Update app.py

app.py

@@ -1,11 +1,13 @@
 import streamlit as st
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
 
-
+# Load the model and tokenizer
 model_name = "gpt2"
 tokenizer = GPT2Tokenizer.from_pretrained(model_name)
 model = GPT2LMHeadModel.from_pretrained(model_name)
-def make_prompt(example_title, example_content, new_title):
+
+# Function to create the prompt
+def make_prompt(new_title):
     prompt = f"""
     Title: The Benefits of Daily Meditation
 
@@ -20,14 +22,22 @@ benefits such as reducing stress, improving concentration, and promoting a healt
     Blog Content:
     """
     return prompt
-def generate_blog(title):
-    input_ids = tokenizer.encode(title, return_tensors='pt')
+
+# Function to generate the blog content
+def generate_blog(prompt):
+    input_ids = tokenizer.encode(prompt, return_tensors='pt')
     output = model.generate(input_ids, max_length=800, num_return_sequences=1, no_repeat_ngram_size=2)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Streamlit interface
+st.title("AI Blog Generator")
+
+# Input box for the blog title
+title = st.text_input("Enter the Blog Title:")
 
 if st.button("Generate Blog"):
     if title:
-        title=make_prompt(title)
-        blog_content = generate_blog(title)
+        prompt = make_prompt(title)
+        blog_content = generate_blog(prompt)
         st.subheader("Generated Blog")
         st.write(blog_content)
-