Update app.py

app.py

@@ -9,22 +9,22 @@ tokenizer1 = AutoTokenizer.from_pretrained("pedramyazdipoor/persian_xlm_roberta_
 
 roberta_large = pipeline(task='question-answering', model=model1, tokenizer=tokenizer1)
 
-def Q_A(contetx, question):
+def Q_A(question, context):
   answer_pedram = roberta_large({"question":question, "context":context})['answer']
   return answer_pedram
 
 
 
 # Create title, description and article strings
-title = "Question and answer based on Roberta model"
+title = "Question and answer based on Roberta model develop by nima asl toghiri"
 description = "سیستم پردازش زبانی پرسش و پاسخ"
 article = "آموزش داده شده با مدل زبانی روبرتا"
 
 
 demo = gr.Interface(fn=Q_A, # mapping function from input to output
-                    inputs=[gr.Textbox(label='پرسش خوذ را وارد کنید:', show_label=True, text_align='right'),
-                            gr.Textbox(label='متن منبع خود را وارد کنید', show_label=True, text_align='right')], # what are the inputs?
-                    outputs=gr.Text(), # what are the outputs?
+                    inputs=[gr.Textbox(label='پرسش خود را وارد کنید:', show_label=True, text_align='right', lines=2),
+                            gr.Textbox(label='متن منبع خود را وارد کنید', show_label=True, text_align='right', lines=8)], # what are the inputs?
+                    outputs=gr.Text(show_copy_button=True), # what are the outputs?
                               # our fn has two outputs, therefore we have two outputs
                     # Create examples list from "examples/" directory
                     title=title,