update language function

app.py

@@ -9,13 +9,13 @@ import os
 
 st.write('Part 1')
 
-text = st.text_input('Posez votre question (en anglais)')
+question = st.text_input('Posez votre question (en anglais)')
 url = st.text_input('mettez le liens de votre image')
 
 if st.button('générer'):
-    responseBase = image(url, text)
+    responseBase = image(url, question)
     st.write('response is :', responseBase)
     st.write('Part 2')
-    st.write(longText(responseBase))
+    st.write(longText(responseBase, question))
 
 print('#### TEST 2####')

language.py

@@ -1,21 +1,10 @@
 print('###### LANGUAGES ######')
-
-input_text = "i have question and answere.\
-the question is : How many cars here ?\
-the response is : 2\
-with this information, can you crate an answere phrase"
-
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 
-tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large")
-
-input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+def longText(answere, question):
 
-outputs = model.generate(input_ids)
-print(tokenizer.decode(outputs[0]))
+    input_text = "i have a question and answer.\nthe question is :",question,"\n the response is :",answere,"\n with this information, can you create an answer phrase?"
 
-def longText(input_text):
     tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
     model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large")
     input_ids = tokenizer(input_text, return_tensors="pt").input_ids