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import streamlit as st
import pandas as pd
import tempfile
import os
from PDFSectionExtractor import PDFSectionExtractor, convert_pdf_to_excel
# Add page config
st.set_page_config(
page_title="PDF Section and Table Extractor",
page_icon=":page_facing_up:",
layout="wide"
)
# Add custom CSS to improve the interface
st.markdown("""
<style>
.stButton>button {
width: 100%;
}
.css-1v0mbdj.e115fcil1 {
max-width: 100%;
}
</style>
""", unsafe_allow_html=True)
def main():
st.title(":page_facing_up: PDF Section and Table Extractor")
st.write("Upload a PDF file to extract sections and tables into an Excel workbook.")
# Add some usage instructions
with st.expander(":information_source: How to use"):
st.write("""
1. Upload a PDF file using the file uploader below
2. Wait for the processing to complete
3. Preview the extracted sections
4. Download the results as an Excel file
""")
# File uploader with additional information
uploaded_file = st.file_uploader(
"Choose a PDF file",
type=['pdf'],
help="Upload a PDF file containing sections and tables to extract"
)
if uploaded_file is not None:
# Create a temporary directory to store the files
with tempfile.TemporaryDirectory() as temp_dir:
# Save the uploaded PDF
pdf_path = os.path.join(temp_dir, uploaded_file.name)
with open(pdf_path, "wb") as f:
f.write(uploaded_file.getvalue())
# Create the Excel output path
excel_filename = os.path.splitext(uploaded_file.name)[0] + "_extracted.xlsx"
excel_path = os.path.join(temp_dir, excel_filename)
try:
with st.spinner(":arrows_counterclockwise: Processing PDF... This may take a moment."):
# Create extractor instance
extractor = PDFSectionExtractor(pdf_path)
# Get document info
doc_name, doc_id = extractor.get_document_info()
# Display document info in a nice format
col1, col2 = st.columns(2)
with col1:
st.info(f":memo: Document Name: {doc_name}")
with col2:
st.info(f":key: Document ID: {doc_id}")
# Extract tables and sections
tables = extractor.extract_tables()
sections = extractor.extract_sections()
# Create Excel file
convert_pdf_to_excel(pdf_path, excel_path)
# Show summary
st.success(":white_check_mark: Successfully processed PDF!")
st.write(f":bar_chart: Found {len(tables)} tables and :bookmark_tabs: {len(sections)} sections.")
# Display sections preview
if sections:
st.subheader("Sections Preview")
df_sections = pd.DataFrame(sections)
st.dataframe(df_sections, use_container_width=True)
else:
st.warning("No sections found in the document.")
# Provide download button for Excel file
with open(excel_path, "rb") as f:
excel_data = f.read()
st.download_button(
label=":inbox_tray: Download Excel File",
data=excel_data,
file_name=excel_filename,
mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
key="download-excel"
)
except Exception as e:
st.error(f":x: An error occurred: {str(e)}")
st.write("Please make sure your PDF file is valid and try again.")
if __name__ == "__main__":
main()
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