Skip to main content
POST
/
api
/
v1
/
runtime
/
v1
/
vectors
/
documents
Add Document
curl --request POST \
  --url https://api.runflow.ai/api/v1/runtime/v1/vectors/documents \
  --header 'Content-Type: application/json' \
  --data '
{
  "vectorStore": "<string>",
  "content": "<string>",
  "metadata": {}
}
'

Documentation Index

Fetch the complete documentation index at: https://docs.runflow.ai/llms.txt

Use this file to discover all available pages before exploring further.

Body

application/json
​
vectorStore
string
required

Vector store name

​
content
string
required

Document content

​
metadata
object

Document metadata

Response

{ success, documentId, vectorStore, message } on success.