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Create app.py
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app.py
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import streamlit as st
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from transformers import pipeline
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# Load summarization model
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@st.cache_resource
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def load_summarizer():
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summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
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return summarizer
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# Summarize input text
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def summarize_text(input_text, max_length=130, min_length=30):
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summarizer = load_summarizer()
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summary = summarizer(input_text, max_length=max_length, min_length=min_length, do_sample=False)
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return summary[0]['summary_text']
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# Streamlit app interface
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def main():
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st.title("Text Summarization App")
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# Input box for text to summarize
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input_text = st.text_area("Enter the text you want to summarize:", "Paste your article or text here...")
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# Slider for max and min length of the summary
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max_length = st.slider("Maximum length of summary:", min_value=50, max_value=300, value=130)
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min_length = st.slider("Minimum length of summary:", min_value=20, max_value=100, value=30)
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# Button to summarize
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if st.button("Summarize"):
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with st.spinner("Summarizing..."):
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summary = summarize_text(input_text, max_length=max_length, min_length=min_length)
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st.subheader("Summary")
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st.write(summary)
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# Run the app
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if __name__ == '__main__':
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main()
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