ApiVector database
Upsert text (integrated embedding)
Embed and upsert records server-side. Requires an integrated-embedding index.
Embed and upsert records server-side. Requires an integrated-embedding index.
Authorization
TokenAuth Authorization<token>
Project API key as Token lb-sk_...
In: header
Path Parameters
name*string
Request Body
application/json
TypeScript Definitions
Use the request body type in TypeScript.
Response Body
application/json
curl -X POST "https://example.com/v1/indexes/string/upsert-text" \ -H "Content-Type: application/json" \ -d '{ "records": [ { "_id": "d1", "text": "The Eiffel Tower is in Paris." } ] }'{ "upserted_count": 0}Query an index POST POST
Query by a raw `vector`, by `text` (integrated-embedding indexes), or by an existing vector `id`. On hybrid indexes a text query defaults to `mode: hybrid` — the dense ANN leg and the sparse full-text leg run concurrently and are fused with Reciprocal Rank Fusion (the fused `score` is an RRF score, not a cosine similarity). One hybrid query meters as a single vector read.
Upsert vectors POST POST
Next Page