Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Load the BART model for text summarization from Hugging Face
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Streamlit app layout
+st.title("Text Summarization Tool")
+st.write("Automatically summarizes long articles or documents into concise summaries using the BART model.")
+
+# Input field for the user to enter or paste the text
+input_text = st.text_area("Enter the text you want to summarize:", height=300)
+
+# Check if there is input text
+if input_text:
+    # Display the original text
+    st.subheader("Original Text:")
+    st.write(input_text)
+
+    # Generate the summary using the pre-trained BART model
+    summary = summarizer(input_text, max_length=200, min_length=50, do_sample=False)
+
+    # Display the summarized text
+    st.subheader("Summary:")
+    st.write(summary[0]['summary_text'])
+
+# Option to clear the input
+if st.button("Clear Text"):
+    st.text_area("Enter the text you want to summarize:", value="")