Update app.py

app.py

@@ -1,14 +1,13 @@
-import streamlit as st 
-from main import generate_text
+import streamlit as st
 from transformers import TFGPT2LMHeadModel ,GPT2Tokenizer, BitsAndBytesConfig
 import tensorflow as tf
 
 tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
 model = TFGPT2LMHeadModel.from_pretrained('gpt2',pad_token_id = tokenizer.eos_token_id)
 
-def generate_text(inp):
+def generate(inp):
     input_ids = tokenizer.encode(inp,return_tensors = 'tf')
-    beam_output =  model.generate(input_ids, max_length = 100,num_beams = 5, no_repeat_ngram_size = 2, early_stopping = True)
+    beam_output =  model.generate(input_ids, max_length = 300,num_beams = 5, no_repeat_ngram_size = 2, early_stopping = True)
     output = tokenizer.decode(beam_output[0],skip_special_tokens = True, clean_up_tokenization_spaces = True)
     return ".".join(output.split(".")[:-1]) + "."
     
@@ -28,7 +27,7 @@ if prompt:
     with st.chat_message("user"):
         st.markdown(prompt)
     st.session_state.messages.append({"role":"user","content":prompt})
-    response = f"ChatBot: {generate_text(prompt)}"
+    response = f"ChatBot: {generate(prompt)}"
     with st.chat_message("assistant"):
         st.markdown(response)
     st.session_state.messages.append({"role":"assistant","content":response})