ASNNetworks Document extraction
Turning a document into a row is easy. Turning it into a row you can post to a ledger without a human looking is the hard part, and it is entirely about knowing which fields you are unsure of.
When to use this
Reading invoices, receipts, purchase orders, contracts, packing slips or forms into structured data. Single file or a directory.
How to run it
Get text out of the file first. Decide which kind of document you have:
python3 scripts/extract.py detect invoice.pdfIt reports
text(a digital PDF with a real text layer),scan(images only, needs OCR), ormixed.Extract.
python3 scripts/extract.py run invoice.pdf --schema invoice --jsonFor a scan, the script shells out to
pdftotext/tesseractwhen they are installed and tells you plainly when they are not. Do not silently return empty fields.Read the confidence block before the data block. Anything below the threshold is a field a human must confirm. Say so in your answer, by name.
Never invent a missing field. A null with a reason beats a plausible guess, every time. This is the rule the whole skill exists for.
The schema
references/schemas.md holds the field sets. The invoice one, which covers most work:
| Field | Type | Notes |
|---|---|---|
invoice_number |
string | As printed. Do not normalise away prefixes |
invoice_date |
ISO date | Watch DD/MM vs MM/DD — see below |
due_date |
ISO date, null | Often expressed as "30 dagen" and must be computed |
supplier.name |
string | The party being paid |
supplier.vat_number |
string, null | Validate the country prefix and length |
supplier.iban |
string, null | Checksum it |
customer.name |
string | |
lines[] |
array | description, quantity, unit_price, line_total |
subtotal |
decimal | |
vat[] |
array | rate + amount per rate. Multiple rates are normal |
total |
decimal | |
currency |
ISO 4217 | Infer from the symbol only when it is unambiguous |
The four mistakes that cost real money
1. Date order. 03/04/2026 is 3 April in the Netherlands and 4 March in the US. Do
not guess from the number alone. Resolve it from: an explicit month name elsewhere in the
document, the supplier's country, or another date in the same document where the day
exceeds 12. If none of those settle it, return the raw string and flag it. A silently
wrong invoice date lands the payment in the wrong quarter.
2. Totals that do not reconcile. Always check sum(lines) == subtotal and
subtotal + sum(vat) == total. When it does not add up, the extraction is wrong, not the
invoice. Report the discrepancy rather than the numbers.
3. Credit notes read as invoices. A negative total, or the words "creditnota" / "credit note", flips the sign of the whole document. Booking one as a payable is a real error with a real cost.
4. Multi-page documents where the total is on page 3. Do not extract page 1 and stop. Concatenate first, extract second.
Reporting
invoice.pdf → invoice
✓ invoice_number 2026-0417
✓ total 1.234,56 EUR
✓ reconciles lines 1.020,30 + btw 214,26 = 1.234,56
⚠ due_date null — "betaling binnen 30 dagen" found, but no invoice_date
to compute from. Needs a human.
Files
scripts/extract.py— detection, text extraction, field parsing, reconciliation.references/schemas.md— the field sets for invoice, receipt, contract and packing slip.