Update app.py

app.py

@@ -1,5 +1,4 @@
 import streamlit as st
-import requests
 import torch
 from transformers import pipeline
 from transformers import BartTokenizer, BartForConditionalGeneration
@@ -12,23 +11,38 @@ model = BartForConditionalGeneration.from_pretrained(model_repo_path)
 tokenizer = BartTokenizer.from_pretrained(model_repo_path)
 
 # Initialize the summarization pipeline
-summarizer = pipeline('summarization', model=model,tokenizer=tokenizer)
+summarizer = pipeline('summarization', model=model, tokenizer=tokenizer)
 
 # Streamlit app layout
+st.set_page_config(page_title="Text Summarization App", page_icon=":memo:", layout="wide")
+
 st.title("Text Summarization App")
+st.write("""
+    This app uses a fine-tuned BART model to generate summaries of your input text.
+    Enter the text you want to summarize in the box below and click "Summarize" to see the result.
+""")
 
 # User input
-text_input = st.text_area("Enter text to summarize", height=300)
+text_input = st.text_area("Enter text to summarize", height=300, placeholder="Paste your text here...")
 
 # Summarize the text
 if st.button("Summarize"):
     if text_input:
         with st.spinner("Generating summary..."):
             try:
+                # Generate summary
                 summary = summarizer(text_input, max_length=150, min_length=30, do_sample=False)
+                
+                # Display summary
                 st.subheader("Summary")
                 st.write(summary[0]['summary_text'])
             except Exception as e:
-                st.error(f"Error during summarization: {e}")
+                st.error(f"An error occurred during summarization: {e}")
     else:
-        st.warning("Please enter some text to summarize.")
+        st.warning("Please enter some text to summarize.")
+
+# Optional: Add a footer or additional information
+st.markdown("""
+    ---
+    Made with ❤️ using [Streamlit](https://streamlit.io) and [Hugging Face Transformers](https://huggingface.co/transformers/).
+""")