# README
title: "Pinecone" lang: "en-US" draft: false description: "Learn about how to set up a VDP Pinecone component https://github.com/instill-ai/instill-core"
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
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 |