update app.py

app.py

@@ -1,6 +1,7 @@
 import streamlit as st
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 from nltk.tokenize import sent_tokenize
+import nltk
 
 nltk.download('punkt')
 
@@ -18,14 +19,9 @@ def parse_text(text):
 
 
 def summarize(text):
-    input_ids = tokenizer.parse(text=text, return_tensors="pt")
-    labels = input_ids.clone()
-    decoder_input_ids = model.generate(input_ids=input_ids)
-
-
-    output = tokenizer.batch_decode(decoder_output_ids.cpu(), skip_specialTokens=True)
-
-
+    input_ids = tokenizer.encode(text, return_tensors="pt")
+    decoder_output_ids = model.generate(input_ids=input_ids)
+    output = tokenizer.batch_decode(decoder_output_ids, skip_special_tokens=True)
     return output[0]
 
 
@@ -34,24 +30,20 @@ def format_messages_for_summary(messages):
     for message in messages:
         if message["role"] == "assistant":
             summary_text_list.append(message["content"].lower())
-
-
     return ''.join(summary_text_list)
 
 
 def main():
     st.title("T5 Chat Interface")
 
+    if 'messages' not in st.session_state:
+        st.session_state['messages'] = []
 
-    user_input = st.text_area("Enter your prompt:")
-
-
-    submitted = st.form_submit_button(label="Submit")
-
+    with st.form(key='input_form'):
+        user_input = st.text_area("Enter your prompt:")
+        submitted = st.form_submit_button(label="Submit")
 
     if submitted:
-
-
         messages = [
             {
                 "role": "user",
@@ -59,14 +51,12 @@ def main():
             }
         ]
 
-
         response = summarize(user_input)
 
-
         st.session_state['messages'].append({
             "role": "assistant",
-            "content": response})
-
+            "content": response
+        })
 
         st.write(format_messages_for_summary(st.session_state['messages']))
 
@@ -76,4 +66,4 @@ def save_session():
 
 
 if __name__ == '__main__':
-    main()
+    main()