curl -X POST https://api.60db.ai/memory/documents/extract \
  -H "Authorization: Bearer your-api-key" \
  -F "[email protected]" \
  -F "collection=company_handbook" \
  -F "type=knowledge" \
  -F "title=Q4 2026 Report"

const form = new FormData();
form.append('file', pdfFile);
form.append('collection', 'company_handbook');
form.append('type', 'knowledge');
form.append('title', 'Q4 2026 Report');

const response = await fetch('https://api.60db.ai/memory/documents/extract', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer your-api-key',
  },
  body: form,
});
const { success, data } = await response.json();
console.log(`Ingested ${data.chunks} chunks from ${data.filename}`);

import requests

with open('quarterly-report.pdf', 'rb') as f:
    response = requests.post(
        'https://api.60db.ai/memory/documents/extract',
        headers={'Authorization': 'Bearer your-api-key'},
        files={'file': ('quarterly-report.pdf', f, 'application/pdf')},
        data={
            'collection': 'company_handbook',
            'type': 'knowledge',
            'title': 'Q4 2026 Report',
        },
    )

result = response.json()
print(f"Ingested {result['data']['chunks']} chunks")

{
  "success": true,
  "data": {
    "collection_id": "company_handbook",
    "collection_label": "Company Handbook",
    "filename": "quarterly-report.pdf",
    "chunks": 18,
    "characters": 24680,
    "memory_type": "knowledge",
    "total_queued": 18,
    "results": [
      { "id": "mem_01HV8K...", "status": "pending", "message": "Queued for processing" },
      { "id": "mem_01HV8L...", "status": "pending", "message": "Queued for processing" }
    ],
    "metadata": {
      "source": "document_upload",
      "filename": "quarterly-report.pdf",
      "mime_type": "application/pdf",
      "page_count": 24,
      "detected_languages": ["eng"],
      "total_chunks": 18
    }
  }
}