Pinecone | Documentation

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

Query
Upsert

#Release Stage

Alpha

#Configuration

The component definition and tasks are defined in the definition.json and tasks.json files respectively.

#Setup

In order to communicate with Pinecone, the following connection details need to be provided. You may specify them directly in a pipeline recipe as key-value pairs within the component's setup block, or you can create a Connection from the Integration Settings page and reference the whole setup as setup: ${connection.<my-connection-id>}.

Field	Field ID	Type	Note
API Key (required)	`api-key`	string	Fill in your Pinecone AI API key. You can create an api key in Pinecone Console.
Pinecone Base URL (required)	`url`	string	Fill in your Pinecone base URL. It is in the form.

#Supported Tasks

#Query

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

Input	ID	Type	Description
Task ID (required)	`task`	string	`TASK_QUERY`
ID	`id`	string	The unique ID of the vector to be used as a query vector. If present, the vector parameter will be ignored.
Vector (required)	`vector`	array[number]	An array of dimensions for the query vector.
Top K (required)	`top-k`	integer	The number of results to return for each query.
Namespace	`namespace`	string	The namespace to query.
Filter	`filter`	object	The filter to apply. You can use vector metadata to limit your search. See more details here.
Minimum Score	`min-score`	number	Exclude results whose score is below this value.
Include Metadata	`include-metadata`	boolean	Indicates whether metadata is included in the response as well as the IDs.
Include Values	`include-values`	boolean	Indicates whether vector values are included in the response.

Output	ID	Type	Description
Namespace	`namespace`	string	The namespace of the query.
Matches	`matches`	array[object]	The matches returned for the query.

Output Objects in Query

Matches

Field	Field ID	Type	Note
ID	`id`	string	The ID of the matched vector.
Metadata	`metadata`	object	Metadata.
Score	`score`	number	A measure of similarity between this vector and the query vector. The higher the score, the more similar they are.
Values	`values`	array	Vector data values.

#Upsert

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

Input	ID	Type	Description
Task ID (required)	`task`	string	`TASK_UPSERT`
ID (required)	`id`	string	This is the vector's unique id.
Values (required)	`values`	array[number]	An array of dimensions for the vector to be saved.
Namespace	`namespace`	string	The namespace to query.
Metadata	`metadata`	object	The vector metadata.

Output	ID	Type	Description
Upserted Count	`upserted-count`	integer	Number of records modified or added.