# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")
index = pc.Index("docs-example")

upsert_response = index.upsert(
    vectors=[
        {
            "id": "vec1",
            "values": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8],
            "sparse_values": {
                "indices": [1, 5],
                "values": [0.5, 0.5]
            },
            "metadata": {
                "genre": "drama"
            }
        },
        {
            "id": "vec2",
            "values": [0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],
            "sparse_values": {
                "indices": [5, 6],
                "values": [0.4, 0.5]
            },
            "metadata": {
                "genre": "action"
            }
        }
    ],
    namespace="example-namespace"
)

// npm install @pinecone-database/pinecone
import { Pinecone } from '@pinecone-database/pinecone'

const pc = new Pinecone({ apiKey: "YOUR_API_KEY" })
const index = pc.index("docs-example")

await index.namespace('example-namespace').upsert([
  {
    id: 'vec1',
    values: [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8],
    sparseValues: {
        indices: [1, 5],
        values: [0.5, 0.5]
    },
    metadata: {'genre': 'drama'},
  },
  {
    id: 'vec2',
    values: [0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],
    metadata: {'genre': 'action'},
    sparseValues: {
        indices: [5, 6],
        values: [0.4, 0.5]
    }
  }
])

import com.google.protobuf.Struct;
import com.google.protobuf.Value;
import io.pinecone.clients.Index;
import io.pinecone.clients.Pinecone;

import java.util.Arrays;
import java.util.List;

public class UpsertExample {
    public static void main(String[] args) {
        Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
        String indexName = "docs-example";
        Index index = pc.getIndexConnection(indexName);
        List<Float> values1 = Arrays.asList(0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f);
        List<Float> values2 = Arrays.asList(0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f, 0.9f);
        Struct metaData1 = Struct.newBuilder()
                .putFields("genre", Value.newBuilder().setStringValue("drama").build())
                .build();
        Struct metaData2 = Struct.newBuilder()
                .putFields("genre", Value.newBuilder().setStringValue("action").build())
                .build();

        index.upsert("A", values1, null, null, metaData1, null);
        index.upsert("B", values2, null, null, metaData2, null);
    }
}

PINECONE_API_KEY="YOUR_API_KEY"
INDEX_HOST="INDEX_HOST"

curl "https://$INDEX_HOST/vectors/upsert" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-Pinecone-Api-Version: 2024-04" \
  -d '{
        "vectors": [
          {
            "id": "vec1",
            "values": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8],
            "sparseValues": {
              "indices": [2, 7],
              "values": [0.4, 0.5]
            },
            "metadata": {
              "genre": "drama"
            }
          },
          {
            "id": "vec2",
            "values": [0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],
            "sparseValues": {
              "indices": [1, 4],
              "values": [0.1, 0.2]
            },
            "metadata": {
              "genre": "action"
            }
          }
        ]
      }'

{"upsertedCount":2}