Pinecone Node.js Client

This is the Node.js client for Pinecone, written in Typescript. It is a wrapper around the Pinecone OpenAPI spec.

⚠️ Warning

This is a public preview ("Beta") client. Test thoroughly before using this client for production workloads. No SLAs or technical support commitments are provided for this client. Expect potential breaking changes in future releases.

Installation

npm i @pinecone-database/pinecone

Usage

Set the following environment variables:

PINECONE_API_KEY=your_api_key
PINECONE_ENVIRONMENT=your_environment

Initializing the client

import{PineconeClient}from"@pinecone-database/pinecone";// Create a clientconstclient=newPineconeClient();// Initialize the clientawaitclient.init({apiKey: process.env.PINECONE_API_KEY,environment: process.env.PINECONE_ENVIRONMENT,});

Control plane operations

The Pinecone control plane allows you to perform the following operations:

1. Create, configure and delete indexes
2. Get information about an existing indexes
3. Create and delete collections
4. Select an index to operate on

Indexes

Create Index

constcreateRequest: CreateRequest={name: indexName,dimension: dimensions,
metric,};awaitclient.createIndex({ createRequest });

Delete Index

awaitclient.deleteIndex({ indexName });

Describe Index

constindexDescription=awaitclient.describeIndex({ indexName });

Example result:

{
"database": {
"name": "my-index",
"metric": "cosine",
"dimension": 10,
"replicas": 1,
"shards": 1,
"pods": 1,
"pod_type": "p1.x1"
},
"status": {
"waiting": [],
"crashed": [],
"host": "my-index-[project-id].svc.[environment].pinecone.io",
"port": 433,
"state": "Ready",
"ready": true
}
}

List Indexes

constlist=awaitclient.listIndexes();

Example result:

["index1", "index2"]

Select an index

To operate on an index, you must select it. This is done by calling the Index method on the client.

constindex=client.Index(indexName);

Collections

Create Collection

constcreateCollectionRequest: CreateCollectionRequest={name: collection,source: indexName,};awaitclient.createCollection({ createCollectionRequest });

Delete Collection

awaitclient.deleteCollection(collection);

Describe Collection

constdescribeCollection=awaitclient.describeCollection({ collectionName });

Example result:

{
"name": "my-collection",
"status": "Ready",
"size": 3059815,
"dimension": 10
}

List Collections

constlist=awaitclient.listCollections();

Example result:

["collection1", "collection2"]

Index operations

The Pinecone index operations allow you to perform the following operations instances of Vector.

A Vector is defined as follows:

typeVector={id: string;values: number[];metadata?: object;sparseValues: {indices: [15,30,11];values: [0.1,0.2,0.3];};// optional sparse values};

After selecting an index to operate on, you can:

Upsert vectors

constupsertRequest: UpsertRequest={
vectors,
namespace,};awaitindex.upsert({ upsertRequest });

Query vectors

constvector=[...]// a vectorconstqueryRequest: QueryRequest={topK: 1,
vector,
namespace,includeMetadata: true,includeValues: true,}

To query with a sparse vector:

constqueryRequest: QueryRequest={topK: 1,
vector,
namespace,includeMetadata: true,includeValues: true,sparseVector: {indices: [15,30,11],values: [0.1,0.2,0.3],},};

To execute the query:

constqueryResponse=awaitindex.query({ queryRequest });

Update a vector

constupdateRequest: UpdateRequest={id: vectorId,// the ID of the vector to updatevalues: [0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0],// the new vector valuessparseValues: {indices: [15,30,11],values: [0.1,0.2,0.3],},// optional sparse valuessetMetadata: metadata,// the new metadata
namespace,};awaitindex.update({ updateRequest });

Fetch vectors by their IDs

constfetchResult=awaitindex.fetch({ids: [vectorIDs],
namespace,});

Delete vectors

awaitindex.delete1({ids: [vectorIDs],
namespace,});

Delete all vectors in a namespace

awaitindex.delete1({deleteAll: true,
namespace,});