Update app.py

app.py

@@ -1,22 +1,21 @@
 import transformers
-from transformers import GPT2LMHeadModel, GPT2Tokenizer
-from transformers import GenerationConfig
+from transformers import GPT2LMHeadModel, GPT2Tokenizer, GenerationConfig
 import streamlit as st
 
 model_name = "gpt2-large"
 model = GPT2LMHeadModel.from_pretrained(model_name)
 tokenizer = GPT2Tokenizer.from_pretrained(model_name)
 
-title = st.text_area("\nEnter a title to generate a blog post:")
+title = st.text_area("Enter a title to generate a blog post:")
 
-input_prompt = f"Blog Title: {title}\n\nBlog Post:\n"
-input_ids = tokenizer.encode(input_prompt, return_tensors='pt')
+if title:
+    input_prompt = f"Blog Title: {title}\n\nBlog Post:\n"
+    input_ids = tokenizer.encode(input_prompt, return_tensors='pt')
 
-generation_config = GenerationConfig(max_new_tokens=100, do_sample=True, temperature=0.7)
+    generation_config = GenerationConfig(max_new_tokens=100, do_sample=True, temperature=0.7)
 
-output_ids = model.generate(input_ids, generation_config=generation_config)[0]
+    output_ids = model.generate(input_ids, generation_config=generation_config)[0]
 
-output_text = tokenizer.decode(output_ids, skip_special_tokens=True)
+    output_text = tokenizer.decode(output_ids, skip_special_tokens=True)
 
-if text:
-    st.write(output_text)
+    st.write(output_text)