Update app.py

app.py

@@ -1,9 +1,20 @@
 import streamlit as st
-from transformers import pipeline
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-pipe = pipeline('sentiment-analysis')
-text = st.text_area('Enter some text:')
+# Define model and tokenizer
+model_name = 'openai-community/gpt2-large'
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
 
-if text:
-    out = pipe(text)
-    st.json(out)
+def generate_blogpost(topic):
+    inputs = tokenizer.encode(topic, return_tensors='pt')
+    outputs = model.generate(inputs, max_length=500, num_return_sequences=1)
+    text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return text
+
+# Streamlit app
+st.title('Blog Post Generator')
+topic = st.text_input('Enter a topic:')
+if topic:
+    blogpost = generate_blogpost(topic)
+    st.write(blogpost)