@pinecone-database/pinecone

What is @pinecone-database/pinecone?

@pinecone-database/pinecone is an npm package that provides a client for interacting with the Pinecone vector database. Pinecone is designed for high-performance vector similarity search, making it useful for applications like recommendation systems, semantic search, and machine learning model deployment.

What are @pinecone-database/pinecone's main functionalities?

Initialize Pinecone Client

This code initializes the Pinecone client with the provided API key and environment. Initialization is the first step to interact with the Pinecone database.

const { PineconeClient } = require('@pinecone-database/pinecone');
const client = new PineconeClient();
client.init({ apiKey: 'your-api-key', environment: 'us-west1-gcp' });

Create Index

This code demonstrates how to create a new index in Pinecone. An index is a collection of vectors that you can query against.

const createIndex = async () => {
  await client.createIndex({
    name: 'example-index',
    dimension: 128
  });
};
createIndex();

Insert Vectors

This code inserts vectors into an existing index. Each vector has an ID and a list of values representing its coordinates in the vector space.

const insertVectors = async () => {
  await client.upsert({
    indexName: 'example-index',
    vectors: [
      { id: 'vec1', values: [0.1, 0.2, 0.3] },
      { id: 'vec2', values: [0.4, 0.5, 0.6] }
    ]
  });
};
insertVectors();

Query Vectors

This code queries the index for the top K most similar vectors to the provided query vector. The result contains the IDs and similarity scores of the closest vectors.

const queryVectors = async () => {
  const result = await client.query({
    indexName: 'example-index',
    topK: 2,
    vector: [0.1, 0.2, 0.3]
  });
  console.log(result);
};
queryVectors();

Delete Index

This code deletes an existing index from Pinecone. This is useful for cleanup or when the index is no longer needed.

const deleteIndex = async () => {
  await client.deleteIndex({
    name: 'example-index'
  });
};
deleteIndex();

Other packages similar to @pinecone-database/pinecone

faiss

Faiss is a library developed by Facebook AI Research for efficient similarity search and clustering of dense vectors. It is highly optimized for performance and can handle large-scale datasets. Unlike Pinecone, Faiss is more of a low-level library and requires more setup and management.

annoy

Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings for performing fast approximate nearest neighbor searches. It is particularly useful for read-heavy workloads and is easy to use. However, it lacks some of the advanced features and scalability options provided by Pinecone.

milvus

Milvus is an open-source vector database designed for scalable similarity search and AI applications. It supports various indexing methods and is highly scalable. Milvus offers more flexibility and control over the indexing and querying process compared to Pinecone.

README

The README file is missing