Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Extract structured fields from w-4 documents.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Tax and finance teams use this recipe to extract W-4 fields from official forms into structured JSON for review, routing, and downstream filing preparation.
Document Extraction (1 credit per page)
You need an Iteration Layer API key. Get one at platform.iterationlayer.com during the 7-day trial.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
curl -X POST https://api.iterationlayer.com/document-extraction/v1/extract \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"files": [
{
"type": "url",
"name": "w-4.pdf",
"url": "https://example.com/documents/w-4-sample.pdf"
}
],
"schema": {
"fields": [
{
"name": "employee_name",
"type": "TEXT",
"description": "Employee full name"
},
{
"name": "social_security_number",
"type": "TEXT",
"description": "Employee Social Security number"
},
{
"name": "address",
"type": "ADDRESS",
"description": "Employee address"
},
{
"name": "filing_status",
"type": "TEXT",
"description": "Selected filing status"
},
{
"name": "dependents_amount",
"type": "CURRENCY_AMOUNT",
"description": "Step 3 dependent and other credits amount"
},
{
"name": "other_income",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(a) other income"
},
{
"name": "deductions",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(b) deductions"
},
{
"name": "extra_withholding",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(c) extra withholding"
},
{
"name": "is_signed",
"type": "BOOLEAN",
"description": "Whether the employee signature is present"
},
{
"name": "signature_date",
"type": "DATE",
"description": "Date signed"
}
]
}
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
const result = await client.extractDocument({
"files": [
{
"type": "url",
"name": "w-4.pdf",
"url": "https://example.com/documents/w-4-sample.pdf"
}
],
"schema": {
"fields": [
{
"name": "employee_name",
"type": "TEXT",
"description": "Employee full name"
},
{
"name": "social_security_number",
"type": "TEXT",
"description": "Employee Social Security number"
},
{
"name": "address",
"type": "ADDRESS",
"description": "Employee address"
},
{
"name": "filing_status",
"type": "TEXT",
"description": "Selected filing status"
},
{
"name": "dependents_amount",
"type": "CURRENCY_AMOUNT",
"description": "Step 3 dependent and other credits amount"
},
{
"name": "other_income",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(a) other income"
},
{
"name": "deductions",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(b) deductions"
},
{
"name": "extra_withholding",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(c) extra withholding"
},
{
"name": "is_signed",
"type": "BOOLEAN",
"description": "Whether the employee signature is present"
},
{
"name": "signature_date",
"type": "DATE",
"description": "Date signed"
}
]
}
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
result = client.extract_document(**{
"files": [
{
"type": "url",
"name": "w-4.pdf",
"url": "https://example.com/documents/w-4-sample.pdf"
}
],
"schema": {
"fields": [
{
"name": "employee_name",
"type": "TEXT",
"description": "Employee full name"
},
{
"name": "social_security_number",
"type": "TEXT",
"description": "Employee Social Security number"
},
{
"name": "address",
"type": "ADDRESS",
"description": "Employee address"
},
{
"name": "filing_status",
"type": "TEXT",
"description": "Selected filing status"
},
{
"name": "dependents_amount",
"type": "CURRENCY_AMOUNT",
"description": "Step 3 dependent and other credits amount"
},
{
"name": "other_income",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(a) other income"
},
{
"name": "deductions",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(b) deductions"
},
{
"name": "extra_withholding",
"type": "CURRENCY_AMOUNT",
"description": "Step 4(c) extra withholding"
},
{
"name": "is_signed",
"type": "BOOLEAN",
"description": "Whether the employee signature is present"
},
{
"name": "signature_date",
"type": "DATE",
"description": "Date signed"
}
]
}
})
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
result, err := client.ExtractDocument(il.ExtractDocumentRequest{
Files: []il.FileInput{
il.FileInput{
Type: "url",
Name: "w-4.pdf",
Url: "https://example.com/documents/w-4-sample.pdf",
},
},
Schema: il.ExtractionSchema{
Fields: []any{
il.TextFieldConfig{
Name: "employee_name",
Type: "TEXT",
Description: "Employee full name",
},
il.TextFieldConfig{
Name: "social_security_number",
Type: "TEXT",
Description: "Employee Social Security number",
},
il.AddressFieldConfig{
Name: "address",
Type: "ADDRESS",
Description: "Employee address",
},
il.TextFieldConfig{
Name: "filing_status",
Type: "TEXT",
Description: "Selected filing status",
},
il.CurrencyAmountFieldConfig{
Name: "dependents_amount",
Type: "CURRENCY_AMOUNT",
Description: "Step 3 dependent and other credits amount",
},
il.CurrencyAmountFieldConfig{
Name: "other_income",
Type: "CURRENCY_AMOUNT",
Description: "Step 4(a) other income",
},
il.CurrencyAmountFieldConfig{
Name: "deductions",
Type: "CURRENCY_AMOUNT",
Description: "Step 4(b) deductions",
},
il.CurrencyAmountFieldConfig{
Name: "extra_withholding",
