Deletes a document and its chunks from the knowledge base.
Removes the document and every chunk produced from it from the asset's vector and full-text indices. The next search against the asset will no longer surface this content. The original source is untouched, so a subsequent `POST /assets/{asset}:refresh` (without a `documentIds` filter) will re-ingest the document. Idempotent at the API surface: deleting an already-removed document returns 404.
Authorization
Bearer JWT Authorization header using the Bearer scheme. Enter 'Bearer' [space] and then your token.
In: header
Path Parameters
The asset ID.
uuidThe document ID.
uuidThe tenant identifier
Response Body
curl -X DELETE "https://api.fruxon.com/v1/tenants/string/assets/497f6eca-6276-4993-bfeb-53cbbbba6f08/documents/497f6eca-6276-4993-bfeb-53cbbbba6f08"{
"type": "string",
"title": "string",
"status": 0,
"detail": "string",
"instance": "string",
"property1": null,
"property2": null
}Lists chunks for a document using cursor-based pagination.
Returns the ordered chunks produced by the ingestion pipeline — the indivisible units that searches return and that the embedding model encoded. Chunk size and overlap are determined by the asset's embedding configuration, not by this call. Primarily used to inspect what the model actually sees for a given document when debugging poor search relevance or unexpected agent answers.
Lists supported embedding models.
Returns the embedding models that the RAG service currently accepts for new assets, including their vector dimensions and pricing identifiers. Pair the chosen model with an asset's `embeddingConfig` when calling `POST /assets` or `POST /assets:file`. The list is tenant-agnostic and rarely changes; clients may cache it for the duration of a session.