Update app.py

app.py

@@ -112,7 +112,7 @@ responses_4 = (gen_prompt | instruct_llm).invoke(
 
 good_responses = responses_1 + responses_2
 poor_responses = responses_3 + responses_4
-    
+model1 = 0
 async def embeding():
     good_tasks = [embed(query) for query in good_responses]
     poor_tasks = [embed(query) for query in poor_responses]
@@ -120,10 +120,11 @@ async def embeding():
     embeds = await asyncio.gather(*all_tasks)
     good_embeds = embeds[:len(good_tasks)]
     poor_embeds = embeds[len(good_tasks):]
+    model1 = train_model_neural_network(poor_embeds, good_embeds)
 
 embeding()
 
-model1 = train_model_neural_network(poor_embeds, good_embeds)
+# model1 = train_model_neural_network(poor_embeds, good_embeds)
 
 def RPrint(preface=""):
     def print_and_return(x, preface=""):