fix: remove redundant model_path checks for vllm backends in vlm_analyze.py

mineru/backend/vlm/vlm_analyze.py

@@ -39,9 +39,6 @@ class ModelSingleton:
             if backend in ['transformers', 'vllm-engine', "vllm-async-engine"] and not model_path:
                 model_path = auto_download_and_get_model_root_path("/","vlm")
                 if backend == "transformers":
-                    if not model_path:
-                        raise ValueError("model_path must be provided when model or processor is None.")
-
                     try:
                         from transformers import (
                             AutoProcessor,
@@ -66,13 +63,10 @@ class ModelSingleton:
                         use_fast=True,
                     )
                 elif backend == "vllm-engine":
-                    if not model_path:
-                        raise ValueError("model_path must be provided when vllm_llm is None.")
                     try:
                         import vllm
                     except ImportError:
                         raise ImportError("Please install vllm to use the vllm-engine backend.")
-                    # logger.debug(kwargs)
                     if "gpu_memory_utilization" not in kwargs:
                         kwargs["gpu_memory_utilization"] = 0.5
                     if "model" not in kwargs:
@@ -80,15 +74,11 @@ class ModelSingleton:
                     # 使用kwargs为 vllm初始化参数
                     vllm_llm = vllm.LLM(**kwargs)
                 elif backend == "vllm-async-engine":
-                    if not model_path:
-                        raise ValueError("model_path must be provided when vllm_llm is None.")
                     try:
                         from vllm.engine.arg_utils import AsyncEngineArgs
                         from vllm.v1.engine.async_llm import AsyncLLM
                     except ImportError:
                         raise ImportError("Please install vllm to use the vllm-async-engine backend.")
-
-                    # logger.debug(kwargs)
                     if "gpu_memory_utilization" not in kwargs:
                         kwargs["gpu_memory_utilization"] = 0.5
                     if "model" not in kwargs: