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POST
/
v1
/
boards
/
{boardId}
/
documents
/
vectorize
curl -X POST "https://api.chatgrid.ai/v1/boards/a1b2c3d4-e5f6-7890-abcd-ef1234567890/documents/vectorize" \
  -H "Authorization: Bearer cgk_live_a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "The quarterly revenue report shows a 15% increase in SaaS subscriptions.\n\nCustomer retention improved to 94% in Q1, up from 91% in Q4.\n\nNew enterprise deals accounted for $2.3M in recurring revenue.",
    "node_id": "e5f6a7b8-c9d0-1234-efab-345678901234",
    "metadata": { "source": "annual-report-2026.pdf", "page": 3 }
  }'
{
  "object": "vectorize_result",
  "data": {
    "board_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "node_id": "e5f6a7b8-c9d0-1234-efab-345678901234",
    "chunks_stored": 3
  }
}
boardId
string
required
Board UUID.
content
string
required
The text content to vectorize. 1-100,000 characters. Content is automatically split into chunks on paragraph boundaries (max 1,000 characters per chunk).
node_id
string
Optional node to associate the chunks with, enabling node-scoped search.
metadata
object
Additional metadata stored alongside each chunk. Useful for tracking source documents, page numbers, or custom tags.
Each chunk is embedded using a text embedding model and stored in the board’s vector store. Use the Search endpoint to query the stored vectors.
curl -X POST "https://api.chatgrid.ai/v1/boards/a1b2c3d4-e5f6-7890-abcd-ef1234567890/documents/vectorize" \
  -H "Authorization: Bearer cgk_live_a1b2c3d4e5f6g7h8i9j0k1l2m3n4o5p6" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "The quarterly revenue report shows a 15% increase in SaaS subscriptions.\n\nCustomer retention improved to 94% in Q1, up from 91% in Q4.\n\nNew enterprise deals accounted for $2.3M in recurring revenue.",
    "node_id": "e5f6a7b8-c9d0-1234-efab-345678901234",
    "metadata": { "source": "annual-report-2026.pdf", "page": 3 }
  }'
{
  "object": "vectorize_result",
  "data": {
    "board_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "node_id": "e5f6a7b8-c9d0-1234-efab-345678901234",
    "chunks_stored": 3
  }
}