Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 from transformers import pipeline
 
 st.set_page_config(page_title="LLM Text Summarizer", layout="centered")
-st.title("LLM-Powered Text Summarizer")
+#st.title("LLM-Powered Text Summarizer")
 #st.markdown("This app summarizes long texts using a Hugging Face transformer model (`facebook/bart-large-cnn`).")
 
 @st.cache_resource
@@ -10,8 +10,20 @@ def load_model():
     return pipeline("summarization", model="facebook/bart-large-cnn")
 
 summarizer = load_model()
+st.markdown("<h1 style='text-align: center;'>🧠 Smart Document Summarizer using BART</h1>", unsafe_allow_html=True)
+st.markdown("<p style='text-align: center; color: gray;'>This app splits long text into chunks and summarizes each part individually for better results.</p>", unsafe_allow_html=True)
 
-text = st.text_area("Enter text to summarize", height=300)
+# Two columns: Input and Output
+col1, col2 = st.columns(2)
+
+with col1:
+    st.markdown("### 📝 Enter Document")
+    text = st.text_area("Paste your long document here...", height=400, label_visibility="collapsed")
+
+with col2:
+    st.markdown("### 🧾 Combined Summary")
+    summary_box = st.empty()
+#text = st.text_area("Enter text to summarize", height=300)
 text = " ".join(text.split()[:700])  # Truncate input to ~700 words