app.py

import streamlit as st
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load GPT-2 model and tokenizer
model_name = "gpt2"
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
model = GPT2LMHeadModel.from_pretrained(model_name)

def generate_blog(title):
    input_ids = tokenizer.encode(title, return_tensors='pt')
    output = model.generate(input_ids, max_length=500, num_return_sequences=1, no_repeat_ngram_size=2, early_stopping=True)
    blog = tokenizer.decode(output[0], skip_special_tokens=True)
    return blog

# Streamlit app
st.title("AI Blog Generator")
st.write("Enter a blog title and the AI will generate the blog content for you.")

# Input blog title
title = st.text_input("Blog Title", "")

if st.button("Generate Blog"):
    if title:
        blog_content = generate_blog(title)
        st.subheader("Generated Blog")
        st.write(blog_content)
    else:
        st.error("Please enter a blog title.")