优化Dify工具逻辑，调整知识提取和重排序流程，增强API调用的重试机制，更新意图识别API以支持更好的错误处理和日志记录，改进多线程检索功能

rag2_0/dify/intent_recognition_api.py

@@ -1,9 +1,14 @@
+from gevent import monkey
+monkey.patch_all()
+
 from flask import Flask, request, Response
 import os
 from dotenv import load_dotenv
 import json
 import time
-import threading
+from gevent.lock import RLock
+
+
 import datetime
 import logging
 # 加载环境变量
@@ -29,12 +34,12 @@ logger = logging.getLogger(__name__)
 app = Flask(__name__)
 
 # 创建线程锁，用于保护共享资源
-recognizer_lock = threading.Lock()
+recognizer_lock = RLock()
 
 # 使用单例模式创建意图识别器
 class RecognizerSingleton:
     _instance = None
-    _lock = threading.Lock()
+    _lock = RLock()
     
     @classmethod
     def get_instance(cls):
@@ -105,14 +110,16 @@ def intent_recognize():
                 "is_complete": slot_filling.get("is_complete", False),
                 "missing_slots": slot_filling.get("missing_slots", {}),
                 "filled_data": slot_filling.get("filled_data", {})
-            }
+            },
+            "query_expand": result["query_expand"]
         }
         return Response(json.dumps(response_result, ensure_ascii=False), content_type='application/json; charset=utf-8')
     except Exception as e:
-        print(f"意图识别出错: {str(e)}")
+        logger.error(f"意图识别出错: {str(e)}",exc_info=True)
         return Response(json.dumps({"error": str(e)}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=500)
 
 if __name__ == "__main__":
     # 开发环境使用Flask内置服务器
-    # 生产环境使用gunicorn支持高并发 poetry run gunicorn -w 10 -k gevent -b 0.0.0.0:8001 rag2_0.dify.intent_recognition_api:app
+    # 生产环境使用gunicorn支持高并发 uv run gunicorn -w 10 -k gevent -b 0.0.0.0:8001 rag2_0.dify.intent_recognition_api:app
+    # uv run gunicorn -w 10 -k gevent --preload -b 0.0.0.0:8001 rag2_0.dify.intent_recognition_api:app
     app.run(host="0.0.0.0", port=8001, threaded=True)