create language function

app.py

@@ -1,4 +1,5 @@
 from image import *
+from language import *
 import streamlit as st
 import torch
 import os
@@ -12,16 +13,9 @@ text = st.text_input('Posez votre question (en anglais)')
 url = st.text_input('mettez le liens de votre image')
 
 if st.button('générer'):
-    st.write('response is :', image(url, text))
-
-st.write('Part 2')
-os.system("language.py")
-
-print('#### TEST 2####')
-
-from transformers import pipeline
-
-model_checkpoint = "Helsinki-NLP/opus-mt-en-fr"
-translator = pipeline("translation", model=model_checkpoint)
-print(translator("How are you?"))
+    responseBase = image(url, text)
+    st.write('response is :', responseBase)
+    st.write('Part 2')
+    st.write(longText(responseBase))
 
+print('#### TEST 2####')

language.py

@@ -13,4 +13,11 @@ model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large")
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids
 
 outputs = model.generate(input_ids)
-print(tokenizer.decode(outputs[0]))
+print(tokenizer.decode(outputs[0]))
+
+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
+    outputs = model.generate(input_ids)
+    return tokenizer.decode(outputs[0])