Update app.py

app.py

@@ -9,42 +9,34 @@ from qwen_agent.gui.gradio import gr
 def  app_gui ():
     # Define the agent
     bot = Assistant(llm={
-                    'model' : os.environ.get( "MODELNAME" ),
-                    'model_type' : 'qwen_dashscope' ,
-                    'generate_cfg' : {
-                        'max_input_tokens' : 32768 ,
-                        'max_retries' : 10 ,
-                        'temperature' : float (os.environ.get( "T" , 0.001 )),
-                        'repetition_penalty' : float (os.environ.get( "R" , 1.0 )),
-                        "top_k" : int (os.environ.get( "K" , 20 )),
-                        "top_p" : float (os.environ.get( "P" , 0.8 )),
+                    'model': 'QwQ-32B-preview', #os.environ.get( "MODELNAME" ),
+                    'model_type': 'qwen_dashscope',
+                    'generate_cfg': {
+                        'max_input_tokens': 32768,
+                        'max_retries': 10,
+                        'temperature': float (os.environ.get( "T", 0.001 )),
+                        'repetition_penalty': float (os.environ.get( "R", 1.0 )),
+                        "top_k": int (os.environ.get( "K", 20 )),
+                        "top_p": float (os.environ.get( "P", 0.8 )),
                     }},
-                    name = 'QwQ-32B-preview' ,
+                    name = 'QwQ-32B-preview',
                     description= 'QwQ-32B-Preview is an experimental research model developed by the Qwen Team, focused on advancing AI reasoning capabilities. As a preview release, it demonstrates promising analytical abilities while having several important limitations such as code switching and recursive reasoning loops. Only single-turn queries are supported in this demo.' ,
                     system_message= 'You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step.' ,
                     rag_cfg={ 'max_ref_token' : 32768 , 'rag_searchers' : []},
                 )
     chatbot_config = {
-        'input.placeholder' : "Type \"/clear\" to clear the history" ,
-        'verbose' : True ,
-        'prompt.suggestions' : [
+        'input.placeholder': "Type \"/clear\" to clear the history",
+        'verbose': True,
+        'prompt.suggestions': [
             {
-                'text' : 'How many r in strawberry'
+                'text': 'How many r in strawberry'
             },
             {
-                'text' : 'Find the least odd prime factor of $2019^8+1$.'
-            },
-            {
-                'text' : '''Mr. S, Mr. P, and Mr. Q know that there are 16 playing cards in the drawer of the table: A, Q, 4 of hearts, J, 8, 4, 2, 7, 3 of spades, K, Q, 5, 4, 6 of clubs, A, 5 of diamonds. Professor John picked a card from the 16 cards and told Mr. P the number of points on the card and Mr. Q the suit of the card. At this time, Professor John asked Mr. P and Mr. Q: Can you infer what card this is from the known number of points or suit? So, Mr. S heard the following conversation:
-Mr. P: I don’t know this card.
-Mr. Q: I know you don’t know this card.
-Mr. P: Now I know this card.
-Mr. Q: I know that too.
-Please tell me: What card is this? '''
+                'text': 'Find the least odd prime factor of $2019^8+1$.'
             },
         ]
     }
-    WebUI(bot, chatbot_config=chatbot_config).run(concurrency_limit= 80)
+    WebUI(bot, chatbot_config=chatbot_config).run(concurrency_limit=80)
 
 if __name__ == '__main__' :
     app_gui()