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import streamlit as st
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from txtai.pipeline import Summary, Textractor
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from PyPDF2 import PdfReader
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st.set_page_config(layout="wide")
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@st.cache_resource
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def text_summary(text, maxlength=None):
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summary = Summary()
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text = (text)
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result = summary(text)
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return result
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def extract_text_from_pdf(file_path):
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with open(file_path, "rb") as f:
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reader = PdfReader(f)
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page = reader.pages[0]
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text = page.extract_text()
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return text
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choice = st.sidebar.selectbox("Select your choice", ["Summarize Text", "Summarize Document"])
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if choice == "Summarize Text":
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st.subheader("Summarize Text")
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input_text = st.text_area("Enter your text here")
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if input_text is not None:
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if st.button("Summarize Text"):
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col1, col2 = st.columns([1,1])
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with col1:
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st.markdown("**Your Input Text**")
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st.info(input_text)
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with col2:
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st.markdown("**Summary Result**")
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result = text_summary(input_text)
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st.success(result)
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elif choice == "Summarize Document":
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st.subheader("Summarize Document")
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input_file = st.file_uploader("Upload your document here", type=['pdf'])
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if input_file is not None:
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if st.button("Summarize Document"):
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with open("doc_file.pdf", "wb") as f:
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f.write(input_file.getbuffer())
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col1, col2 = st.columns([1,1])
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with col1:
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st.info("File uploaded successfully")
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extracted_text = extract_text_from_pdf("doc_file.pdf")
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st.markdown("**Extracted Text is Below:**")
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st.info(extracted_text)
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with col2:
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st.markdown("**Summary Result**")
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text = extract_text_from_pdf("doc_file.pdf")
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doc_summary = text_summary(text)
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st.success(doc_summary)
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