@orka-js/pinecone

Pinecone vector database adapter for OrkaJS — managed cloud vector search.

Installation

npm install @orka-js/pinecone

Quick Start

import { PineconeAdapter } from '@orka-js/pinecone'
import { OpenAIAdapter } from '@orka-js/openai'
import { Orka } from '@orka-js/core'

const vectorDB = new PineconeAdapter({
  apiKey: process.env.PINECONE_API_KEY!,
  environment: 'us-east1-gcp',
  indexName: 'my-index',
})

const orka = new Orka({ llm, vectorDB })

// Ingest documents
await orka.knowledge.ingest([
  { id: 'doc-1', content: 'Hello world', metadata: { source: 'manual' } }
])

// Semantic search
const results = await orka.knowledge.query('hello', 5)

Direct Usage

const adapter = new PineconeAdapter({ apiKey, environment, indexName })

await adapter.createCollection('documents', 1536)
await adapter.upsert('documents', [
  { id: 'doc-1', vector: [...], metadata: { text: 'Hello world' } }
])
const results = await adapter.search('documents', queryVector, 5)
await adapter.delete('documents', ['doc-1'])

Configuration

| Option | Type | Description | |--------|------|-------------| | apiKey | string | Pinecone API key (required) | | environment | string | Pinecone environment, e.g. us-east1-gcp (required) | | indexName | string | Index name to use (required) |

API

PineconeAdapter

adapter.createCollection(name, dimension)           // Promise<void>
adapter.deleteCollection(name)                      // Promise<void>
adapter.upsert(collection, docs)                    // Promise<void>
adapter.search(collection, vector, topK, filter?)   // Promise<SearchResult[]>
adapter.delete(collection, ids)                     // Promise<void>

Implements: VectorDBAdapter

Related Packages

• @orka-js/core — VectorDBAdapter interface
• @orka-js/qdrant — Self-hosted alternative
• @orka-js/memory — In-memory adapter for dev/testing
• orkajs — Full bundle