Function run_batch_processing

mainprogress/determine_toc_levels.py:442–482

(image_files: list, output_path: Path)

        print("首图处理失败，脚本停止。请检查日志。")
        return

    # 2. 并发处理剩余图片
    if len(image_files) > 1:
        write_log("阶段 2: 基于首图示例并发处理剩余图片")
        tasks = []
        for img_file in image_files[1:]:
            csv_file = output_path / f"{img_file.stem}.csv"
            tasks.append(process_level_async(semaphore, img_file, csv_file, output_path))
        
        results = await asyncio.gather(*tasks, return_exceptions=True)
        success_count = sum(1 for r in results if r is True)
        fail_count = sum(1 for r in results if r is False)
        exception_count = sum(1 for r in results if isinstance(r, Exception))
        
        print(f"并发处理完成。成功：{success_count}, 失败/空结果：{fail_count}, 异常：{exception_count}")
    else:
        print("仅有一张图片，处理完毕。")

    # 处理完成后清空图片缓存，释放内存
    IMAGE_CACHE.clear()

async def main_async():
    load_dotenv()
    
    global LLM_CONFIG, client
    try:
        LLM_CONFIG = load_llm_config()
    except Exception as e:
        print(f"加载 LLM 配置失败：{e}")
        sys.exit(1)
    
    # 初始化 OpenAI 客户端
    client = AsyncOpenAI(
        api_key=LLM_CONFIG["api_key"],
        base_url=LLM_CONFIG["base_url"],
        timeout=REQUEST_TIMEOUT,
        max_retries=2
    )
    
    base_dir = os.getenv("BASE_DIR")
    if base_dir:
        input_path = Path(base_dir) / "mark" / "input_image"
        output_path = Path(base_dir) / "raw_content"
    else: