Anonimizar PDF con entrada base64
Anonimice un archivo PDF detectando y redactando PII (Información de Identificación Personal). Acepta PDF como cadena codificada en base64 en el cuerpo de la solicitud. Devuelve PDF anonimizado, entidades PII detectadas y métricas de procesamiento. Admite múltiples idiomas OCR, detección de texto rotado y detección personalizable de etiquetas PII. Solo procesa la primera página del PDF.
In: header
Request Body
application/json
Base64-encoded PDF document to be processed
List of predefined PII tags to detect and redact. If empty, all available tags are used. Available values: DATE, PERSON_NAME, ORGANIZATION, LOCATION, EMAIL, PHONE, ID, ACCOUNT, ZIP_CODE, ADDRESS, IP, URL, SSN, DRIVER_LICENSE, PASSPORT, PASSWORD, AGE, CREDIT_CARD, MONEY_AMOUNT, SIGNATURE, QR_CODE, FACE
Force OCR processing even if text is extractable from PDF
falseList of OCR languages to use for text recognition. Multiple languages can be specified for multilingual documents Available values: eng, spa, fra, deu, ita, por, rus
["eng"]Enable detection and recognition of rotated text in the document
falseEnable text redaction using NER. When enabled, detected PII entities are redacted (blacked out) in the output PDF
trueMinimum chunk size for text processing. Used to control text segmentation for NER processing. Larger values may improve accuracy but increase processing time
0List of custom tags to detect and redact. These tags are added to the standard PII tags
Response Body
application/json
application/json
application/json
application/json
application/json
application/json
application/json
curl -X POST "https://api.pdf-redaction.com/api/anonymize/pdf" \ -H "Content-Type: application/json" \ -d '{ "force_ocr": true, "pdf": "base64_encoded_pdf_string" }'{
"pdf": "base64_encoded_pdf_string",
"detected_pii": {
"path": "memory",
"entities": [
{
"entity_group": "PERSON_NAME",
"score": 0.95,
"word": "John Doe",
"start": 0,
"end": 8,
"boxes": [
{
"text": "John Doe",
"score": 0.95,
"x": 100,
"y": 200,
"width": 150,
"height": 25
}
]
},
{
"entity_group": "EMAIL",
"score": 0.98,
"word": "[email protected]",
"start": 0,
"end": 20,
"boxes": [
{
"text": "[email protected]",
"score": 0.98,
"x": 100,
"y": 250,
"width": 200,
"height": 25
}
]
}
],
"exception": "",
"json": ""
},
"processing_time": {
"total": 2.9577243328094482,
"stages": {
"PdfDataToSingleImage": 0.5639204978942871,
"PdfDataToDocument": 0.0037207603454589844,
"Ocr": 0.0004279613494873047,
"Ner": 1.7787754535675049,
"ImageDrawBoxes": 0.5246167182922363,
"SingleImageToPdf": 0.08531355857849121
}
}
}{
"error_code": "NER_CALL_ERROR",
"message": "string"
}{
"error_code": "UNAUTHORIZED",
"message": "Invalid token"
}{
"error_code": "FORBIDDEN",
"message": "Missing credentials: provide X-API-Key or Authorization: Bearer token"
}{
"error_code": "PROCESSING_ERROR",
"message": "Failed to process the PDF file"
}{
"detail": [
{
"loc": [
"string"
],
"msg": "string",
"type": "string"
}
]
}{
"error_code": "TOO_MANY_REQUESTS",
"message": "Rate limit exceeded: 5 per 1 minute"
}