import os import sys from mineru.utils.models_download_utils import auto_download_and_get_model_root_path def main(): args = sys.argv[1:] has_port_arg = False has_gpu_memory_utilization_arg = False has_log_level_arg = False has_device_arg = False device_type = "cuda" # 检查现有参数 for i, arg in enumerate(args): if arg == "--server-port" or arg.startswith("--server-port="): has_port_arg = True if arg == "--cache-max-entry-count" or arg.startswith("--cache-max-entry-count="): has_gpu_memory_utilization_arg = True if arg == "--log-level" or arg.startswith("--log-level="): has_log_level_arg = True if arg == "--device": has_device_arg = True if i + 1 < len(args): device_type = args[i + 1] elif arg.startswith("--device="): has_device_arg = True device_type = arg.split("=", 1)[1] # 添加默认参数 if not has_port_arg: args.extend(["--server-port", "30000"]) if not has_gpu_memory_utilization_arg: args.extend(["--cache-max-entry-count", "0.5"]) if not has_log_level_arg: args.extend(["--log-level", "ERROR"]) if has_device_arg: if device_type.lower() in ["ascend", "maca", "camb"]: args.extend(["--backend", "pytorch"]) model_path = auto_download_and_get_model_root_path("/", "vlm") # 重构参数,将模型路径作为位置参数 sys.argv = [sys.argv[0]] + ["serve", "api_server", model_path] + args if os.getenv('OMP_NUM_THREADS') is None: os.environ["OMP_NUM_THREADS"] = "1" # 启动 lmdeploy 服务器 print(f"start lmdeploy server: {sys.argv}") # 使用os.system调用启动lmdeploy服务器 os.system("lmdeploy " + " ".join(sys.argv[1:])) if __name__ == "__main__": main()