预加载asr，修改import路径

backend/algorithm/pipeline.py

@@ -51,10 +51,11 @@ def _setup_environment(video_path: str):
 
     return main_output_path, video_name, timestamp
 
-def _run_asr_and_process(video_path: str, video_name: str, main_output_path: str):
+def _run_asr_and_process(video_path: str, video_name: str, main_output_path: str, asr_engine=None):
     """Runs ASR on the video and processes the result."""
     logging.info("--- 步骤 0 & 1: 语音识别与数据处理 ---")
-    asr_engine = VideoDevourASRParaformerV2()
+    if asr_engine is None:
+        asr_engine = VideoDevourASRParaformerV2()
     asr_result = asr_engine.devour_video(video_path)
     asr_result_path = os.path.join(main_output_path, f"{video_name}_asr_result.json")
     with open(asr_result_path, 'w', encoding='utf-8') as f:
@@ -119,12 +120,12 @@ def _generate_and_match_outline(processed_dialogue: list, main_output_path: str)
     logging.info("--- 文本块匹配完成 ---")
     return matched_data, headings_with_level, headings, outline
 
-def run_full_pipeline(video_path: str):
+def run_full_pipeline(video_path: str, asr_engine=None):
     """Orchestrates the full video processing pipeline."""
     try:
         main_output_path, video_name, timestamp = _setup_environment(video_path)
 
-        processed_dialogue = _run_asr_and_process(video_path, video_name, main_output_path)
+        processed_dialogue = _run_asr_and_process(video_path, video_name, main_output_path, asr_engine)
         if not processed_dialogue:
             raise ValueError("ASR处理后对话为空，流程中止。")
 

backend/algorithm/vlm_handler.py

@@ -7,7 +7,7 @@
 from typing import List, Tuple, Union
 from PIL import Image
 import io
-import backend.algorithm.config as config
+import config
 
 
 class VLMHandler:

backend/api/main.py

@@ -10,6 +10,7 @@
 import shutil
 import asyncio
 import json
+import logging
 from pathlib import Path
 from typing import Dict, List, Optional
 from datetime import datetime
@@ -25,13 +26,18 @@
 sys.path.insert(0, str(PROJECT_ROOT))
 
 from backend.algorithm.pipeline import run_full_pipeline
+from backend.devour.asr_engine_paraformer_v2 import VideoDevourASRParaformerV2
+
+# 配置日志
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
 # 创建FastAPI应用
 app = FastAPI(
     title="VideoDevour API",
     description="视频处理和分析服务",
     version="1.0.0"
 )
+asr_engine = None
 
 # 配置CORS
 app.add_middleware(
@@ -80,6 +86,21 @@ def save_tasks():
 # 启动时加载任务数据
 load_tasks()
 
+@app.on_event("startup")
+async def startup_event():
+    """
+    预加载 ASR 模型
+    """
+    global asr_engine
+    try:
+        logging.info("正在预加载 ASR 模型...")
+        asr_engine = VideoDevourASRParaformerV2()
+        _ = asr_engine.asr_model
+        logging.info("ASR 模型预加载完成")
+    except Exception as e:
+        logging.error(f"ASR 模型预加载失败: {str(e)}")
+        asr_engine = None
+
 # 数据模型
 class TaskStatus(BaseModel):
     task_id: str
@@ -718,7 +739,8 @@ def update_progress(progress: int, message: str, stage: str = None):
         # 使用线程池执行器运行同步函数
         with concurrent.futures.ThreadPoolExecutor() as executor:
             # 在执行过程中定期更新进度
-            future = executor.submit(run_full_pipeline, video_path)
+            # 预加载模型
+            future = executor.submit(run_full_pipeline, video_path, asr_engine)
 
             # 模拟进度更新
             progress_steps = [