A lightweight Streamlit web app to ingest case lists (CSV/XLSX) and parse one or more PDFs to extract case number, name, amount, and address using customizable regex rules.

• Bulk upload CSV/XLSX; normalize common headers
• Upload and parse multiple PDFs
  • Text extraction with pdfplumber
  • Optional OCR per page if Tesseract is installed (Use OCR checkbox)
• Customizable extraction rules via JSON (regex)
• Filter by minimum amount (e.g., show ≥ $10,000)
• Dedupe by case number
• Preview table and export CSVs (all and ≥$10k)
• Optional ZIP of raw page texts for auditing

1. Install Python 3.10+
2. Create a virtual environment and install requirements:

   python -m venv .venv && source .venv/bin/activate
   pip install -r requirements.txt

3. (Optional OCR) Install Tesseract:
   • macOS (brew): brew install tesseract
   • Ubuntu: sudo apt-get install tesseract-ocr
4. Run:

   streamlit run app.py

5. Open the local URL printed in your terminal.

• Streamlit Community Cloud: create a public Git repo with these files and "New app".
• Replit: create a new Python Repl, add files, and run streamlit run app.py.
• Railway/Render: deploy as a web service; set start command to streamlit run app.py --server.port $PORT --server.address 0.0.0.0.

• Tune the regex rules in the sidebar for your county formats.
• If PDFs are scanned, toggle Use OCR (requires Tesseract installed on the host).

Made for fast, no-drama case data wrangling.