receipt-tracker-setup

You can automatically extract receipt data by setting up a folder watcher that monitors an input directory for new receipt images or PDFs. The system uses AI extraction to parse merchant details and line items, then stores them in a searchable SQLite database for continuous expense tracking.

SQLite is used for expense tracking by storing extracted receipt details like merchant information, line-item descriptions, and minor-unit amounts. You can query the database directly to see recent merchants and totals by currency after the AI extraction processes new files.

Python is required to run the receipt and invoice parser, as it implements folder watching and file archiving using Python-based dependencies. The setup runs as a managed background service with auto-restart capabilities to continuously process new files.

The best way to archive processed receipt files is using a managed service that moves successfully parsed files from the input folder to a designated archive folder. This ensures original receipt images and PDFs are kept for auditability while the extracted data goes to the database.

Automated receipt extraction works with both image files and PDFs dropped into the watched input folder. The AI extraction API parses both formats to extract merchant and line-item details before moving the originals to the archive folder.

If the receipt tracker service stops processing new files, the managed service execution includes auto-restart and log outputs to help diagnose issues. Check the logs for errors related to AI extraction or file archiving to identify the root cause.