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import streamlit as st | |
from transformers import pipeline | |
summarizer = pipeline("summarization", model="facebook/bart-large-cnn") | |
def main(): | |
st.title("Text Summarizer App") | |
input_text = st.text_area("Enter the text you want to summarize:") | |
# Sidebar | |
min_length = st.sidebar.slider("Minimum Summary Length", 10, 200, 50) | |
max_length = st.sidebar.slider("Maximum Summary Length", 50, 500, 100) | |
if st.button("Generate Summary"): | |
if input_text: | |
# Generate summary | |
summary = summarizer(input_text, max_length=max_length, min_length=min_length, do_sample=False) | |
st.subheader("Generated Summary:") | |
st.write(summary[0]["summary_text"]) | |
else: | |
st.warning("Please enter some text to summarize.") | |
if __name__ == "__main__": | |
main() | |