The Pinecone component is a data component that allows users to build and search vector datasets. It can carry out the following tasks:

#Release Stage



The component configuration is defined and maintained here.


FieldField IDTypeNote
API Key (required)api-keystringFill your Pinecone AI API key. You can create a api key in Pinecone Console
Pinecone Base URL (required)urlstringFill in your Pinecone base URL. It is in the form

#Supported Tasks


Retrieve the ids of the most similar items in a namespace, along with their similarity scores.

Task ID (required)taskstringTASK_QUERY
IDidstringThe unique ID of the vector to be used as a query vector. If present, the vector parameter will be ignored.
Vector (required)vectorarray[number]An array of dimensions for the query vector.
Top K (required)top-kintegerThe number of results to return for each query
NamespacenamespacestringThe namespace to query
FilterfilterobjectThe filter to apply. You can use vector metadata to limit your search. See
Minimum Scoremin-scorenumberExclude results whose score is below this value
Include Metadatainclude-metadatabooleanIndicates whether metadata is included in the response as well as the IDs
Include Valuesinclude-valuesbooleanIndicates whether vector values are included in the response
NamespacenamespacestringThe namespace of the query
Matchesmatchesarray[object]The matches returned for the query


Writes vectors into a namespace. If a new value is upserted for an existing vector id, it will overwrite the previous value.

Task ID (required)taskstringTASK_UPSERT
ID (required)idstringThis is the vector's unique id
Values (required)valuesarray[number]An array of dimensions for the vector to be saved
NamespacenamespacestringThe namespace to query
MetadatametadataobjectThe vector metadata
Upserted Countupserted-countintegerNumber of records modified or added

Last updated: 6/18/2024, 11:35:38 AM