"""解析启动轮询间隔，并拒绝会导致逻辑异常的负数。"""
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parsed = float(value)
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if parsed < 0:
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raise argparse.ArgumentTypeError("value must be non-negative")
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return parsed
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def build_parser() -> argparse.ArgumentParser:
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"""创建宿主机启动参数解析器，默认值允许通过环境变量统一覆盖。"""
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parser = argparse.ArgumentParser(description=__doc__)
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add_arguments(parser)
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return parser
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def add_arguments(parser: argparse.ArgumentParser) -> None:
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"""注册模型、网络端点和启动检查循环相关的命令行参数。"""
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parser.add_argument(
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"--model",
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default=os.getenv("QWEN3_ASR_MODEL", "default"),
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help="Model alias, exact model ID, or default",
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)
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parser.add_argument(
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"--models-dir",
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type=Path,
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default=Path(os.getenv("MODEL_DIR", str(Path(__file__).resolve().parents[1] / "models"))),
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help="Root directory containing downloaded model files",
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)
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parser.add_argument("--host", default=os.getenv("VLLM_HOST", "0.0.0.0"))
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parser.add_argument(
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"--display-host",
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default=os.getenv("VLLM_DISPLAY_HOST", "127.0.0.1"),
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help="Host name shown in the ready message; does not change the bind address",
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)
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parser.add_argument(
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"--probe-host",
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default=os.getenv("VLLM_PROBE_HOST", "127.0.0.1"),
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help="Host used by the startup health probe",
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)
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parser.add_argument(
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"--startup-check-loops",
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type=positive_int,
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default=positive_int(os.getenv("VLLM_STARTUP_CHECK_LOOPS", "60")),
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help="Maximum number of health checks before startup fails",
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)
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parser.add_argument(
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"--startup-check-interval",
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type=non_negative_float,
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default=non_negative_float(os.getenv("VLLM_STARTUP_CHECK_INTERVAL_SECONDS", "2")),
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help="Seconds between startup health checks",
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)
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parser.add_argument("--served-model-name", default=os.getenv("VLLM_SERVED_MODEL_NAME"))
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parser.add_argument(
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"--gpu-memory-utilization",
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default=os.getenv("VLLM_GPU_MEMORY_UTILIZATION", "0.3"),
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)
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parser.add_argument("--max-model-len", default=os.getenv("VLLM_MAX_MODEL_LEN", "16384"))
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parser.add_argument("--max-num-seqs", default=os.getenv("VLLM_MAX_NUM_SEQS", "16"))
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parser.add_argument("--tensor-parallel-size", default=os.getenv("VLLM_TENSOR_PARALLEL_SIZE", "1"))
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parser.add_argument(
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"--enforce-eager",
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action=argparse.BooleanOptionalAction,
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default=os.getenv("VLLM_ENFORCE_EAGER", "true").lower() == "true",
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)
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def build_server_command(args: argparse.Namespace, model_id: str, model_path: Path) -> list[str]:
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"""构造新版 VLLM 原生启动命令，不依赖 qwen-asr-serve。"""
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# Qwen3-ASR 已由新版 VLLM 原生支持，因此这里调用 vllm serve，避免
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# qwen-asr-serve 对旧版 VLLM 的固定依赖影响 GB10 部署环境。
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executable_name = os.getenv("VLLM_EXECUTABLE", "vllm")
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executable = shutil.which(executable_name)
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if executable is None:
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raise RuntimeError(f"{executable_name} was not found; install requirements-deploy.txt first")
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served_model_name = args.served_model_name or model_id
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command = [
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executable,
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"serve",
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str(model_path),
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"--host",
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args.host,
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"--port",
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str(SERVER_PORT),
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"--served-model-name",
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served_model_name,
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"--gpu-memory-utilization",
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str(args.gpu_memory_utilization),
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"--max-model-len",
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str(args.max_model_len),
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"--max-num-seqs",
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str(args.max_num_seqs),
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"--tensor-parallel-size",
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str(args.tensor_parallel_size),
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]
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if args.enforce_eager:
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command.append("--enforce-eager")
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return command
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def wait_until_ready(process: subprocess.Popen[bytes], probe_url: str, loops: int, interval: float) -> None:
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"""按调用方指定的次数和间隔轮询 VLLM 健康接口，直到服务就绪或失败。"""
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for attempt in range(1, loops + 1):
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if process.poll() is not None:
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raise RuntimeError(f"VLLM exited during startup with code {process.returncode}")
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try:
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with urlopen(probe_url, timeout=2) as response:
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if 200 <= response.status < 300:
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return
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except (OSError, URLError):
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pass
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print(f"Waiting for VLLM startup ({attempt}/{loops})...", flush=True)
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if attempt < loops:
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time.sleep(interval)
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raise TimeoutError(f"VLLM did not become ready after {loops} health checks: {probe_url}")
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def stop_process(process: subprocess.Popen[bytes]) -> None:
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"""向 VLLM 子进程转发优雅停止信号，并在超时后执行兜底清理。"""
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if process.poll() is not None:
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return
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if os.name == "nt":
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process.send_signal(signal.CTRL_BREAK_EVENT)
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else:
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process.send_signal(signal.SIGINT)
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try:
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process.wait(timeout=10)
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except subprocess.TimeoutExpired:
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process.terminate()
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process.wait(timeout=10)
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def main() -> int:
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"""解析一个本地模型、启动 VLLM，并持续托管宿主机子进程。"""
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args = build_parser().parse_args()
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manifest = load_manifest()
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model_id = resolve_model_id(args.model, manifest)
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model_path = model_directory(model_id, manifest, args.models_dir.resolve())
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if not has_model_weights(model_path):
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print(f"Model is missing or incomplete: {model_id} ({model_path})", file=sys.stderr)
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print("Run scripts/download_models.py for the same model first.", file=sys.stderr)
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return 1
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command = build_server_command(args, model_id, model_path)
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probe_url = f"http://{args.probe_host}:{SERVER_PORT}/health"
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display_url = f"http://{args.display_host}:{SERVER_PORT}"
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print(f"Starting Qwen3-ASR VLLM service on host: {display_url}", flush=True)
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print(f"Model: {model_id}", flush=True)
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print(f"Startup checks: {args.startup_check_loops} x {args.startup_check_interval}s", flush=True)
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process = subprocess.Popen(command)
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try:
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wait_until_ready(process, probe_url, args.startup_check_loops, args.startup_check_interval)
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print(f"VLLM ready: {display_url}", flush=True)
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print(f"OpenAI endpoint: {display_url}/v1", flush=True)
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while process.poll() is None:
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time.sleep(0.5)
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return int(process.returncode or 0)
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except (KeyboardInterrupt, TimeoutError, RuntimeError) as exc:
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print(str(exc), file=sys.stderr)
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return 1
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finally:
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stop_process(process)
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if __name__ == "__main__":
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raise SystemExit(main())
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