Search a collection with near-vector
Performs a similarity search over the objects of a collection, anchored at a vector supplied by the caller: the query vector is searched against the vector index and the closest objects are returned, each as an envelope of its id, the selected properties, the selected references and, when requested, its retrieval metadata. No query is vectorized, so collections without a vectorizer module are fully searchable. The query vector must have the dimensionality of the vector space it is searched against, that is of the collection's (target) vector. A vector of the wrong dimensionality is rejected with 422 by uncompressed HNSW and flat indexes; a BQ- or RQ-compressed HNSW index does not detect it and yields an empty result set instead.
Request
- Base URL: https://localhost:8080/v1
- URL: https://localhost:8080/v1/search/{collection}/near-vector
- Auth: one of:
- none
- OAuth 2 (implicit, authorization URL http://to-be-configured-in-the-application-config)
Path parameters
The name (or alias) of the collection to search. A lowercase first letter is normalized to the canonical uppercase form.
Request body
Example request
{
"where": {
"operator": "GreaterThanEqual",
"path": [
"inCity",
"city",
"name"
],
"valueInt": 2000,
"valueNumber": 3.14,
"valueString": "my search term",
"valueText": "my search term",
"valueDate": "TODO",
"valueNumberArray": [
3.14
],
"valueBooleanArray": [
true,
false
],
"valueStringArray": [
"my search term"
],
"valueTextArray": [
"my search term"
]
}
}Response
Search performed successfully.
Changes
No recorded changes to this operation across all 1 revision of this API.