Processing Invoices

Ocupación

Categorías

Documentos

Step 3: Parse fields

Extract from text:

• vendor: Company name (usually at document top, in larger font)
• invoice_number: Look for "Invoice #", "Invoice No.", "INV-", "#"
• date: Invoice/billing date -> convert to YYYY-MM-DD
• total: Final amount ("Total:", "Amount Due:", "Balance:")
• currency: Default USD if not specified

Step 4: Validate

Run: python scripts/validate_invoice.py output.json

Step 5: Fix and re-validate

If validation fails:

1. Read the specific error message
2. Re-examine PDF text for that field
3. Update JSON with corrected value
4. Run validation again
5. Repeat until validation passes

Common issues: See TROUBLESHOOTING.md

Step 6: Save results

Save two files:

1. Output file (requested by user):

{
  "vendor": "...",
  "invoice_number": "...",
  "date": "YYYY-MM-DD",
  "total": 0.00
}

2. Eval log (always append to eval_results/all_evals.jsonl):

python scripts/collect_eval.py "<task_id>" "<original_task_prompt>" "<output_file>" "<notes>"

Example:

python scripts/collect_eval.py "invoice-basic" "Extract invoice data from invoice.pdf" "output.json" "validation passed on first attempt"

Always append to eval_results/all_evals.jsonl (one JSON per line) if it exists.

Output format

{
  "vendor": "Company Name",
  "invoice_number": "INV-2025-001",
  "date": "2025-01-15",
  "total": 1250.00,
  "currency": "USD",
  "line_items": []
}

Validation rules

See VALIDATION.md for complete rules.