import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the GPT-2 large model and tokenizer
model_name = "gpt2-large"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

def generate_blogpost(topic):
    input_text = f"Write a blog post about {topic}:"
    inputs = tokenizer.encode(input_text, return_tensors="pt")
    outputs = model.generate(inputs, max_length=500, num_return_sequences=1)
    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return generated_text

# Streamlit UI
st.title("Blog Post Generator")
st.write("Generate a blog post for a given topic using GPT-2 large.")

topic = st.text_input("Enter the topic:")
if st.button("Generate"):
    if topic:
        blog_post = generate_blogpost(topic)
        st.write(blog_post)
    else:
        st.write("Please enter a topic to generate a blog post.")