Update app.py

app.py

@@ -40,28 +40,18 @@ def the_process(input_text, model_choice):
     print("Inside the_process for python 1", model_choice)
     if(model_choice==1):
       if(pythonFlag == "false"):
-        print("Inside llama for python")
+        print("Inside starcoder for python")
         tokenizer = AutoTokenizer.from_pretrained("nadiamaqbool81/starcoderbase-1b-hf_python")
         model = AutoModelForCausalLM.from_pretrained("nadiamaqbool81/starcoderbase-1b-hf_python")
         output = run_predict(input_text, model, tokenizer)
         print("output" , output)
-        pythonFlag = "true"
-      elif(pythonFlag == "true"):
-        print("pythonFlag", pythonFlag)
-        output = run_predict(input_text, model, tokenizer)
-        print("output" , output)
     if(model_choice==0):
         if(javaFlag == "false"):
-            print("Inside llama for python")
+            print("Inside starcoder for python")
             tokenizer = AutoTokenizer.from_pretrained("nadiamaqbool81/starcoderbase-1b-hf")
             model = AutoModelForCausalLM.from_pretrained("nadiamaqbool81/starcoderbase-1b-hf")
             output = run_predict(input_text, model, tokenizer)
             print("output" , output)
-            javaFlag = "true"
-        elif(javaFlag == "true"):
-            print("javaFlag", javaFlag)
-            output = run_predict(input_text, model, tokenizer)
-            print("output" , output)
     else:
       a_variable = model_box[model_choice]
       output = a_variable(input_text)