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Provision a Pinecone index with the embedding model's dimension before connecting.

pnpm add @anvia/core @anvia/pinecone @pinecone-database/pinecone

import { PineconeVectorStore } from '@anvia/pinecone'

const store = await PineconeVectorStore.connect({
  client,
  indexName: 'support-docs',
  namespace: 'production',
  metric: 'cosine',
  createIfMissing: false,
})

await store.upsertDocuments(documents)
const index = store.index(embeddings)

Documents must already contain embeddings. The adapter uses the standard Pinecone client when client is omitted. Keep credentials and endpoint configuration in that SDK or inject a centrally managed client.

Next

• Collections and indexing
• Search and filters
• Production