@mastra/pinecone

Vector store implementation for Pinecone, using the official @pinecone-database/pinecone SDK with added telemetry support.

Installation

pnpm add @mastra/pinecone

Usage

import { PineconeVector } from '@mastra/pinecone';

const vectorStore = new PineconeVector(
  'your-api-key',
  'optional-environment-url'
);

// Create a new index
await vectorStore.createIndex({ indexName: 'my-index', dimension: 1536, metric: 'cosine' });

// Add vectors
const vectors = [[0.1, 0.2, ...], [0.3, 0.4, ...]];
const metadata = [{ text: 'doc1' }, { text: 'doc2' }];
const ids = await vectorStore.upsert({ indexName: 'my-index', vectors, metadata });

// Query vectors
const results = await vectorStore.query({
  indexName: 'my-index',
  queryVector: [0.1, 0.2, ...],
  topK: 10, // topK
  filter: { text: { $eq: 'doc1' } }, // optional filter
  includeVector: false, // includeValues
});

Configuration

Required:

• apiKey: Your Pinecone API key

Optional:

• environment: Your Pinecone environment URL (controller host URL)

Features

• Serverless deployment on AWS (us-east-1)
• Vector similarity search with cosine, euclidean, and dot product metrics
• Automatic batching for large upserts (100 vectors per request)
• Built-in telemetry support
• Metadata filtering
• Optional vector inclusion in query results
• Automatic UUID generation for vectors
• Built on top of @pinecone-database/pinecone SDK

Methods

• createIndex({indexName, dimension, metric?}): Create a new index
• upsert({indexName, vectors, metadata?, ids?}): Add or update vectors
• query({indexName, queryVector, topK?, filter?, includeVector?}): Search for similar vectors
• listIndexes(): List all indexes
• describeIndex(indexName): Get index statistics
• deleteIndex(indexName): Delete an index

Related Links

• Pinecone Documentation
• Pinecone Node.js SDK