Search batch points | Qdrant

1 from qdrant_client import QdrantClient, models 2 3 client = QdrantClient(url="http://localhost:6333") 4 5 filter_ = models.Filter( 6 must=[ 7 models.FieldCondition( 8 key="city", 9 match=models.MatchValue( 10 value="London", 11 ), 12 ) 13 ] 14 ) 15 16 search_queries = [ 17 models.SearchRequest(vector=[0.2, 0.1, 0.9, 0.7], filter=filter_, limit=3), 18 models.SearchRequest(vector=[0.5, 0.3, 0.2, 0.3], filter=filter_, limit=3), 19 ] 20 21 client.search_batch(collection_name="{collection_name}", requests=search_queries)

1 { 2 "usage": { 3 "cpu": 1, 4 "payload_io_read": 1, 5 "payload_io_write": 1, 6 "payload_index_io_read": 1, 7 "payload_index_io_write": 1, 8 "vector_io_read": 1, 9 "vector_io_write": 1 10 }, 11 "time": 0.002, 12 "status": "ok", 13 "result": [ 14 [ 15 { 16 "id": 42, 17 "version": 3, 18 "score": 0.75, 19 "payload": {}, 20 "vector": {}, 21 "shard_key": "region_1", 22 "order_value": 42 23 } 24 ] 25 ] 26 }

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

Authentication

api-keystring

API Key authentication via header

Path parameters

collection_namestringRequired

Name of the collection to search in

Query parameters

consistencyinteger or enumOptional

Define read consistency guarantees for the operation

timeoutintegerOptional>=1

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

Request

Search batch request

searcheslist of objectsRequired

Response

successful operation

usageobject or any or null

timedouble or null

Time spent to process this request

statusstring or null

resultlist of lists of objects or null