ballerinax/pinecone.vector Ballerina library

Overview

This is a generated connector for the Vector Operations under Pinecone Vector Database API OpenAPI specification. Pinecone is a fully managed vector database, which allows storing data objects and vector embeddings from the ML models, including the LLMs offered by OpenAI, Hugging Face, and Cohere. The Pinecone vector database makes it easy to build developer-friendly, easily scalable, and high-performance vector search applications without infrastructure hassles.

Key Features

• Programmatic access to create and manage resources via REST API
• Send and publish data through the API
• Secure authentication with API key or OAuth support

Prerequisites

Before using this connector in your Ballerina application, complete the following:

1. Sign up and log in to Pinecone.
2. Create a new project and specify an environment.
3. Click on API Keys and create an API key.

Quick start

To use the Pinecone.vector connector in your Ballerina application, update the .bal file as follows:

Step 1: Import the connector

First, import the ballerinax/pinecone.vector module into the Ballerina project.

import ballerinax/pinecone.vector;

Step 2: Create a new connector instance

Create and initialize a vector:Client with your Service URL and the obtained Authentication key.

vector:Client pineconeVectorClient = check new ({
    apiKey: "XXXXX"
}, serviceUrl = "https://<index_name>-<project_name>.svc.<environment>.pinecone.io");

Step 3: Invoke the connector operation

1. Now, you can use the operations available within the connector. You can describe the statistics of your index as follows.

   vector:DescribeIndexStatsResponse indexStats = check pineconeVectorClient->/describe_index_stats.post({});

2. Use the bal run command to compile and run the Ballerina program.