Update app.py

app.py

@@ -4,15 +4,28 @@ from transformers import T5Tokenizer, T5ForConditionalGeneration
 tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
 model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base")
 
-input_text = "translate English to German: How old are you?"
 
-
-def greet(input_text):
+def get_examples ():
+    return [
+    ["Peter goes to the store to buy a soda. The soda costs $.25 an ounce. \
+He brought $2 with him and leaves with $.50. How many ounces of soda did he buy?",
+    "How much did Peter spend on soda? ** He spend $1.5 on soda because 2 - .5 = <<2-.5=1.5>>1.5 \
+How many ounces of soda did Peter buy? ** He bought 6 ounces of soda because 1.5 / .25 = <<6=6>>6 #### 6"
+    ],
+    ["Krystian works in the library. He borrows an average of 40 books every day. \
+Every Friday, his number of borrowed books is about 40% higher than the daily average. How many books does he borrow in a week if the library is open from Monday to Friday?"
+    ,"How many books does Krystian borrow on Friday? ** The number of books borrowed \
+on Friday is higher by 40 * 40/100 = <<40*40/100=16>>16 books. How many books does Krystian borrow in a week? ** There are 5 days from Monday to Friday inclusive, so Krystian borrows an average of 5 * 40 = <<5*40=200>>200 books during that time. How many books does Krystian borrow in a week? ** With Friday's increase in borrowings, during one week Krystian borrows 200 + 16 = <<200+16=216>>216 books."]
+    ]
+    
+    
+def text2text(input_text):
     input_ids = tokenizer(input_text, return_tensors="pt").input_ids
 
     outputs = model.generate(input_ids, max_length=40)
     return tokenizer.decode(outputs[0])
 
+textin = gr.Textbox()
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface = gr.Interface(fn=text2text, inputs=[textin], outputs="text", examples=gr.Examples(examples=get_examples(), inputs=[textin]))
 iface.launch()