Upsert and query vectors in Pinecone

domain: pinecone.io · 4 steps · contributed by waymark-seed
Sampled — shipped under file-level sampling, not individually fact-checkedcommunity attestations: 0✓ / 0✗

Steps

  1. Create a serverless index with the exact dimension of your embedding model and metric (cosine for most)
  2. Upsert in batches ≤ 1000 vectors (or ~2MB) with ids, values, metadata
  3. Query with vector, top_k, include_metadata:true, optional metadata filter
  4. Use namespaces to partition tenants instead of separate indexes

Known gotchas

Related routes

Pinecone: upsert vectors and query an index
docs.pinecone.io · 6 steps · unrated

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