Resumable Query
Start with Data
Perform queries using text data that can be resumed to fetch additional results.
POST
Request
string
required
The text data to be embedded and used for querying.
number
default:"10"
The total number of the vectors that you want to receive as a query result.
The response will be sorted based on the distance metric score, and at most
topK many vectors will be returned.boolean
default:"false"
Whether to include the metadata of the vectors in the response, if any. It is
recommended to set this to
true to easily identify vectors.boolean
default:"false"
Whether to include the vector values in the response. It is recommended to set
this to
false as the vector values can be quite big, and not needed most of
the time.boolean
default:"false"
Whether to include the data of the vectors in the response, if any.
string
default:""
Metadata filter to apply.
number
Maximum idle time for the resumable query in seconds.
string
For sparse vectors of sparse and hybrid indexes, specifies what kind of
weighting strategy should be used while querying the matching non-zero
dimension values of the query vector with the documents.If not provided, no weighting will be used.Only possible value is
IDF (inverse document frequency).string
Fusion algorithm to use while fusing scores
from dense and sparse components of a hybrid index.If not provided, defaults to
RRF (Reciprocal Rank Fusion).Other possible value is DBSF (Distribution-Based Score Fusion).string
Query mode for hybrid indexes with Upstash-hosted
embedding models.Specifies whether to run the query in only the
dense index, only the sparse index, or in both.If not provided, defaults to
HYBRID.Possible values are HYBRID, DENSE, and SPARSE.Path
string
default:""
The namespace to use. When no namespace is specified, the default namespace
will be used.