更新环境配置，添加gevent和gunicorn依赖；新增chat_dify_by_workorder.py文件以处理工单对话逻辑；优化PgSql类中的异常处理，确保连接失败时抛出异常；改进意图识别API，使用单例模式管理意图识别器实例，增强线程安全性；新增workflow_chat.py文件以支持新工作流对话功能。

rag2_0/dify/intent_recognition_api.py

@@ -4,16 +4,32 @@ from dotenv import load_dotenv
 from rag2_0.intent_recognition import IntentRecognizer
 import json
 import time
+import threading
+import datetime
+
 # 加载环境变量
 load_dotenv()
 
 app = Flask(__name__)
 
-# 初始化意图识别器
-api_key = os.getenv("OPENAI_API_KEY")
-base_url = os.getenv("OPENAI_API_BASE")
-model_name = os.getenv("LLM_MODEL_NAME", "gpt-3.5-turbo")
-recognizer = IntentRecognizer(api_key=api_key, base_url=base_url, model_name=model_name)
+# 创建线程锁，用于保护共享资源
+recognizer_lock = threading.Lock()
+
+# 使用单例模式创建意图识别器
+class RecognizerSingleton:
+    _instance = None
+    _lock = threading.Lock()
+    
+    @classmethod
+    def get_instance(cls):
+        if cls._instance is None:
+            with cls._lock:
+                if cls._instance is None:
+                    api_key = os.getenv("OPENAI_API_KEY")
+                    base_url = os.getenv("OPENAI_API_BASE")
+                    model_name = os.getenv("LLM_MODEL_NAME", "gpt-3.5-turbo")
+                    cls._instance = IntentRecognizer(api_key=api_key, base_url=base_url, model_name=model_name)
+        return cls._instance
 
 @app.route('/intent_recognize', methods=['POST'])
 def intent_recognize():
@@ -22,10 +38,16 @@ def intent_recognize():
         query = data.get('query')
         if not query:
             return Response(json.dumps({"error": "缺少query参数"}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=400)
+        
         start_time = time.time()
+        
+        # 获取单例实例并使用线程锁保护关键操作
+        recognizer = RecognizerSingleton.get_instance()
         result = recognizer.process_query_with_slots(query)
+            
         end_time = time.time()
-        print(f"意图识别耗时: {end_time - start_time:.2f}秒")
+        current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S %z")
+        print(f"[{current_time}] [{os.getpid()}] [INFO] 意图识别耗时: {end_time - start_time:.2f}秒")
         
         # 提取分类信息
         classification = result["classification"]
@@ -63,7 +85,10 @@ def intent_recognize():
         }
         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)}")
         return Response(json.dumps({"error": str(e)}, ensure_ascii=False), content_type='application/json; charset=utf-8', status=500)
 
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=8001) 
+    # 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
+    app.run(host="0.0.0.0", port=8001, threaded=True)