Type: "CURRENCY_AMOUNT",
Description: "Step 4(c) extra withholding",
},
il.BooleanFieldConfig{
Name: "is_signed",
Type: "BOOLEAN",
Description: "Whether the employee signature is present",
},
il.DateFieldConfig{
Name: "signature_date",
Type: "DATE",
Description: "Date signed",
},
},
},
})
if err != nil {
panic(err)
}
_ = result
}
{
"name": "Extract W-4 Data",
"nodes": [
{
"parameters": {
"content": "## Extract W-4 Data\n\nTax and finance teams use this recipe to extract W-4 fields from official forms into structured JSON for review, routing, and downstream filing preparation.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes on self-hosted n8n, or add it directly on n8n Cloud with Verified Community Nodes enabled.",
"height": 280,
"width": 500,
"color": 2
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
200,
40
],
"id": "extract-w-4-data-overview",
"name": "Overview"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "extract-w-4-data-trigger",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "documentExtraction",
"schemaInputMode": "rawJson",
"schemaJson": "{\n \"fields\": [\n {\n \"name\": \"employee_name\",\n \"type\": \"TEXT\",\n \"description\": \"Employee full name\"\n },\n {\n \"name\": \"social_security_number\",\n \"type\": \"TEXT\",\n \"description\": \"Employee Social Security number\"\n },\n {\n \"name\": \"address\",\n \"type\": \"ADDRESS\",\n \"description\": \"Employee address\"\n },\n {\n \"name\": \"filing_status\",\n \"type\": \"TEXT\",\n \"description\": \"Selected filing status\"\n },\n {\n \"name\": \"dependents_amount\",\n \"type\": \"CURRENCY_AMOUNT\",\n \"description\": \"Step 3 dependent and other credits amount\"\n },\n {\n \"name\": \"other_income\",\n \"type\": \"CURRENCY_AMOUNT\",\n \"description\": \"Step 4(a) other income\"\n },\n {\n \"name\": \"deductions\",\n \"type\": \"CURRENCY_AMOUNT\",\n \"description\": \"Step 4(b) deductions\"\n },\n {\n \"name\": \"extra_withholding\",\n \"type\": \"CURRENCY_AMOUNT\",\n \"description\": \"Step 4(c) extra withholding\"\n },\n {\n \"name\": \"is_signed\",\n \"type\": \"BOOLEAN\",\n \"description\": \"Whether the employee signature is present\"\n },\n {\n \"name\": \"signature_date\",\n \"type\": \"DATE\",\n \"description\": \"Date signed\"\n }\n ]\n}",
"files": {
"fileValues": [
{
"fileInputMode": "url",
"fileName": "w-4.pdf",
"fileUrl": "https://example.com/documents/w-4-sample.pdf"
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "extract-w-4-data-extract",
"name": "Extract Data",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Extract Data",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
Extract w-4 data from the file at [file URL]. Use the extract_document tool with these fields:
- employee_name (TEXT): Employee full name
- social_security_number (TEXT): Employee Social Security number
- address (ADDRESS): Employee address
- filing_status (TEXT): Selected filing status
- dependents_amount (CURRENCY_AMOUNT): Step 3 dependent and other credits amount
- other_income (CURRENCY_AMOUNT): Step 4(a) other income
- deductions (CURRENCY_AMOUNT): Step 4(b) deductions
- extra_withholding (CURRENCY_AMOUNT): Step 4(c) extra withholding
- is_signed (BOOLEAN): Whether the employee signature is present
- signature_date (DATE): Date signed
{
"success": true,
"data": {
"employee_name": {
"value": "Employee Name",
"confidence": 0.97,
"citations": [
"EMPLOYEE NAME"
]
},
"social_security_number": {
"value": "Social Security Number",
"confidence": 0.97,
"citations": [
"SOCIAL SECURITY NUMBER"
]
},
"address": {
"value": {
"street": "100 Market Street",
"city": "Berlin",
"postal_code": "10115",
"country": "DE"
},
"confidence": 0.97,
"citations": [
"ADDRESS"
]
},
"filing_status": {
"value": "Filing Status",
"confidence": 0.97,
"citations": [
"FILING STATUS"
]
},
"dependents_amount": {
"value": {
"amount": "1234.56",
"currency": "USD"
},
"confidence": 0.97,
"citations": [
"$1,234.56"
]
},
"other_income": {
"value": {
"amount": "1234.56",
"currency": "USD"
},
"confidence": 0.97,
"citations": [
"$1,234.56"
]
},
"deductions": {
"value": {
"amount": "1234.56",
"currency": "USD"
},
"confidence": 0.97,
"citations": [
"$1,234.56"
]
},
"extra_withholding": {
"value": {
"amount": "1234.56",
"currency": "USD"
},
"confidence": 0.97,
"citations": [
"$1,234.56"
]
},
"is_signed": {
"value": true,
"confidence": 0.97,
"citations": [
"IS SIGNED"
]
},
"signature_date": {
"value": "2026-04-15",
"confidence": 0.97,
"citations": [
"15 Apr 2026"
]
}
}
}
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Compress an image to fit within a specific file size in bytes using quality-first compression.
日本語の概要は準備中です。原文の説明を表示しています。
Convert a contract PDF to clean markdown for clause extraction or LLM analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Convert external documents — specs, contracts, reports — to markdown for knowledge base ingestion.
日本語の概要は準備中です。原文の説明を表示しています。
Convert a document to clean markdown suitable for chunking and embedding in a RAG pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Convert an image between PNG, JPEG, and WebP formats with quality control for web optimization.
日本語の概要は準備中です。原文の説明を表示しています。