extract-document-datalisted

# Extract Document Data Extract structured JSON from documents with per-value grounding: every extracted value cites where it came from (page number, confidence), and values that aren't clearly present are reported in `not_found` rather than hallucinated. Uses the Stipple API (free anonymous tier). ## When to use - Parsing payslips, invoices, bank statements, receipts, or contracts - Converting unstructured documents to JSON for downstream systems - Any extraction where hallucinated values are worse than missing values (lending, accounting, compliance) ## Instructions 1. **Get the document.** URL or local file path (PDF, PNG, JPEG, DOCX). 2. **Choose the extraction mode:** - **Ad-hoc fields** — tell the API exactly which fields you want: ```bash curl -X POST https://www.stipple.sh/v1/extract \ -F "file=@payslip.pdf" \ -F 'fields=[{"name":"employer_name"},{"name":"net_pay"},{"name":"pay_date"}]' \ -H "Authorization: Bearer $STIPPLE_API_KEY" ``` - **Template** — use a built-in schema: `payslip`, `tax_invoice`, `bank_statement`, `receipt`, `contract` - **Schema-free** — omit `fields` and let the model extract what it finds 3. **Interpret the response.** ```json { "mode": "schema_free", "document_type": "payslip", "pages_read": 1, "fields": { "employer_name": {"value": "Acme Cleaning Pty Ltd", "confidence": 0.95, "page": 1}, "net_pay": {"value": "2845.10", "confidence": 0.97, "page": 1}