Search with a vector

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

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

index.query(
    namespace="example-namespace",
    vector=[0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
    filter={
        "genre": {"$eq": "documentary"}
    },
    top_k=3,
    include_values=True
)

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

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

const queryResponse = await index.namespace('example-namespace').query({
    vector: [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
    filter: {
      'genre': {'$eq': 'documentary'}
    },
    topK: 3,
    includeValues: true
});

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

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

public class QueryByMetadataExample {
    public static void main(String[] args) {
        Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
        Index index = pc.getIndexConnection("pinecone-index");
        List<Float> query = Arrays.asList(0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f, 0.3f);
        Struct filter = Struct.newBuilder()
                .putFields("genre", Value.newBuilder()
                        .setStructValue(Struct.newBuilder()
                                .putFields("$eq", Value.newBuilder()
                                        .setStringValue("documentary")
                                        .build()))
                        .build())
                .build();

        QueryResponseWithUnsignedIndices queryResponse = index.query(3, query, null, null, null, "example-namespace", filter, false, true);

        System.out.println(queryResponse);
    }
}

PINECONE_API_KEY="YOUR_API_KEY"
INDEX_HOST="INDEX_HOST"

curl "https://$INDEX_HOST/query" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-Pinecone-Api-Version: 2024-04" \
  -d '{
    "vector": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3],
    "filter": {"genre": {"$eq": "documentary"}},
    "topK": 3,
    "includeValues": true
  }'

{
  "matches":[
    {
      "id": "vec3",
      "score": 0,
      "values": [0.3,0.3,0.3,0.3,0.3,0.3,0.3,0.3]
    },
    {
      "id": "vec2",
      "score": 0.0800000429,
      "values": [0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2]
    },
    {
      "id": "vec4",
      "score": 0.0799999237,
      "values": [0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4]
    }
  ],
  "namespace": "example-namespace",
  "usage": {"read_units": 6}
}