Search points

POST

Retrieves the closest points based on vector similarity and given filtering conditions.

Path parameters

collection_namestringRequired

Name of the collection to search in

Query parameters

consistencyinteger or enumOptional

Define read consistency guarantees for the operation

timeoutintegerOptional

If set, overrides global timeout for this request. Unit is seconds.

Request

This endpoint expects an object.

vectorlist of doubles or objectRequired

Vector data separator for named and unnamed modes Unnamed mode:

{ “vector”: [1.0, 2.0, 3.0] }

or named mode:

{ “vector”: { “vector”: [1.0, 2.0, 3.0], “name”: “image-embeddings” } }

limitintegerRequired>=1

Max number of result to return

shard_keystring or uint64 or list of strings or uint64s or anyOptional

Specify in which shards to look for the points, if not specified - look in all shards

filterobject or anyOptional

Look only for points which satisfies this conditions

paramsobject or anyOptional

Additional search params

offsetintegerOptional>=0

Offset of the first result to return. May be used to paginate results. Note: large offset values may cause performance issues.

with_payloadboolean or list of strings or object or anyOptional

Select which payload to return with the response. Default is false.

with_vectorboolean or list of strings or anyOptional

Options for specifying which vectors to include into response. Default is false.

score_thresholddoubleOptional

Define a minimal score threshold for the result. If defined, less similar results will not be returned. Score of the returned result might be higher or smaller than the threshold depending on the Distance function used. E.g. for cosine similarity only higher scores will be returned.

Response

successful operation

timedoubleOptional

Time spent to process this request

statusstringOptional

resultlist of objectsOptional

POST

1 curl  -X POST \
2   'http://localhost:6333/collections/collection_name/points/search' \
3   --header 'api-key: <api-key-value>' \
4   --header 'Content-Type: application/json' \
5   --data-raw '{
6   "vector": [
7     0.2,
8     0.1,
9     0.9,
10     0.7
11   ],
12   "limit": 1,
13   "filter": {
14     "must": [
15       {
16         "key": "city",
17         "match": {
18           "value": "London"
19         }
20       }
21     ]
22   }
23 }'

200Successful

1 {
2   "time": 0.002,
3   "status": "ok",
4   "result": [
5     {
6       "id": 42,
7       "version": 3,
8       "score": 0.75,
9       "payload": {
10         "city": "London",
11         "color": "green"
12       },
13       "vector": [
14         0.875,
15         0.140625,
16         0.897599995136261
17       ],
18       "shard_key": "region_1",
19       "order_value": 42
20     }
21   ]
22 }

Search batch points

Up Next

Built with

1	curl -X POST \
2	'http://localhost:6333/collections/collection_name/points/search' \
3	--header 'api-key: <api-key-value>' \
4	--header 'Content-Type: application/json' \
5	--data-raw '{
6	"vector": [
7	0.2,
8	0.1,
9	0.9,
10	0.7
11	],
12	"limit": 1,
13	"filter": {
14	"must": [
15	{
16	"key": "city",
17	"match": {
18	"value": "London"
19	}
20	}
21	]
22	}
23	}'

1	{
2	"time": 0.002,
3	"status": "ok",
4	"result": [
5	{
6	"id": 42,
7	"version": 3,
8	"score": 0.75,
9	"payload": {
10	"city": "London",
11	"color": "green"
12	},
13	"vector": [
14	0.875,
15	0.140625,
16	0.897599995136261
17	],
18	"shard_key": "region_1",
19	"order_value": 42
20	}
21	]
22	}