Update app.py

app.py

@@ -1,9 +1,28 @@
 import streamlit as st
-from transformers import pipeline
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
 
-pipe=pipeline('sentiment-analysis')
-text=st.text_area("Enter Text: ")
+# Load GPT-2 model and tokenizer
+model_name = "gpt2"
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+model = GPT2LMHeadModel.from_pretrained(model_name)
 
-if text:
-    out= pipe(text)
-    st.json(out)
+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.")